Tag: Experimental nuclear physics

  • High-temperature 205Tl decay clarifies 205Pb dating in early Solar System

    High-temperature 205Tl decay clarifies 205Pb dating in early Solar System

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    Q value for 205Tl81+

    The Q value for the bound-state β decay of 205Tl81+ is given by

    $${Q}_{{\beta }_{b}}(81+\to K,{E}^{* })=-{Q}_{{\rm{EC}}}-{E}^{* }-| \Delta {B}_{{\rm{e}}}| +{B}_{{\rm{K}}}=31.1(5)\,{\rm{keV}}.$$

    (3)

    The Q value of the electron-capture decay of the ground state of neutral 205Pb is QEC = 50.6(5) keV (ref. 26). The energy of the first excited state of 205Pb is E* = 2.329(7) keV (ref. 27). The difference in the total atomic binding energy between Tl and Pb is ΔBe = 17.338(1) keV and the effective ionization energy of the K shell of bare 205Pb82+ is BK = 101.336(1) keV (refs. 28,55,56,57). All uncertainties are 1σ Gaussian.

    Experimental details

    We would like to emphasize that the production and storage (for extended periods of time) of fully ionized 205Tl beams is only possible at present at the GSI facilities in Darmstadt. Because 205Tl is stable and abundant on Earth, the easiest solution would be to directly produce a primary beam from an ion source, as was done in the first bound-state β-decay studies on ‘stable’ 163Dy (ref. 58) and 187Re (ref. 59). However, owing to its poisonous vapour, using thallium at GSI is not permitted. Various approaches have been investigated since the 1990s, such as installing a dedicated single-use source, but all were found to be impractical. Hence, the only solution was to produce a secondary beam of 205Tl in a nuclear reaction. This production process was demonstrated in ref. 60 by creating 207Tl81+ from a 208Pb beam; however, the investigators required much lower beam intensity than the present experiment and, because of a much higher Q value, were able to observe contaminants directly. Our use of a secondary beam introduces serious complications compared with the methods used in refs. 58,59—whose measurement methods are more directly comparable—owing to the production of daughter contaminants that are mixed with the parent beam.

    Production and separation of 205Tl81+ ions

    According to varying predictions in the literature35,36,37,38,39, the experiment was planned to be sensitive to the bound-state β-decay half-life of 205Tl of up to one year. This required at least roughly 106 stored, fully ionized 205Tl81+ ions per measurement cycle. Only recently have the advances in ion source technology and a thorough optimization of the GSI accelerator chain, which includes the linear accelerator UNILAC and the heavy-ion synchrotron SIS-18, enabled accelerated lead beams with a reasonably high intensity of 2 × 109 particles per spill.

    A sample of enriched 206Pb was used in the ion source. 206Pb beams were accelerated by the SIS-18 to relativistic energies of 678 MeV per nucleon. This energy was specifically selected to enable stochastic cooling in the ESR (see below). After acceleration, 206Pb beams were extracted from the SIS-18 within a single revolution, yielding 0.5-μs bunches that were transported to the entrance of the FRS34. Here they were impinged on a production target composed of 1,607 mg cm−2 of beryllium with 223 mg cm2 of niobium backing. The niobium was used to facilitate the production of fully stripped ions, which dominated the charge-state distribution. All the matter used in the FRS was thick enough to assume that the emerging ions followed equilibrium charge-state distributions61.

    In the projectile fragmentation nuclear reaction, numerous fragments are created by removing nucleons from the projectile. The corresponding cross-sections rapidly decrease with the number of removed nucleons62. The primary challenge for our experiment was to eliminate the daughter ions of the studied bound-state β decay, 205Pb81+, which are amply produced in the reaction through single-neutron removal. All other contaminants were either easily eliminated in the FRS or well separated in the ESR, and were thus not critical.

    Owing to the reaction kinematics, as well as energy and angular straggling in the target63,64,65, the broad secondary beams of 205Tl81+ and 205Pb81+ ions were indistinguishable after the target. The FRS was tuned such that the beam of 205Tl81+ was centred throughout the separator; see Fig. 2a. At the middle focal plane of the FRS, a wedge-shaped, 735 mg cm−2 aluminium energy degrader was placed. The stopping power of relativistic ions in matter depends mostly on their Z2 (ref. 66), and this differential energy loss introduced a spatial separation of 205Tl81+ and 205Pb81+ on the slits in front of the ESR, despite the broad momentum spread of the beams. Using a thicker degrader improved the separation but at the cost of reduced transmission of the ions of interest. Even with this spatial separation, 205Pb81+ ions could not be completely removed and the amount of contamination could only be quantitatively estimated in the offline analysis (see below). Roughly 104 205Tl81+ ions were injected into the ESR per SIS-18 pulse, with approximately 0.1% 205Pb81+ contamination.

    Cooling, accumulation and storage

    The ions were injected on an outer orbit of the ESR, where the beam was stochastically cooled67,68. Outer versus inner orbits of the ESR refers to the wide horizontal acceptance of the ring and can be adjusted by ramping the dipole magnets. Stochastic cooling operates at a fixed beam energy of 400 MeV per nucleon. Hence, the energy of the primary beam was selected such that the 205Tl81+ ions had a mean energy of 400 MeV per nucleon after passing through all the matter in the FRS. A radio-frequency cavity was then used to move the cooled beam to the inner part of the ring, in which several injections were stacked. On the inner orbit, the accumulated beam was continuously cooled by a monoenergetic electron beam produced by the electron cooler69. Up to 200 stacks were accumulated. Once the accumulated intensity was sufficient, the beam was moved by the radio-frequency cavity to the middle orbit of the ring, where it was stored for time periods ranging from 0 to 10 h.

    The cooling determined the velocity of the ions. Owing to the Lorentz force, the orbit and revolution frequency of the cooled ions were defined only by their mass over charge (m/q) ratio. Stored 205Tl81+, 205Pb81+ and 205Pb82+ ions were subject to several processes:

    • Recombination in the electron cooler: if a 205Tl81+ or 205Pb81+ ion captured an electron, its charge state was reduced to q = 80+ and its orbit was substantially altered, causing it to be lost from the ESR acceptance. Similar electron recombination for 205Pb82+ ions reduced their charge state to q = 81+, where they returned to the main beam and remained in the ESR. To minimize the recombination rate, the density of electrons in the cooler during the storage time was set to 20 mA, which was found to be the minimum value to maintain the beam.

    • Collisions with the rest-gas atoms: in such collisions, 205Tl81+ and 205Pb81+ ions underwent charge-exchange reactions. If a 205Tl81+ or 205Pb81+ ion captured an electron, it was lost from the ring (as above). If a 205Pb81+ ion lost an electron, it remained stored in the ESR on an inner orbit. Capture of an electron by 205Pb82+ moved it to the main beam at q = 81+. Thanks to the ultrahigh vacuum of the ESR, the collision rate was low, as demonstrated by the achieved storage times of up to 10 h.

    • Bound-state β decay of 205Tl81+: this is the process of interest. As noted previously, the mass difference (Q value), between 205Tl81+ and 205Pb81+ is only 31 keV, which meant that both beams completely overlapped in the ESR and remained stored on the central orbit.

    The 205Tl81+ loss rate during storage as a result of all of the above processes was determined to be \({\lambda }_{{\rm{Tl}}}^{{\rm{loss}}}=4.34(6)\times 1{0}^{-5}\,{{\rm{s}}}^{-1}\), corresponding to a beam half-life of 4.4 h. The 205Pb81+ loss rate was determined by a theoretical scaling of the relative radiative recombination rates, resulting in a differential loss rate of \({\lambda }_{{\rm{Tl}}}^{{\rm{loss}}}-{\lambda }_{{\rm{Pb}}}^{{\rm{loss}}}=3.47{(5)}_{{\rm{stat}}}{(87)}_{{\rm{syst}}}\times 1{0}^{-6}\,{{\rm{s}}}^{-1}\).

    Detection

    The 205Pb81+ ions detected at the end of the storage period consisted of both ions created by bound-state β decay and the contamination transmitted from the FRS. The only way to separate the few 205Pb81+ ions from the vast amount of 205Tl81+ ions was to remove the bound electron from 205Pb81+. This was done by using the supersonic Ar gas-jet target that is installed in the ESR70,71. The density of Ar gas was about 1012 atoms cm2 and it was switched on for 10 min. During this time, to keep the beam together, the density of the electrons in the cooler had to be increased to 200 mA. Charge-exchange reactions and different recombination rates had to be taken into account; see the analysis details below. 205Pb82+ ions produced during this stripping were moved to the inner orbit of the ESR, where they were cooled and counted non-destructively.

    Several detectors were implemented throughout the experiment:

    • A current comparator is an inductive device to measure the total current produced by the stored beam. It is permanently installed at the ESR for diagnostics purposes and is sensitive to beam intensities in excess of about 104 particles. This detector was used to continuously monitor the high-intensity 205Tl81+ beam assuming that the contribution from all other contaminants was negligible.

    • Multiwire proportional chambers are position-sensitive, gas-filled detectors installed in special pockets separated from the ESR vacuum by 25-μm, stainless-steel windows72. These detectors were used to count produced q = 80+ ions to determine the charge-changing cross-section ratio (see below) and for a complementary measurement of the beam lifetime during the crucial gas-stripping phase.

    • A non-destructive Schottky detector was used to continuously monitor frequency-resolved intensities of individual ion species throughout the entire experiment without interruptions. This detector features a cavity of air separated from the ring vacuum by a ceramic gap73. Relativistic ions that pass by induce an electric field in the cavity. The ions revolved at about 2.0 MHz, whereas the cavity was resonant at about 245 MHz, meaning that the detector was sensitive to roughly the 125th harmonic. The Fourier transform of the amplified noise from the cavity yielded a noise-power-density spectrum, of which an example spectrum is shown in Extended Data Fig. 1, in which the frequencies of the peaks corresponded to the m/q ratios of the stored ion species74, whereas the intensities were proportional to the corresponding number of stored ions75,76. The Schottky detector had a wide dynamic range, meaning that the detector itself is sensitive to very low as well as very high excitation amplitudes without any distortion, even in the same spectrum. This allows the Schottky detector to monitor millions of ions while still being sensitive to single ions77,78. Unfortunately, in this experiment, the detector was saturated for high-intensity beams and had to be cross-calibrated with the current comparator.

    Determination of the bound-state β-decay rate

    The number of 205Tl81+ ions in the ESR decreased exponentially throughout the storage period owing to radiative electron recombination in the electron cooler and charge-changing collisions with the rest-gas atoms, resulting in 205Tl80+ ions that left the acceptance of the storage ring. The growth of 205Pb81+ daughters must then be solved with a differential equation: the details are provided in ref. 79. The full solution to the differential equations is

    $$\begin{array}{l}\frac{{N}_{{\rm{Pb}}}({t}_{{\rm{s}}})}{{N}_{{\rm{Tl}}}({t}_{{\rm{s}}})}\,=\,\left(\frac{{N}_{{\rm{Pb}}}(0)}{{N}_{{\rm{Tl}}}(0)}+\frac{{\lambda }_{{\beta }_{b}}/\gamma }{{\lambda }_{{\beta }_{b}}/\gamma +{\lambda }_{{\rm{Tl}}}^{{\rm{loss}}}-{\lambda }_{{\rm{Pb}}}^{{\rm{loss}}}}\right)\\ \,\,\,\,\,\exp (({\lambda }_{{\beta }_{b}}/\gamma +{\lambda }_{{\rm{Tl}}}^{{\rm{loss}}}-{\lambda }_{{\rm{Pb}}}^{{\rm{loss}}}){t}_{{\rm{s}}})\\ \,\,\,\,\,-\frac{{\lambda }_{{\beta }_{b}}/\gamma }{{\lambda }_{{\beta }_{b}}/\gamma +{\lambda }_{{\rm{Tl}}}^{{\rm{loss}}}-{\lambda }_{{\rm{Pb}}}^{{\rm{loss}}}},\end{array}$$

    (4)

    with the same notation as in equation (1). The storage ring loss rate \({\lambda }_{{\rm{Tl}}}^{{\rm{loss}}}\) was determined from the exponential decrease (Fig. 2b shows an example measurement) whereas \({\lambda }_{{\rm{Pb}}}^{{\rm{loss}}}\) was scaled using a theoretical calculation from \({\lambda }_{{\rm{Tl}}}^{{\rm{loss}}}\). Using a Taylor series expansion and noting that \({\lambda }_{{\beta }_{b}}\ll ({\lambda }_{{\rm{Tl}}}^{{\rm{loss}}}-{\lambda }_{{\rm{Pb}}}^{{\rm{loss}}})\), this full solution can be well approximated by equation (1), with <0.2% difference over our storage lengths.

