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Given the rapidly expanding capabilities of generative AI models for radiology, there is a need for robust metrics that can accurately measure the quality of AI-generated radiology reports across diverse hospitals. We develop ReXamine-Global, a LLM-powered, multi-site framework that tests metrics across different writing styles and patient populations, exposing gaps in their generalization. First, our method tests whether a metric is undesirably sensitive to reporting style, providing different scores depending on whether AI-generated reports are stylistically similar to ground-truth reports or not. Second, our method measures whether a metric reliably agrees with experts, or whether metric and expert scores of AI-generated report quality diverge for some sites. Using 240 reports from 6 hospitals around the world, we apply ReXamine-Global to 7 established report evaluation metrics and uncover serious gaps in their generalizability. Developers can apply ReXamine-Global when designing new report evaluation metrics, ensuring their robustness across sites. Additionally, our analysis of existing metrics can guide users of those metrics towards evaluation procedures that work reliably at their sites of interest.

Thermomechanical controlled processing (TMCP) is widely used to optimize the final properties of high strength low alloy (HSLA) steels, via microstructure engineering. The room temperature microstructures are influenced by the high temperature austenite phase, and the austenite microstructure is commonly accessed by reconstruction using electron backscatter diffraction (EBSD) data of the final microstructure. A challenge for reconstruction of the PAG microstructure and subsequent austenite grain size measurement is the presence of austenite-phase annealing twins, and we address challenge with a new 're-sort' algorithm. Our algorithm has been validated using the retained austenite regions (which were recovered via advanced pattern matching of EBSD patterns). We demonstrate that the re-sort algorithm improves the PAG reconstruction significantly, especially for the grain boundary network and correlation with other methods of grain size assessment and development of TMCP steels.

We present a problem to be assigned or done as an in-class activity in an upper-division undergraduate course on computational physics. The problem involves a home run hit by Mickey Mantle on May 22, 1963, which he famously called ``the hardest ball I ever hit''. Is this home run truly one for the record books, or has it been eclipsed by players in the modern era? Modeling the trajectory of a baseball involves consideration of both wind resistance and the Magnus effect, and is an interesting application of numerical solution of ordinary differential equations. Ultimately, the answer is that Mantle would compare favorably to the most powerful batters currently playing, but to arrive at that conclusion we must reflect on the plausibility of results and sources of uncertainty., Comment: Accepted for publication in American Journal of Physics. 15 pages, 4 figures. Fig 1 licensed from Getty Images

We study the phenomenon of bounces, as predicted by Belinski, Khalatnikov and Lifshitz (BKL) in the study of singularities arising from Einstein's equations, as an instability mechanism within the setting of the (inhomogeneous) Einstein-Maxwell-scalar field system in surface symmetry. This article can be viewed as a companion to our other article "BKL bounces outside homogeneity: Gowdy symmetric spacetimes" [27], where we study bounces for the Einstein vacuum equations in Gowdy symmetry. That is, we show many features of such bounces generalize to the matter model described, albeit in a different symmetry class. The articles may be read independently. In analogy to [27], we describe a wide class of inhomogeneous initial data which permit formation of a spacelike singularity, but such that the dynamics towards different spatial points at the singularity are well-described by independent nonlinear ODEs reminiscent of BKL bounces. A major ingredient is the proof of so-called Asymptotically Velocity Term Dominated behaviour even in the presence of such bounces, though one difference from [27] is that our model does not permit the existence of so-called "spikes". One particular application is the study of (past) instability of certain generalized Kasner spacetimes with no electromagnetic field present. Perturbations of such spacetimes are such that the singularity persists, but for perturbations with electromagnetism turned on the intermediate dynamics - between data and the singularity - features up to one BKL-like bounce. This is in analogy with the instability of polarized Gowdy spacetimes due to non-polarized perturbations in [27]., Comment: 58 pages, 4 figures. This paper was written in parallel with our companion article "BKL bounces outside homogeneity: Gowdy symmetric spacetimes" and shares many structural features, including some text overlap. The two papers may be read independently

We study the phenomenon of bounces, as predicted by Belinski, Khalatnikov and Lifshitz (BKL), as an instability mechanism within the setting of the Einstein vacuum equations in Gowdy symmetry. In particular, for a wide class of inhomogeneous initial data we prove that the dynamics near the $t = 0$ singularity are well-described by ODEs reminiscent of Kasner bounces. Unlike previous works regarding bounces, our spacetimes are not necessarily spatially homogeneous, and a crucial step is proving so-called asymptotically velocity term dominated (AVTD) behaviour, even in the presence of nonlinear BKL bounces and other phenomena such as spikes. (A similar phenomenon involving bounces and AVTD behaviour, though not spikes, can also be seen in our companion paper "BKL bounces outside homogeneity: Einstein-Maxwell-scalar field in surface symmetry", albeit in the context of the Einstein-Maxwell-scalar field model in surface symmetry.) One particular application is the study of (past) instability of certain polarized Gowdy spacetimes, including some Kasner spacetimes. Perturbations of such spacetimes are such that the singularity persists, but the intermediate dynamics -- between initial data and the singularity -- feature BKL bounces., Comment: 43 pages, 2 figures. This paper was written in parallel with our companion article "BKL bounces outside homogeneity: Einstein-Maxwell-scalar field in surface symmetry", and shares many structural features including some text overlap. The two papers can be read independently

