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We present an architecture for remotely connecting cavity-coupled trapped ions via a quantum repeater based on rare-earth-doped crystals. The main challenge for its realization lies in interfacing these two physical platforms, which produce photons with a typical temporal mismatch of one or two orders of magnitude. To address this, we propose an efficient protocol that enables custom temporal reshaping of single-photon pulses whilst preserving purity. Our approach is to modify a commonly used memory protocol, called atomic frequency comb, for systems exhibiting inhomogeneous broadening like rare-earth-doped crystals. Our results offer a viable solution for uniting quantum processing nodes with a quantum repeater backbone., Comment: 4.5 pages of main text, 50 pages of appendices, 10 figures

We address the problem of testing hypotheses about a specific value of the Fr\'echet mean in metric spaces, extending classical mean testing from Euclidean spaces to more general settings. We extend an Euclidean testing procedure progresively, starting with test construction in Riemannian manifolds, leveraging their natural geometric structure through exponential and logarithm maps, and then extend to general metric spaces through the introduction of admissible randomization techniques. This approach preserves essential geometric properties required for valid statistical inference while maintaining broad applicability. We establish theoretical guarantees for our testing procedure and demonstrate its effectiveness through numerical experiments across different metric spaces and distributional settings. The practical utility of our method is further illustrated through an application to wind data in western Denmark, showcasing its relevance for real-world statistical analysis.

Docking marine surface vessels remains a largely manual task due to its safety-critical nature. In this paper, we develop a hierarchical symbolic control architecture for autonomous docking maneuvers of a dynamic positioning vessel, to provide formal safety guarantees. At the upper-level, we treat the vessel's desired surge, sway, and yaw velocities as control inputs and synthesize a symbolic controller in real-time. The desired velocities are then transmitted to and executed by the vessel's low-level velocity feedback control loop. Given a synthesized symbolic controller, we investigate methods to optimize the performance of the proposed control scheme for the docking task. The efficacy of this methodology is evaluated on a low-fidelity simulation model of a marine surface vessel in the presence of static and dynamic obstacles and, for the first time, through physical experiments on a scaled model vessel.

Bootstrapping is often applied to get confidence limits for semiparametric inference of a target parameter in the presence of nuisance parameters. Bootstrapping with replacement can be computationally expensive and problematic when cross-validation is used in the estimation algorithm due to duplicate observations in the bootstrap samples. We provide a valid, fast, easy-to-implement subsampling bootstrap method for constructing confidence intervals for asymptotically linear estimators and discuss its application to semiparametric causal inference. Our method, inspired by the Cheap Bootstrap (Lam, 2022), leverages the quantiles of a t-distribution and has the desired coverage with few bootstrap replications. We show that the method is asymptotically valid if the subsample size is chosen appropriately as a function of the sample size. We illustrate our method with data from the LEADER trial (Marso et al., 2016), obtaining confidence intervals for a longitudinal targeted minimum loss-based estimator (van der Laan and Gruber, 2012). Through a series of empirical experiments, we also explore the impact of subsample size, sample size, and the number of bootstrap repetitions on the performance of the confidence interval.

Biosensing based on optically trapped fluorescent nanodiamonds is an intriguing research direction potentially allowing to resolve biochemical processes inside living cells. Towards this goal, we investigate infrared near (NIR) laser irradiation at 1064 nm on fluorescent nanodiamonds (FNDs) containing nitrogen-vacancy (NV) centers. By conducting comprehensive experiments, we aim to understand how NIR exposure influences the fluorescence and sensing properties of FNDs and to determine the potential implications for the use of FNDs in various sensing applications. The experimental setup involved exposing FNDs to varying intensities of NIR laser light and analyzing the resultant changes in their optical and physical properties. Key measurements included T1 relaxation times, optical spectroscopy, and optically detected magnetic resonance (ODMR) spectra. The findings reveal how increased NIR laser power correlates with alterations in ODMR central frequency but also that charge state dynamics under NIR irradiation of NV centers plays a role. We suggest protocols with NIR and green light that mitigate the effect of NIR, and demonstrate that FND biosensing works well with such a protocol.

The ability to engineer pairs of entangled photons is essential to quantum information science, and generating these states using spontaneous parametric down-conversion (SPDC) in nano- and micrometer-scale materials offers numerous advantages. To properly engineer such sources, a reliable model describing nano- and micrometer-scale SPDC is necessary; however, such a theoretical description remains a challenge. Here, we propose a simplified model to describe SPDC in resonant structures, which considers the generation of photon pairs and the resonant enhancement of spectral bands to be separate processes, even though they actually occur simultaneously. We compare our simplified model to both the rigorous theory of SPDC in an etalon - a simple example of a resonant structure - and our experiments on SPDC in etalons and find agreement for low-gain SPDC. By simplifying the calculations required to generate photon pairs, our model promises to make designing complex resonant structures easier, and it promises to hasten the iteration of designs across the field of quantum state engineering., Comment: 9 pages, 7 figures

Longitudinal imaging allows for the study of structural changes over time. One approach to detecting such changes is by non-linear image registration. This study introduces Multi-Session Temporal Registration (MUSTER), a novel method that facilitates longitudinal analysis of changes in extended series of medical images. MUSTER improves upon conventional pairwise registration by incorporating more than two imaging sessions to recover longitudinal deformations. Longitudinal analysis at a voxel-level is challenging due to effects of a changing image contrast as well as instrumental and environmental sources of bias between sessions. We show that local normalized cross-correlation as an image similarity metric leads to biased results and propose a robust alternative. We test the performance of MUSTER on a synthetic multi-site, multi-session neuroimaging dataset and show that, in various scenarios, using MUSTER significantly enhances the estimated deformations relative to pairwise registration. Additionally, we apply MUSTER on a sample of older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. The results show that MUSTER can effectively identify patterns of neuro-degeneration from T1-weighted images and that these changes correlate with changes in cognition, matching the performance of state of the art segmentation methods. By leveraging GPU acceleration, MUSTER efficiently handles large datasets, making it feasible also in situations with limited computational resources.