    The ion intensity inside the storage ring was monitored by the Schottky detector described above, in which the noise-power density integrated over a peak (SA) in the spectrum is directly proportional to the ion number of that species. Thus, the ratio of the number of 205Pb81+ daughter ions to the number of 205Tl81+ parent ions is equivalent to the ratio of respective Schottky integrals, after several corrections have been applied:

    $$\frac{{N}_{{\rm{Pb}}}({t}_{{\rm{s}}})}{{N}_{{\rm{Tl}}}({t}_{{\rm{s}}})}=\frac{{{\rm{SA}}}_{{\rm{Pb}}}({t}_{{\rm{s}}})}{{{\rm{SA}}}_{{\rm{Tl}}}({t}_{{\rm{s}}})}\frac{1}{{\rm{SC}}({t}_{{\rm{s}}})}\frac{1}{{\rm{RC}}}\frac{{\varepsilon }_{{\rm{Tl}}}({t}_{{\rm{s}}})}{{\varepsilon }_{{\rm{Pb}}}({t}_{{\rm{s}}})}\frac{{\sigma }_{{\rm{str}}}+{\sigma }_{{\rm{rec}}}}{{\sigma }_{{\rm{str}}}}.$$

    (5)

    There are four corrections that need to be implemented:

    1. 1.

      The saturation correction SC corrects for an observed saturation of the Schottky DAQ system78 at large noise-power densities owing to a mismatched amplifier switch. This correction was determined individually for each measurement by calibrating the observed non-exponential decay against the exponential decay constant measured in the multiwire proportional chamber. The uncertainty in this correction was dominated by the calibration fit, so is a systematic uncertainty.

    2. 2.

      The resonance correction RC accounts for the resonance response of the Schottky detector, which resulted in an amplification of the noise-power density at the 205Tl81+ frequency when compared with the 205Pb82+ frequency. This correction was extracted by observing the Schottky area change at the orbit shift after accumulation. Because it is a property of the Schottky detector, the correction was applied globally and is also a systematic uncertainty.

    3. 3.

      The interaction efficiency ϵ corrects for the number of ions that interacted with the gas target before the Schottky measurement, accounting for the loss of 205Tl81+ owing to electron recombination and the proportion of 205Pb81+ that were stripped to the 82+ charge state. This correction was determined from the multiwire proportional chamber event rate and was highly correlated with the gas target density, and so was applied individually. As a result, it contributed to the statistical uncertainty of the measurement.

    4. 4.

      The charge charge-changing cross-section ratio (σs + σr)/σs, which corrects for any 205Pb daughter ions lost to electron recombination rather than stripping in the gas target. This correction was determined by counting both atomic reaction channels using a 206Pb81+ beam. This is a physical constant and so was applied globally, contributing to the systematic error.

    Full details on these corrections are discussed in refs. 79,80 and in the upcoming thesis of G. Leckenby. Intermediate and result data after these corrections have been applied are available in ref. 81.

    Estimated contamination variation

    One source of error that could not be independently determined was the variation in the amount of contaminant 205Pb81+ ions injected into the storage ring from the projectile fragmentation reaction. The presence of the contamination is obvious from the non-zero t = 0 intercept, as seen in Extended Data Fig. 2, but variation in that contamination is impossible to measure and account for without purging the 205Tl81+ beam using the gas target, which would reduce intensities and hence the accumulated signal. Initially, we expected any variation in the contaminant yield to be negligible. However, by cutting away everything but the extreme tails of the 205Pb81+ fragmentation distribution, the impact of instabilities in the yield becomes notable. The presence of unaccounted uncertainty in the data is obvious, both visually when considering the residuals in Extended Data Fig. 2a and noting that the 95% confidence interval for 14 degrees of freedom is χ2 = [6.6, 23.7], whereas our data have χ2 = 303. We have exhausted all other possibilities of stochastic error and thus conclude that we must estimate the variation of contaminant 205Pb81+ from the data itself.

    Appealing to the central limit theorem, we assume that the contamination variation is normally distributed. To estimate the missing uncertainty from the data, the χ2(ν = 14) distribution was sampled for each Monte Carlo run and then a value for the missing uncertainty was determined by solving the following χ2 for our data:

    $${\chi }^{2}=\sum _{i}\frac{{({{\rm{data}}}_{i}-{{\rm{model}}}_{i})}^{2}}{{\sigma }_{i,{\rm{stat}}}^{2}+{(\exp [({\lambda }_{{\rm{Tl}}}^{{\rm{loss}}}-{\lambda }_{{\rm{Pb}}}^{{\rm{loss}}}){t}_{{\rm{s}}}]\times {\sigma }_{{\rm{CV}}})}^{2}},$$

    (6)

    in which σCV is the estimated contamination variation and σstat is the statistical uncertainty from all other sources. Note that the growth factor \(\exp \,[({\lambda }_{{\rm{Tl}}}^{{\rm{loss}}}-{\lambda }_{{\rm{Pb}}}^{{\rm{loss}}}){t}_{{\rm{s}}}]\) is included to account for how the initial contamination evolves with storage time. This growth factor is required to ensure that the terms of the sum follow a unit normal distribution to satisfy the requirements of a χ2 distribution. Thus, for each iteration of the Monte Carlo error propagation, a different value of χ2 is used to estimate the missing uncertainty to account for the stochastic nature of the distribution. The code for this Monte Carlo error propagation is available in ref. 82.

    The error-propagation method described above was double-checked by performing a Bayesian analysis considering the systematic uncertainties as prior distributions83,84,85, which confirmed our Monte Carlo method within the quoted uncertainties.

    205Pb and 205Tl weak rates calculation

    The bound-state β-decay rate, \({\lambda }_{{\beta }_{b}}\), of fully ionized 205Tl81+ with the production of an electron in the K shell is given by

    $${\lambda }_{{\beta }_{b}}=\frac{{\rm{ln}}(2)}{{\mathcal{K}}}{C}_{{\rm{K}}}\,{f}_{{\rm{K}}},$$

    (7)

    with \({\mathcal{K}}=2\overline{F}t=6144.5(37)\,{\rm{s}}\) the decay constant determined by measurements of super-allowed β decay86, \({f}_{{\rm{K}}}={\rm{\pi }}{Q}_{{\beta }_{b}}^{2}{\beta }_{{\rm{K}}}^{2}{{\mathcal{B}}}_{{\rm{K}}}/2{m}_{{\rm{e}}}^{2}\) the phase space for bound β decay with \({Q}_{{{\rm{\beta }}}_{b}}\) the Q value given in equation (3), me the electron mass, βK the Coulomb amplitude of the K-shell electron wavefunction and \({{\mathcal{B}}}_{{\rm{K}}}\) the exchange and overlap correction87. Using \({\beta }_{{\rm{K}}}^{2}{{\mathcal{B}}}_{{\rm{K}}}=5.567\) for hydrogen-like 205Pb81+ computed with the atomic code from ref. 88, we have fK = 0.032(1), which—together with the measured decay rate—gives a value for the nuclear shape factor for bound β decay CK = 7.6(8) × 10−3, corresponding to \(\log (\,ft)=\log ({\mathcal{K}}/{C}_{{\rm{K}}})=5.91(5)\).

    Following the β-decay formalism of refs. 87,89, the nuclear shape factor can be expressed as a combination of different first-forbidden matrix elements. Although the value of the matrix elements connecting the 205Tl(1/2+) and 205Pb(1/2) states is independent of the weak process considered, they appear in different combinations for bound β decay of 205Tl and continuous and bound-electron capture of 205Pb. To disentangle the individual nuclear matrix elements, we have performed shell-model calculations using the code NATHAN90 and the Kuo–Herling interaction40 (for details, see R.M., T.N. & G.M.-P., manuscript in preparation).

    Depending on the stellar conditions, 205Tl and 205Pb ions will be present in different ionization states. To determine their population, we follow the procedure in ref. 43. However, we have revised the treatment of the Coulomb energy of the ion in the stellar plasma. We treat the multicomponent stellar plasma within the additive approximation, that is, all of the thermodynamic quantities are computed as a sum of individual contributions for each species. Furthermore, we assume that the electron distribution is not affected by the presence of charged ions (uniform background approximation). Under these approximations, the energy of the ion in the stellar plasma can be obtained by91

    $${\mathcal{E}}({Z}_{i})={{\mathcal{E}}}_{0}({Z}_{i})+{\mu }_{{\rm{C}}},\quad {\mu }_{{\rm{C}}}={k}_{{\rm{B}}}T{f}_{{\rm{C}}}({\varGamma }_{i}),\quad {\varGamma }_{i}=\frac{{Z}_{i}^{5/3}{e}^{2}}{{a}_{{\rm{e}}}{k}_{{\rm{B}}}T},\quad {a}_{{\rm{e}}}={\left(\frac{3}{4{\rm{\pi }}{n}_{{\rm{e}}}}\right)}^{1/3}$$

    (8)

    with \({{\mathcal{E}}}_{0}\) the energy of the ion in vacuum, Zi the net charge of the ion, ne the electron density and fC(Γi) the Coulomb free energy per ion in units of kBT that we approximate following equation (2.87) in ref. 92. We note that, in our approximation, the Coulomb energy of an ion in the stellar plasma depends only on the net charge of the ion and is independent of the internal structure of the ion. Hence, all states with the same net charge are corrected in the same way. Under this approximation, Coulomb corrections only affect processes in which the net charge of the ion is modified. This includes ionization and continuous electron capture, whereas bound-electron capture and bound β decay are not modified. We differ in the treatment of the latter from ref. 43. The effective ionization energy of a specific ionic state in the stellar plasma is reduced by an amount Δχ(Zi) = μC(Zi + 1) − μC(Zi) (we notice that μC is negative with our definition and grows in magnitude with increasing Zi). This reduction is denoted as depletion of the continuum in ref. 43. Similarly, the Q value for continuous electron capture on an ion with net charge Zi changes by an amount ΔQC = μC(Zi) − μC(Zi − 1). After accounting for these corrections, the different stellar weak processes are computed using the standard expressions (see, for example, ref. 43).

    Extended Data Fig. 3 compares the weak rates connecting 205Pb and 205Tl for two different electron densities, ne = 1025 cm−3 and ne = 1027 cm−3, as a function of temperature. We find that electron-capture processes on 205Pb are dominated by bound-electron capture except at very high densities ne 1027 cm−3. At very low temperatures, the capture rate approaches the laboratory value λec = 4.1(2) × 10–8 year−1 plus a correction owing to continuous electron capture at high electron densities. With increasing temperature, the rate increases as a result of the thermal population of the 1/2 excited state of 205Pb. Bound-electron capture proceeds mainly from L-shell electrons and it is suppressed once the temperature is high enough for 205Pb to be at ionization states for which the L-shell orbits are empty, T 50 MK. At these conditions, holes in the K shell start to appear and bound β decay of 205Tl becomes the dominating weak process once the temperature reaches T 100 MK.

    Revised (n, γ) cross-sections

    Recommended (n, γ) cross-sections for s-process energies (kT = 5–100 keV) are available as Maxwellian-averaged cross-sections for nuclei in the ground-state from the KADoNiS database93. The available version 0.3 (ref. 94) was last updated around 2009. A partial, however incomplete, update to KADoNiS v1.0 was done in 2014 (ref. 48). For this publication, the neutron-capture cross-sections of nine isotopes were revisited and new recommended values with the latest experimental data were provided (Extended Data Table 1). This included the stable isotopes 202Hg, 204Hg, 203Tl, 205Tl, 204Pb and 206Pb, as well as the radioactive isotopes 203Hg, 204Tl and 205Pb. For the stellar-abundance calculations, the recommended Maxwellian-averaged cross-section values have to be multiplied by the (temperature-dependent) stellar enhancement factor (SEF) to simulate the impact of the population of excited states in a stellar plasma. These values are listed for each isotope in the KADoNiS v1.0 database but, for ease of access, we give the SEF of the nine isotopes here discussed in Extended Data Table 1.

    It should be emphasized that, to identify whether a given cross-section measured in the laboratory (in the ground state) can also help constrain the stellar cross-section (captures from excited states), Rauscher et al.95 have introduced the ground-state contribution X. This factor X is also given in the latest KADoNiS version and is shown in Extended Data Table 1. A large deviation from 1 implies that the (unmeasured) contributions from excited states have a larger impact on the stellar cross-section.

    For the six stable nuclei, revised experimental information was included as follows:

    • 202Hg: the kT = 30 keV activation data and its uncertainty96 has been renormalized by f = 1.0785 to the new 197Au(n, γ)198Au value at this energy and extrapolated with the energy dependencies from the JEFF-3.1 (ref. 97), JENDL-3.3 (ref. 98) and ENDFB/VII.1 (ref. 99) libraries.

    • 204Hg: same procedure as for 202Hg (ref. 96) but the experimental uncertainty of 47% was used for the whole energy range. The libraries JEFF-3.3 (ref. 100) and ENDF/B-VIII.0 (ref. 101) were excluded, as they show unphysical trends at energies below 1 keV. Only the energy dependencies of TENDL-2019 (ref. 102) and JEFF-3.0A (ref. 103) were used for the extrapolations.

    • 203Tl: the new recommended values are an average of recently evaluated data libraries (TENDL-2019 (ref. 102), JEFF-3.3 (ref. 100), JEFF-3.0A (ref. 103) and ENDF/B-VIII.0 (ref. 101)). These libraries include the only available experimental time-of-flight data from 1976. The uncertainty is estimated as the standard deviation between the four libraries.

    • 205Tl: only the ENDF/B-VIII.0 (ref. 101) data reproduce previous measurements and were used for the recommendation. A 25% uncertainty was assumed for the whole energy region.