At first light, the Thirty Meter Telescope (TMT) near-infrared (NIR) instruments will be fed by a multiconjugate adaptive optics instrument known as the Narrow Field Infrared Adaptive Optics System (NFIRAOS). NFIRAOS will use six laser guide stars to sense atmospheric turbulence in a volume corresponding to a field of view of 2', but natural guide stars (NGSs) will be required to sense tip/tilt and focus. To achieve high sky coverage (50% at the north Galactic pole), the NFIRAOS client instruments use NIR on-instrument wavefront sensors that take advantage of the sharpening of the stars by NFIRAOS. A catalog of guide stars with NIR magnitudes as faint as 22 mag in the J band (Vega system), covering the TMT-observable sky, will be a critical resource for the efficient operation of NFIRAOS, and no such catalog currently exists. Hence, it is essential to develop such a catalog by computing the expected NIR magnitudes of stellar sources identified in deep optical sky surveys using their optical magnitudes. This paper discusses the generation of a partial NIR Guide Star Catalog (IRGSC), similar to the final IRGSC for TMT operations. The partial catalog is generated by applying stellar atmospheric models to the optical data of stellar sources from the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) optical data and then computing their expected NIR magnitudes. We validated the computed NIR magnitudes of the sources in some fields by using the available NIR data for those fields. We identified the remaining challenges of this approach. We outlined the path for producing the final IRGSC using the Pan-STARRS data. We have named the Python code to generate the IRGSC as irgsctool, which generates a list of NGS for a field using optical data from the Pan-STARRS 3pi survey and also a list of NGSs having observed NIR data from the UKIRT Infrared Deep Sky Survey if they are available.

This paper describes a semantics for pure Prolog programs with negation that provides meaning to metaprograms. Metaprograms are programs that construct and use data structures as programs. In Prolog a primary mataprogramming construct is the use of a variable as a literal in the body of a clause. The traditional Prolog 3-line metainterpreter is another example of a metaprogram. The account given here also supplies a meaning for clauses that have a variable as head, even though most Prolog systems do not support such clauses. This semantics naturally includes such programs, giving them their intuitive meaning. Ideas from M. Denecker and his colleagues form the basis of this approach. The key idea is to notice that if we give meanings to all propositional programs and treat Prolog rules with variables as the set of their ground instances, then we can give meanings to all programs. We must treat Prolog rules (which may be metarules) as templates for generating ground propositional rules, and not as first-order formulas, which they may not be. We use parameterized inductive definitions to give propositional models to Prolog programs, in which the propositions are expressions. Then the set of expressions of a propositional model determine a first-order Herbrand Model, providing a first-order logical semantics for all (pure) Prolog programs, including metaprograms. We give examples to show the applicability of this theory. We also demonstrate how this theory makes proofs of some important properties of metaprograms very straightforward., Comment: 16 pages, 3 figures, appeared in the International Conference on Logic Programming 2024 (ICLP-2024)

This paper focuses on studying the configuration spaces of graphs realised in $\mathbb C^2$, such that the configuration space is, after normalisation, one dimensional. If this is the case, then the configuration space is, generically, a smooth complex curve, and can be seen as a Riemann surface. The property of interest in this paper is the genus of this curve. Using tropical geometry, we give an algorithm to compute this genus. We provide an implementation in Python and give various examples.

In this work, we introduce Gemma 2, a new addition to the Gemma family of lightweight, state-of-the-art open models, ranging in scale from 2 billion to 27 billion parameters. In this new version, we apply several known technical modifications to the Transformer architecture, such as interleaving local-global attentions (Beltagy et al., 2020a) and group-query attention (Ainslie et al., 2023). We also train the 2B and 9B models with knowledge distillation (Hinton et al., 2015) instead of next token prediction. The resulting models deliver the best performance for their size, and even offer competitive alternatives to models that are 2-3 times bigger. We release all our models to the community.

Swept laser interferometry is an extremely powerful solution embedded in several recent technologies such as absolute distance measurement, light detection and ranging, optical frequency domain reflectometry, optical coherence tomography, microresonator characterization, and gas spectroscopy. Nonlinearity in the optical frequency sweeping of tunable lasers is a fatal drawback in gaining the expected outcome from these technologies. Here, we introduce an onchip, millimeter scale, 7 m spiral resonator that is made of ultralow loss silicon nitride to act as a frequency ruler for correction of the tunable lasers sweeping nonlinearities. The sharp 2 MHz frequency lines of the 85 M high-quality resonator and the narrow spaced 25.57 MHz frequency ticks of the 7 m spiral allow unprecedented precise nonlinearity correction on an integrated photonics platform. Accurate measurements of the rulers frequency spacing, linewidth, and temperature and wavelength sensitivities of the frequency ticks are performed here to demonstrate the quality of the frequency ruler. In addition, the spiral resonator is implemented in an FMCW LiDAR experiment to demonstrate a potential application of the proposed onchip frequency ruler., Comment: 12 pages