The Bayesian Mallows model is a flexible tool for analyzing data in the form of complete or partial rankings, and transitive or intransitive pairwise preferences. In many potential applications of preference learning, data arrive sequentially and it is of practical interest to update posterior beliefs and predictions efficiently, based on the currently available data. Despite this, most algorithms proposed so far have focused on batch inference. In this paper we present an algorithm for sequentially estimating the posterior distributions of the Bayesian Mallows model using nested sequential Monte Carlo. As it requires minimum user input in form of tuning parameters, is straightforward to parallelize, and returns the marginal likelihood as a direct byproduct of estimation, the algorithm is an alternative to Markov chain Monte Carlo techniques also in batch estimation settings.

We study the single photon purity of a resonantly driven single-photon source in the realistic scenario where the excitation laser can leak into the detection path. We find that the duration of the excitation pulse strongly influences the quality of the single-photon source. We calculate the influence of this on the effective parameters describing the most relevant properties, including the two-photon component and Hong-Ou-Mandel (HOM) visibility. Furthermore, we analyze how these properties can be strongly affected by frequency filtering of the outgoing field. Our results highlight that the relation between the two-photon component of the emission and the HOM visibility is more complicated than typically assumed in the literature, and depends on the specific details of the source., Comment: 14 pages, 9 figures + appendix

We report on a search for millicharged particles (mCPs) produced in cosmic ray proton atmospheric interactions using data collected during the first science run of the LUX-ZEPLIN experiment. The mCPs produced by two processes -- meson decay and proton bremsstrahlung -- are considered in this study. This search utilized a novel signature unique to liquid xenon (LXe) time projection chambers (TPCs), allowing sensitivity to mCPs with masses ranging from 10 to 1000 MeV/c$^2$ and fractional charges between 0.001 and 0.02 of the electron charge e. With an exposure of 60 live days and a 5.5 tonne fiducial mass, we observed no significant excess over background. This represents the first experimental search for atmospheric mCPs and the first search for mCPs using an underground LXe experiment.

Graph states are the key resources for measurement- and fusion-based quantum computing with photons, yet their creation is experimentally challenging. We optimize a hybrid graph-state generation scheme using a single quantum emitter and linear optics Bell-state measurements, called fusions. We first generate a restricted class of states from a single quantum emitter and then apply fusions to create a target graph state, where we use a dynamic programming approach to find the construction that requires the lowest possible number of fusions. Our analysis yields a lookup table for constructing $\sim 2.8\times 10^7$ non-isomorphic graph states with the minimum number of fusions. The lookup table covers all graph states with up to eight qubits and several other ones with up to 14 qubits. We present construction protocols of selected graph states and provide the lookup table. For large graph states that are not in the lookup table, we derive bounds for the required number of fusions using graph-theoretic properties. Finally, we use the lookup table to search for the best graph codes for loss-tolerant encodings, given a fixed number of fusions for their construction.

We investigate under which circumstances there exists nonzero {\it{projective}} smooth $\field[G]$-modules, where $\field$ is a field of characteristic $p$ and $G$ is a locally pro-$p$ group. We prove the non-existence of (non-trivial) projective objects for so-called {\it{fair}} groups -- a family including $\bf{G}(\frak{F})$ for a connected reductive group $\bf{G}$ defined over a non-archimedean local field $\frak{F}$. This was proved in \cite{SS24} for finite extensions $\frak{F}/\Bbb{Q}_p$. The argument we present in this note has the benefit of being completely elementary and, perhaps more importantly, adaptable to $\frak{F}=\Bbb{F}_q(\!(t)\!)$. Finally, we elucidate the fairness condition via a criterion in the Chabauty space of $G$., Comment: 12 pages

Satellite-based quantum repeaters are a promising means to reach global distances in quantum networking due to the polynomial decrease of optical transmission with distance in free space, in contrast to the exponential decrease in optical fibers. We propose a satellite-based quantum repeater architecture with trapped individual atomic qubits, which can serve both as quantum memories and true single photon sources. This hardware allows for nearly deterministic Bell measurements and exhibits long coherence times without the need for costly cryogenic technology in space. We develop a detailed analytical model of the repeater, which includes the main imperfections of the quantum hardware and the optical link, allowing us to estimate that high-rate and high-fidelity entanglement distribution can be achieved over inter-continental distances. In particular, we find that high fidelity entanglement distribution over thousands of kilometres at a rate of 100 Hz can be achieved with orders of magnitude fewer memory modes than conventional architectures based on optical Bell state measurements., Comment: 10 pages, 4 figures

