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Superconducting sensors doped with rare isotopes have recently demonstrated powerful sensing performance for sub-keV radiation from nuclear decay. Here, we report the first high-resolution recoil spectroscopy of a single, selected nuclear state using superconducting tunnel junction (STJ) sensors. The STJ sensors were used to measure the eV-scale nuclear recoils produced in $^7$Be electron capture decay in coincidence with the 478 keV $\gamma$-ray emitted in decays to the excited nuclear state in $^7$Li. Details of the Doppler broadened recoil spectrum depend on the slow-down dynamics of the recoil ion and can constrain the interaction potential between the recoiling Li and the Ta matrix of the STJ sensor. The results have implications in several areas from nuclear structure and stopping powers at eV-scale energies to direct searches for dark matter, neutrino mass measurements, and other physics beyond the standard model.

Mass measurements with the ISOLTRAP mass spectrometer at CERN-ISOLDE improve mass uncertainties of neutron-deficient tin isotopes towards doubly-magic $^{100}$Sn. The mass uncertainty of $^{103}$Sn was reduced by a factor of 4, and the new value for the mass excess of -67104(18) keV is compared with nuclear \textit{ab initio} and density functional theory calculations. Based on these results and local trends in the mass surface, the masses of $^{101,103}$Sn, as determined through their $Q_{\textrm{EC}}$ values, were found to be inconsistent with the new results. From our measurement for $^{103}$Sn, we extrapolate the mass excess of $^{101}$Sn to -60005(300) keV, which is significantly more bound than previously suggested. By correcting the mass values for $^{101,103}$Sn, we also adjust the values of $^{104}$Sb, $^{105,107}$Te, $^{108}$I, $^{109,111}$Xe, and $^{112}$Cs near the proton drip line which are connected through their $\alpha$- and proton $Q$-values. The results show an overall smoothening of the mass surface, suggesting the absence of deformation energy above the ${N=50}$ shell closure., Comment: 13 pages, 6 figures

Federated Learning (FL) is gaining traction as a learning paradigm for training Machine Learning (ML) models in a decentralized way. Batch Normalization (BN) is ubiquitous in Deep Neural Networks (DNN), as it improves convergence and generalization. However, BN has been reported to hinder performance of DNNs in heterogeneous FL. Recently, the FedTAN algorithm has been proposed to mitigate the effect of heterogeneity on BN, by aggregating BN statistics and gradients from all the clients. However, it has a high communication cost, that increases linearly with the depth of the DNN. SCAFFOLD is a variance reduction algorithm, that estimates and corrects the client drift in a communication-efficient manner. Despite its promising results in heterogeneous FL settings, it has been reported to underperform for models with BN. In this work, we seek to revive SCAFFOLD, and more generally variance reduction, as an efficient way of training DNN with BN in heterogeneous FL. We introduce a unified theoretical framework for analyzing the convergence of variance reduction algorithms in the BN-DNN setting, inspired of by the work of Wang et al. 2023, and show that SCAFFOLD is unable to remove the bias introduced by BN. We thus propose the BN-SCAFFOLD algorithm, which extends the client drift correction of SCAFFOLD to BN statistics. We prove convergence using the aforementioned framework and validate the theoretical results with experiments on MNIST and CIFAR-10. BN-SCAFFOLD equals the performance of FedTAN, without its high communication cost, outperforming Federated Averaging (FedAvg), SCAFFOLD, and other FL algorithms designed to mitigate BN heterogeneity.

The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST) experiment searches for evidence of heavy neutrino mass eigenstates in the nuclear electron capture decay of $^7$Be by precisely measuring the recoil energy of the $^7$Li daughter. In Phase-III, the BeEST experiment has been scaled from a single superconducting tunnel junction (STJ) sensor to a 36-pixel array to increase sensitivity and mitigate gamma-induced backgrounds. Phase-III also uses a new continuous data acquisition system that greatly increases the flexibility for signal processing and data cleaning. We have developed procedures for signal processing and spectral fitting that are sufficiently robust to be automated for large data sets. This article presents the optimized procedures before unblinding the majority of the Phase-III data set to search for physics beyond the standard model.