We present follow-up spectroscopy and a detailed model atmosphere analysis of 29 wide double white dwarfs, including eight systems with a crystallized C/O core member. We use state-of-the-art evolutionary models to constrain the physical parameters of each star, including the total age. Assuming that the members of wide binaries are coeval, any age difference between the binary members can be used to test the cooling physics for white dwarf stars, including potential delays due to crystallization and $^{22}$Ne distillation. We use our control sample of 14 wide binaries with non-crystallized members to show that this method works well; the control sample shows an age difference of only $\Delta$Age = $-0.03 \pm$ 0.15 Gyr between its members. For the eight crystallized C/O core systems we find a cooling anomaly of $\Delta$Age= 1.13$^{+1.20}_{-1.07}$ Gyr. Even though our results are consistent with a small additional cooling delay ($\sim1$ Gyr) from $^{22}$Ne distillation and other neutron-rich impurities, the large uncertainties make this result not statistically significant. Nevertheless, we rule out cooling delays longer than 3.6 Gyr at the 99.7% ($3\sigma$) confidence level for 0.6-0.9 $M_{\odot}$ white dwarfs. Further progress requires larger samples of wide binaries with crystallized massive white dwarf members. We provide a list of subgiant + white dwarf binaries that could be used for this purpose in the future., Comment: 19 pages, including 6 figures and 4 tables, accepted for publication in ApJ

For pedestrians moving without spatial constraints, extensive research has been devoted to develop methods of density estimation. In this paper we present a new approach based on Voronoi cells, offering a means to estimate density for individuals in small, unbounded pedestrian groups. A thorough evaluation of existing methods, encompassing both Lagrangian and Eulerian approaches employed in similar contexts, reveals notable limitations. Specifically, these methods turn out to be ill-defined for realistic density estimation along a pedestrian's trajectory, exhibiting systematic biases and fluctuations that depend on the choice of parameters. There is thus a need for a parameter-independent method to eliminate this bias. We propose a modification of the widely used Voronoi-cell based density estimate to accommodate pedestrian groups, irrespective of their size. The advantages of this modified Voronoi method are that it is an instantaneous method that requires only knowledge of the pedestrians' positions at a give time, does not depend on the choice of parameter values, gives us a realistic estimate of density in an individual's neighborhood, and has appropriate physical meaning for both small and large human crowds in a wide variety of situations. We conclude with general remarks about the meaning of density measurements for small groups of pedestrians., Comment: 27 pages, 10 figures. arXiv admin note: text overlap with arXiv:2212.01338

The high contrast and spatial resolution requirements for directly imaging exoplanets requires effective coordination of wavefront control, coronagraphy, observation techniques, and post-processing algorithms. However, even with this suite of tools, identifying and retrieving exoplanet signals embedded in resolved scattered light regions can be extremely challenging due to the increased noise from scattered light off the circumstellar disk and the potential misinterpretation of the true nature of the detected signal. This issue pertains not only to imaging terrestrial planets in habitable zones within zodiacal and exozodiacal emission but also to young planets embedded in circumstellar, transitional, and debris disks. This is particularly true for H{\alpha} detection of exoplanets in transitional disks. This work delves into recent H{\alpha} observations of three transitional disks systems with MagAO-X, an extreme adaptive optics system for the 6.5-meter Magellan Clay telescope. We employed angular differential imaging (ADI) and simultaneous spectral differential imaging (SSDI) in combination with KLIP, a PCA algorithm in post-processing, for optimal starlight suppression and quasi-static noise removal. We discuss the challenges in protoplanet identification with MagAO-X in environments rich with scattered and reflected light from disk structures and explore a potential solution for removing noise contributions from real astronomical objects with current observation and post-processing techniques.

The next generation of extreme adaptive optics (AO) must be calibrated exceptionally well to achieve the desired contrast for ground-based direct imaging exoplanet targets. Current wavefront sensing and control system responses deviate from lab calibration throughout the night due to non linearities in the wavefront sensor (WFS) and signal loss. One cause of these changes is the optical gain (OG) effect, which shows that the difference between actual and reconstructed wavefronts is sensitive to residual wavefront errors from partially corrected turbulence. This work details on-sky measurement of optical gain on MagAO-X, an extreme AO system on the Magellan Clay 6.5m. We ultimately plan on using a method of high-temporal frequency probes on our deformable mirror to track optical gain on the Pyramid WFS. The high-temporal frequency probes, used to create PSF copies at 10-22 lambda /D, are already routinely used by our system for coronagraph centering and post-observation calibration. This method is supported by the OG measurements from the modal response, measured simultaneously by sequenced pokes of each mode. When tracked with DIMM measurements, optical gain calibrations show a clear dependence on Strehl Ratio, and this relationship is discussed. This more accurate method of calibration is a crucial next step in enabling higher fidelity correction and post processing techniques for direct imaging ground based systems., Comment: 7 pages, 6 figures, proceedings of Adaptive Optics Systems IX at SPIE Astronomical Telescopes + Instrumentation 2024