    • 204Pb: the new recommended values are based on the time-of-flight measurement by ref. 104 and have been included in JENDL-4.0 (ref. 105) over the whole energy range. An uncertainty of 5% was assumed, slightly higher than the uncertainties of 3.0–4.4% from the experiment.

    • 206Pb: the new recommended values are based on the two time-of-flight measurements106,107 up to kT = 50 keV and the respective uncertainty was used. Beyond that energy, an average of recently evaluated data libraries (JEFF-3.3, JENDL-4.0, JEFF-3.0A and ENDF/B-VIII.0) gives a good representation, and an uncertainty of 7% was used for kT = 50–100 keV.

    For the three radioactive N = 123 isotones 203Hg (t1/2 = 46.594 days), 204Tl (t1/2 = 3.783 years) and 205Pb (t1/2 = 17.0 Myr), the KADoNiS database could, so far, only provide ‘semiempirical’ estimates because no experimental data existed. The n_TOF collaboration has now measured 204Tl(n, γ) for the first time108. The new experimental data are a factor of 2 lower than the values given by TENDL-2019, ENDF/B-VIII.0 and JEFF-3.3, and a factor of up to 2 higher than the TENDL-2021 and JEFF-3.0A values. This shows the importance of replacing theoretical values with experimental data when available, especially for astrophysical model calculations.

    For 203Hg and 205Pb, for which no experimental information exists, the best approach is to take the average of the most recently revised (recalculated) cross-section libraries and assign a large uncertainty, commonly the standard deviation between the libraries. The (n, γ) cross-sections for the isotopes of interest for each of these libraries have been investigated, and those with unexplained ‘nonphysical’ trends (such as, for example, for JEFF-3.3 and ENDF/B-VIII.0 in the case of 204Hg) have been excluded for the calculation of the averaged cross-section. For the recommended 203Hg and 205Pb cross-sections, the libraries used were ENDF/B-VIII.0, JEFF-3.3, TENDL-2019 and TENDL-2021. However, given the large deviations between the libraries, these values should be better constrained as soon as possible with experimental data.

    The new recommended Maxwellian-averaged cross-section for kT = 5–100 keV for the nine discussed isotopes are given in Extended Data Table 1. The listed SEFs and X factors have been extracted from the KADoNiS database48 and are also given for completeness, but these values have not been changed.

    The 205Pb/204Pb ratio in the early Solar System

    The method to extract isotopic ratios of short-lived radioactive isotopes relative to a stable, or long-lived, isotope of the same element at the time of the formation of the first solids in the early Solar System is founded on chemistry. It is based on a linear regression between, on the y axis, the measured ratio of the daughter nucleus relative to another stable isotope of the same element (for example, 205Tl/203Tl) and, on the x axis, the ratio of a stable isotope of the same element as the short-lived radioactive isotope relative to the same denominator as the y axis (for example, 204Pb/203Tl). Data points from the same meteorite, or meteoritic inclusion, will sample material with a variety of 204Pb/203Tl ratios, depending on their chemistry. If 205Tl/203Tl varies with 204Pb/203Tl, then it can be concluded that the correlation is driven by the decay of 205Pb, as this isotope will chemically correlate with 204Pb. The slope of this correlation line (also referred to as isochrone, as all the data points lying on it would have formed at the same time) provides the 205Pb/204Pb ratio at the time of the formation of the sample material (meteorite or inclusion). The initial value in the early Solar System can be derived by reversing the radioactive decay of the ratio using the age difference between the sample material and the first solids, that is, the oldest meteoritic calcium–aluminium inclusions. The sample ages can be derived using other radiogenic systems, such as U–Pb.

    Although the method is robust, the variations to be measured are so small (in the case of 205Tl/203Tl, they may be on the third or fourth significant digit) that the handling of the uncertainties and the removal of isotopic variations owing to effects other than the radiogenic contribution becomes particularly crucial. Among such variations, the most prominent are those resulting from the chemical effects that depend on the mass of the isotope. These can usually be removed by internal calibration; however, this requires at least three isotopes to be measured. This is not possible for either Tl, as it only has two stable isotopes, or Pb, because three out of its four stable isotopes are affected by radiogenic contributions from U–Th decay chains. Furthermore, the original Pb abundance in the sample is easily contaminated by anthropogenic Pb. Because of these difficulties, it was not possible to derive robust 205Pb/204Pb ratios in the early Solar System until the 2000s. Since then, three studies have attempted to obtain reliable data from iron meteorites11,109 and carbonaceous chondrites10. Reference 10 also measured the Pb and Cd isotopic compositions of the meteorites and ref. 11 also measured Pt. Because Cd and Pt behave similarly to Tl from the point of view of chemistry, these data allowed the identification and therefore elimination of samples affected by mass-fractionation processing. Furthermore, ref. 10 also measured the Pb isotopic compositions to correct for terrestrial Pb contamination.

    The carbonaceous chondrites data10 resulted in an isochrone with slope (1.0 ± 0.4) × 10−3 (at 2σ). This is taken to be representative of the early Solar System because these meteorites are believed to record nebular processes. The analysed iron meteorites instead record later formation times, typically 10–20 Myr later (which means that the slope of their isochrone is, by definition, lower than that of the carbonaceous chondrites), and—by evaluating different age determinations—it is possible to establish whether the different data are consistent with each other. The value measured by the isochrone of ref. 109 requires much longer formation times (on the order of 60 Myr) or, alternatively, a much lower initial value, by roughly a factor of 10, than that derived by ref. 10. The value measured by ref. 11 instead provides more consistent ages, in agreement with the initial value of ref. 10. However, the y-axis intercept of the isochrone of ref. 11, that is, at the zero value of 204Pb/203Tl, is lower by a few parts per ten thousand than that of ref. 10. This prompted the suggestion that the actual slope of the carbonaceous chondrites data should be higher, that is, (2 ± 1) × 10−3 (at 2σ), such that its intercept would the same as the new iron meteorite data. Given these inherent uncertainties, it was suggested by ref. 9 to use an initial value that covers the range of the two studies, that is, (1.8 ± 1.2) × 10−3 (at 2σ). We have used both the range suggested by ref. 9 and the original unmodified slope from carbonaceous chondrites reported in ref. 10.

    The previous predicted AGB upper limit for the 205Pb/204Pb ISM ratio of 5 × 10−4 (ref. 15) is in contradiction with (that is, it is lower than) the most recent laboratory data. Our new predicted ISM value resolves this tension, as it is roughly an order of magnitude higher, although the two values are not directly comparable with each other. In fact, the previous upper limit represents the ratio expected from the ejecta of one single AGB star only and without the inclusion of the main (13C(α, n)16O) neutron source, therefore, of an AGB star that would not produce s-process isotopes. The original aim was to avoid overproduction of all the s-process short-lived isotopes (especially 107Pd) relative to 26Al in the scenario in which a single AGB star located near the early Solar System would have contributed all these radioactive isotopes (see also ref. 110). Our results and those from ref. 18 show that, instead, the s-process isotopes have a separate origin from 26Al: they are all self-consistently explained by the chemical evolution of the Galaxy driven by the material ejected by many different AGB stars, in agreement with the latest 205Pb/204Pb laboratory meteoritic analysis. Furthermore, because our results generally agree better with the lowest values of the range recommended at present, they support the value derived from the slope of the original carbonaceous chondrites isochrone.

    Yields from AGB star models

    The AGB models were calculated to simulate s-process nucleosynthesis in these stars (as described in detail in ref. 3) using a revised version of the Monash nucleosynthesis tools49,111, which allow detailed incorporation of the temperature and density of β-decay and electron-capture rates. The Monash nucleosynthesis code is a post-processing tool, which acts on a nuclear network coupled to stellar structure inputs generated by the Monash stellar evolution code. The post-processing method is relatively fast and works under the assumption, valid here, that the reaction rates under investigation do not contribute to the bulk of the stellar energy generation. The nucleosynthesis code simultaneously solves the changes owing to nuclear burning and to convection, implemented through an advective scheme. Specifically, this means that, within convective regions (that is, the thermal pulses and the envelope of the star), 205Tl and 205Pb decay, while at the same time they are mixed through different stellar layers of different temperature and densities. The relevant (n, γ) rates were included as described above and, when compared with models using previous values of these rates, the differences were on the order of 10% or less. The rate of the debated neutron source 22Ne(α, n)25Mg was taken from ref. 112; see also discussion in ref. 113. Using the lower rate in ref. 114 resulted in less than 10% difference.

    To determine the yield of a population of AGB stars at the time of the formation of the Sun, we considered the ejecta from stars of masses 2.0–4.5 M, that is, those expected to contribute towards s-process element production in the Galaxy115, for an initial composition that is the same as the proto-solar nebula, in which Z = 0.014 (ref. 116). We also tested the case in which the initial metallicity of the AGB stars is Z = 0.02, as discussed further below. The resulting yields, that is, the total ejected mass of the indicated isotope and their ratios, are listed in Extended Data Table 2. The 205Pb/204Pb ratio shows the main effect of temperature on the production of 205Pb. Increasing the stellar mass, the temperature also increases: the maximum temperature reached in the thermal pulse increases from 280 to 356 MK for the mass range considered in Extended Data Table 2. This means that, in the higher-mass stars, during the activation of the 22Ne neutron source, 205Tl and 205Pb experience stronger and weaker decays, respectively (see Fig. 3, noting that the most relevant electron density for the intershell of AGB stars is around the 1027 cm−3 value, that is, on the order of 3,000 g cm−3). As described in the main text, the two isotopes will continue to decay after the thermal pulse is extinguished and before they are dredged up to the envelope. The exact effect of this phase depends on the detailed temperature and density structure of the region, as well as the time that elapses between the thermal pulse and the following dredge-up. The average mass yield ratio of this AGB stellar population is 0.168 (0.167 by number abundance) when using the trapezoidal rule to integrate the yields over Salpeter’s initial mass function. In our models, stars less than 2 M, at this metallicity, do not eject s-process elements111; however, this result is model-dependent. We tested the most conservative scenario of extending the range of masses down to 1.5 M by assuming the same 204Pb yield as the 2 M model and no ejection of 205Pb, owing to the colder temperature. Even in this extreme case, the average yield ratio decreases by only less than 10%. Similarly, if we extended our mass grid to reach masses of 6 M, in the conservative case in which they ejected the same amounts of 204,205Pb as the 4.5 M model, we would obtain an increase of the final ratio by 10%. Overall, AGB stars with masses beyond the range considered here would not have a substantial impact on our results.

    Differences appear when comparing AGB models calculated using different evolutionary codes. This is mostly because of the fact that different codes produce stellar models with different temperatures, which—as seen above—has the greatest impact on the final results. To perform this analysis quantitatively, we computed a 3 M model of metallicity Z = 0.02 using the Monash, FUNS and NuGrid tools. The FUNS models have been calculated with the most recent version of the code, which includes mixing induced by magnetic fields50,117. These models use as a reference the solar mixture published by Lodders118, with updates from ref. 119. In the FUNS models, the nucleosynthesis is directly calculated with the physical evolution of the structure, thus no post-processing technique is applied. The NuGrid models are based on the stellar structure computed51 with the stellar evolution code MESA120 including a convective boundary mixing prescription at the border of convective regions121. The solar distribution used as a reference is given in ref. 122. The detailed nucleosynthesis is calculated using the stellar structure evolution data as input for a separate post-processing code123. The FUNS results provided a 205Pb/204Pb ratio of 0.021, roughly a factor of 3 lower than the corresponding Monash ratio of 0.071. In the case of NuGrid, instead, the adopted convective boundary mixing prescription results in higher temperatures and, in turn, a higher 205Pb/204Pb ratio of 0.176. With the Monash code, we also tested implementing different opacities and initial abundances (to mimic the choices made in the other codes) and the results were affected by less than 10%. Therefore, the overall variation of roughly a factor of 10 between the three different models is most probably because of: (1) the inclusion of overshoot at the base of the thermal pulse in the NuGrid models, which results in higher temperatures than the other models, and (2) the different mass-loss rates implemented: ref. 124 in Monash, ref. 125 in NuGrid and ref. 126 in the FUNS model.

    Radioactive nuclei in GCE

    The calculation of the ISM abundance ratio 205Pb/204Pb according to equation (2) includes a factor, K, which allows us to account for the impact of various galactic processes. As described in detail previously53, current observations can be used to constrain models of the Milky Way galaxy, including the gas inflow rate, the mass of gas, the star formation rate, the mass of stars and the core-collapse supernova and Type Ia supernova rates. It is therefore possible to produce several realizations of the Milky Way galaxy that reproduce the observed ranges of such properties, and each of these realizations will result in a different radioactive-to-stable isotope ratio. After analysis of the possible effects, ref. 53 provided a lower limit, a best fit and an upper limit for the value of K of 1.6, 2.3 and 5.7, respectively, which can be used in equation (2) to account for galactic uncertainties. In the main text, we have focused on the best fit K = 2.3 case; here in Extended Data Fig. 4 and Extended Data Table 3, we also show the results using the upper and lower limits. Note that each value of K represents a different realization of the Milky Way galaxy, therefore time intervals can only be compared with each other when they are calculated using the same K.