We report on mass measurements of three long-lived states in $^{114}$Rh performed with the JYFLTRAP Penning-trap mass spectrometer: the ground state and two isomers with estimated half-lives of about one second. The used Phase-Imaging Ion-Cyclotron-Resonance technique allowed for the discovery of a so far unknown second long-lived isomer. All three states were produced directly in proton-induced fission on a uranium target, whereas only the isomeric states were populated in the $\beta$ decay of the $^{114}$Ru ground state with spin-parity $0^+$. We propose spin-parity assignments of $(6^-)$ for the ground state, and $(3^+)$ and $(0^-)$ for the isomers. They resolve the puzzle of anomalous fission yields of this isotope despite the existing literature assigning a low angular momentum to the ground state. The experimental evidence is further supported by a detailed analysis based on mean-field calculations with the BSkG3 model. As for many other nuclei in this mass region, considering triaxial shapes is decisive for the interpretation of low-lying states of this nucleus. The discovery of a new isomer in $^{114}$Rh and our theoretical work challenge the currently adopted spin-parity assignments in this and several other odd-odd neutron-rich Rh isotopes., Comment: 11 pages, 4 figures

The mass of $^{109}$Ag isotope was measured with respect to $^{110}$Cd with the phase-imaging ion-cyclotron-resonance technique using the JYFLTRAP double Penning trap at the IGISOL facility. By combining this new result with the known spectroscopic information, the $Q_\beta$ value of $405(135)$ eV between the $6^+$ isomer of $^{110}$Ag and the $5^+_2$ state in $^{110}$Cd was determined. This is the lowest $Q_\beta$ for any allowed transition observed to date. The nuclear shell-model results were performed with the {\sc kshell} code employing the \textit{jj45pnb} interaction, and combined with the state-of-the-art atomic calculations. The theoretical partial half-life, $2.23^{+5.24}_{-1.28} \times 10^7$ years, and the resulting branching ratio, $3.07^{+4.16}_{-2.15} \times 10^{-8}$, combined with a viable production method, thermal-neutron capture on stable $^{109}$Ag, make $^{110}$Ag$^{m}$ as a promising candidate for future antineutrino mass measurement experiments., Comment: 9 pages, 3 figures, 1 additional figure and 3 tables in Supplemental material

Recent advancements in multimodal Variational AutoEncoders (VAEs) have highlighted their potential for modeling complex data from multiple modalities. However, many existing approaches use relatively straightforward aggregating schemes that may not fully capture the complex dynamics present between different modalities. This work introduces a novel multimodal VAE that incorporates a Markov Random Field (MRF) into both the prior and posterior distributions. This integration aims to capture complex intermodal interactions more effectively. Unlike previous models, our approach is specifically designed to model and leverage the intricacies of these relationships, enabling a more faithful representation of multimodal data. Our experiments demonstrate that our model performs competitively on the standard PolyMNIST dataset and shows superior performance in managing complex intermodal dependencies in a specially designed synthetic dataset, intended to test intricate relationships.

We report on high-precision atomic mass measurements of $^{148\text{-}153}$La and $^{151}$Ce performed with the JYFLTRAP double Penning trap using the Phase-Imaging Ion-Cyclotron-Resonance technique. The masses of $^{152,153}$La were experimentally determined for the first time. We confirm the sharp kink in the two-neutron separation energies at the neutron number ${N=93}$ in the cerium (${Z=58}$) isotopic chain. Our precision mass measurements of the most exotic neutron-rich lanthanum (${Z=57}$) isotopes reveal a sudden increase in two-neutron separation energies from ${N=92}$ to ${N=93}$. Unlike in the cerium isotopic chain, the kink is not sharp but extends to ${N=94}$ forming a prominent bump. The gain in energy is about 0.4 MeV, making it one of the strongest changes in two-neutron separation energies over the whole chart of nuclides, away from nuclear shell closures. The results call for further studies to elucidate the structure of neutron-rich lanthanum isotopes., Comment: 9 pages, 4 figures

We have performed high-precision mass measurements of neutron-rich rare-earth Tb, Dy and Ho isotopes using the Phase-Imaging Ion-Cyclotron-Resonance technique at the JYFLTRAP double Penning trap. We report on the first experimentally determined mass values for $^{169}$Tb, $^{170}$Dy and $^{171}$Dy, as well as the first high-precision mass measurements of $^{169}$Dy and $^{169\text{-}171}$Ho. For $^{170}$Ho, the two long-lived ground and isomeric states were resolved and their mass measured, yielding an isomer excitation energy of $E_\text{exc}=150.8(54)$~keV. In addition, we have performed independent crosschecks of previous Penning-trap values obtained for $^{167\text{,} 168}$Tb and $^{167\text{,} 168}$Dy. We have extended the systematics of two-neutron separation energies to the neutron midshell at $N=104$ in all of the studied isotopic chains. Our updated and new mass measurements provide better mass-related constraints for the neutron-capture reaction rates relevant to the astrophysical rapid neutron capture (r) process. The r-process abundances calculated with the new mass values seem to produce a steeper minimum at A=170 and differ by around 15-30\% from the abundances computed with the Atomic Mass Evaluation 2020 values., Comment: 10 pages, 7 figures