MagAO-X is the extreme coronagraphic adaptive optics (AO) instrument for the 6.5-meter Magellan Clay telescope and is currently undergoing a comprehensive batch of upgrades. One innovation that the instrument features is a deformable mirror (DM) dedicated for non-common path aberration correction (NCPC) within the coronagraph arm. We recently upgraded the 97 actuator NCPC DM with a 1000 actuator Boston Micromachines Kilo-DM which serves to (1) correct non-common path aberrations which hamper performance at small inner-working angles, (2) facilitate focal-plane wavefront control algorithms (e.g., electric field conjugation) and (3) enable 10 kHz correction speeds (up from 2 kHz) to assist post-AO, real-time low-order wavefront control. We present details on the characterization and installation of this new DM on MagAO-X as part of our efforts to improve deep contrast performance for imaging circumstellar objects in reflected light. Pre-installation procedures included use of a Twyman-Green interferometer to build an interaction matrix for commanding the DM surface, in closed-loop, to a flat state for seamless integration into the instrument. With this new NCPC DM now installed, we report on-sky results from the MagAO-X observing run in March -- May 2024 for the Focus Diversity Phase Retrieval and implicit Electric Field Conjugation algorithms for quasistatic speckle removal and in-situ Strehl ratio optimization, respectively., Comment: 9 pages, 9 figures, proceedings of SPIE Astronomical Telescopes + Instrumentation 2024

MagAO-X is the coronagraphic extreme adaptive optics system for the 6.5 m Magellan Clay Telescope. We report the results of commissioning the first phase of MagAO-X. Components now available for routine observations include: the >2 kHz high-order control loop consisting of a 97 actuator woofer deformable mirror (DM), a 2040 actuator tweeter DM, and a modulated pyramid wavefront sensor (WFS); classical Lyot coronagraphs with integrated low-order (LO) WFS and control using a third 97-actuator non-common path correcting (NCPC) DM; broad band imaging in g, r, i, and z filters with two EMCCDs; simultaneous differential imaging in H-alpha; and integral field spectroscopy with the VIS-X module. Early science results include the discovery of an H-alpha jet, images of accreting protoplanets at H-alpha, images of young extrasolar giant planets in the optical, discovery of new white dwarf companions, resolved images of evolved stars, and high-contrast images of circumstellar disks in scattered light in g-band (500 nm). We have commenced an upgrade program, called "Phase II", to enable high-contrast observations at the smallest inner working angles possible. These upgrades include a new 952 actuator NCPC DM to enable coronagraphic wavefront control; phase induced amplitude apodization coronagraphs; new fast cameras for LOWFS and Lyot-LOWFS; and real-time computer upgrades. We will report the status of these upgrades and results of first on-sky testing in March-May 2024., Comment: Presented at SPIE Astronomical Telescopes

High-contrast imaging data analysis depends on removing residual starlight from the host star to reveal planets and disks. Most observers do this with principal components analysis (i.e. KLIP) using modes computed from the science images themselves. These modes may not be orthogonal to planet and disk signals, leading to over-subtraction. The wavefront sensor data recorded during the observation provide an independent signal with which to predict the instrument point-spread function (PSF). MagAO-X is an extreme adaptive optics (ExAO) system for the 6.5-meter Magellan Clay telescope and a technology pathfinder for ExAO with GMagAO-X on the upcoming Giant Magellan Telescope. MagAO-X is designed to save all sensor information, including kHz-speed wavefront measurements. Our software and compressed data formats were designed to record the millions of training samples required for machine learning with high throughput. The large volume of image and sensor data lets us learn a PSF model incorporating all the information available. This will eventually allow us to probe smaller star-planet separations at greater sensitivities, which will be needed for rocky planet imaging., Comment: 9 pages, 5 figures, proceedings of Adaptive Optics Systems IX at SPIE Astronomical Telescopes + Instrumentation 2024

We prove a Liouville type result for convex solutions of the Lagrangian mean curvature flow with restricted quadratic growth assumptions at antiquity on the solutions., Comment: 13 pages

Mars' tadpole craters are small, young craters whose crater rims are incised by one or more exit breaches but lack visible inlets. The tadpole forming climate records the poorly understood drying of Mars since the Early Hesperian. A third of tadpole craters have multiple breaches, therefore a process is needed that was able to generate crater rim incision in multiple locations. We use HiRISE data for four multiple breach tadpole craters to measure their crater fill, rims, and exit breaches. We compare these measurements and other data to our calculations of liquid water supply by rain, surface melting, groundwater discharge, and basal ice sheet melting to discriminate between four proposed formation hypotheses for tadpole breaches, favoring scenarios with ice-filled craters and supraglacial melting. We conclude that multiple breach tadpole craters record hundreds of meters of mid-latitude ice and climate conditions enabling intermittent melting in the Late Hesperian and Amazonian, suggesting that liquid water on Mars has been available in association with water ice for billions of years., Comment: Planetary Science Journal, in press

The X$_2$MH$_6$ family, consisting of an electropositive cation X and a main group metal M octahedrally coordinated by hydrogen, has been predicted to hold promise for high-temperature conventional superconductivity. Herein, we analyze the electronic structure of two members of this family, Mg$_2$IrH$_6$ and Ca$_2$IrH$_6$, showing why the former may possess superconducting properties rivaling those of the cuprates, whereas the latter does not. Within Mg$_2$IrH$_6$ the vibrations of the IrH$_6^{4-}$ anions are key for the superconducting mechanism, and they induce coupling in the $e_g^*$ set, which are antibonding between the H 1$s$ and the Ir $d_{x^2-y^2}$ or $d_{z^2}$ orbitals. Because calcium possesses low-lying d-orbitals, $e_g^* \rightarrow$ Ca $d$ back-donation is preferred, quenching the superconductivity. Our analysis explains why high critical temperatures were only predicted for second or third row X metal atoms, and may hold implications for superconductivity in other systems where the antibonding anionic states are filled.