    The use of equation (2) is not as accurate as a full GCE model because it allows for only one stellar production ratio, whereas this number varies with stellar mass and metallicity. To check its validity, we tested the results of using equation (2) for 107Pd/108Pd, 135Cs/133Cs and 182Hf/180Hf against those of the GCE models18. We found that the steady-state equation reproduces the more accurate, full GCE simulations that include variable yields within 50%. Furthermore, the production ratios P calculated from AGB stars are s-process production ratios. As noted in the main text, the contribution of live r-process abundances to the s-process short-lived radionuclides is negligible. However, the s-process production ratio P must be scaled to account for the r-process contribution to the stable reference isotope. We use the s-process fraction of the stable reference calculated for the Monash GCE models provided in ref. 18. To do this, we multiply the s-process production ratios by the s-process fraction of the stable reference calculated for the Monash GCE models provided in ref. 18.

    All of the distributions plotted in Extended Data Fig. 4 also include the uncertainties in the steady-state value owing to the fact that stellar ejections are not continuous but discrete events, with a time interval competing with the decay time. We calculated these uncertainties by running simulations with the Monte Carlo code developed in ref. 54, in which a stellar ejection event consists of injecting a unit of material into a parcel of interstellar gas with the intent to simulate the enrichment of that parcel with radioactive isotopes from one or many AGB star sources. According to the full analysis of ref. 54, the steady-state assumption is valid for this process if the ratio of the mean life τ and the interval δ that elapses between each injection event is greater than 2. Therefore, for 107Pd/108Pd and 182Hf/180Hf, we used the same choice of parameters as ref. 18, that is, the most conservative choice δ 3 Myr and τ/δ ≈ 3–4. Given its longer mean life, this assumption is also satisfied for 205Pb. Physically, AGB winds may not have enough energy to be able to carry material far enough from the source to realize the relatively short δ assumed here (a simple calculation of δ based on energy conservation would instead give values on the order of 50 Myr (ref. 1)). However, other processes, such as core-collapse supernova shock waves127 and diffusion128,129, probably contribute to further spreading of AGB material in the Galaxy, thereby allowing it to reach more parcels of gas in shorter time intervals.

    The shorter mean life of 135Cs means that this isotope would be in steady-state equilibrium only if δ 1 Myr, in which case we can derive lower limits for the corresponding isolation time, which are shown in Extended Data Fig. 4. (Note that, for δ 3 Myr, only an upper limit of the 135Cs abundance can be derived; see Table 4 of ref. 54. As an upper limit is also only available for the early Solar System, the isolation time is undefined in this case). The new values for the isolation time are shorter than those provided in ref. 18. This is because of the combined effect of the revised τ used here (1.92 Myr), which is 70% lower than the value used in ref. 18 (3.3 Myr), and the roughly two times higher production ratio of 135Cs/133Cs, owing to the new rate of the decay of 134Cs (refs. 130,131), the branching point leading to the production of 135Cs.

    When the value of K increases, all of the radioactive-to-stable isotope ratios increase, according to equation (2). Therefore, as shown in Extended Data Fig. 4, the isolation time also increases and the increase is proportional to the mean life of each isotope, which is why the shift is the largest for the 205Pb distribution. The overlap between the three distributions is the largest for K = 5.7. If we assume that the 205Pb/204Pb average mass yield ratio varies according to the results of the FUNS and NuGrid models discussed in the previous section (that is, /3.4 and ×2.5, respectively, relative to the Monash models), then the 205Pb/204Pb time distributions in Extended Data Fig. 4 shift by −30 Myr and +22 Myr, respectively. These variations call for a more detailed future analysis of the production of the four s-process short-lived isotopes in different AGB models. The s-process 107Pd/108Pd production ratio is typically 0.14, as it is controlled by the ratio of the neutron-capture cross-sections of the two isotopes, which are relatively well known132,133. Therefore, the main challenge for nuclear-physics inputs remain for the 182Hf/180Hf ratio, which is controlled by activation of the temperature-dependent branching point at 181Hf, a function of the decay rate of 181Hf (ref. 21), and the neutron density produced by the still uncertain 22Ne(α, n)25Mg reaction.

    As described above, all of the calculations so far are based on the assumption that the ratios under consideration are well represented by the steady-state equation (2) and its associated distribution uncertainties for τ/δ > 2. Still, we need to consider the possibility that δ may instead be longer than τ. For example, if τ/δ < 0.3, then it is statistically more likely that the radioactive abundances we observe in the Solar System are exclusively because of the contribution of the last event that enriched the galactic ISM parcel from which the Sun was born54. This is the case for the radioactive nuclei 129I and 247Cm of r-process origin, for which δ values are larger than their mean lives given the rarity of their stellar sources22. In the case of the s-process nuclei, δ larger than 30–70 Myr would imply an origin from a single event. For 107Pd and 182Hf, it was possible to identify some AGB models that could provide a self-consistent solution, with the best-fit event occurring roughly 25 Myr before the formation of the first solids in the early Solar System18. Here we test whether this scenario could also account for the 205Pb/204Pb ratios. When considering all three isotopes using the set of Monash models with Z = 0.014, stellar masses below roughly 3 M are not hot enough to produce as much 205Pb as needed, whereas models above this mass typically produce too much 205Pb and 182Hf, relative to 107Pd. The model of mass 3 M produces self-consistent times around 30 Myr from the last event when using K = 5.7 and the lowest 2σ value of the early Solar System 205Pb/204Pb ratio. Overall, a last-event solution may require more fine-tuning than the steady-state solution because, in this case, we do not have any galactic, stochastic uncertainty to allow for a spread in the derived time intervals (as in each panel of Extended Data Fig. 4). Also for this scenario, stellar and nuclear uncertainties need to be carefully evaluated, together with the further constraints that can be derived from the ratios of the radioactive isotopes relative to each other, such as 107Pd/182Hf and 182Hf/205Pb (refs. 18,134).

    Finally, the abundances of all the isotopes considered here may have been contributed to by nucleosynthesis occurring in the massive stars that lived in the same molecular cloud in which the Sun formed and ejected these nuclei within a short enough time to pollute their environment before star formation was extinguished. If such contribution was present and substantial, it needs to be added on top of the contribution that we have calculated here from the AGB stars that evolved before the formation of the molecular cloud and contributed to the chemical evolution of the Galaxy. Wolf–Rayet winds from very massive (>40 M), very short-lived (<5 Myr) and very rare stars may produce 107Pd and 205Pb (refs. 135,136) but not 182Hf, which requires higher neutron densities than available in those conditions to activate the branching point at the unstable 181Hf. Such possible partial contribution does not seem to be required, as GCE already provides a self-consistent solution for all three isotopes together. Core-collapse supernovae, instead, can eject all three isotopes. To provide a successful combination with the GCE contribution, at least according to results calculated with the Monash models, it is required that a potential local core-collapse supernova source produced 107Pd and 182Hf in similar amounts as in AGB stars and 205Pb in potentially higher amounts. This may be achieved, although other factors would play a role in the rich nucleosynthetic environment of a core-collapse supernova, for example, 135Cs is expected to be strongly overproduced relative to the current observed upper limit110, and the long-standing problems of overproduction of 53Mn and 60Fe by a nearby core-collapse supernova would need to be addressed as well.

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  • Imaging shapes of atomic nuclei in high-energy nuclear collisions

    Imaging shapes of atomic nuclei in high-energy nuclear collisions

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    Accessing information in the intrinsic frame

    The nuclear shape in the intrinsic frame is not directly observable in low-energy experiments. However, in high-energy collisions, the collective flow phenomenon is sensitive to the shape and size of the nucleon distribution in the overlap region of the transverse plane. This distribution, denoted as \(\rho \left({\bf{r}}\right)\) with r = x + iy, provides a direct link to the shape characteristics of the two colliding nuclei in their intrinsic frames, as discussed below.

    The elliptic shape of the heavy-ion initial state is characterized by its amplitude ε2 and direction Φ2, defined by nucleon positions as

    $${{\mathcal{E}}}_{2}\equiv {\varepsilon }_{2}{{\rm{e}}}^{2{\rm{i}}{\varPhi }_{2}}=\frac{{\int }_{{\bf{r}}}{{\bf{r}}}^{2}\rho \left({\bf{r}}\right)}{{\int }_{{\bf{r}}}| {\bf{r}}{| }^{2}\rho ({\bf{r}})},{\int }_{{\bf{r}}}=\int \,{\rm{d}}x{\rm{d}}y.$$

    (4)

    When the coordinate system is rotated such that x and y coincide with the minor and major axes, the elliptic eccentricity coincides with the usual definition \({\varepsilon }_{2}=\frac{\langle {y}^{2}\rangle -\langle {x}^{2}\rangle }{\langle {y}^{2}\rangle +\langle {x}^{2}\rangle }\). The parameter ε2 drives the elliptic flow v2: v2ε2.

    Let us now consider collisions at zero impact parameter, in which, without loss of generality, the average elliptic geometry vanishes, that is, \(\langle {{\mathcal{E}}}_{2}\rangle =0\). The second moment of eccentricity over many events is given by53,54

    $$\langle {\varepsilon }_{2}^{2}\rangle =\langle {{\mathcal{E}}}_{2}{{\mathcal{E}}}_{2}^{* }\rangle \approx \frac{{\int }_{{{\bf{r}}}_{1},{{\bf{r}}}_{2}}{\left({{\bf{r}}}_{1}\right)}^{2}{\left({{\bf{r}}}_{2}^{* }\right)}^{2}\rho \left({{\bf{r}}}_{1},{{\bf{r}}}_{2}\right)}{{\left({\int }_{{\bf{r}}}| {\bf{r}}{| }^{2}\langle \rho ({\bf{r}})\rangle \right)}^{2}},$$

    (5)

    where \(\langle \rho ({\bf{r}})\rangle \) represents the event-averaged profile, and

    $$\rho \left({{\bf{r}}}_{1},{{\bf{r}}}_{2}\right)=\langle \delta \rho ({{\bf{r}}}_{1})\delta \rho ({{\bf{r}}}_{2})\rangle =\langle \rho ({{\bf{r}}}_{1})\rho ({{\bf{r}}}_{2})\rangle -\langle \rho ({{\bf{r}}}_{1})\rangle \langle \rho ({{\bf{r}}}_{2})\rangle $$

    is the usual two-body distribution. Similarly, the third central moments are related to the three-body distribution, \(\rho \left({{\bf{r}}}_{1},{{\bf{r}}}_{2},{{\bf{r}}}_{3}\right)\,=\) \(\langle \delta \rho ({{\bf{r}}}_{1})\delta \rho ({{\bf{r}}}_{2})\delta \rho ({{\bf{r}}}_{3})\rangle \). For example,

    $$\langle {\varepsilon }_{2}^{2}\delta {d}_{\perp }/{d}_{\perp }\rangle \approx -\frac{{\int }_{{{\bf{r}}}_{1},{{\bf{r}}}_{2},{{\bf{r}}}_{3}}{({{\bf{r}}}_{1})}^{2}{({{\bf{r}}}_{2}^{\ast })}^{2}|{{\bf{r}}}_{3}^{2}|\rho ({{\bf{r}}}_{1},{{\bf{r}}}_{2},{{\bf{r}}}_{3})}{{({\int }_{{\bf{r}}}|{\bf{r}}{|}^{2}\langle \rho ({\bf{r}})\rangle )}^{3}},$$

    (6)

    where we define \(\delta {d}_{\perp }/{d}_{\perp }\equiv ({d}_{\perp }-\langle {d}_{\perp }\rangle )/\langle {d}_{\perp }\rangle \), and the relation \(\frac{\delta {d}_{\perp }}{{d}_{\perp }}\approx -\frac{\delta \langle | \,{{\bf{r}}}^{2}\,| \rangle }{\langle | \,{{\bf{r}}}^{2}\,| \rangle }\,=\) \(-\frac{{\int }_{{\bf{r}}}| \,{{\bf{r}}}^{2}\,| \delta \rho \left({\bf{r}}\right)}{{\int }_{{\bf{r}}}| \,{\bf{r}}\,{| }^{2}\langle \rho ({\bf{r}})\rangle }\) is used.