We present a light-weight approach for detecting nonfactual outputs from retrieval-augmented generation (RAG). Given a context and putative output, we compute a factuality score that can be thresholded to yield a binary decision to check the results of LLM-based question-answering, summarization, or other systems. Unlike factuality checkers that themselves rely on LLMs, we use compact, open-source natural language inference (NLI) models that yield a freely accessible solution with low latency and low cost at run-time, and no need for LLM fine-tuning. The approach also enables downstream mitigation and correction of hallucinations, by tracing them back to specific context chunks. Our experiments show high area under the ROC curve (AUC) across a wide range of relevant open source datasets, indicating the effectiveness of our method for fact-checking RAG output., Comment: To appear in Proceedings of EMNLP 2024 Industry Track

Scanning probe microscopy (SPM) is a powerful technique for mapping nanoscale surface properties through tip-sample interactions. Thermal scanning-probe lithography (tSPL) is an advanced SPM variant that uses a silicon tip on a heated cantilever to sculpt and measure polymer films with nanometer precision. The surfaces produced by tSPL-smooth topographic landscapes-allow mathematically defined contours to be fabricated on the nanoscale, enabling sophisticated functionalities for photonic, electronic, chemical, and biological technologies. Evaluating the physical effects of a landscape requires fitting arbitrary mathematical functions to SPM datasets, however, this capability does not exist in standard analysis programs. Here, we provide an open-source software package (FunFit) to fit analytical functions to SPM data and develop a fabrication and characterization protocol based on this analysis. We demonstrate the benefit of this approach by patterning periodic and quasiperiodic landscapes in a polymer resist with tSPL, which we transfer to hexagonal boron nitride (hBN) flakes with high fidelity via reactive-ion etching. The topographic landscapes in polymers and hBN are measured with tSPL and atomic force microscopy (AFM), respectively. Within the FunFit program, the datasets are corrected for artefacts, fit with analytical functions, and compared, providing critical feedback on the fabrication procedure. Beyond application to tSPL, this protocol can improve analysis, reproducibility, and process development for a broad range of SPM experiments. The protocol can be performed within a working day by an inexperienced user, where fabrication and characterization take a few hours and software analysis takes a few minutes.

The XLZD collaboration is developing a two-phase xenon time projection chamber with an active mass of 60 to 80 t capable of probing the remaining WIMP-nucleon interaction parameter space down to the so-called neutrino fog. In this work we show that, based on the performance of currently operating detectors using the same technology and a realistic reduction of radioactivity in detector materials, such an experiment will also be able to competitively search for neutrinoless double beta decay in $^{136}$Xe using a natural-abundance xenon target. XLZD can reach a 3$\sigma$ discovery potential half-life of 5.7$\times$10$^{27}$ yr (and a 90% CL exclusion of 1.3$\times$10$^{28}$ yr) with 10 years of data taking, corresponding to a Majorana mass range of 7.3-31.3 meV (4.8-20.5 meV). XLZD will thus exclude the inverted neutrino mass ordering parameter space and will start to probe the normal ordering region for most of the nuclear matrix elements commonly considered by the community., Comment: 29 pages, 7 figures

This report describes the experimental strategy and technologies for a next-generation xenon observatory sensitive to dark matter and neutrino physics. The detector will have an active liquid xenon target mass of 60-80 tonnes and is proposed by the XENON-LUX-ZEPLIN-DARWIN (XLZD) collaboration. The design is based on the mature liquid xenon time projection chamber technology of the current-generation experiments, LZ and XENONnT. A baseline design and opportunities for further optimization of the individual detector components are discussed. The experiment envisaged here has the capability to explore parameter space for Weakly Interacting Massive Particle (WIMP) dark matter down to the neutrino fog, with a 3$\sigma$ evidence potential for the spin-independent WIMP-nucleon cross sections as low as $3\times10^{-49}\rm cm^2$ (at 40 GeV/c$^2$ WIMP mass). The observatory is also projected to have a 3$\sigma$ observation potential of neutrinoless double-beta decay of $^{136}$Xe at a half-life of up to $5.7\times 10^{27}$ years. Additionally, it is sensitive to astrophysical neutrinos from the atmosphere, sun, and galactic supernovae., Comment: 32 pages, 14 figures

We report results of a search for nuclear recoils induced by weakly interacting massive particle (WIMP) dark matter using the LUX-ZEPLIN (LZ) two-phase xenon time projection chamber. This analysis uses a total exposure of $4.2\pm0.1$ tonne-years from 280 live days of LZ operation, of which $3.3\pm0.1$ tonne-years and 220 live days are new. A technique to actively tag background electronic recoils from $^{214}$Pb $\beta$ decays is featured for the first time. Enhanced electron-ion recombination is observed in two-neutrino double electron capture decays of $^{124}$Xe, representing a noteworthy new background. After removal of artificial signal-like events injected into the data set to mitigate analyzer bias, we find no evidence for an excess over expected backgrounds. World-leading constraints are placed on spin-independent (SI) and spin-dependent WIMP-nucleon cross sections for masses $\geq$9 GeV/$c^2$. The strongest SI exclusion set is $2.1\times10^{-48}$ cm$^{2}$ at the 90% confidence level at a mass of 36 GeV/$c^2$, and the best SI median sensitivity achieved is $5.0\times10^{-48}$ cm$^{2}$ for a mass of 40 GeV/$c^2$., Comment: 9 pages, 7 figures. See https://www.hepdata.net/record/155182 for a data release related to this paper