Physics-Informed Neural Networks (PINNs) have gained considerable interest in diverse engineering domains thanks to their capacity to integrate physical laws into deep learning models. Recently, geometry-aware PINN-based approaches that employ the strong form of underlying physical system equations have been developed with the aim of integrating geometric information into PINNs. Despite ongoing research, the assessment of PINNs in problems with various geometries remains an active area of investigation. In this work, we introduce a novel physics-informed framework named the Geometry-Aware Deep Energy Method (GADEM) for solving structural mechanics problems on different geometries. As the weak form of the physical system equation (or the energy-based approach) has demonstrated clear advantages compared to the strong form for solving solid mechanics problems, GADEM employs the weak form and aims to infer the solution on multiple shapes of geometries. Integrating a geometry-aware framework into an energy-based method results in an effective physics-informed deep learning model in terms of accuracy and computational cost. Different ways to represent the geometric information and to encode the geometric latent vectors are investigated in this work. We introduce a loss function of GADEM which is minimized based on the potential energy of all considered geometries. An adaptive learning method is also employed for the sampling of collocation points to enhance the performance of GADEM. We present some applications of GADEM to solve solid mechanics problems, including a loading simulation of a toy tire involving contact mechanics and large deformation hyperelasticity. The numerical results of this work demonstrate the remarkable capability of GADEM to infer the solution on various and new shapes of geometries using only one trained model., Comment: 28 pages, 26 figures, 4 tables

Despite their high relative abundance in our Universe, neutrinos are the least understood fundamental particles of nature. They also provide a unique system to study quantum coherence and the wavelike nature of particles in fundamental systems due to their extremely weak interaction probabilities. In fact, the quantum properties of neutrinos emitted in experimentally relevant sources are virtually unknown and the spatial extent of the neutrino wavepacket is only loosely constrained by reactor neutrino oscillation data with a spread of 13 orders of magnitude. Here, we present the first direct limits of this quantity through a new experimental concept to extract the energy width, $\sigma_{\textrm{N},E}$, of the recoil daughter nucleus emitted in the nuclear electron capture (EC) decay of $^7$Be. The final state in the EC decay process contains a recoiling $^7$Li nucleus and an electron neutrino ($\nu_e$) which are entangled at their creation. The $^7$Li energy spectrum is measured to high precision by directly embedding $^7$Be radioisotopes into a high resolution superconducting tunnel junction that is operated as a cryogenic sensor. The lower limit on the spatial uncertainty of the recoil daughter was found to be $\sigma_{\textrm{N}, x} \geq 6.2$\,pm, which implies the final-state system is localized at a scale more than a thousand times larger than the nucleus itself. From this measurement, the first direct lower limits on the spatial extent of the neutrino wavepacket were extracted using two different theoretical methods. These results have wide-reaching implications in several areas including the nature of spatial localization at sub-atomic scales, interpretation of neutrino physics data, and the potential reach of future large-scale experiments., Comment: 20 pages, 3 figures, v3 corrects and updates one of the wavepacket width calculations

The masses of $^{84}$Br, $^{105}$Mo, $^{115,119,121}$Pd, $^{122}$Ag, $^{127,129}$In, $^{132}$Sb and their respective isomeric states have been measured with the JYFLTRAP Penning trap mass spectrometer using the phase-imaging ion-cyclotron-resonance technique. The excitation energies of the isomeric states in $^{132}$Sb and $^{119}$Pd were experimentally determined for the first time, while for $^{84}$Br, $^{115}$Pd and $^{127,129}$In, the precision of the mass values was substantially improved. In $^{105}$Mo and $^{121}$Pd there were no signs of a long-lived isomeric state. The ground-state measurements of $^{119}$Pd and $^{122}$Ag indicated that both are significantly more bound than the literature values. For $^{122}$Ag, there was no indication of a proposed third long-lived state. The results for the $N=49$ nucleus $^{84}$Br and isomers close to doubly magic $^{132}$Sn have been compared to the shell-model and the microscopic quasiparticle-phonon model calculations., Comment: 14 pages, 10 figures

We report on new precision mass measurements of neutron-rich $^{137}$Sb and $^{136-142}$I isotopes from the JYFLTRAP double Penning trap mass spectrometer. We confirm the value from the previous Penning-trap measurement of $^{137}$Sb at the Canadian Penning Trap and therefore rule out the conflicting result from the Experimental Storage Ring. The ground state and isomer in $^{136}$I were resolved and measured directly for the first time. The isomer excitation energy, $E_x = 215.1(43)$ keV, agrees with the literature but is three times more precise. The measurements have improved the precision of the mass values and confirmed previous results in the majority of cases. However, for $^{138,140}$I the results differ by 17(6) keV and 23(12) keV, respectively. This could be explained by an unresolved contamination or different ratio of unresolved isomeric states in the case of $^{140}$I., Comment: 8 pages, 6 figures