    The quantities \({{\mathcal{E}}}_{2}\) and δd/d depend not only on the nuclear shape but also on the random orientations of the projectile and target nuclei, denoted by Euler angles Ωp and Ωt. For small quadrupole deformation, it suffices to consider the leading-order forms33:

    $$\begin{array}{l}\frac{\delta {d}_{\perp }}{{d}_{\perp }}\,\approx \,{\delta }_{d}+{p}_{0}({\varOmega }_{p},{\gamma }_{p}){\beta }_{2p}+{p}_{0}({\varOmega }_{t},{\gamma }_{t}){\beta }_{2t},\\ \,{{\mathcal{E}}}_{2}\,\approx \,{{\mathcal{E}}}_{0}+{{\bf{p}}}_{2}({\varOmega }_{p},{\gamma }_{p}){\beta }_{2p}+{{\bf{p}}}_{2}({\varOmega }_{t},{\gamma }_{t}){\beta }_{2t}.\end{array}$$

    (7)

    Here, the scalar δd and vector \({{\mathcal{E}}}_{0}\) represent values for spherical nuclei. The values of scalar p0 and vector p2 are directly connected to the xy-projected one-body distribution ρ(r). Therefore, they depend on the orientation of the two nuclei. The fluctuations of δd (\({{\mathcal{E}}}_{0}\)) are uncorrelated with p0 and the fluctuations of \({{\mathcal{E}}}_{0}\) are uncorrelated with p2. After averaging over collisions with different Euler angles and setting β2p = β2t and γp = γt, we obtain

    $$\begin{array}{l}\,\,\,\langle {\varepsilon }_{2}^{2}\rangle \,=\,\langle {\varepsilon }_{0}^{2}\rangle +2\langle {{\bf{p}}}_{2}(\gamma ){{\bf{p}}}_{2}^{* }(\gamma )\rangle {\beta }_{2}^{2}\\ \langle {(\delta {d}_{\perp }/{d}_{\perp })}^{2}\rangle \,=\,\langle {\delta }_{d}^{2}\rangle +2\langle {p}_{0}{(\gamma )}^{2}\rangle {\beta }_{2}^{2}\\ \langle {\varepsilon }_{2}^{2}\delta {d}_{\perp }/{d}_{\perp }\rangle \,=\,\langle {\varepsilon }_{0}^{2}{\delta }_{d}\rangle +2\langle {p}_{0}(\gamma ){{\bf{p}}}_{2}(\gamma ){{\bf{p}}}_{2}{(\gamma )}^{* }\rangle {\beta }_{2}^{3}.\end{array}$$

    (8)

    It is found that \(\langle {{\bf{p}}}_{2}(\gamma ){{\bf{p}}}_{2}^{* }(\gamma )\rangle \) and \(\langle {p}_{0}{(\gamma )}^{2}\rangle \) are independent of γ, while \(\langle {p}_{0}(\gamma ){{\bf{p}}}_{2}(\gamma ){{\bf{p}}}_{2}{(\gamma )}^{* }\rangle \propto -\cos (3\gamma )\), resulting in expressions in equation (2).

    The event-averaged moments in equation (8) are rotationally invariant and capture the intrinsic many-body distributions of \(\rho \left({\bf{r}}\right)\). Note that the coefficients an in equation (2) are strong functions of centrality that decrease towards central collisions, whereas coefficients bn vary weakly with centrality. Therefore, the impact of deformation is always largest in the most central collisions. In general, it can be shown that the n-particle correlations reflect the rotational invariant nth central moments of \(\rho \left({\bf{r}}\right)\), which in turn are connected to the nth moments of the nuclear shape in the intrinsic frame.

    Previous experimental attempts on nuclear shapes at high energy

    The idea that v2 can be enhanced by β2 was recognized early55,56,57,58,59. Studies at RHIC60 and the LHC61,62,63 in 238U + 238U and 129Xe + 129Xe collisions indicated the influence of β2 on v2. Several later theoretical investigations assessed the extent to which β2 can be constrained by v2 alone64,65,66,67. A challenge with v2 is that its a1 term in equation (2) is affected by \({\varepsilon }_{2}^{{\rm{rp}}}\), which often exceeds the \({b}_{1}\,{\beta }_{2}^{2}\) term even in central collisions. A recent measurement of \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \) aimed to assess the triaxiality of 129Xe (ref. 42), but the extraction of γXe was hindered by needing previous knowledge of β2Xe and potentially substantial fluctuations in γXe (refs. 39,68,69,70,71). The combination of several observables in this study allows for a more quantitative extraction of nuclear shape parameters.

    Event selection

    In high-energy experiments, the polar angle θ is usually mapped to the so-called pseudorapidity variable η = −ln(tan(θ/2). The STAR TPC polar angle range θ − 90° < 50° corresponds to η < 1.

    The collision events are selected by requiring a coincidence of signals from two vertex position detectors on each side of the STAR barrel, covering a pseudorapidity range of 4.4 < η < 4.9. To increase the statistics for ultra-central collision (UCC) events, a special sample of Au + Au data in 2010 and U + U data is chosen based on the criteria of high multiplicity in the STAR TPC and minimal activity in the zero-degree calorimeters that cover the beam rapidity72.

    In the offline analysis, events are selected to have collision vertices zvtx within 30 cm of the TPC centre along the beamline and within 2 cm of the beam spot in the transverse plane. Furthermore, a selection criterion based on the correlation between the number of TPC tracks and the number of tracks matched to the time-of-flight detector covering η < 0.9 is applied to suppress pileup events (events containing more than one collision in the TPC)73 and background events.

    After applying these selection criteria, the Au + Au dataset has approximately 528 million minimum-bias events (including 370 million in 2011) and 120 million UCC events. The U + U dataset comprises around 300 million minimum-bias events and 5 million UCC events.

    Track selection

    For this analysis, tracks are selected with η < 1 and the transverse momentum range 0.2 < pT < 3.0 GeV/c. To ensure good quality, the selected tracks must have at least 16 fit points out of a maximum of 45, and the ratio of the number of fit points to the number of possible points must be greater than 0.52. Moreover, to reduce contributions from secondary decays, the distance of the closest approach (DCA) of the track to the primary collision vertex must be less than 3 cm.

    The tracking efficiency in the TPC was evaluated using the standard STAR Monte Carlo embedding technique74. The efficiencies are nearly independent of pT for pT > 0.5 GeV/c, with plateau values ranging from 0.72 in the most central Au + Au collisions and from 0.69 in the most central U + U collisions to 0.92 in the most peripheral collisions. The efficiency exhibits some pT-dependent variation, of the order of 10% of the plateau values, within the range of 0.2 < pT < 0.5 GeV/c.

    Centrality

    The centrality of each collision is determined using \({N}_{{\rm{ch}}}^{{\rm{rec}}}\), which represents the number of raw reconstructed tracks in η < 0.5, satisfying pT > 0.15 GeV/c and having more than 10 fit points. After applying a correction to account for the dependence on the collision vertex position and the luminosity, the distribution of \({N}_{{\rm{ch}}}^{{\rm{rec}}}\) is compared with a Monte Carlo Glauber calculation74. This comparison allows for determining centrality intervals, expressed as a percentage of the total nucleus–nucleus inelastic cross-section.

    Calculation of observables

    The \(\langle {v}_{2}^{2}\rangle \), \(\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle \) and \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \) are calculated using charged tracks as follows:

    $$\begin{array}{rcl}[{p}_{{\rm{T}}}] & = & \frac{{\sum }_{i}{w}_{i}{p}_{{\rm{T}},i}}{{\sum }_{i}{w}_{i}},\langle \langle {p}_{{\rm{T}}}\rangle \rangle \equiv {\langle [{p}_{{\rm{T}}}]\rangle }_{{\rm{evt}}}\\ \langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle & = & {\langle \frac{{\sum }_{i\ne j}{w}_{i}{w}_{j}({p}_{{\rm{T}},i}-\langle \langle {p}_{{\rm{T}}}\rangle \rangle )({p}_{{\rm{T}},j}-\langle \langle {p}_{{\rm{T}}}\rangle \rangle )}{{\sum }_{i\ne j}{w}_{i}{w}_{j}}\rangle }_{{\rm{evt}}}\\ \langle {v}_{2}^{2}\rangle & = & {\langle \frac{{\sum }_{i\ne j}{w}_{i}{w}_{j}\cos (2({\phi }_{i}-{\phi }_{j}))}{{\sum }_{i\ne j}{w}_{i}{w}_{j}}\rangle }_{{\rm{evt}}}\\ \langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle & = & {\langle \frac{{\sum }_{i\ne j\ne k}{w}_{i}{w}_{j}{w}_{k}\cos (2({\phi }_{i}-{\phi }_{j}))({p}_{{\rm{T}},k}-\langle \langle {p}_{{\rm{T}}}\rangle \rangle )}{{\sum }_{i\ne j\ne k}{w}_{i}{w}_{j}{w}_{k}}\rangle }_{{\rm{evt}}}.\end{array}$$

    (9)

    The averages are performed first on all multiplets within a single event and then over all events in a fixed \({N}_{{\rm{ch}}}^{{\rm{rec}}}\) bin. The track-wise weights wi,j,k account for tracking efficiency and its η and ϕ dependent variations. The values of \(\langle {v}_{2}^{2}\rangle \) and \(\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle \) are obtained using the standard method, in which particles i and j are selected from η < 1, as well as the two-subevent method, in which particles i and j are selected from pseudorapidity ranges of −1 < ηi < −0.1 and 0.1 < ηj < 1, respectively. We also calculate the efficiency-corrected charged particle multiplicity in η < 0.5, defined as Nch = ∑iwi. This observable is used to evaluate the systematics.

    The covariance \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \) is calculated by averaging over all triplets labelled by particle indices i, j and k. The standard cumulant framework is used to obtain the results instead of directly calculating all triplets41. We also calculated \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \) using the two-subevent method42, in which particles i and j are taken from ranges of  −1 < ηi < −0.1 and 0.1 < ηj < 1, whereas particle k is taken from either subevents. Including a pseudorapidity gap between the particle pairs or triplets suppresses the short-range non-flow correlations arising from resonance decays and jets75.

    The calculation of \({\rho }_{2}=\frac{\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle }{\langle {v}_{2}^{2}\rangle \sqrt{\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle }}\) relies on the input values of \(\langle {v}_{2}^{2}\rangle \), \(\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle \) and \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \). These components and ρ2 are shown in Extended Data Fig. 1 as a function of centrality. In the central region, enhancements of \(\langle {v}_{2}^{2}\rangle \) and \(\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle \) are observed in U + U relative to Au + Au collisions, which is consistent with the influence of large β2U. By contrast, the values of \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \) are markedly suppressed in U + U compared with Au + Au collisions across the entire centrality range shown. This suppression is consistent with the negative contribution expected for strong prolate deformation of U as described in equation (2).

    In this analysis, the default results are obtained using the two-subevent method. The differences between the standard and two-subevent methods are used to evaluate the impact of non-flow correlations discussed below.

    Influence of non-flow correlations

    An important background in our measurement is non-flow: correlations among a few particles originated from a common source, such as resonance decays and jets, which are uncorrelated with the initial geometry. Two approaches are used to estimate the non-flow contributions. Non-flow correlations are short-range in η and can be suppressed by the subevent method by requiring a rapidity gap between the pairs or triplets of particles in equation (9). Hence, in the first approach, the differences between the standard and subevent methods provide an estimate of the non-flow contribution. However, part of the rapidity gap dependence of the signal in central collisions may arise from longitudinal fluctuations in [pT] and v2 because of variations in the initial geometry in η (ref. 42).

    The second approach assumes that the clusters causing non-flow correlations are mutually independent. In this independent-source scenario, non-flow in n-particle cumulants is expected to be diluted by the charged particle multiplicity as \(1/{N}_{{\rm{ch}}}^{n-1}\) (ref. 76). Therefore, non-flow (nf) contributions in a given centrality can be estimated by

    $$\begin{array}{l}{\langle {v}_{2}^{2}\rangle }_{{\rm{nf}}}\approx \frac{{\left[\langle {v}_{2}^{2}\rangle {N}_{{\rm{ch}}}\right]}_{{\rm{peri}}}}{{N}_{{\rm{ch}}}},\\ {\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle }_{{\rm{nf}}}\approx \frac{{\left[\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle {N}_{{\rm{ch}}}\right]}_{{\rm{peri}}}}{{N}_{{\rm{ch}}}},\\ {\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle }_{{\rm{nf}}}\approx \frac{{\left[\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle {N}_{{\rm{ch}}}^{2}\right]}_{{\rm{peri}}}}{{N}_{{\rm{ch}}}^{2}}\end{array}$$

    (10)

    where the subscript ‘peri’ is a label for the peripheral bin. This procedure makes two assumptions that are not fully valid: (1) the signal in the peripheral bin is all non-flow and (2) non-flow in other centralities is unmodified by final state medium effects. For example, the medium effects strongly suppress the jet yield and modify the azimuthal structure of non-flow correlations. Hence, this approach provides only a qualitative estimate of the non-flow. Moreover, this approach is not applicable for \(\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle \), as medium effects are expected to reduce the momentum differences of non-flow particles as they are out of local equilibrium.

    Extended Data Fig. 2 shows the Nch-scaled values of \(\langle {v}_{2}^{2}\rangle \), \(\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle \) and \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \) as a function of centrality in Au + Au collisions. The requirement of subevent reduces the signal in the most peripheral bin by 50%, 40% and 80%, respectively, which can be treated as the amount of non-flow rejected by the subevent requirement. Therefore, we use the differences between the standard and subevent methods to estimate the non-flow in the subevent method. These differences vary with centrality because of the combined effects of medium modification of non-flow and longitudinal flow decorrelations77. These differences are propagated to the ratios of these observables between U + U and Au + Au. They are found to be 1.1%, 3.5% and 11% for \({R}_{{v}_{2}^{2}}\), \({R}_{{(\delta {p}_{{\rm{T}}})}^{2}}\) and \({R}_{{v}_{2}^{2}\delta {p}_{{\rm{T}}}}\), respectively.