Transformer-based language models have shown state-of-the-art performance on a variety of natural language understanding tasks. To achieve this performance, these models are first pre-trained on general corpus and then fine-tuned on downstream tasks. Previous work studied the effect of pruning the training set of the downstream tasks on the performance of the model on its evaluation set. In this work, we propose an automatic dataset pruning method for the training set of fine-tuning tasks. Our method is based on the model's success rate in correctly classifying each training data point. Unlike previous work which relies on user feedback to determine subset size, our method automatically extracts training subsets that are adapted for each pair of model and fine-tuning task. Our method provides multiple subsets for use in dataset pruning that navigate the trade-off between subset size and evaluation accuracy. Our largest subset, which we also refer to as the winning ticket subset, is on average $3 \times$ smaller than the original training set of the fine-tuning task. Our experiments on 5 downstream tasks and 2 language models show that, on average, fine-tuning on the winning ticket subsets results in a $0.1 \%$ increase in the evaluation performance of the model., Comment: 28 pages, 17 figures. Accepted at the Third Conference on Lifelong Learning Agents (CoLLAs 2024)

The stochastic noise of splitting, defined initially on the (basic) algebra of unions of intervals of the real line, is extended to a maximal class of domains. The $\sigma$-fields of this largest extension constitute the completion, in the sense of noise-type Boolean algebras, of the range of the unextended (basic) splitting noise. A Lebesgue measurable domain to which the extension is possible is characterized by a certain stability property: under independent perturbation of Brownian increments off the domain, of the times of Brownian local maxima belonging to the domain; together with the same property for the complement of the domain. A set that is equal to an open set modulo a Lebesgue negligible one, with the same being true of its complement, has this stability property, but others have it too: the extension is non-trivial. Some domains are totally unstable with respect to the indicated perturbation, and to them the extension cannot be made.

We present a detailed model atmosphere analysis of massive white dwarfs with $M > 0.9~M_\odot$ and $T_{\rm eff}\geq11,000$ K in the Montreal White Dwarf Database 100 pc sample and the Pan-STARRS footprint. We obtained follow-up optical spectroscopy of 109 objects with no previous spectral classification in the literature. Our spectroscopic follow-up is now complete for all 204 objects in the sample. We find 118 normal DA white dwarfs, including 45 massive DAs near the ZZ Ceti instability strip. There are no normal massive DBs: the six DBs in the sample are strongly magnetic and/or rapidly rotating. There are 20 massive DQ white dwarfs in our sample, and all are found in the crystallization sequence. In addition, 66 targets are magnetic (32% of the sample). We use magnetic white dwarf atmosphere models to constrain the field strength and geometry using offset dipole models. We also use magnetism, kinematics, and rotation measurements to constrain the fraction of merger remnant candidates among this population. The merger fraction of this sample increases from 25% for 0.9-$1~M_{\odot}$ white dwarfs to 49% for 1.2-$1.3~M_{\odot}$. However, this fraction is as high as $78_{-7}^{+4}$% for 1.1-$1.2~M_{\odot}$ white dwarfs. Previous works have demonstrated that 5-9% of high-mass white dwarfs stop cooling for $\sim8$ Gyr due to the $^{22}$Ne distillation process, which leads to an overdensity of Q-branch stars in the solar neighborhood. We demonstrate that the over-abundance of the merger remnant candidates in our sample is likely due to the same process., Comment: 34 pages, 16 figures, accepted for publication in ApJ

We prove a localization theorem for exotic diffeomorphisms, showing that every diffeomorphism of a compact simply-connected 4-manifold that is isotopic to the identity after stabilizing with one copy of $S^2 \times S^2$, is smoothly isotopic to a diffeomorphism that is supported on a contractible submanifold. For those that require more than one copy of $S^2 \times S^2$, we prove that the diffeomorphism can be isotoped to one that is supported in a submanifold homotopy equivalent to a wedge of 2-spheres, with null-homotopic inclusion map. We investigate the implications of these results by applying them to known exotic diffeomorphisms., Comment: 32 pages, 8 figures

For infectious diseases, characterizing symptom duration is of clinical and public health importance. Symptom duration may be assessed by surveying infected individuals and querying symptom status at the time of survey response. For example, in a SARS-CoV-2 testing program at the University of Washington, participants were surveyed at least 28 days after testing positive and asked to report current symptom status. This study design yielded current status data: outcome measurements for each respondent consisted only of the time of survey response and a binary indicator of whether symptoms had resolved by that time. Such study design benefits from limited risk of recall bias, but analyzing the resulting data necessitates tailored statistical tools. Here, we review methods for current status data and describe a novel application of modern nonparametric techniques to this setting. The proposed approach is valid under weaker assumptions compared to existing methods, allows use of flexible machine learning tools, and handles potential survey nonresponse. From the university study, we estimate that 19% of participants experienced ongoing symptoms 30 days after testing positive, decreasing to 7% at 90 days. Female sex, history of seasonal allergies, fatigue during acute infection, and higher viral load were associated with slower symptom resolution., Comment: The first two authors contributed equally to this work. Main text: 20 pages, 1 figure, 4 tables. Supplement: 14 pages, 8 figures, 0 tables