We describe observations of low energy excess (LEE) events (background events observed in all light dark matter direct detection calorimeters) and noise in a two-channel silicon athermal phonon detector with 375 meV baseline energy resolution. We measure two distinct LEE populations: ``shared'' multichannel events with a pulse shape consistent with athermal phonon events, and sub-eV events which couple nearly exclusively to a single channel with a significantly faster pulse shape. These ``singles'' are consistent with events occurring within the aluminum athermal phonon collection fins. Similarly, our measured detector noise is higher than the theoretical expectation. Measured noise can be split into an uncorrelated component, consistent with shot noise from small energy depositions within the athermal phonon sensor itself, and a correlated component, consistent with shot noise from energy depositions within the silicon crystal's phonon system., Comment: 6 pages, 5 figures

We describe design studies for a pulsed quasi-monoenergetic 2-keV neutron source for calibration of sub-keV nuclear recoils. Such a calibration is required for detectors sensitive to sub-GeV dark matter and also the coherent elastic scattering of reactor neutrinos. In our design, neutrons from a commercial deuterium-tritium generator are moderated to the keV scale and then filtered to the monoenergetic spectrum using a feature in the neutron cross section of scandium. In this approach, unmoderated high-energy neutrons form a challenging background, along with gammas from neutron capture in the moderator materials. We describe the optimization of the moderator+filter and shielding geometry, and find a geometry that in simulation achieves both the target neutron flux at 2 keV and subdominant rates of background interactions. Lastly, we describe a future path to lower-energy (few eV scale) calibrations using time-of-flight and sub-keV neutrons., Comment: 10 pages, 7 figures

McXtrace is an established Monte Carlo based ray-tracing tool to simulate synchrotron beamlines and X-ray laboratory instruments. This work explains and demonstrates the new capability of GPU-accelerated McXtrace ray-tracing simulations. The openACC implementation is presented, followed by a demonstration of the achieved speed-up factor for several types of instruments across different types of hardware. The instruments achieve speed-up factors around \SIrange{250}{600}{} dependent on the instrument complexity. Instruments requiring repeated memory access might require optimised memory access procedures to avoid severe penalties in the simulation time when using GPUs. The importance of reducing the simulations was demonstrated for an aviation security application by comparing the simulation time of a projection of an energy-dispersive X-ray computed tomography instrument.

Fusion-based quantum computation is a promising quantum computing model where small-sized photonic resource states are simultaneously entangled and measured by fusion gates. Such operations can be readily implemented with scalable photonic hardware: resource states can be deterministically generated by quantum emitters and fusions require only shallow linear-optical circuits. Here, we propose fusion-based architectures tailored to the capabilities and noise models in quantum emitters. We show that high tolerance to dominant physical error mechanisms can be achieved, with fault-tolerance thresholds of 8% for photon loss, 4% for photon distinguishability between emitters, and spin noise thresholds well above memory-induced errors for typical spin-photon interfaces. Our construction and analysis provide guidelines for the development of photonic quantum hardware targeting fault-tolerant applications with quantum emitters., Comment: Added proofs in Supplementary

This white paper is the result of a collaboration by those that attended a workshop at the Facility for Rare Isotope Beams (FRIB), organized by the FRIB Theory Alliance (FRIB-TA), on Theoretical Justifications and Motivations for Early High-Profile FRIB Experiments. It covers a wide range of topics related to the science that will be explored at FRIB. After a brief introduction, the sections address: (II) Overview of theoretical methods, (III) Experimental capabilities, (IV) Structure, (V) Near-threshold Physics, (VI) Reaction mechanisms, (VII) Nuclear equations of state, (VIII) Nuclear astrophysics, (IX) Fundamental symmetries, and (X) Experimental design and uncertainty quantification., Comment: 227 pages, 24 figures

Recent calls for pluralistic alignment emphasize that AI systems should address the diverse needs of all people. Yet, efforts in this space often require sorting people into fixed buckets of pre-specified diversity-defining dimensions (e.g., demographics, personalities, communication styles), risking smoothing out or even stereotyping the rich spectrum of individualistic variations. To achieve an authentic representation of diversity that respects individuality, we propose individualistic alignment. While individualistic alignment can take various forms, in this paper, we introduce IndieValueCatalog, a dataset transformed from the influential World Values Survey (WVS), to study language models (LMs) on the specific challenge of individualistic value reasoning. Specifically, given a sample of an individual's value-expressing statements, models are tasked with predicting their value judgments in novel cases. With IndieValueCatalog, we reveal critical limitations in frontier LMs' abilities to reason about individualistic human values with accuracies, only ranging between 55% to 65%. Moreover, our results highlight that a precise description of individualistic values cannot be approximated only via demographic information. We also identify a partiality of LMs in reasoning about global individualistic values, as measured by our proposed Value Inequity Index ({\sigma}INEQUITY). Finally, we train a series of Individualistic Value Reasoners (IndieValueReasoner) using IndieValueCatalog to enhance models' individualistic value reasoning capability, revealing new patterns and dynamics into global human values. We outline future research challenges and opportunities for advancing individualistic alignment.