Long-term operation of nuclear steam generators can result in the occurrence of clogging, a deposition phenomenon that may increase the risk of mechanical and vibration loadings on tube bundles and internal structures as well as potentially affecting their response to hypothetical accidental transients. To manage and prevent this issue, a robust maintenance program that requires a fine understanding of the underlying physics is essential. This study focuses on the utilization of a clogging simulation code developed by EDF R\&D. This numerical tool employs specific physical models to simulate the kinetics of clogging and generates time dependent clogging rate profiles for particular steam generators. However, certain parameters in this code are subject to uncertainties. To address these uncertainties, Monte Carlo simulations are conducted to assess the distribution of the clogging rate. Subsequently, polynomial chaos expansions are used in order to build a metamodel while time-dependent Sobol' indices are computed to understand the impact of the random input parameters throughout the whole operating time. Comparisons are made with a previous published study and additional Hilbert-Schmidt independence criterion sensitivity indices are computed. Key input-output dependencies are exhibited in the different chemical conditionings and new behavior patterns in high-pH regimes are uncovered by the sensitivity analysis. These findings contribute to a better understanding of the clogging phenomenon while opening future lines of modeling research and helping in robustifying maintenance planning.

The stability of a dark matter detector on the timescale of a few years is a key requirement due to the large exposure needed to achieve a competitive sensitivity. It is especially crucial to enable the detector to potentially detect any annual event rate modulation, an expected dark matter signature. In this work, we present the performance history of the DarkSide-50 dual-phase argon time projection chamber over its almost three-year low-radioactivity argon run. In particular, we focus on the electroluminescence signal that enables sensitivity to sub-keV energy depositions. The stability of the electroluminescence yield is found to be better than 0.5%. Finally, we show the temporal evolution of the observed event rate around the sub-keV region being consistent to the background prediction., Comment: 13 pages, 5 figures

The BeEST experiment is a precision laboratory search for physics beyond the standard model that measures the electron capture decay of $^7$Be implanted into superconducting tunnel junction (STJ) detectors. For Phase-III of the experiment, we constructed a continuously sampling data acquisition system to extract pulse shape and timing information from 16 STJ pixels offline. Four additional pixels are read out with a fast list-mode digitizer, and one with a nuclear MCA already used in the earlier limit-setting phases of the experiment. We present the performance of the data acquisition system and discuss the relative advantages of the different digitizers., Comment: 8 pages, 4 figures, proceedings for The 20th International Conference on Low Temperature Detectors

We report on the precise mass measurements of the $^{91}$Sr and $^{95}$Y isotopes performed using the JYFLTRAP double Penning trap mass spectrometer. The mass-excess values from this work, ${\mathrm{ME}(^{91}\mathrm{Sr}) = -83645.5(13)}$ keV and ${\mathrm{ME}(^{95}\mathrm{Y}) = -81226.4(10)}$ keV, deviate by 6.5(52) keV and $-18(7)$ keV from the Atomic Mass Evaluation 2020 (AME20). In the case of $^{91}$Sr the new result disagrees with the ISOLTRAP value, while for $^{95}$Y, it agrees with the older JYFLTRAP value., Comment: 6 pages, 2 figures

Isomers close to doubly-magic $^{78}_{28}$Ni$_{50}$ provide essential information on the shell evolution and shape coexistence near the ${Z=28}$ and ${N=50}$ double shell closure. We report the excitation energy measurement of the $1/2^{+}$ isomer in $^{79}_{30}$Zn$_{49}$ through independent high-precision mass measurements with the JYFLTRAP double Penning trap and with the ISOLTRAP Multi-Reflection Time-of-Flight Mass Spectrometer. We unambiguously place the $1/2^{+}$ isomer at 942(10) keV, slightly below the $5/2^+$ state at 983(3) keV. With the use of state-of-the-art shell-model diagonalizations, complemented with Discrete Non Orthogonal shell-model calculations which are used here the first time to interpret shape coexistence, we find low-lying deformed intruder states, similar to other ${N=49}$ isotones. The $1/2^{+}$ isomer is interpreted as the band-head of a low-lying deformed structure akin to a predicted low-lying deformed band in $^{80}$Zn, and points to shape coexistence in $^{79,80}$Zn similar to the one observed in $^{78}$Ni. The results make a strong case for confirming the claim of shape coexistence in this key region of the nuclear chart., Comment: 10 pages, three figures, two tables. Accepted to Phys. Rev. Lett