    Extended Data Fig. 2 also provides an estimate of non-flow based on the Nch-scaling method. We assume that the entire signals in the 80–100% centrality in two-subevent are non-flow, and then use equation (10) to estimate the fraction of non-flow as a function of centrality. As mentioned earlier, we use this approach for \(\langle {v}_{2}^{2}\rangle \) and \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \), in which the medium effects may redistribute non-flow correlations in azimuthal angle, instead of suppressing them. This approach is unsuitable for \(\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle \), for which the medium effects should always suppress the non-flow contribution. In the 0–5% most central collisions, the estimated non-flow is about 6% for \(\langle {v}_{2}^{2}\rangle \) and only about 1.4% for \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \). These differences, when propagated to the ratios, are reduced for \({R}_{{v}_{2}^{2}}\), which is positive, and increased for \({R}_{{v}_{2}^{2}\delta {p}_{{\rm{T}}}}\), which is negative. They amount to about 2.8% for \({R}_{{v}_{2}^{2}}\) and 2.5% for \({R}_{{v}_{2}^{2}\delta {p}_{{\rm{T}}}}\).

    The non-flow systematic uncertainties are taken as the larger of the two approaches for \({R}_{{v}_{2}^{2}}\) and \({R}_{{v}_{2}^{2}\delta {p}_{{\rm{T}}}}\), whereas for \({R}_{{(\delta {p}_{{\rm{T}}})}^{2}}\), the difference between standard and subevent methods is used. The total non-flow uncertainties in the 0–5% centrality are 2.8%, 3.5% and 11% for \({R}_{{v}_{2}^{2}}\), \({R}_{{(\delta {p}_{{\rm{T}}})}^{2}}\) and \({R}_{{v}_{2}^{2}\delta {p}_{{\rm{T}}}}\), respectively.

    Extended Data Fig. 3 contrasts the non-flow systematic uncertainties with other sources of uncertainties (next section) in this analysis. In the 0–5% centrality, the non-flow uncertainties are comparable or slightly larger than other sources, whereas they are subdominant in other centrality ranges.

    In the literature, non-flow contributions are sometimes estimated using the HIJING model78, which has only non-flow correlations. The latter were found to follow very closely equation (10) (refs. 79,80). In our second approach, instead of relying on the HIJING model, we assume this Nch-scaling behaviour but use real peripheral data as the baseline for non-flow contributions. Our findings indicate that the HIJING model fails to quantitatively capture the features of non-flow. Specifically, the HIJING model predicts a much weaker Δη dependence for \(\langle {v}_{2}^{2}\rangle \), with only a 13% difference between the standard and two-subevent methods, whereas the data indicate a 50% decrease81 (fig. 25 in ref. 81 for p + p collisions). Furthermore, we found that the values of \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \) predicted by HIJING are three times larger than the data in peripheral Au + Au collisions. Therefore, the non-flow estimation based on the HIJING model in ref. 80 seems to be exaggerated. A more recent estimate46, based on a transport model incorporating full medium dynamics and equation (10), yields a non-flow fraction consistent with STAR data. This study also suggests a potential increase of the \({R}_{{v}_{2}^{2}}\) with Δη associated with flow decorrelation effects.

    Understanding non-flow correlations as a physical process has always been a work in progress. As our knowledge deepens, the non-flow uncertainties are expected to reduce. Rather than merely contributing to experimental uncertainties or even being corrected for in the data, non-flow physics should ultimately be incorporated into hydrodynamic models. Currently, these models include non-flow effects from resonance decays but lack contributions from jet fragmentation.

    Systematic uncertainties

    Systematic uncertainties include an estimate of the non-flow contributions discussed above and other sources accounting for detector effects and analysis procedure. These other sources are estimated by varying the track quality selections, the zvtx cuts, examining the influence of pileup, comparing results from periods with different detector conditions and closure test. The influence of track selection criteria is studied by varying the number of fit hits on the track from a minimum of 16 to 19 and by varying DCA cut from  <3 cm to  <2.5 cm, resulting in variations of 1–5% for \(\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle \). The impacts on \(\langle {v}_{2}^{2}\rangle \) and \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \) are up to 2.5% and 4%, respectively.

    The influence of track reconstruction on the collision vertex is examined by comparing the results for different zvtx cuts, with variations found to be 0.5–3% for all observables. Comparisons between data-taking periods, particularly normal and reverse magnetic field runs in Au + Au collisions, show consistency within their statistical uncertainties. The influence of pileup and background events is studied by varying the cut on the correlation between \({N}_{{\rm{ch}}}^{{\rm{rec}}}\) and the number of hits in the TOF. The influence is found to be 1–3% for \(\langle {v}_{2}^{2}\rangle \) and \(\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle \), and reaches 2–10% for \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \). Comparisons are also made between the 2010 and 2011 Au + Au datasets, which have different active acceptances in the TPC. The results are largely consistent with the quoted uncertainties, although some differences are observed, particularly in the central region, in which variations reach 5–10% for \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \).

    A closure test was conducted, in which the reconstruction efficiency and its variations in η and ϕ from the data were used to retain a fraction of the particles generated from a multi-phase transport model82. Subsequently, a track-by-track weight, as described in equation (9), was applied to the accepted particles. All observables are calculated using the accepted particles and compared with those obtained using the original particles. This procedure allowed us to recover \(\langle {v}_{2}^{2}\rangle \) and \(\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle \) within their statistical uncertainties. However, a 2–3% nonclosure was observed in \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \). Nevertheless, it is important to note that such non-closures largely cancel when considering the ratios between U + U and Au + Au collisions.

    Several additional cross-checks were carried out. The track reconstruction efficiency has about 5% uncertainty because of its reliance on particle type and occupancy dependence. We repeated the analysis by varying this efficiency, and the variations in the results were either less than 1% or consistent within their statistical uncertainties. The reconstructed pT can differ from the true value because of finite momentum resolution. This effect was investigated by smearing the reconstructed pT according to the known resolution, calculating the observable and comparing the results with the original ones. A discrepancy of approximately 0.5% was observed for \(\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle \), whereas other observables remained consistent within their statistical uncertainties. These effects cancel in the ratios between °U + U and Au + Au collisions.

    The default results are obtained from the two-subevent method. The total systematic uncertainties, including these sources and non-flow, are calculated as a function of centrality. The uncertainties of the ratios between U + U and Au + Au are evaluated for each source and combined in quadrature to form the total systematic uncertainties. This process results in a partial cancellation of the uncertainties between the two systems. The uncertainties from different sources discussed above on the ratios are shown by the black boxes in Extended Data Fig. 3. The total systematic uncertainties, including non-flow in the 0–5% centrality range, amount to 3.9%, 4.4% and 12.5% for \({R}_{{v}_{2}^{2}}\), \({R}_{{(\delta {p}_{{\rm{T}}})}^{2}}\), and \({R}_{{v}_{2}^{2}\delta {p}_{{\rm{T}}}}\), respectively.

    Hydrodynamic model setup and simulation

    Extended Data Table 1 details the Woods–Saxon parameters for Au and U used in the IP-Glasma + MUSIC model calculations. The nucleon–nucleon inelastic cross-sections are the standard values 42 mb and 40.6 mb for Au + Au collisions at 200 GeV and U + U collisions at 193 GeV, respectively. For U, the nuclear shape in equation (1) is extended to include a possible small axial hexadecapole deformation β4:

    $$R(\theta ,\phi )={R}_{0}(1+{\beta }_{2}[\cos \gamma {Y}_{2,0}+\sin \gamma {Y}_{2,2}]+{\beta }_{4}{Y}_{4,0}).$$

    (11)

    Most low-energy nuclear structure models favour a modest oblate deformation for 197Au (ref. 34). We assume β2Au = 0.14 and γAu = 45° as the default choice for 197Au, which are varied in the range of β2Au ≈ 0.12–0.14 and γAu ≈ 37–53° according to refs. 34,67. These calculations reasonably reproduce many observables related to the ground-state nuclear deformation. For 238U, we scan several β2U values ranging from 0 to 0.34. We also vary β4U from 0 to 0.09 and γU in the range of 0°–20° to examine the sensitivity of the U + U results to hexadecapole deformation and triaxiality. For each setting, about 100,000–400,000 events are generated using the officially available IP-Glasma + MUSIC25,44. Each event is oversampled at least 100 times to minimize statistical fluctuations in the hadronic transport. These calculations were performed using services provided by the Open Science Grid Consortium83,84.

    The role of final state effects is studied by varying the shear and bulk viscosities simultaneously up and down by 50%. The impacts on \(\langle {v}_{2}^{2}\rangle \), \(\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle \) and \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \) are shown for Au + Au collisions in Extended Data Fig. 4 (top). The values of these flow observables are changed by more than a factor of two as a function of centrality. Yet, the ratios between U + U and Au + Au collisions (Extended Data Fig. 4, bottom) are relatively stable. A small reduction of \({R}_{{v}_{2}^{2}}\) and \({R}_{{(\delta {p}_{{\rm{T}}})}^{2}}\) are observed in non-central collisions, when values of viscosities are halved. However, this change is an overestimate because the calculated flow observables greatly overestimate the data. So, in the end, half of the variations of the ratios are included in the model uncertainty.

    The main theoretical uncertainties arise from variations in nuclear structure parameters. Parameters common between two collision systems, such as the minimum inter-nucleon distance in nuclei dmin, are not expected to contribute to the uncertainty significantly. However, other parameters, including nuclear radius R0, skin a and higher-order hexadecapole deformation β4, could be different between Au and U and hence contribute more to the theoretical uncertainty.

    Extended Data Table 1 provides a list of variations of nuclear structure parameters. The impact of these variations on ratios of flow observables is shown in Extended Data Fig. 5. The ratios of flow observables are insensitive to these variations in the most central collisions. \({R}_{{v}_{2}^{2}}\) is particularly sensitive to skin parameter a. This is understandable, as v2 has a large contribution from the reaction plane flow, which varies strongly with the value of a (ref. 45).

    Model uncertainties for the ratios are derived by combining the impact of varying viscosities, together with various sources from Extended Data Fig. 5. As a consequence, checks that are consistent with the default calculation within their statistical uncertainties do not contribute to the model uncertainties. The combined model uncertainties for 1 standard deviation are shown in Fig. 3.

    A cross-check is conducted for an alternative hydrodynamic code, the Trajectum model22,85. This model has 20 parameter sets obtained from a Bayesian analysis of the Pb + Pb data at the LHC but was not tuned to the RHIC data. For this calculation, we simply repeat the calculation at RHIC energy and calculate the same observables. Although the description of \(\langle {v}_{2}^{2}\rangle \) and \(\langle {(\delta {p}_{{\rm{T}}})}^{2}\rangle \) is reasonable, several parameter sets give negative values of \(\langle {v}_{2}^{2}\delta {p}_{{\rm{T}}}\rangle \) in mid-central collisions, and are subsequently not used. The calculation is performed for the remaining 16 parameter sets as a function of centrality, and root mean square variations among these calculations are assigned as the uncertainty.

    Extended Data Fig. 6 shows the ratios of flow observables from Trajectum and compares them with IP-Glasma + MUSIC. The results from these two models agree in their uncertainties for \({R}_{{v}_{2}^{2}}\) and \({R}_{{(\delta {p}_{{\rm{T}}})}^{2}}\), with Trajectum predictions slightly higher in the UCC region. This leads to slightly lower values of β2U than the IP-Glasma model: β2U = 0.228 ± 0.013 for \({R}_{{v}_{2}^{2}}\) and β2U = 0.276 ± 0.018 for \({R}_{{(\delta {p}_{{\rm{T}}})}^{2}}\).

    For \({R}_{{v}_{2}^{2}\delta {p}_{{\rm{T}}}}\), however, the Trajectum model tends to systematically underpredict the data, as well as has much larger uncertainties compared with the IP-Glasma model. In central collisions, this discrepancy can be improved by using a larger triaxiality parameter value γU ~ 15°. Overall, the comparison of the Trajectum model with data gives similar constraints on β2U with comparable uncertainties but a larger γU value with bigger uncertainties (next section).

    Assigning uncertainties on β
    2U and γ
    U

    A standard pseudo-experiment procedure, similar to that in ref. 86, is used to combine the uncertainties from \({R}_{{(\delta {p}_{{\rm{T}}})}^{2}}\) and \({R}_{{v}_{2}^{2}\delta {p}_{{\rm{T}}}}\) shown in Fig. 3g. We assume that the total uncertainties extracted from the two observables are independent, and we model the probability density function as follows:

    $$P({\beta }_{2{\rm{U}}},{\gamma }_{{\rm{U}}})\propto \exp \,\left(-\frac{{({\beta }_{2{\rm{U}}}-{\bar{\beta }}_{a})}^{2}}{2{\sigma }_{a}^{2}}-\frac{{({\beta }_{2{\rm{U}}}-{\bar{\beta }}_{b}({\gamma }_{{\rm{U}}}))}^{2}}{2{\sigma }_{b}^{2}({\gamma }_{{\rm{U}}})}\right).$$

    (12)

    Here, \({\bar{\beta }}_{a}=0.294\) and σa = 0.021 represent the mean and uncertainty of β2U extracted from \({R}_{{(\delta {p}_{{\rm{T}}})}^{2}}\) in Fig. 3g from the IP-Glasma + MUSIC model. Similarly, \({\bar{\beta }}_{b}\) and σb are the mean and uncertainty of β2U from \({R}_{{v}_{2}^{2}\delta {p}_{{\rm{T}}}}\), and they depend on the parameter γU. We sample a uniform prior distribution in β2U and γU to obtain the posterior distribution. From this posterior distribution, we obtained the mean and 1 standard deviation uncertainty of β2U and γU, β2U = 0.297 ± 0.015 and γU = 8.5° ± 4.8°, as well as the confidence contours shown in Fig. 3g. This statistical analysis is also performed for \({R}_{{(\delta {p}_{{\rm{T}}})}^{2}}\) and \({R}_{{v}_{2}^{2}\delta {p}_{{\rm{T}}}}\) for the Trajectum model, yielding constraints of β2U = 0.275 ± 0.017 and γU = 15.5° ± 7.8°.