We report the first measurement of the azimuthal anisotropy of J$/\psi$ at forward rapidity ($1.2<|\eta|<2.2$) in Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV at the Relativistic Heavy Ion Collider. The data were collected by the PHENIX experiment in 2014 and 2016 with integrated luminosity of 14.5~nb$^{-1}$. The second Fourier coefficient ($v_2$) of the azimuthal distribution of $J/\psi$ is determined as a function of the transverse momentum ($p_T$) using the event-plane method. The measurements were performed for several selections of collision centrality: 0\%--50\%, 10\%--60\%, and 10\%-40\%. We find that in all cases the values of $v_2(p_T)$, which quantify the elliptic flow of J$/\psi$, are consistent with zero. The results are consistent with measurements at midrapidity, indicating no significant elliptic flow of the J$/\psi$ within the quark-gluon-plasma medium at collision energies of $\sqrt{s_{_{NN}}}=200$ GeV., Comment: 369 authors from 72 institutions, 12 pages, 7 figures, 5 tables. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

We present the first forward-rapidity measurements of elliptic anisotropy of open-heavy-flavor muons at the BNL Relativistic Heavy Ion Collider. The measurements are based on data samples of Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV collected by the PHENIX experiment in 2014 and 2016 with integrated luminosity of 14.5~nb$^{-1}$. The measurements are performed in the pseudorapidity range $1.2<|\eta|<2$ and cover transverse momenta $1

2D materials research has reached significant scientific milestones, accompanied by a rapidly growing industrial sector in the two decades since the field's inception. Such rapid progress requires pushing past the boundary of what is technically and scientifically feasible and carries the risk of disseminating irreproducible research results. This Expert Recommendation addresses the need for enhanced reproducibility in 2D materials science and physics. Through a comprehensive examination of the factors that affect reproducibility the authors present a set of concrete guidelines designed to improve the reliability of research results. The introduction of a Standardised Template for Experimental Procedures (STEP) offers a novel approach to documenting experimental details that are crucial for replication and troubleshooting. We emphasise the importance of involving stakeholders from research, industry, publishing, funding agencies, and policymaking to foster a culture of transparency, reliability, and trust without blind angles and critical oversights. By addressing systemic issues that hinder reproducibility and presenting actionable steps for improvement, we aim to pave the way for more robust research practices in 2D materials science, contributing to the field's scientific maturation and the subsequent development of beneficial technologies., Comment: 24 pages, 3 textboxes, 1 figure, 2 tables

This paper investigates the effects of the staggered roll-out of a pollution reduction programme introduced in the UK in the 1950s. The policy allowed local authorities to introduce so-called Smoke Control Areas (SCAs) which banned smoke emissions. We start by digitizing historical pollution data to show that the policy led to an immediate reduction in black smoke concentrations. We then merge data on the exact location, boundary and month of introduction of SCAs to individual-level outcomes in older age using individuals' year-month and location of birth. We show that exposure to the programme increased individuals' birth weights as well as height in adulthood. We find no impact on their years of education or fluid intelligence.

Bessel functions are critical in scientific computing for applications such as machine learning, protein structure modeling, and robotics. However, currently, available routines lack precision or fail for certain input ranges, such as when the order $v$ is large, and GPU-specific implementations are limited. We address the precision limitations of current numerical implementations while dramatically improving the runtime. We propose two novel algorithms for computing the logarithm of modified Bessel functions of the first and second kinds by computing intermediate values on a logarithmic scale. Our algorithms are robust and never have issues with underflows or overflows while having relative errors on the order of machine precision, even for inputs where existing libraries fail. In C++/CUDA, our algorithms have median and maximum speedups of 45x and 6150x for GPU and 17x and 3403x for CPU, respectively, over the ranges of inputs and third-party libraries tested. Compared to SciPy, the algorithms have median and maximum speedups of 77x and 300x for GPU and 35x and 98x for CPU, respectively, over the tested inputs. The ability to robustly compute a solution and the low relative errors allow us to fit von Mises-Fisher, vMF, distributions to high-dimensional neural network features. This is, e.g., relevant for uncertainty quantification in metric learning. We obtain image feature data by processing CIFAR10 training images with the convolutional layers of a pre-trained ResNet50. We successfully fit vMF distributions to 2048-, 8192-, and 32768-dimensional image feature data using our algorithms. Our approach provides fast and accurate results while existing implementations in SciPy and mpmath fail to fit successfully. Our approach is readily implementable on GPUs, and we provide a fast open-source implementation alongside this paper., Comment: Accepted at ICS 2024

The $J/\psi$ and $\psi(2S)$ charmonium states, composed of $c\bar{c}$ quark pairs and known since the 1970s, are widely believed to serve as ideal probes to test quantum chromodynamics in high-energy hadronic interactions. However, there is not yet a complete understanding of the charmonium-production mechanism. Recent measurements of $J/\psi$ production as a function of event charged-particle multiplicity at the collision energies of both the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC) show enhanced $J/\psi$ production yields with increasing multiplicity. One potential explanation for this type of dependence is multiparton interactions (MPI). We carry out the first measurements of self-normalized $J/\psi$ yields and the $\psi(2S)$ to $J/\psi$ ratio at both forward and backward rapidities as a function of self-normalized charged-particle multiplicity in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV. In addition, detailed {\sc pythia} studies tuned to RHIC energies were performed to investigate the MPI impacts. We find that the PHENIX data at RHIC are consistent with recent LHC measurements and can only be described by {\sc pythia} calculations that include MPI effects. The forward and backward $\psi(2S)$ to $J/\psi$ ratio, which serves as a unique and powerful approach to study final-state effects on charmonium production, is found to be less dependent on the charged-particle multiplicity., Comment: 301 authors from 69 institutions, 8 pages, 3 figures. v1 is version submitted to Physical Review D Letters. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