This paper deals with uncertainty quantification and out-of-distribution detection in deep learning using Bayesian and ensemble methods. It proposes a practical solution to the lack of prediction diversity observed recently for standard approaches when used out-of-distribution (Ovadia et al., 2019; Liu et al., 2021). Considering that this issue is mainly related to a lack of weight diversity, we claim that standard methods sample in "over-restricted" regions of the weight space due to the use of "over-regularization" processes, such as weight decay and zero-mean centered Gaussian priors. We propose to solve the problem by adopting the maximum entropy principle for the weight distribution, with the underlying idea to maximize the weight diversity. Under this paradigm, the epistemic uncertainty is described by the weight distribution of maximal entropy that produces neural networks "consistent" with the training observations. Considering stochastic neural networks, a practical optimization is derived to build such a distribution, defined as a trade-off between the average empirical risk and the weight distribution entropy. We develop a novel weight parameterization for the stochastic model, based on the singular value decomposition of the neural network's hidden representations, which enables a large increase of the weight entropy for a small empirical risk penalization. We provide both theoretical and numerical results to assess the efficiency of the approach. In particular, the proposed algorithm appears in the top three best methods in all configurations of an extensive out-of-distribution detection benchmark including more than thirty competitors., Comment: 60 pages, 9 figures, 6 tables

Highly precise measurements of the $^{99}$Tc beta spectrum were performed in two laboratories using metallic magnetic calorimeters. Independent sample preparations, evaluation methods and analyses yield consistent results and the spectrum could be measured down to less than 1 keV. Consistent beta spectra were also obtained via cross-evaluations of the experimental data sets. An additional independent measurement with silicon detectors in a $4\pi$ configuration confirms the spectrum shape above 25 keV. Detailed theoretical calculations were performed including nuclear structure and atomic effects. The spectrum shape was found to be sensitive to the effective value of the axial-vector coupling constant. Combining measurements and predictions, we extracted $Q_{\beta}=$295.82(16) keV and $g_A^{\text{eff}} = 1.530 (83)$. Furthermore, we derived the mean energy of the beta spectrum $\overline{E}_{\beta}$=98.45(20) keV, $\log f = -0.47660 (22)$ and $\log ft = 12.3478 (23)$., Comment: 15 pages, 9 figures, adjusted the legend symbols in figures 6-9 to the format (italics, subscripts etc.) used in the text [version 2], corrected assignment of author affiliations and capital lettering in references [version 3]

We report on the first direct mass measurements of the $^{118,119}$Cd and $^{117-119}$In isotopes performed at the Ion Guide Isotope Separator On-Line facility using the JYFLTRAP double Penning trap mass spectrometer. The masses of $^{117}$In and $^{118}$Cd isotopes are in agreement with the literature, while $^{118,119}$In and $^{119}$Cd differ from literature by 49, 13 and 85 keV (6.1, 1.9 and 2.1 standard deviations), respectively. The excitation energy of the $^{118}$In first isomeric state, $E_x = 40.3(25)$ keV, was determined for the first time. The updated mass values removed the fluctuations observed in the two-neutron separation energies and lead to a smoother linear decrease of both isotopic chains. The $\log(ft)$ value for the $^{118}$Cd decay is also found to increase from 3.93(6) to 4.089(8). The reported results indicate an absence of significant structural changes around $N=70$., Comment: 8 pages, 3 figures

We report on the precise mass measurement of the $^{173}$Hf isotope performed at the Ion Guide Isotope Separator On-Line facility using the JYFLTRAP double Penning trap mass spectrometer. The new mass-excess value, ${\mathrm{ME} = -55390.8(30)}$ keV, is in agreement with the literature while being nine times more precise. The newly determined $^{173}$Hf electron-capture $Q$ value, $Q_{EC} = 1490.2(34)$ keV, allows us to firmly reject the population of an excited state at 1578 keV in $^{173}$Lu and 11 transitions tentatively assigned to the decay of $^{173}$Hf. Our refined mass value of $^{173}$Hf reduces mass-related uncertainties in the reaction rate of $^{174}$Hf$(\gamma,n)^{173}$Hf. Thus, the rate for the main photodisintegration destruction channel of the $p$ nuclide $^{174}$Hf in the relevant temperature region for the $\gamma$ process is better constrained., Comment: 5 pages, 2 figures