We report an estimation of the injected mass composition of ultra-high energy cosmic rays (UHECRs) at energies higher than 10 EeV. The composition is inferred from an energy-dependent sky distribution of UHECR events observed by the Telescope Array surface detector by comparing it to the Large Scale Structure of the local Universe. In the case of negligible extra-galactic magnetic fields the results are consistent with a relatively heavy injected composition at E ~ 10 EeV that becomes lighter up to E ~ 100 EeV, while the composition at E > 100 EeV is very heavy. The latter is true even in the presence of highest experimentally allowed extra-galactic magnetic fields, while the composition at lower energies can be light if a strong EGMF is present. The effect of the uncertainty in the galactic magnetic field on these results is subdominant., Comment: 8 pages, 3 figures, accepted for publication in PRL

We use a new method to estimate the injected mass composition of ultrahigh cosmic rays (UHECRs) at energies higher than 10 EeV. The method is based on comparison of the energy-dependent distribution of cosmic ray arrival directions as measured by the Telescope Array experiment (TA) with that calculated in a given putative model of UHECR under the assumption that sources trace the large-scale structure (LSS) of the Universe. As we report in the companion letter, the TA data show large deflections with respect to the LSS which can be explained, assuming small extra-galactic magnetic fields (EGMF), by an intermediate composition changing to a heavy one (iron) in the highest energy bin. Here we show that these results are robust to uncertainties in UHECR injection spectra, the energy scale of the experiment and galactic magnetic fields (GMF). The assumption of weak EGMF, however, strongly affects this interpretation at all but the highest energies E > 100 EeV, where the remarkable isotropy of the data implies a heavy injected composition even in the case of strong EGMF. This result also holds if UHECR sources are as rare as $2 \times 10^{-5}$ Mpc$^{-3}$, that is the conservative lower limit for the source number density., Comment: 18 pages, 11 figures, accepted for publication in PRD

Safety constraints of nonlinear control systems are commonly enforced through the use of control barrier functions (CBFs). Uncertainties in the dynamic model can disrupt forward invariance guarantees or cause the state to be restricted to an overly conservative subset of the safe set. In this paper, adaptive deep neural networks (DNNs) are combined with CBFs to produce a family of controllers that ensure safety while learning the system's dynamics in real-time without the requirement for pre-training. By basing the least squares adaptation law on a state derivative estimator-based identification error, the DNN parameter estimation error is shown to be uniformly ultimately bounded. The convergent bound on the parameter estimation error is then used to formulate CBF-constraints in an optimization-based controller to guarantee safety despite model uncertainty. Furthermore, the developed method is applicable for use under intermittent loss of state-feedback. Comparative simulation results demonstrate the ability of the developed method to ensure safety in an adaptive cruise control problem and when feedback is lost, unlike baseline methods., Comment: 7 pages, 2 figures, 28 references

The front-end electronics of silicon detectors are typically designed to ensure optimal noise performance for the expected input charge. A combination of preamplifiers and shaper circuits result in a nontrivial response of the front-end to injected charge, and the magnitude of the response may be sizeable in readout windows subsequent to that in which the charge was initially injected. The modulation of the discriminator threshold due to the superposition of the front-end response across multiple readout windows is coined "threshold bounce". In this paper, we report a measurement of threshold bounce using silicon modules built for the Phase-II Upgrade of the ATLAS detector at the Large Hadron Collider. These modules utilize ATLAS Binary Chips for their hit readout. The measurement was performed using a micro-focused 15 keV photon beam at the Diamond Light Source synchrotron. The effect of the choice of photon flux and discriminator threshold on the magnitude of the threshold bounce is studied. A Monte Carlo simulation which accounts for the front-end behaviour of the silicon modules is developed, and its predicted hit efficiency is found to be in good agreement with the measured hit efficiency., Comment: 22 pages; accepted to JINST

High-performance, high-volume-manufacturing Si3N4 photonics requires extremely low waveguide losses augmented with heterogeneously integrated lasers for applications beyond traditional markets of high-capacity interconnects. State-of-the-art quality factors (Q) over 200 million at 1550 nm have been shown previously; however, maintaining high Qs throughout laser fabrication has not been shown. Here, Si3N4 resonator intrinsic Qs over 100 million are demonstrated on a fully integrated heterogeneous laser platform. Qi is measured throughout laser processing steps, showing degradation down to 50 million from dry etching, metal evaporation, and ion implant steps, and controllable recovery to over 100 million from annealing at 250C - 350C.