We construct explicit jointly invariant measures for the periodic KPZ equation (and therefore also the stochastic Burgers' and stochastic heat equations) for general slope parameters and prove their uniqueness via a one force--one solution principle. The measures are given by polymer-like transforms of independent Brownian bridges. We describe several properties and limits of these measures, including an extension to a continuous process in the slope parameter that we term the periodic KPZ horizon. As an application of our construction, we prove a Gaussian process limit theorem with an explicit covariance function for the long-time height function fluctuations of the periodic KPZ equation when started from varying slopes. In connection with this, we conjecture a formula for the fluctuations of cumulants of the endpoint distribution for the periodic continuum directed random polymer. To prove joint invariance, we address the analogous problem for a semi-discrete system of SDEs related to the periodic O'Connell-Yor polymer model and then perform a scaling limit of the model and jointly invariant measures. For the semi-discrete system, we demonstrate a bijection that maps our systems of SDEs to another system with product invariant measure. Inverting the map on this product measure yields our invariant measures. This map relates to a periodic version of the discrete geometric Pitman transform that we introduce and probe. As a by-product of this, we show that the jointly invariant measures for a periodic version of the inverse-gamma polymer are the same as those for the O'Connell-Yor polymer., Comment: 104 pages, 12 figures

We provide a class of diffusion processes for continuous time-varying multivariate angular data with explicit transition probability densities, enabling exact likelihood inference. The presented diffusions are time-reversible and can be constructed for any pre-specified stationary distribution on the torus, including highly-multimodal mixtures. We give results on asymptotic likelihood theory allowing one-sample inference and tests of linear hypotheses for $k$ groups of diffusions, including homogeneity. We show that exact and direct diffusion bridge simulation is possible too. A class of circular jump processes with similar properties is also proposed. Several numerical experiments illustrate the methodology for the circular and two-dimensional torus cases. The new family of diffusions is applied (i) to test several homogeneity hypotheses on the movement of ants and (ii) to simulate bridges between the three-dimensional backbones of two related proteins., Comment: 23 pages, 7 figures, 2 tables

The correctness of complex software depends on the correctness of both the source code and the compilers that generate corresponding binary code. Compilers must do more than preserve the semantics of a single source file: they must ensure that generated binaries can be composed with other binaries to form a final executable. The compatibility of composition is ensured using an Application Binary Interface (ABI), which specifies details of calling conventions, exception handling, and so on. Unfortunately, there are no official ABIs for concurrent programs, so different atomics mappings, although correct in isolation, may induce bugs when composed. Indeed, today, mixing binaries generated by different compilers can lead to an erroneous resulting binary. We present mix testing: a new technique designed to find compiler bugs when the instructions of a C/C++ test are separately compiled for multiple compatible architectures and then mixed together. We define a class of compiler bugs, coined mixing bugs, that arise when parts of a program are compiled separately using different mappings from C/C++ atomic operations to assembly sequences. To demonstrate the generality of mix testing, we have designed and implemented a tool, atomic-mixer, which we have used: (a) to reproduce one existing non-mixing bug that state-of-the-art concurrency testing tools are limited to being able to find (showing that atomic-mixer at least meets the capabilities of these tools), and (b) to find four previously-unknown mixing bugs in LLVM and GCC, and one prospective mixing bug in mappings proposed for the Java Virtual Machine. Lastly, we have worked with engineers at Arm to specify, for the first time, an atomics ABI for Armv8, and have used atomic-mixer to validate the LLVM and GCC compilers against it., Comment: 26 pages, Accepted to OOPSLA (Object-oriented Programming, Systems, Languages, and Applications) 2024

We perform a finite-size scaling analysis of net-proton number cumulants in Au+Au collisions at center-of-mass energies between $\sqrt{s_{\rm{NN}}} = 2.4$ GeV and 54.4 GeV to search for evidence of a critical point in the QCD phase diagram. In our analysis, we use both susceptibility and Binder cumulants which we extract from the second and fourth moments of the net-proton number distributions. We take measurements in different rapidity bin widths, corresponding to different subvolumes of the system, as probes of different length scales. We use model simulations to verify the applicability of this approach, then apply it to data and find evidence for a critical point near the baryon chemical potential of $\mu_{B} \approx 625$ MeV and temperature of $T \approx 140$ MeV. The Binder cumulants, also analyzed in varying rapidity bin widths, provide complementary evidence for a critical point in a similar region. This is the first analysis of experimental data to locate the critical point in a range consistent with theoretical predictions.

