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This work focuses on developing efficient post-hoc explanations for quantum AI algorithms. In classical contexts, the cooperative game theory concept of the Shapley value adapts naturally to post-hoc explanations, where it can be used to identify which factors are important in an AI's decision-making process. An interesting question is how to translate Shapley values to the quantum setting and whether quantum effects could be used to accelerate their calculation. We propose quantum algorithms that can extract Shapley values within some confidence interval. Our method is capable of quadratically outperforming classical Monte Carlo approaches to approximating Shapley values up to polylogarithmic factors in various circumstances. We demonstrate the validity of our approach empirically with specific voting games and provide rigorous proofs of performance for general cooperative games., Comment: 26 pages, 4 figures, 4 tables, 45 citations

The Projected Gradient Descent (PGD) algorithm is a widely used and efficient first-order method for solving constrained optimization problems due to its simplicity and scalability in large design spaces. Building on recent advancements in the PGD algorithm where an inertial step component has been introduced to improve efficiency in solving constrained optimization problems this study introduces two key enhancements to further improve the algorithm's performance and adaptability in large-scale design spaces. First, univariate constraints (such as design variable bounds constraints) are directly incorporated into the projection step via the Schur complement and an improved active set algorithm with bulk constraints manipulation, avoiding issues with min-max clipping. Second, the update step is decomposed relative to the constraint vector space, enabling a post-projection adjustment based on the state of the constraints and an approximation of the Lagrangian, significantly improving the algorithm's robustness for problems with nonlinear constraints. Applied to a topology optimization problem for heat sink design, the proposed PGD algorithm demonstrates performance comparable to or exceeding that of the Method of Moving Asymptotes (MMA), with minimal parameter tuning. These results position the enhanced PGD as a robust tool for complex optimization problems with large variable space, such as topology optimization problems.

This work introduces a quantum algorithm for computing the arcsine function to an arbitrary accuracy. We leverage a technique from embedded computing and field-programmable gate array (FPGA), called COordinate Rotation DIgital Computer (CORDIC). CORDIC is a family of iterative algorithms that, in a classical context, can approximate various trigonometric, hyperbolic, and elementary functions using only bit shifts and additions. Adapting CORDIC to the quantum context is non-trivial, as the algorithm traditionally uses several non-reversible operations. We detail a method for CORDIC which avoids such non-reversible operations. We propose multiple approaches to calculate the arcsine function reversibly with CORDIC. For n bits of precision, our method has space complexity of order n qubits, a layer count in the order of n times log n, and a CNOT count in the order of n squared. This primitive function is a required step for the Harrow-Hassidim-Lloyd (HHL) algorithm, is necessary for quantum digital-to-analog conversion, can simplify a quantum speed-up for Monte-Carlo methods, and has direct applications in the quantum estimation of Shapley values., Comment: 6 pages, 3 figures, 3 algorithms, pending acceptance at peer-reviewed conference

Porous media are ubiquitous in the fields of energy storage and conversion, catalysis, biomechanics, hydrogeology, and other chemical engineering processes. These media possess high surface-to-volume ratios and their complex channels can restrict and direct the flow. This makes them key components of multiple equipment despite the challenges in selecting design parameters for specific applications. Pore-resolved CFD reveals the effects of their structure at the microscopic scale, but is currently limited by high computing costs and the performance of mesh generation algorithms. This work introduces a RBF-based representation of solids in a massively parallel immersed-boundary framework, enabling both the usage of non-conformal grids and dynamic mesh adaptation. We verify it using the method of manufactured solutions. We validate it using pressure drop measurements through porous silicone monoliths digitized by X-ray computed microtomography for Reynolds numbers up to 30, using grids of 200 M cells distributed over 8 k cores. The reliable model is then used to highlight that pore network structure is the main factor describing pressure evolution and that preferential channels are present at this scale of the porous media. This work opens the door to design and optimize processes by linking microscopic flow to macroscopic properties through the usage of physics-based digital twins of complex porous media., Comment: 26 pages, 18 figures

We report the first detection of coherent elastic neutrino-nucleus scattering (CEvNS) on germanium, measured at the Spallation Neutron Source at Oak Ridge National Laboratory. The Ge-Mini detector of the COHERENT collaboration employs large-mass, low-noise, high-purity germanium spectrometers, enabling excellent energy resolution, and an analysis threshold of 1.5 keV electron-equivalent ionization energy. We observe a on-beam excess of 20.6$_{+7.1}^{-6.3}$ counts with a total exposure of 10.22 GWhkg and we reject the no-CEvNS hypothesis with 3.9 sigma significance. The result agrees with the predicted standard model of particle physics signal rate within 2 sigma., Comment: 7 pages, 5 figures