We report on an observation of the difference between northern and southern skies of the ultrahigh energy cosmic ray energy spectrum with a significance of ${\sim}8\sigma$. We use measurements from the two largest experiments$\unicode{x2014}$the Telescope Array observing the northern hemisphere and the Pierre Auger Observatory viewing the southern hemisphere. Since the comparison of two measurements from different observatories introduces the issue of possible systematic differences between detectors and analyses, we validate the methodology of the comparison by examining the region of the sky where the apertures of the two observatories overlap. Although the spectra differ in this region, we find that there is only a $1.8\sigma$ difference between the spectrum measurements when anisotropic regions are removed and a fiducial cut in the aperture is applied., Comment: 8 pages, 6 figures

A key challenge in quantum computing is speeding up measurement and initialization. Here, we experimentally demonstrate a dispersive measurement method for superconducting qubits that simultaneously measures the qubit and returns the readout resonator to its initial state. The approach is based on universal analytical pulses and requires knowledge of the qubit and resonator parameters, but needs no direct optimization of the pulse shape, even when accounting for the nonlinearity of the system. Moreover, the method generalizes to measuring an arbitrary number of modes and states. For the qubit readout, we can drive the resonator to $\sim 10^2$ photons and back to $\sim 10^{-3}$ photons in less than $3 \kappa^{-1}$, while still achieving a $T_1$-limited assignment error below 1\%. We also present universal pulse shapes and experimental results for qutrit readout., Comment: 8 pages, 6 figures

We demonstrate through high-fidelity particle-in-cell simulations a simple approach for efficiently generating 20+ GeV electron beams with the necessary charge, energy spread, and emittance for use as the injector for an electron arm of a future linear collider or a next generation XFEL. The self-focusing of an unmatched, relatively low quality, drive beam results in self-injection by elongating the wakefield excited in the nonlinear blowout regime. Over pump depletion distances, the drive beam dynamics and self-loading from the injected beam leads to extremely high quality and high energy output beams. For plasma densities of $10^{18} \ \text{cm}^{-3}$, PIC simulation results indicate that self-injected beams with $0.52 \ \text{nC}$ of charge can be accelerated to $\sim 20$ GeV energies with projected energy spreads, $\lesssim 1\%$ within the beam core, slice normalized emittances as low as $110 \ \text{nm}$, a peak normalized brightness $\gtrsim 10^{19} \ \text{A}/\text{m}^2/\text{rad}^2$, and energy transfer efficiencies $\gtrsim 54\%$.

Gradient approximations are a class of numerical approximation techniques that are of central importance in numerical optimization. In derivative-free optimization, most of the gradient approximations, including the simplex gradient, centred simplex gradient, and adapted centred simplex gradient, are in the form of simplex derivatives. Owing to machine precision, the approximation accuracy of any numerical approximation technique is subject to the influence of floating point errors. In this paper, we provide a general framework for floating point error analysis of simplex derivatives. Our framework is independent of the choice of the simplex derivative as long as it satisfies a general form. We review the definition and approximation accuracy of the generalized simplex gradient and generalized centred simplex gradient. We define and analyze the accuracy of a generalized version of the adapted centred simplex gradient. As examples, we apply our framework to the generalized simplex gradient, generalized centred simplex gradient, and generalized adapted centred simplex gradient. Based on the results, we give suggestions on the minimal choice of approximate diameter of the sample set.

Ranking distributions according to a stochastic order has wide applications in diverse areas. Although stochastic dominance has received much attention,convex order, particularly in general dimensions, has yet to be investigated from a statistical point of view. This article addresses this gap by introducing a simple statistical test for convex order based on the Wasserstein projection distance. This projection distance not only encodes whether two distributions are indeed in convex order, but also quantifies the deviation from the desired convex order and produces an optimal convex order approximation. Lipschitz stability of the backward and forward Wasserstein projection distance is proved, which leads to elegant consistency results of the estimator we employ as our test statistic. Combining these with state of the art results regarding the convergence rate of empirical distributions, we also derive upper bounds for the $p$-value and type I error our test statistic, as well as upper bounds on the type II error for an appropriate class of strict alternatives. Lastly, we provide an efficient numerical scheme for our test statistic, by way of an entropic Frank-Wolfe algorithm. Some experiments based on synthetic data sets illuminates the success of our approach empirically.

Accurate modeling of quantum systems interacting with environments requires addressing non-unitary dynamics, which significantly complicates computational approaches. In this work, we enhance an open quantum system (OQS) theory using density-matrix purification, enabling a unitary description of dynamics by entangling the system with an environment of equal dimension. We first establish the connection between density-matrix purification and conventional OQS methods. We then demonstrate the standalone applicability of purification theory by deriving system-environment interactions from fundamental design principles. Using model systems, we show that the purification approach extends beyond the complete positivity condition and effectively models both Markovian and non-Markovian dynamics. Finally, we implement density-matrix purification on a quantum simulator, illustrating its capability to map non-unitary OQS dynamics onto a unitary framework suitable for quantum computers.