The atomic exchange effect will lead to a significant increase in the probability density of $\beta$ decays below a few keV. This effect is very important for scientific experiments that performed by low-energy electron spectroscopy measurements. However, the atomic exchange effect involves multi-electron interactions, especially for a system with 82 electrons such as lead. Different parameters will lead to different trends in the energy spectrum predicted by the theory, so it is urgent to carry out experimental measurements to provide parameter limits for the theory. The probability increase brought about by the atomic exchange effect is most obvious near 0keV, and the $\beta$ energy spectrum is accurately measured near this energy point, so as to provide constraints for the physical model of atomic exchange. However, it is extremely difficult to measure the $\beta$ energy spectrum at 0keV due to the limitations of electronic noise and internal conversion effects. The excited decay path of $^{210}$Pb was taken as the observation object,by measuring the total energy spectrum of $\beta$ rays and cascaded gamma rays, the precise measurement of the $\beta$ energy spectrum near 0keV has been completed. The analysis of the $\beta$ energy spectrum of $^{210}$Pb gives the following conclusions. The experimental results first verified the theory that the exchange effect causes the probability increase at the low energy end near 0keV. At the same time, the experimental results are higher than the existing predictions of the atomic exchange effect. At least for Pb element, all the electron shells have played a role in improving the probability density of the low end of the $\beta$ energy spectrum. This discovery will promote the theoretical calculation of the $\beta$ energy spectrum of $^{214}$Pb, at the same time, it also indicates that the reactor neutrinos have a higher probability density at the omnipotent end.

Dark matter induced event rate in an Earth-based detector is predicted to show an annual modulation as a result of the Earth's orbital motion around the Sun. We searched for this modulation signature using the ionization signal of the DarkSide-50 liquid argon time projection chamber. No significant signature compatible with dark matter is observed in the electron recoil equivalent energy range above $40~{\rm eV_{ee}}$, the lowest threshold ever achieved in such a search., Comment: 10 pages, 5 figures

Generative design is an increasingly important tool in the industrial world. It allows the designers and engineers to easily explore vast ranges of design options, providing a cheaper and faster alternative to the trial and failure approaches. Thanks to the flexibility they offer, Deep Generative Models are gaining popularity amongst Generative Design technologies. However, developing and evaluating these models can be challenging. The field lacks accessible benchmarks, in order to evaluate and compare objectively different Deep Generative Models architectures. Moreover, vanilla Deep Generative Models appear to be unable to accurately generate multi-components industrial systems that are controlled by latent design constraints. To address these challenges, we propose an industry-inspired use case that incorporates actual industrial system characteristics. This use case can be quickly generated and used as a benchmark. We propose a Meta-VAE capable of producing multi-component industrial systems and showcase its application on the proposed use case.

We report on precision mass measurements of $^{113,115,117}$Ru performed with the JYFLTRAP double Penning trap mass spectrometer at the Accelerator Laboratory of University of Jyv\"askyl\"a. The phase-imaging ion-cyclotron-resonance technique was used to resolve the ground and isomeric states in $^{113,115}$Ru and enabled for the first time a measurement of the isomer excitation energies, $E_x(^{113}$Ru$^{m})=100.5(8)$ keV and $E_x(^{115}$Ru$^{m})=129(5)$ keV. The ground state of $^{117}$Ru was measured using the time-of-flight ion-cyclotron-resonance technique. The new mass-excess value for $^{117}$Ru is around 36 keV lower and 7 times more precise than the previous literature value. With the more precise ground-state mass values, the evolution of the two-neutron separation energies is further constrained and a similar trend as predicted by the BSkG1 model is obtained up to the neutron number $N=71$., Comment: 12 pages, 9 figures, submitted to Physical Review C

The excitation energy of the 1/2$^-$ isomer in $^{99}$In at ${N=50}$ is measured to be 671(37) keV and the mass uncertainty of the 9/2$^+$ ground state is significantly reduced using the ISOLTRAP mass spectrometer at ISOLDE/CERN. The measurements exploit a major improvement in the resolution of the multi-reflection time-of-flight mass spectrometer. The results reveal an intriguing constancy of the $1/2^-$ isomer excitation energies in neutron-deficient indium that persists down to the $N = 50$ shell closure, even when all neutrons are removed from the valence shell. This trend is used to test large-scale shell model, \textit{ab initio}, and density functional theory calculations. The models have difficulties describing both the isomer excitation energies and ground-state electromagnetic moments along the indium chain., Comment: 13 pages, 4 figures