The broad physics reach of the LUX-ZEPLIN (LZ) experiment covers rare phenomena beyond the direct detection of dark matter. We report precise measurements of the extremely rare decay of $^{124}$Xe through the process of two-neutrino double electron capture (2$\nu$2EC), utilizing a $1.39\,\mathrm{kg} \times \mathrm{yr}$ isotopic exposure from the first LZ science run. A half-life of $T_{1/2}^{2\nu2\mathrm{EC}} = (1.09 \pm 0.14_{\text{stat}} \pm 0.05_{\text{sys}}) \times 10^{22}\,\mathrm{yr}$ is observed with a statistical significance of $8.3\,\sigma$, in agreement with literature. First empirical measurements of the KK capture fraction relative to other K-shell modes were conducted, and demonstrate consistency with respect to recent signal models at the $1.4\,\sigma$ level., Comment: 15 pages, 3 figures

Stochastic differential equations provide a powerful tool for modelling dynamic phenomena affected by random noise. In case of repeated observations of time series for several experimental units, it is often the case that some of the parameters vary between the individual experimental units, which has motivated a considerable interest in stochastic differential equations with mixed effects, where a subset of the parameters are random. These models enable simultaneous representation of randomness in the dynamics and variability between experimental units. When the data are observations at discrete time points, the likelihood function is only rarely explicitly available, so for likelihood-based inference to be feasible, numerical methods are needed. We present Gibbs samplers and stochastic EM-algorithms based on augmented data obtained by the simple method for simulation of diffusion bridges in Bladt and S{\o}rensen (2014). This method is easy to implement and has no tuning parameters. The method is, moreover, computationally efficient at low sampling frequencies because the computing time increases linearly with the time between observations. The algorithms can be extended to models with measurement errors. The Gibbs sampler as well as the EM-algorithm are shown to simplify considerably for exponential families of diffusion processes, including many models used in practice. In a simulation study, the estimation methods are shown to work well for Ornstein-Uhlenbeck processes and t-diffusions with mixed effects. Finally, the Gibbs sampler is applied to neuronal data.

The jet cross-section and jet-substructure observables in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV were measured by the PHENIX Collaboration at the Relativistic Heavy Ion Collider (RHIC). Jets are reconstructed from charged-particle tracks and electromagnetic-calorimeter clusters using the anti-$k_{t}$ algorithm with a jet radius $R=0.3$ for jets with transverse momentum within $8.0

Topological insulators were originally discovered for electron waves in condensed matter systems. Recently this concept has been transferred to bosonic systems such as photons and phonons, which propagate in materials patterned with artificial lattices that emulate spin-Hall physics. This work has been motivated, in part, by the prospect of topologically protected transport along edge channels in on-chip circuits. Importantly, even in principle, topology protects propagation against backscattering, but not against loss, which has remained limited to the dB/cm-level for phonon waveguides, be they topological or not. Here, we combine advanced dissipation engineering, in particular the recently introduced method of soft-clamping, with the concept of a valley-Hall topological insulator for phonons. This enables on-chip phononic waveguides with propagation losses of 3 dB/km at room temperature, orders of magnitude below any previous chip-scale devices. For the first time, the low losses also allow us to accurately quantify backscattering protection in a topological phonon waveguide, using high-resolution ultrasound spectroscopy. We infer that phonons follow a sharp, 120 degree-bend with a 99.99%-probability instead of being scattered back, and less than one phonon in a million is lost. The extraordinary combination of features of this novel platform suggest applications in classical and quantum signal routing, processing, and storage., Comment: Main manuscript (16 pages, 4 figures) and supplementary information (19 pages, 10 figures)

The axion kinetic misalignment mechanism (KMM) opens the possibility of explaining dark matter for almost any axion mass and decay constant that are not accessible by the standard misalignment mechanism, in particular at low values of the axion decay constant (i.e. large coupling). This is a new opportunity for most axion experiments which could be sensitive to dark matter and probe new regimes of axion cosmology. We scrutinise UV completions that lead to the KMM mechanism. These mainly rely on the early dynamics of the axion partner, the radial mode of the complex scalar field, from which the axion inherits kinetic energy. The damping of the radial-mode energy density is then a necessary ingredient. We study in detail thermal damping from interactions in the plasma. A minimal and rather natural implementation consists of a KSVZ-type model with a nearly-quadratic potential for the radial mode extended by U(1)-breaking higher-dimensional operators. Furthermore, we study Higgs portal interactions as an alternative damping mechanism and improve upon previously proposed implementations based on quartic potentials. These implementations can lead to the QCD axion being dark matter and in the reach of IAXO, while MADMAX, IAXO and ALPS II can be sensitive to a generic Axion-Like-Particle (ALP) as dark matter. Such models typically feature a kination era. We also show that ALP dark matter from KMM points to a particular realization of inflation., Comment: 51 pages, 21 figures (main text without references) + 47 pages, 25 figures (appendices)

The Peccei-Quinn (PQ) symmetry does not need to be exact, and even a tiny source of PQ breaking not aligned with the QCD anomaly might have significant phenomenological implications. In this study, we examine the effects of a general class of PQ-breaking operators on the axion cosmological production via misalignment, focussing on both temperature-dependent and independent PQ-breaking potentials. In particular, we show that a variant of the trapped misalignment mechanism can delay the onset of axion oscillation, leading to an axion dark matter window with $m_a \gg 10^{-5}$ eV. This scenario is testable through various experimental approaches, including standard axion haloscopes and helioscopes, as well as searches for electric dipole moments and axion-mediated forces., Comment: 22 pages, 4 figures

Chaotic systems, such as turbulent flows, are ubiquitous in science and engineering. However, their study remains a challenge due to the large range scales, and the strong interaction with other, often not fully understood, physics. As a consequence, the spatiotemporal resolution required for accurate simulation of these systems is typically computationally infeasible, particularly for applications of long-term risk assessment, such as the quantification of extreme weather risk due to climate change. While data-driven modeling offers some promise of alleviating these obstacles, the scarcity of high-quality simulations results in limited available data to train such models, which is often compounded by the lack of stability for long-horizon simulations. As such, the computational, algorithmic, and data restrictions generally imply that the probability of rare extreme events is not accurately captured. In this work we present a general strategy for training neural network models to non-intrusively correct under-resolved long-time simulations of chaotic systems. The approach is based on training a post-processing correction operator on under-resolved simulations nudged towards a high-fidelity reference. This enables us to learn the dynamics of the underlying system directly, which allows us to use very little training data, even when the statistics thereof are far from converged. Additionally, through the use of probabilistic network architectures we are able to leverage the uncertainty due to the limited training data to further improve extrapolation capabilities. We apply our framework to severely under-resolved simulations of quasi-geostrophic flow and demonstrate its ability to accurately predict the anisotropic statistics over time horizons more than 30 times longer than the data seen in training.