The amount of light produced by nuclear recoils in scintillating targets is strongly quenched compared to that produced by electrons. A precise understanding of the quenching factor is particularly interesting for WIMP searches and CE{\nu}NS measurements since both rely on nuclear recoils, whereas energy calibrations are more readily accessible from electron recoils. There is a wide variation among the current measurements of the quenching factor in sodium iodide (NaI) crystals, especially below 10 keV, the energy region of interest for dark matter and CE{\nu}NS studies. A better understanding of the quenching factor in NaI(Tl) is of particular interest for resolving the decades-old puzzle in the field of dark matter between the null results of most WIMP searches and the claim for dark matter detection by the DAMA/LIBRA collaboration. In this work, we measured sodium and iodine quenching factors for five small NaI(Tl) crystals grown with similar thallium concentrations and growth procedures. Unlike previous experiments, multiple crystals were tested, with measurements made in the same experimental setup to control systematic effects. The quenching factors agree in all crystals we investigated, and both sodium and iodine quenching factors are smaller than those reported by DAMA/LIBRA. The dominant systematic effect was due to the electron equivalent energy calibration originating from the non-proportional behavior of the NaI(Tl) light yield at lower energies, potentially the cause for the discrepancies among the previous measurements., Comment: 22 pages, 27 figures, 7 tables. arXiv admin note: text overlap with arXiv:2310.07339

We consider the potential for a 10-kg undoped cryogenic CsI detector operating at the Spallation Neutron Source to measure coherent elastic neutrino-nucleus scattering and its sensitivity to discover new physics beyond the standard model. Through a combination of increased event rate, lower threshold, and good timing resolution, such a detector would significantly improve on past measurements. We considered tests of several beyond-the-standard-model scenarios such as neutrino non-standard interactions and accelerator-produced dark matter. This detector's performance was also studied for relevant questions in nuclear physics and neutrino astronomy, namely the weak charge distribution of CsI nuclei and detection of neutrinos from a core-collapse supernova.

Detection of low-energy nuclear recoil events plays a central role in searches for particle dark matter interactions with atomic matter and studies of coherent neutrino scatters. Precise nuclear recoil calibration data allow the responses of these dark matter and neutrino detectors to be characterized and enable in situ evaluation of an experiment's sensitivity to anticipated signals. This article reviews the common methods for detection of nuclear recoil events and the wide variety of techniques that have been developed to calibrate detector response to nuclear recoils. We summarize the main experimental factors that are critical for accurate nuclear recoil calibrations, investigate mitigation strategies for different backgrounds and biases, and discuss how the presentation of calibration results can facilitate comparison between experiments. Lastly, we discuss the challenges for future nuclear recoil calibration efforts and the physics opportunities they may enable., Comment: 25 pages, 4 figures

Description of the data release 10.13139/OLCF/1969085 (https://doi.ccs.ornl.gov/ui/doi/426) from the measurements of the CsI[Na] response to low energy nuclear recoils by the COHERENT collaboration. The release corresponds to the results published in "D. Akimov et al 2022 JINST 17 P10034". We share the data in the form of raw ADC waveforms, provide benchmark values, and share plots to enhance the transparency and reproducibility of our results. This document describes the contents of the data release as well as guidance on the use of the data.

Using an 185-kg NaI[Tl] array, COHERENT has measured the inclusive electron-neutrino charged-current cross section on ${}^{127}$I with pion decay-at-rest neutrinos produced by the Spallation Neutron Source at Oak Ridge National Laboratory. Iodine is one the heaviest targets for which low-energy ($\leq$ 50 MeV) inelastic neutrino-nucleus processes have been measured, and this is the first measurement of its inclusive cross section. After a five-year detector exposure, COHERENT reports a flux-averaged cross section for electron neutrinos of $9.2^{+2.1}_{-1.8} \times 10^{-40}$ cm$^2$. This corresponds to a value that is $\sim$41% lower than predicted using the MARLEY event generator with a measured Gamow-Teller strength distribution. In addition, the observed visible spectrum from charged-current scattering on $^{127}$I has been measured between 10 and 55 MeV, and the exclusive zero-neutron and one-or-more-neutron emission cross sections are measured to be $5.2^{+3.4}_{-3.1} \times 10^{-40}$ and $2.2^{+3.5}_{-2.2} \times 10^{-40}$ cm$^2$, respectively., Comment: 10 pages, 7 figures