In large-scale regression problems, random Fourier features (RFFs) have significantly enhanced the computational scalability and flexibility of Gaussian processes (GPs) by defining kernels through their spectral density, from which a finite set of Monte Carlo samples can be used to form an approximate low-rank GP. However, the efficacy of RFFs in kernel approximation and Bayesian kernel learning depends on the ability to tractably sample the kernel spectral measure and the quality of the generated samples. We introduce Stein random features (SRF), leveraging Stein variational gradient descent, which can be used to both generate high-quality RFF samples of known spectral densities as well as flexibly and efficiently approximate traditionally non-analytical spectral measure posteriors. SRFs require only the evaluation of log-probability gradients to perform both kernel approximation and Bayesian kernel learning that results in superior performance over traditional approaches. We empirically validate the effectiveness of SRFs by comparing them to baselines on kernel approximation and well-known GP regression problems., Comment: To appear at UAI24

Effective meetings are effortful, but traditional videoconferencing systems offer little support for reducing this effort across the meeting lifecycle. Generative AI (GenAI) has the potential to radically redefine meetings by augmenting intentional meeting behaviors. CoExplorer, our novel adaptive meeting prototype, preemptively generates likely phases that meetings would undergo, tools that allow capturing attendees' thoughts before the meeting, and for each phase, window layouts, and appropriate applications and files. Using CoExplorer as a technology probe in a guided walkthrough, we studied its potential in a sample of participants from a global technology company. Our findings suggest that GenAI has the potential to help meetings stay on track and reduce workload, although concerns were raised about users' agency, trust, and possible disruption to traditional meeting norms. We discuss these concerns and their design implications for the development of GenAI meeting technology., Comment: DIS 2024

CrX$_3$ (X = Cl, Br, I) have the same crystal structure and Hamiltonian but different ligand spin-orbit coupling (SOC) constant $\lambda_X$, providing excellent material platform exploring for exotic two-dimensional (2D) spin orders. Their microscopic mechanism underlying 2D spin physics and Hamiltonian remain unestablished, along with experimental corroboration of Kitaev exchange interaction, central to realizing topological quantum spin liquids. We report Kitaev interaction signature in magnetic anisotropy measured by ferromagnetic resonance (FMR) spectroscopy. We present measured values of Heisenberg J, Kitaev K, and off-diagonal symmetric $\Gamma$ exchange interactions in CrX$_3$ determined using FMR and exact diagonalization. K and $\Gamma$ exhibit dominant quadratic dependencies on $\lambda_X$, indicating its central role in 2D magnetism. Our study provides foundation for exploring exotic 2D magnetic topologies by tuning intrinsic material parameters such as SOC., Comment: 18 pages, 4 figures

The integration of Large Language Models (LLMs) into the healthcare domain has the potential to significantly enhance patient care and support through the development of empathetic, patient-facing chatbots. This study investigates an intriguing question Can ChatGPT respond with a greater degree of empathy than those typically offered by physicians? To answer this question, we collect a de-identified dataset of patient messages and physician responses from Mayo Clinic and generate alternative replies using ChatGPT. Our analyses incorporate novel empathy ranking evaluation (EMRank) involving both automated metrics and human assessments to gauge the empathy level of responses. Our findings indicate that LLM-powered chatbots have the potential to surpass human physicians in delivering empathetic communication, suggesting a promising avenue for enhancing patient care and reducing professional burnout. The study not only highlights the importance of empathy in patient interactions but also proposes a set of effective automatic empathy ranking metrics, paving the way for the broader adoption of LLMs in healthcare.

We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in that it focused on meningiomas, which are typically benign extra-axial tumors with diverse radiologic and anatomical presentation and a propensity for multiplicity. Nine participating teams each developed deep-learning automated segmentation models using image data from the largest multi-institutional systematically expert annotated multilabel multi-sequence meningioma MRI dataset to date, which included 1000 training set cases, 141 validation set cases, and 283 hidden test set cases. Each case included T2, T2/FLAIR, T1, and T1Gd brain MRI sequences with associated tumor compartment labels delineating enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Participant automated segmentation models were evaluated and ranked based on a scoring system evaluating lesion-wise metrics including dice similarity coefficient (DSC) and 95% Hausdorff Distance. The top ranked team had a lesion-wise median dice similarity coefficient (DSC) of 0.976, 0.976, and 0.964 for enhancing tumor, tumor core, and whole tumor, respectively and a corresponding average DSC of 0.899, 0.904, and 0.871, respectively. These results serve as state-of-the-art benchmarks for future pre-operative meningioma automated segmentation algorithms. Additionally, we found that 1286 of 1424 cases (90.3%) had at least 1 compartment voxel abutting the edge of the skull-stripped image edge, which requires further investigation into optimal pre-processing face anonymization steps., Comment: 16 pages, 11 tables, 10 figures, MICCAI

The brightest gamma ray burst (GRB) ever observed, GRB221009A, produced a surprisingly large flux of gamma rays with multi-TeV energies, which are expected to be absorbed in interactions with extragalactic background light (EBL). If the highest energy gamma rays were produced at the source, their spectral shape would have to exhibit a nonphysical spike even for the lowest levels of EBL. We show that, for widely accepted models of EBL, the data can be explained by secondary gamma rays produced in cosmic ray interactions along the line of sight, as long as the extragalactic magnetic fields (EGMFs) are $10^{-16}$G or smaller, assuming 1 Mpc correlation length. Our interpretation supports the widely held expectation that GRB jets can accelerate cosmic rays to energies as high as 10 EeV and above, and it has implications for understanding the magnitudes of EGMFs., Comment: 6 pages, 3 figures