    Finally, we perform an analysis to combine the constraints of the IP-Glasma + MUSIC and Trajectum models. This is achieved by multiplying the probability density function equation (12) from the two models, treating their constraints as statistically independent. This approach yields β2U = 0.286 ± 0.012 and γU = 8.7° ± 4.5°. We noticed that the Trajectum model does not affect the constraints on γU because of the large uncertainty of the model, but the uncertainty on β2U reduces markedly because of the comparable precision in the two models. Therefore, we also include the difference of the extracted β2U values between the two models as an additional theoretical uncertainty. The final constraints given by this procedure are β2U = 0.286 ± 0.025 and γU = 8.7° ± 4. 5°.

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  • Smooth trends in fermium charge radii and the impact of shell effects

    Smooth trends in fermium charge radii and the impact of shell effects

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    Experimental techniques

    The long chain of fermium isotopes studied in this work was measured by combining different production schemes along with two laser spectroscopy techniques for the respective measurements. Spectroscopy of the isotopes 245,246,248,249,250,254Fm was performed via the RADRIS technique30,31, with the set-up located behind the velocity filter SHIP at the GSI Helmholtzzentrum für Schwerionenforschung in Darmstadt, Germany35,36. Further details on RADRIS and the latest developments introduced to the set-up are given in refs. 34,37,54. For the on-line measurements of fermium with RADRIS, a 1 × 0.025 mm2 hafnium-strip filament was used for collection and neutralization of directly produced nuclei entering the buffer-gas cell filled with 95-mbar high-purity argon gas. A heat-pulse temperature of 1,450 °C was applied to desorb accumulated fermium ions from the filament as neutral atoms for subsequent laser spectroscopy. For the measurements on 255No, a 125μm-diameter tantalum-wire filament and desorption temperatures of 1,100 °C were used.

    The long-lived fermium isotopes 255Fm and 257Fm produced by neutron capture in the nuclear reactor became accessible by in-source hot-cavity laser spectroscopy at the RISIKO mass separator at Johannes Gutenberg-Universität Mainz41,55,56. Here, the sample was placed in a heated reservoir, with a temperature of up to 1,600 K, and the atom vapour was probed by lasers for resonant ionization. The resulting ions were extracted by an electric potential of 30 kV and mass separated using a magnetic dipole to separate the species of interest from unwanted surface ions.

    Laser set-up for in-gas-cell laser spectroscopy at RADRIS

    Laser spectroscopy of fermium was performed by exciting from the 5f127s2 3H6 atomic ground state to the known 5f127s7p \(\genfrac{}{}{0ex}{}{5}{}{{\rm{G}}}_{5}^{{\rm{o}}}\) atomic level around 25,111.8 cm−1 (refs. 42,43). For nobelium, the excitation occurred from the 5f147s2 1S0 ground state to the recently identified excited level 5f147s7p \(\genfrac{}{}{0ex}{}{1}{}{{\rm{P}}}_{1}^{{\rm{o}}}\) at \({\mathrm{29,961.457}}_{-0.007}^{+0.041}\,{{\rm{cm}}}^{-1}\) for 254No (ref. 32). A dye laser (Lambda Physics, FL series) pumped by a Xe:Cl excimer laser (Lambda Physik, LPX240) with 5-ns pulse length and 100-Hz repetition rate was used for laser spectroscopy with up to 500 μJ average energy per pulse and a spectral linewidth of 1.5 GHz using an intracavity etalon for narrow spectral linewidth operation. The laser wavelength was continuously monitored with a wavelength meter (HighFinesse-Ångstrom, WS/7-UVU) that was calibrated to an internal neon lamp. The laser light was transported to the buffer-gas cell using ultraviolet-grade optical fibres and was shaped to illuminate an area of about 3 cm2 around the filament. The average energy of the laser pulse at the cell was kept in a range of 70–120 μJ for the scanning laser for fermium, matching the reported saturation intensity given in ref. 42, and about 10 μJ for nobelium, in accordance with the measurements presented in ref. 33 on lighter nobelium isotopes. The pump laser for the first excitation step dye laser and the Xe:F excimer laser (Lambda Physik, LPX220), the latter providing the laser light for subsequent photoionization, were synchronized with excimer laser synchronization units (Lambda Physik, LPA 97). The ionizing laser featured about 30 mJ average energy per pulse at the cell after beam transport with mirrors. Both lasers had pulse lengths of about 18 ns.

    Laser set-up for in-source laser spectroscopy at RISIKO

    The laser system for the hot-cavity in-source laser spectroscopy of fermium isotopes at RISIKO consisted of nanosecond-pulsed titanium:sapphire lasers, pumped by two frequency-doubled neodymium-doped yttrium aluminium garnet lasers with a 10-kHz repetition rate. The titanium:sapphire lasers can be equipped with either a grating or a birefringent-etalon combination as a frequency-selective element and featured an internal second harmonic generation. One titanium:sapphire laser with an average power of up to 1.2 W was used for photoionization. A high ionization efficiency was achieved by exploiting an auto-ionizing resonance at 52,166 cm−1. For detailed laser spectroscopy of the first excitation step at 25,111.8 cm−1 in 257Fm, one grating-tuned titanium:sapphire laser was equipped with an additional etalon, which reduced the spectral linewidth to about 1 GHz (ref. 57), while the average laser power resulted in about 200 mW. Both laser beams were overlapped anti-collinearly with the ion beam in the hot cavity via a viewport at the bending magnet. For spectroscopy of 255Fm, the Perpendicularly-Illuminated Laser Ion Source Trap (PI-LIST) was employed using the atomic vapour effusing from the hot cavity and a perpendicular overlap of a narrow-linewidth laser to the atomic beam as discussed in more detail in ref. 55. Here, an injection-locked titanium:sapphire laser, seeded by a continuous-wave titanium:sapphire laser58 and equipped with an external single-pass second-harmonic-generation unit59 provided laser light with a band spectral linewidth of 20 MHz and an average power of 100 mW. A laser pulse length of 40 ns was maintained for all lasers and pulse synchronization was achieved by external triggering of the pump lasers with a pulse delay generator. The laser wavenumber of the spectroscopic transition was monitored using two commercial wavelength meters (High Finesse, WS7 and WSU), which were regularly calibrated with a laser locked to a rubidium reference cell60.

    Isotope production

    Different production schemes were applied to access the investigated isotopes in this work for laser spectroscopy studies.

    Direct production on-line

    The isotopes 245Fm (t1/2 = 5.6 s) and 246Fm (t1/2 = 1.54 s) were produced at the velocity filter SHIP, using the fusion-evaporation reactions 208Pb(40Ar, 3n and 2n)245,246Fm with reported cross-sections of 32 nb for 245Fm (ref. 61) and 10 nb for 246Fm (ref. 62). An 40Ar8+ primary beam featuring a macro-pulse structure of 5 ms beam-on and 15 ms beam-off periods, with a beam energy of 185 MeV for 246Fm and 193 MeV for 245Fm, and average intensities of 2 particle microampere (1.2 × 1013 ions per second) was provided by the linear accelerator UNILAC. This primary beam impacted thin lead-sulfide (PbS) targets with an areal density of typically 470 μg cm−2 for PbS on a 30 μg cm−2 carbon backing and with a 10 μg cm−2 carbon cover layer, the latter side facing SHIP. The targets were manufactured at the GSI target laboratory and mounted on a rotating target wheel to distribute the heat from the energy loss of the primary beam over a large area.

    Indirect production on-line

    The isotopes 248Fm (t1/2 = 34.5 s), 249Fm (t1/2 = 2.6 m), 250Fm (t1/2 = 30 m) were obtained from the α-decay of the isotopes 252,253,254No, directly produced in the fusion-evaporation reactions 206,207,208Pb(48Ca, 2n)252,253,254No with respective cross-sections of 0.5 μb, 1.3 μb and 2 μb (ref. 63). 254Fm was obtained from the radioactive decay of 254No using the 10% electron-capture branch to 254Md (t1/2 = 10 m), which then decays exclusively by electron capture to 254Fm (t1/2 = 3.24 h). The nobelium isotope 255No (t1/2 = 3.52 m) was similarly obtained indirectly via the electron-capture branch (<30% (ref. 64), and evaluation of previous data taken at SHIP published in ref. 65) of 255Lr (t1/2 = 31.1 s).

    The primary 48Ca10+ beam was delivered with average intensities of 0.8 particle microampere (5 × 1012 ions per second), impinging on thin 206,207,208PbS targets. The collection cycle of RADRIS was adapted to breed the fermium decay-daughter isotopes on the filament34. Accumulation was done for 25 s (248Fm), 295 s (249Fm) and 355 s (250Fm), before evaporation of collected atoms from the filament followed by resonance ionization laser spectroscopy. For 254Fm, the long lifetime of the intermediate isotope 254Md necessitated a collection time of 3,600 s. This indirect isotope breeding reduced the total efficiency due to decay-branching ratios, recoil implantation into the filament material, and the half-life of mother and daughter nuclide, respectively. The effective yield was especially impacted in the case of 249Fm, which features a similar lifetime to its mother nuclide 253No (T1/2 = 1.62 m) and an α-branching ratio of 55%. For the longer-lived 254Fm, a dedicated rotatable detection set-up consisting of three silicon detectors was used to enable longer counting times of accumulated laser ions parallel to a new collection of laser ions (see ref. 37).

    Production off-line

    For the production of 257Fm, a 248Cm target was irradiated in the High Flux Isotope Reactor at Oak Ridge National Laboratory, USA66,67. The fermium fraction of this sample, containing remaining einsteinium40, was first used for studies at Florida State University and then made available for Mainz University for further investigations. For production of 255Fm, a sample of 290 pg (1.3 × 1014 atoms) 254Es provided by Oak Ridge National Laboratory and Florida State University, USA, was encapsulated in a quartz ampule inside a titanium cylinder and shipped to the high-flux research reactor at the Institut Laue-Langevin in Grenoble, France, for a neutron irradiation of 7 days duration. After a cool-down period of 4 days and shipping to Johannes Gutenberg-Universität Mainz, Germany, the sample contained 7.5 × 1010 atoms of 255Es (t1/2 = 39.8 d) as determined by α-decay spectroscopy. This provided a generator system for the β-decay daughter 255Fm (t1/2 = 20.1 h) present in secular equilibrium. A chemical separation of fermium was performed four times in appropriate intervals to allow ingrowth of 255Fm into the 255Es fraction between individual separations. This procedure was based on an α-hydroxyisobutyrate separation by cation exchange on a Mitsubishi CK10Y resin. The α-hydroxyisobutyrate complex was converted to a nitrate form; the final sample was obtained after cation exchange separation on an AG50WX8 column, placed on a zirconium metal foil of 10 × 10 mm2, which promotes the release of neutral atoms68, and evaporated to dryness. With this method, 255Fm samples of about 7 × 108 atoms and one 257Fm sample with at most 5 × 107 atoms were available for laser spectroscopy.

    Data analysis

    Events from resonant laser ionization were recorded as a function of the set wavenumber to analyse the respective transition resonance centre value and thus extract the isotope shift. In the on-line measurements, the α-decay events from the ions were registered and an α-energy range of interest was selected in the analysis. To account for unavoidable fluctuations in the primary beam intensity, extracted event rates were normalized to the accumulated primary beam charge integral on the beam dump of SHIP. For the off-line measurements, the ions were detected with an ion detector after acceleration and mass separation. Gating the signal on the time-of-flight structure of the resonantly produced ions improved the signal-to-noise ratio. To average over signal variations, the laser wavenumber was scanned slowly and repetitively over the resonance multiple times and the obtained counts were binned and normalized according to the time spent at the respective wavenumber. Observed laser resonances for fermium are presented in Extended Data Fig. 1 and the resonance of 255No is shown in Fig. 1 (bottom).

    Centroid position

    The centroid wavenumbers of the individual measured resonances in the obtained spectra were determined via a fit of a Voigt profile to the data for all even-A isotopes (A denoting the atomic mass number). The odd-mass-number isotopes feature a hyperfine structure splitting of more than 20 lines due to (tentatively assigned) nuclear spins of I = 7/2 for 249,255Fm (refs. 69,70) and I = 9/2 for 257Fm (ref. 71), which could be only partly resolved for 255Fm. This spectrum was analysed using the SATLAS Python package72,73. Owing to the broadening mechanisms inherent in the spectral linewidth of 245,249,257Fm from the environmental conditions of the gas cell and the hot cavity, the hyperfine structure could not be resolved. A Gaussian fit to the data for 257Fm and a Voigt fit for 245,249Fm were used to extract the centre of the structures. The choice of fit profile was connected to the main broadening mechanisms dominating the lineshape in the respective measurement. For the analysis of 255No, with observed underlying hyperfine structure, a nuclear spin of I = 1/2 was assumed for the fit, as tentatively assigned from α-decay hindrance factor systematics74. The results on transition resonance wavenumbers and extracted isotope shifts are summarized in Extended Data Table 1.