Accurate segmentation of thalamic nuclei, crucial for understanding their role in healthy cognition and in pathologies, is challenging to achieve on standard T1-weighted (T1w) magnetic resonance imaging (MRI) due to poor image contrast. White-matter-nulled (WMn) MRI sequences improve intrathalamic contrast but are not part of clinical protocols or extant databases. Here, we introduce Histogram-based polynomial synthesis (HIPS), a fast preprocessing step that synthesizes WMn-like image contrast from standard T1w MRI using a polynomial approximation. HIPS was incorporated into our Thalamus Optimized Multi-Atlas Segmentation (THOMAS) pipeline, developed and optimized for WMn MRI. HIPS-THOMAS was compared to a convolutional neural network (CNN)-based segmentation method and THOMAS modified for T1w images (T1w-THOMAS). The robustness and accuracy of the three methods were tested across different image contrasts, scanner manufacturers, and field strength. HIPS-synthesized images improved intra-thalamic contrast and thalamic boundaries, and their segmentations yielded significantly better mean Dice, lower percentage of volume error, and lower standard deviations compared to both the CNN method and T1w-THOMAS. Finally, using THOMAS, HIPS-synthesized images were as effective as WMn images for identifying thalamic nuclei atrophy in alcohol use disorders subjects relative to healthy controls, with a higher area under the ROC curve compared to T1w-THOMAS (0.79 vs 0.73)., Comment: 5 Figures, 3 Tables, 1 Supplemental Figure, Submitted to Scientific Reports Apr 12 2023

This whitepaper presents the research priorities decided on by attendees of the 2022 Town Meeting for Fundamental Symmetries, Neutrons and Neutrinos, which took place December 13-15, 2022 in Chapel Hill, NC, as part of the Nuclear Science Advisory Committee (NSAC) 2023 Long Range Planning process. A total of 275 scientists registered for the meeting. The whitepaper makes a number of explicit recommendations and justifies them in detail.

Generative Adversarial Networks trained on samples of simulated or actual events have been proposed as a way of generating large simulated datasets at a reduced computational cost. In this work, a novel approach to perform the simulation of photodetector signals from the time projection chamber of the EXO-200 experiment is demonstrated. The method is based on a Wasserstein Generative Adversarial Network - a deep learning technique allowing for implicit non-parametric estimation of the population distribution for a given set of objects. Our network is trained on real calibration data using raw scintillation waveforms as input. We find that it is able to produce high-quality simulated waveforms an order of magnitude faster than the traditional simulation approach and, importantly, generalize from the training sample and discern salient high-level features of the data. In particular, the network correctly deduces position dependency of scintillation light response in the detector and correctly recognizes dead photodetector channels. The network output is then integrated into the EXO-200 analysis framework to show that the standard EXO-200 reconstruction routine processes the simulated waveforms to produce energy distributions comparable to that of real waveforms. Finally, the remaining discrepancies and potential ways to improve the approach further are highlighted., Comment: As accepted by JINST

We measured the nuclear--recoil ionization yield in silicon with a cryogenic phonon-sensitive gram-scale detector. Neutrons from a mono-energetic beam scatter off of the silicon nuclei at angles corresponding to energy depositions from 4\,keV down to 100\,eV, the lowest energy probed so far. The results show no sign of an ionization production threshold above 100\,eV. These results call for further investigation of the ionization yield theory and a comprehensive determination of the detector response function at energies below the keV scale.

A new search for two-neutrino double-beta ($2\nu\beta\beta$) decay of $^{136}\rm Xe$ to the $0^+_1$ excited state of $^{136}\rm Ba$ is performed with the full EXO-200 dataset. A deep learning-based convolutional neural network is used to discriminate signal from background events. Signal detection efficiency is increased relative to previous searches by EXO-200 by more than a factor of two. With the addition of the Phase II dataset taken with an upgraded detector, the median 90$\%$ confidence level half-life sensitivity of $2\nu\beta\beta$ decay to the $0^+_1$ state of $^{136}\rm Ba$ is $2.9 \times 10^{24}~\rm yr$ using a total $^{136}\rm Xe$ exposure of $234.1~\rm kg~yr$. No statistically significant evidence for $2\nu\beta\beta$ decay to the $0^+_1$ state is observed, leading to a lower limit of $T^{2\nu}_{1/2}(0^+ \rightarrow 0^+_1) > 1.4\times10^{24}~\rm yr$ at 90$\%$ confidence level, improved by 70$\%$ relative to the current world's best constraint., Comment: 9 pages, 7 figures, 2 tables