The summation method for the calculation of reactor $\bar{\nu}_e$ fluxes and spectra is methodically revised and improved. For the first time, a complete uncertainty budget accounting for all known effects likely to impact these calculations is proposed. Uncertainties of a few percents at low energies and ranging up to 20% at high energies are obtained on the calculation of a typical reactor $\bar{\nu}_e$ spectrum. Although huge improvements have been achieved over the past decade, the quality and incompleteness of the present day evaluated nuclear decay data still limit the accuracy of the calculations and therefore dominate by far these uncertainties. Pushing the $\beta$-decay modeling of the thousands of branches making a reactor $\bar{\nu}_e$ spectrum to a high level of details comparatively brings modest changes. In particular, including nuclear structure calculations in the evaluation of the non-unique forbidden transitions gives a smaller impact than anticipated in past studies. Finally, this new modeling is challenged against state-of-the-art predictions and measurements. While a good agreement is observed with the most recent Inverse Beta Decay measurements of reactor $\bar{\nu}_e$ fluxes and spectra, it is unable to properly describe the reference aggregate $\beta$ spectra measured at the Institut Laue-Langevin High-Flux reactor in the 80s. This result adds to recent suspicions $\beta$ the reliability of these data and preferentially points toward a misprediction of the $^{235}$U $\bar{\nu}_e$ spectrum., Comment: Reformatted figures. Added supplementary materials

We consider the problem of uncertainty quantification in high dimensional regression and classification for which deep ensemble have proven to be promising methods. Recent observations have shown that deep ensemble often return overconfident estimates outside the training domain, which is a major limitation because shifted distributions are often encountered in real-life scenarios. The principal challenge for this problem is to solve the trade-off between increasing the diversity of the ensemble outputs and making accurate in-distribution predictions. In this work, we show that an ensemble of networks with large weights fitting the training data are likely to meet these two objectives. We derive a simple and practical approach to produce such ensembles, based on an original anti-regularization term penalizing small weights and a control process of the weight increase which maintains the in-distribution loss under an acceptable threshold. The developed approach does not require any out-of-distribution training data neither any trade-off hyper-parameter calibration. We derive a theoretical framework for this approach and show that the proposed optimization can be seen as a "water-filling" problem. Several experiments in both regression and classification settings highlight that Deep Anti-Regularized Ensembles (DARE) significantly improve uncertainty quantification outside the training domain in comparison to recent deep ensembles and out-of-distribution detection methods. All the conducted experiments are reproducible and the source code is available at \url{https://github.com/antoinedemathelin/DARE}., Comment: 26 pages, 9 figures

Accelerator-based techniques are one of the leading ways to produce radioactive nuclei. In this work, the Isotope Separation On-Line method was employed at the CERN-ISOLDE facility to produce neptunium and plutonium from a uranium carbide target material using 1.4-GeV protons. Neptunium and plutonium were laser-ionized and extracted as 30-keV ion beams. A Multi-Reflection Time-of-Flight mass spectrometer was used for ion identification by means of time-of-flight measurements as well as for isobaric separation. Isotope shifts were investigated for the 395.6-nm ground state transition in $^{236,237,239}$Np and the 413.4-nm ground state transition in $^{236,239,240}$Pu. Rates of $^{235-241}$Np and $^{234-241}$Pu ions were measured and compared with predictions of in-target production mechanisms simulated with GEANT4 and FLUKA to elucidate the processes by which these nuclei, which contain more protons than the target nucleus, are formed. $^{241}$Pu is the heaviest nuclide produced and identified at a proton-accelerator-driven facility to date. We report the availability of neptunium and plutonium as two additional elements at CERN-ISOLDE and discuss the limit of accelerator-based isotope production at high-energy proton accelerator facilities for nuclides in the actinide region., Comment: 12 pages, 12 figures

The use of radioactive molecules for fundamental physics research is a developing interdisciplinary field limited dominantly by their scarce availability. In this work, radioactive molecular ion beams containing actinide nuclei extracted from uranium carbide targets are produced via the Isotope Separation On-Line technique at the CERN-ISOLDE facility. Two methods of molecular beam production are studied: extraction of molecular ion beams from the ion source, and formation of molecular ions from the mass-separated ion beam in a gas-filled radio-frequency quadrupole ion trap. Ion currents of U$^+$, UO$_{1-3}^+$, UC$_{1-3}^+$, UF$_{1-4}^+$, UF$_{1,2}$O$_{1,2}^+$ are reported. Metastable tantalum and uranium fluoride molecular ions are identified. Formation of UO$_{1-3}^+$, U(OH)$_{1-3}^+$, UC$_{1-3}^+$, UF$_{1,2}$O$_{1,2}^+$ from mass-separated beams of U$^+$, UF$_{1,2}^+$ with residual gas is observed in the ion trap. The effect of trapping time on molecular formation is presented., Comment: 6 pages, 7 figures