    The RADRIS measurements were performed inside a cell filled with 95-mbar argon buffer gas and are thus affected by a pressure shift and broadening. The broadening is effectively taken into account in the fitting routine, while the pressure shift, equivalent across all RADRIS measurements, effectively does not contribute to the isotope-shift measurement. For comparison with the off-line measurements, the pressure shift had to be evaluated. In the element erbium, a pressure shift of 4(1) MHz mbar−1 was recently reported75, which is in line with observations in actinium76. Therefore, a shift of about −400(300) MHz can be inferred for the in-gas-cell laser spectroscopy measurements, with a 3 times larger uncertainty assumed for the application to fermium.

    The off-line measurements were performed inside the hot cavity with an anti-collinearly propagating laser beam for 257Fm and 255Fm, and with a perpendicular arrangement of the laser beam and the atomic beam for 255Fm. The latter measurement corresponds to the rest frame of the atom in vacuum conditions. The Doppler shift from the moving ensemble of atoms in the hot cavity can be determined from the 255Fm measurements (anti-collinear and perpendicular) to −100(100) MHz, in agreement with observations reported in californium55. For comparison with the gas-cell measurements, with 250Fm being the reference for isotope-shift measurements, the obtained resonance frequencies for 255Fm and 257Fm, which were measured in vacuum conditions, have therefore to be shifted by −400(300) MHz and −300(400) MHz, respectively.

    The individual experimental cycle of the RADRIS technique (for details, see refs. 30,31) adapted to each on-line studied isotope leads to a suppression of known isomers in isotopes 248,250Fm, which are shorter lived than the ground state. This ensured that purely the nuclear ground state was probed.

    The accuracies of the extracted centroid wavenumbers are mainly limited by broadening processes. Pressure broadening is the dominant mechanism for all measurements performed in the gas cell. For 257Fm, Doppler broadening owing to the high temperature in the hot-cavity environment needs to be considered. Power broadening mechanisms only had a role in the case of 250Fm, for which an increased laser power of 150 μJ per pulse was utilized. The origins of effects contributing to the isotope-shift uncertainty are summarized in Extended Data Table 2. This includes the accuracy in the wavenumber measurement. The fit uncertainty for extraction of the centroid position in the analysis is included. As the granularity of data points and counting statistics is small for the on-line investigated isotopes, an uncertainty of half the mean-step size in these measurements can be considered instead, to avoid underestimating the centroid uncertainty. Both factors are included in the table; the respective larger contribution was considered for the total accuracy of the isotope shift.

    To account for the model uncertainty for the odd–even isotopes 245,249,257Fm by choosing a single line profile for the extraction of the resonance centroid, one-third of the full-width at half-maximum of the fit profile was considered in the uncertainty analysis. For 255Fm, the hyperfine structure was resolved, and thus the uncertainty in the determination of the hyperfine parameters was used to determine the model uncertainty in the centre of gravity.

    Determination of δr
    2

    The changes in the mean-square charge radius δr2A,A relative to a reference isotope A can be extracted from the measured isotope shifts via the relation

    $${\rm{\delta }}{\nu }^{A,{A}^{{\prime} }}=\frac{{m}^{{A}^{{\prime} }}-{m}^{A}}{{m}^{{A}^{{\prime} }}{m}^{A}}M+F{\rm{\delta }}{\langle {r}^{2}\rangle }^{A,{A}^{{\prime} }},$$

    (1)

    with the measured isotope shift δνA,A = νAνA in the atomic transition of isotopes with mass number A and A′, the mass-shift constant M = MNMS + MSMS, with normal mass shift (NMS) and specific mass shift (SMS), and the field-shift constant F.

    Recently published results from atomic model calculations provided the field-shift constant F for fermium44 to evaluate the changes in the nuclear mean-square charge radii. This was performed analogously for nobelium in ref. 33, which was also used for the evaluation of 255No. Here, an uncertainty of 0.007 cm−1 of the reference isotope 254No in the argon buffer-gas atmosphere as stated in ref. 32 was assumed to contribute to the isotope-shift measurement’s uncertainty.

    The error on δr2A,A results from a propagation of the isotope-shift uncertainty, whereas the uncertainty from the atomic coupling factors is included as a systematic uncertainty. For the field-shift constant, which was predicted with F = −3.14 cm−1 fm−2, the uncertainty evaluated from the atomic calculations amounts to 10%.

    Although the mass shift can be neglected for the calculation of δr2A,A, a contribution of the mass shift to the final uncertainty is nevertheless considered.

    The NMS can be calculated to MNMS = meν ≈ 0.4 THz × u with the transition frequency ν and the electron mass me. So far, the SMS contribution can be only estimated. For sp transitions as in our case, the SMS is usually on the order of the NMS. For transitions including orbitals with a higher main quantum number, it can be more than ten times larger. Therefore, a value of 2 THz × u, 5 times larger than the NMS, is considered as a conservative estimate for the contribution to the total systematic uncertainty in the change in mean-square charge radius77.

    The additional effect of the isotope shift depending on the nuclear deformation proposed in ref. 44 was investigated. With the available information on the expected deformation change, this proposed additional effect amounts to −0.003 fm2, which is small compared with the uncertainties and is thus neglected.

    Nuclear-structure models

    Below, we provide a brief description of the models used to interpret experimental findings. All our models are based on the nuclear EDF approach. For a detailed discussion of EDF, see refs. 78,79.

    In this study, calculations using six different EDF models were performed: Fy(IVP) (P.-G.R. & W.N., manuscript in preparation), D1M80, BSkG281, SV-min82 and SLyMR183 (note that this model is called SLyMR13b in ref. 83). This selection aims to represent current EDF models. Concerning the functional form, SV-min and BSkG2 are based on standard Skyrme functionals and density-dependent contact pairing interactions. SLyMR1 uses an extended Skyrme functional, where the density dependences are replaced by an explicit three-body interaction84. D1M is based on the Gogny functional. Finally, Fy(IVP) uses the Fayans functional85,86. SV-min and Fy(IVP) are based on a single-reference approach, whereas D1M and BSkG2 also include approximated beyond-mean-field corrections. SLyMR1 involves explicit configuration mixing and restoration of particle-number and angular-momentum symmetries87,88,89, hence it is a multi-reference approach. The models were calibrated on experimental ground-state properties of finite nuclei but differ in the choice of the calibration data. SV-min and Fy(IVP) include a statistical analysis of the underlying parameterizations. This allows predictions to be given together with a statistical calibration47,48.

    To assess the predictive power of the theory frameworks, we computed three-point differences

    $${\Delta }_{{\mathcal{O}}}^{(3,2)}=\frac{{\mathcal{O}}(Z,N+2)-2{\mathcal{O}}(Z,N)+{\mathcal{O}}(Z,N-2)}{2}$$

    in the binding energy (\({\mathcal{O}}=E\)) or squared charge radius (\({\mathcal{O}}={r}^{2}\)). For N = 82, N = 126 and N = 152, Extended Data Fig. 2 shows predictions of the SV-min and Fy(IVP) models compared with experimental values.

    Both EDF frameworks reproduce the trends in the shell gaps and agree with the data that the N = 152 gap is weak. As discussed in ref. 3, the size of this shell gap strongly depends on model details, see, for example, ref. 18 for the predictions of this subshell with different models. In particular, the Fy(IVP) model reproduces the experimental values for 132Sn and 208Pb, giving confidence also in the value for 252Fm. This is in agreement with the reported smooth trends along the isotopic chains.

    Treatment of odd-A nuclei

    EDF calculations for odd-mass nuclei are not straightforward: solving the self-consistent equations requires the creation of a one-quasiparticle excitation on top of a reference state that is typically associated with an even–even nucleus. For each iteration, identifying the physically relevant quasiparticle while guaranteeing convergence of the self-consistent procedure is a non-trivial task. Most calculations for odd-mass nuclei in this study concern the predicted ground state. In the case of SV-min and Fy(IVP), all one-quasiparticle configurations below 1-MeV excitation energy have been investigated, and the states with lowest energy for each angular-momentum projection K have been examined. It became apparent that the radii vary little with K (variance about 0.001 fm), such that taking the minimal-energy state is an acceptable choice. The other exception is SLyMR1: among the several many-body states with different angular momenta that result from symmetry restoration, we select those states matching the (often tentative) experimental quantum numbers. Although the blocking strategy is common to all models, they differ in their treatment of the blocked quasiparticle. D1M relies on the equal filling approximation90, a computationally efficient approximation that includes the blocking effect of the odd nucleon(s), but ignores the effect of any time-odd currents or densities that might develop due to the polarization effects91. The calculations with BSkG2, Fy(IVP), SLyMR1 and SV-min invoke no approximations in this respect.

    Nuclear-matter properties of EDF-based models

    The leading properties of our models can be characterized in terms of the infinite nuclear-matter properties shown in Extended Data Table 3: saturation density ρsat, binding energy per particle E/A, incompressibility K, (isoscalar) effective mass m*/m, symmetry energy at saturation J, and slope of symmetry energy L. The isoscalar effective mass m*/m shows the largest variation. This parameter impacts the single-particle level density around the Fermi level and hence the magnitude of shell effects. The other matter parameters show fewer variations.

    Predicted charge radii

    In SV-min and Fy(IVP), the charge radii were calculated directly from the charge form factor that contains the proton form factor folded with the intrinsic form factors of the free nucleons, relativistic corrections and the centre-of-mass correction92. A similar procedure is followed for BSkG2 and D1M but without relativistic corrections. It is noted that D1M also adds a quadrupole correction estimated by solving the collective Schrödinger equation with the five-dimensional collective Hamiltonian to the absolute charge radius, as described in ref. 80. In SLyMR1 calculations, the charge radii were computed from the expectation value of the squared point-proton radius operator at the beyond-mean-field level corrected for the finite size of the protons and neutrons88.

    To check that our models produce sensible results for the total charge radii in the heavy actinides, Extended Data Table 4 compares our predictions with the measured radii for 232Th, 238U and 244Pu. Given the high computational cost of multi-reference calculations, for SLyMR1, we report only the value for 238U. The errors given for SV-min and Fy(IVP) are the estimated extrapolation errors from statistical analysis of the underlying χ2 fits. The predictions are in good agreement with available data within uncertainties. This instills confidence in the validity of predictions for fermium and nobelium isotopes.

    The predicted root-mean-square charge radii for fermium and nobelium isotopes are shown in Extended Data Fig. 3. Prediction uncertainties are indicated for SV-min. Unlike for differential radii, the results for the total radii show a larger spread between the models. This complies with the observation that the isoscalar matter for parameters in Extended Data Table 3 differ outside error bands. Following the discussion in ref. 93, one would expect that the radii would be sorted according to saturation densities in Extended Data Table 3. This is not necessarily the case as the data on charge radii were used in the calibration of individual models and this spoils the correlation93. Still, the inter-model similarity of charge radii is related to similar saturation densities of our models.

    Multipole decomposition of densities

    The fermium isotopes under consideration are all deformed in shape, and hence their intrinsic densities are non-spherical. To make an inter-model comparison of proton densities ρp, we carry out a multipole decomposition. To this end, we define a radial proton density ρp,ℓm(r) as an angular average:

    $${\rho }_{{\rm{p}},{\ell }m}(r)=\int {Y}_{{\ell }m}(\varOmega ){\rho }_{{\rm{p}}}({\bf{r}})\,{\rm{d}}\varOmega .$$

    (2)

    Here Ylm is the spherical harmonics of degree l and order m and Ω represents angular coordinates. For an axially deformed nucleus, m = 0 and we denote ρp, ≡ ρp,ℓm=0. These radial densities are related by a Fourier transformation to the radial scattering form factors typically discussed in the context of electron scattering94. The root-mean-square point-proton radius can be obtained from the monopole component of the proton density:

    $$\langle {r}_{{\rm{p}}}^{2}\rangle =\frac{\sqrt{4{\rm{\pi }}}}{A}\int {\rm{d}}r\,{r}^{4}{\rho }_{{\rm{p}},00}(r),$$

    (3)

    where A is the mass number of the nucleus.

    Higher-multipolarity radial densities define axial shape deformation parameters:

    $${\beta }_{{\ell }}=4{\rm{\pi }}\frac{\langle {r}^{{\ell }}{Y}_{{\ell }0}\rangle }{3Z{R}^{{\ell }}}=4{\rm{\pi }}\frac{\int \,{\rm{d}}r\,{r}^{{\ell }+2}{\rho }_{{\rm{p}},{\ell }0}(r)}{3Z{R}^{{\ell }}},$$

    (4)

    where R = 1.2A1/3 fm. The calculated quadrupole ( = 2) and hexadecapole ( = 4) radial densities are shown in Fig. 3.

    For the nuclei we study here, single-reference models predict nuclear densities that are deformed but retain both reflection symmetry and axial symmetry. The multi-reference techniques used in SLyMR1 render the comparison with the other models slightly more intricate. For comparison purposes, we use the multipole decomposition of the density of the deformed reference state with lowest particle-number restored energy. This deformed state also breaks axial symmetry. However, the triaxial components are small compared with the axial ones, as also found within the D1M and BSkG2 calculations.

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