Entanglement distribution is a core mechanism for the future quantum Internet. The quantum world is, however, a faulty environment. Hence, successful entanglement swapping is error-prone. The occurrence of quantum state errors can be mitigated using purification and error correction, which can be repeated in the former case and concatenated in the latter case. Repeated purification merges low-fidelity qubits into higher-quality ones, while concatenated error correction builds upon the redundancy of quantum information. In this article, we study in-depth and compare the two options: repeated purification and concatenated error correction. We consider using repeated purification and concatenated error correction to mitigate the presence of faults that occur during the establishment of Bell pairs between remote network nodes. We compare their performance versus the number of repetitions or concatenations, to reach a certain level of fidelity in quantum networks. We study their resource requirements, namely, their work memory complexity (e.g., number of stored qubits) and operational complexity (e.g., number of operations). Our analysis demonstrates that concatenated error correction, versus repeated purification, requires fewer iterations and has lower operational complexity than repeated purification to reach high fidelity at the expense of increased memory requirements., Comment: ACM Format, 21 pages, 14 figures, 1 table

The 2021-22 High-Energy Physics Community Planning Exercise (a.k.a. ``Snowmass 2021'') was organized by the Division of Particles and Fields of the American Physical Society. Snowmass 2021 was a scientific study that provided an opportunity for the entire U.S. particle physics community, along with its international partners, to identify the most important scientific questions in High Energy Physics for the following decade, with an eye to the decade after that, and the experiments, facilities, infrastructure, and R&D needed to pursue them. This Snowmass summary report synthesizes the lessons learned and the main conclusions of the Community Planning Exercise as a whole and presents a community-informed synopsis of U.S. particle physics at the beginning of 2023. This document, along with the Snowmass reports from the various subfields, will provide input to the 2023 Particle Physics Project Prioritization Panel (P5) subpanel of the U.S. High-Energy Physics Advisory Panel (HEPAP), and will help to guide and inform the activity of the U.S. particle physics community during the next decade and beyond., Comment: 75 pages, 3 figures, 2 tables. This is the first chapter and summary of the full report of the Snowmass 2021 Workshop. This version fixes an important omission from Table 2, adds two references that were not available at the time of the original version, fixes a minor few typos, and adds a small amount of material to section 1.1.3

In the classical context, the cooperative game theory concept of the Shapley value has been adapted for post hoc explanations of machine learning models. However, this approach does not easily translate to eXplainable Quantum ML (XQML). Finding Shapley values can be highly computationally complex. We propose quantum algorithms which can extract Shapley values within some confidence interval. Our results perform in polynomial time. We demonstrate the validity of each approach under specific examples of cooperative voting games., Comment: 9 pages, 4 figures, 24 references, preprint of QCE 2023 (IEEE International Conference on Quantum Computing and Engineering) Technical Paper (Quantum Algorithms for Shapley Value Calculation), available at https://doi.org/10.1109/QCE57702.2023.00024

Using neutrinos produced at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL), the COHERENT collaboration has studied the Pb($\nu_e$,X$n$) process with a lead neutrino-induced-neutron (NIN) detector. Data from this detector are fit jointly with previously collected COHERENT data on this process. A combined analysis of the two datasets yields a cross section that is $0.29^{+0.17}_{-0.16}$ times that predicted by the MARLEY event generator using experimentally-measured Gamow-Teller strength distributions, consistent with no NIN events at 1.8$\sigma$. This is the first inelastic neutrino-nucleus process COHERENT has studied, among several planned exploiting the high flux of low-energy neutrinos produced at the SNS., Comment: 11 pages, 9 figures, version accepted by Phys. Rev. D

This White Paper, prepared for the Fundamental Symmetries, Neutrons, and Neutrinos Town Meeting related to the 2023 Nuclear Physics Long Range Plan, makes the case for double beta decay as a critical component of the future nuclear physics program. The major experimental collaborations and many theorists have endorsed this white paper., Comment: white paper submitted for the Fundamental Symmetries, Neutrons, and Neutrinos Town Meeting in support of the US Nuclear Physics Long Range Planning Process