We present a novel approach for the search of dark matter in the DarkSide-50 experiment, relying on Bayesian Networks. This method incorporates the detector response model into the likelihood function, explicitly maintaining the connection with the quantity of interest. No assumptions about the linearity of the problem or the shape of the probability distribution functions are required, and there is no need to morph signal and background spectra as a function of nuisance parameters. By expressing the problem in terms of Bayesian Networks, we have developed an inference algorithm based on a Markov Chain Monte Carlo to calculate the posterior probability. A clever description of the detector response model in terms of parametric matrices allows us to study the impact of systematic variations of any parameter on the final results. Our approach not only provides the desired information on the parameter of interest, but also potential constraints on the response model. Our results are consistent with recent published analyses and further refine the parameters of the detector response model., Comment: 24 pages, 12 figures, 1 table

Physics-Informed Neural Networks (PINNs) have gained much attention in various fields of engineering thanks to their capability of incorporating physical laws into the models. PINNs integrate the physical constraints by minimizing the partial differential equations (PDEs) residuals on a set of collocation points. The distribution of these collocation points appears to have a huge impact on the performance of PINNs and the assessment of the sampling methods for these points is still an active topic. In this paper, we propose a Fixed-Budget Online Adaptive Learning (FBOAL) method, which decomposes the domain into sub-domains, for training collocation points based on local maxima and local minima of the PDEs residuals. The effectiveness of FBOAL is demonstrated for non-parameterized and parameterized problems. The comparison with other adaptive sampling methods is also illustrated. The numerical results demonstrate important gains in terms of the accuracy and computational cost of PINNs with FBOAL over the classical PINNs with non-adaptive collocation points. We also apply FBOAL in a complex industrial application involving coupling between mechanical and thermal fields. We show that FBOAL is able to identify the high-gradient locations and even give better predictions for some physical fields than the classical PINNs with collocation points sampled on a pre-adapted finite element mesh built thanks to numerical expert knowledge. From the present study, it is expected that the use of FBOAL will help to improve the conventional numerical solver in the construction of the mesh., Comment: 22 pages, 30 figures, 3 tables

When analyzing a dataset, it can be useful to assess how smooth the decision boundaries need to be for a model to better fit the data. This paper addresses this question by proposing the quantification of how much should the 'rigid' decision boundaries, produced by an algorithm that naturally finds such solutions, be relaxed to obtain a performance improvement. The approach we propose starts with the rigid decision boundaries of a seed Decision Tree (seed DT), which is used to initialize a Neural DT (NDT). The initial boundaries are challenged by relaxing them progressively through training the NDT. During this process, we measure the NDT's performance and decision agreement to its seed DT. We show how these two measures can help the user in figuring out how expressive his model should be, before exploring it further via model selection. The validity of our approach is demonstrated with experiments on simulated and benchmark datasets., Comment: 12 pages, 3 figures, 3 tables. arXiv admin note: text overlap with arXiv:2006.11458

The bound beta-decay (BoB) of neutron is also known as the two-body neutron decay, which is a rare decay mode into a hydrogen atom and an anti-neutrino. The state of neutrino can be exactly inferred by measuring the state of hydrogen atom, providing a possible pathway to explore new physics. However, this rare decay mode has not yet been observed so far since it was predicted in 1947. The challenge in observing this decay is not only that its cross section is extremely low, equivalent to about branching ratio of the order of $10^{-6}$ of the three-body decay, but also that the final-state hydrogen atom is neutral and has extremely low kinetic energy, which cannot be effectively detected. In this study, we propose a microcalorimeter-based scheme for measuring the kinetic energies of hydrogen atoms produced from BoB of ultracold neutrons, which has a great advantage in terms of accuracy of the energy measurement. In this study, first, several important issues that require rigorous considerations for the decay measurements and possible solutions are discussed. Then, the requirements of the neutron flux and the appropriate structure design of the microcalorimeter are present by theoretical calculations. In short, this paper outlines our proposed novel experimental scheme for observing the BoB mode, addressing the possible solutions to all the necessary problems.

Bias in datasets can be very detrimental for appropriate statistical estimation. In response to this problem, importance weighting methods have been developed to match any biased distribution to its corresponding target unbiased distribution. The seminal Kernel Mean Matching (KMM) method is, nowadays, still considered as state of the art in this research field. However, one of the main drawbacks of this method is the computational burden for large datasets. Building on previous works by Huang et al. (2007) and de Mathelin et al. (2021), we derive a novel importance weighting algorithm which scales to large datasets by using a neural network to predict the instance weights. We show, on multiple public datasets, under various sample biases, that our proposed approach drastically reduces the computational time on large dataset while maintaining similar sample bias correction performance compared to other importance weighting methods. The proposed approach appears to be the only one able to give relevant reweighting in a reasonable time for large dataset with up to two million data., Comment: 16 pages, 3 figures