The thermal conductivity of glasses is well-known to be significantly harder to theoretically describe compared to crystalline materials. Because of this fact, the fundamental understanding of thermal conductivity in glasses remain extremely poor when moving beyond the case of simple glasses, e.g., glassy SiO$_2$, and into so-called 'modified' oxide glasses, that is, glasses where other oxides (e.g. alkali oxides) have been added to break up the network and alter e.g. elastic and thermal properties. This lack of knowledge is apparent despite how modified glasses comprise the far majority of known glasses. In the present work we study an archetypical series of sodium silicate ($x\text{Na}_2\text{O}\text{-}(100\text{-}x)\text{SiO}_2$) glasses. Analyses of modal contributions reveal how increasing Na$_2$O content induces increasing vibrational localization with a change of vibrations to be less ordered, and a related general decrease in modal contributions to thermal conductivity. We find the vibrational phases (acoustic vs. optical) of sodium vibrations to be relatively disordered compared to the network-forming silicon and oxygen species, explaining how increasing Na$_2$O content decreases thermal conductivity. Our work sheds new light on the fundamentals of glassy heat transfer as well as the interplay between thermal conduction and modal characteristics in glasses., Comment: The following article has been submitted to The Journal of Chemical Physics

Cube satellites, or CubeSats, are small satellites commonly used to perform Earth imaging and on-orbit scientific experiments. CubeSats are often powered using expensive, inflexible commercial-off-the-shelf solar panels, largely due to a lack of flight-qualified open-source alternatives. Here, we describe the design of customizable, deployable solar panels, offering an open-source, cost-effective alternative. Towards a fully open-source CubeSat, our designs have mission-tailored power generation capabilities and simple electrical and mechanical integration. The solar panel designs were demonstrated on-orbit on three satellites in the Northern SPIRIT constellation and will be on AlbertaSat's Ex-Alta~3 satellite, which will launch in 2025. The design files, assembly procedures, and best practices will be open-source-published online. This work lowers the barrier of entry into space, making satellite design easier and less expensive -- students helping students design better satellites., Comment: 9 pages, 8 figures, presented at the 2024 SmallSat Conference in Logan, Utah, USA

Fast decoding algorithms are decisive for real-time quantum error correction and for analyzing properties of error correction codes. Here, we develop variants of the union-find decoder that simplify its implementation and provide potential decoding speed advantages. Furthermore, we show how these methods can be adapted to decode non-topological quantum low-density-parity-check (qLDPC) codes. All the developed decoders can directly include both qubit erasures and Pauli errors in the decoding step, thus addressing the dominant noise mechanisms for photonic quantum computing. We investigate the strengths and weaknesses of the different decoder variants, benchmark their speed and threshold error rates on several codes, and provide the used source code.

Axion-mediated forces are enhanced by the presence of CP-violating axion couplings, which are however tightly constrained by electric dipole moment (EDM) searches. We discuss the underlying hypotheses behind different sources of CP violation at high energies and the interplay between axion-mediated force experiments and EDM observables. Specifically, we identify various mechanisms, based on new sources of CP violation or Peccei-Quinn symmetry breaking, that can significantly relax EDM constraints, leading to a substantial redefinition of the QCD axion window for axion-mediated forces. By considerably enlarging the QCD axion parameter space, our results provide a well-motivated target for experiments probing scalar axion couplings to matter fields. These include fifth-force tests of gravity, as well as searches for spin-dependent forces via precision magnetometry, proton storage rings and ultracold molecules., Comment: 8 pages, 1 figure, 1 appendix

The rhythmic pumping motion of the heart stands as a cornerstone in life, as it circulates blood to the entire human body through a series of carefully timed contractions of the individual chambers. Changes in the size, shape and movement of the chambers can be important markers for cardiac disease and modeling this in relation to clinical demography or disease is therefore of interest. Existing methods for spatio-temporal modeling of the human heart require shape correspondence over time or suffer from large memory requirements, making it difficult to use for complex anatomies. We introduce a novel conditional generative model, where the shape and movement is modeled implicitly in the form of a spatio-temporal neural distance field and conditioned on clinical demography. The model is based on an auto-decoder architecture and aims to disentangle the individual variations from that related to the clinical demography. It is tested on the left atrium (including the left atrial appendage), where it outperforms current state-of-the-art methods for anatomical sequence completion and generates synthetic sequences that realistically mimics the shape and motion of the real left atrium. In practice, this means we can infer functional measurements from a static image, generate synthetic populations with specified demography or disease and investigate how non-imaging clinical data effect the shape and motion of cardiac anatomies., Comment: Accepted for MICCAI2024