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This brief continues ongoing research by NWEA® examining the degree to which the COVID-19 pandemic, and its associated school closures, influenced student learning. Prior research focused on math and reading and found that the pandemic's negative impact steadily accumulated during the 2020-2021 school year, with significant disparities in achievement and growth compared to prepandemic trends (Lewis, Kuhfeld, Ruzek, & McEachin, 2021). Although there were modest rebounds in reading and math during the 2021-2022 school year, progress toward pandemic recovery largely stalled in 2022-2023 and 2023-2024, with achievement and growth trends still trailing behind prepandemic levels (Kuhfeld & Lewis, 2022; Lewis & Kuhfeld, 2023; Lewis & Kuhfeld, 2024). Building on previous research series focused on math and reading achievement, this brief explores how the pandemic influenced student achievement in science. It examines science test scores across seven school years to understand how COVID-19 influenced science achievement.

The purpose of this technical appendix is to share detailed results and more fully describe the sample and methods used to produce the research brief, "COVID's Impact on Science Achievement: Trends from 2019 through 2024. We investigated three main research questions in this brief: 1) How did science achievement in 2021 and 2024 compare to achievement in 2019, before the pandemic? 2) How much additional schooling was required in spring 2021 and spring 2024 to return to spring 2019 levels? 3) How do these patterns differ by race/ethnicity?

The Latino and Adult Student Success (LASS) Academy is a multi-year initiative administered by CAEL (the Council for Adult and Experiential Learning) focused on supporting Hispanic-Serving Institutions (HSIs) in their efforts to improve outcomes for adult and Latino adult learners. In its first phase, from 2018 through 2021, the LASS Academy supported fifteen postsecondary initiatives across the country. In the second phase, from 2022 through 2024, the LASS Academy continued its work with four Texas institutions: Austin Community College (ACC), South Texas College (STC), Texas A&M University-Corpus Christi (TAMU-CC), and the University of Texas Rio Grande Valley (UTRGV). The LASS Academy model facilitates institutional change through four key activities: identify key priorities and action steps; provide technical assistance; collect, analyze, and report data; and facilitate peer-to-peer learning. During the second LASS Academy, each of the four participating institutions made progress toward their goals, buttressed by change management support from CAEL and collaboration with other technical assistance partners. Throughout this work, the institutions gained important insights into ways they can improve their services for adult and Latino adult learners.

This brief is a continuation of NWEA's research series examining the impact of the COVID-19 pandemic on student achievement and progress toward academic recovery. Initiated in the early phase of the pandemic, this series has leveraged NWEA's large national sample of longitudinal MAP® Growth™ data to track student performance and compare it to historical trends. The authors have tracked two critical aspects of student performance in the wake of the pandemic: achievement and growth. Achievement data reveals the extent of unfinished learning. The authors refer to the distance between current test scores and prepandemic trends as "achievement gaps." Growth data estimate how much test scores increase over time. They use these data to indicate whether students are making gains that keep pace with prepandemic trends. Understanding and tracking both achievement and growth is important. Achievement gaps quantify how much unfinished learning remains, while growth patterns help gauge the rate at which gaps will close. The system needs accelerated or above-average growth for students to catch up. The data provide insights into how effectively this is happening. The cumulative research shows that the harmful effects of the pandemic on student achievement steadily accumulated over the course of the 2020-21 school year (Lewis, Kuhfeld, Ruzek, & McEachin, 2021). Growth generally returned to, or slightly exceeded, prepandemic trends in the 2021-22 school year (Kuhfeld & Lewis, 2022). Progress stalled in 2022-23 when growth in nearly all grades fell short of prepandemic trends (Lewis & Kuhfeld, 2023). In this analysis, the authors use 2023-24 school year data to examine the current progress toward recovery. They examine test scores from approximately 7.7 million students currently in grades 3-8 in 22,400 public schools who have taken MAP Growth reading and math assessments since the onset of the pandemic. The "COVID sample" consists of six separate cohorts of students followed longitudinally across the last three school years. For instance, current fifth-graders are part of the grade 3-5 cohort; they measure this cohort's achievement across third grade in 2021-22, fourth grade in 2022-23, and fifth grade in 2023-24. The authors compared this COVID sample to a comparable group of 10 million students who tested in grades 3-8 in the pre-COVID school years of 2016-17 through 2018-19.

School districts have historically operated summer programs to give students extra learning and enrichment opportunities to promote positive academic and behavioral outcomes. Despite the potential benefits and policymakers' endorsement of summer programming, recent research suggests that summer programs have a limited impact on post-pandemic academic recovery, with modest gains in math test scores and no impact in reading. This may be partly due to the challenges districts face in implementing academic recovery programs at the scale needed to impact student outcomes. This brief highlights the efficacy of summer programs for literacy, math and social-emotional learning (SEL) outcomes, showing that well-designed summer programs can meaningfully boost student achievement. The report also provides recommendations for district leaders to use as a framework for planning and implementing effective summer programming.

This study investigates the role of college major choices in labor market outcomes, with a focus on racial minorities and immigrants. Drawing upon research on school-to-work linkages, we examine two measures, linkage, the connection between college majors and specific occupations in the labor market, and match, the alignment of workers' occupations with their college majors. Analyzing data from the American Community Survey, 2013-2017, we show that linkage positively predicts earnings, particularly for workers in matched occupations, and negatively predicts unemployment. Notably, Black, Hispanic, and foreign-born workers in matched occupations benefit more from linkage strength than their White and U.S.-born counterparts. This advantage is more pronounced in states that are popular destinations for immigrants. Our findings suggest that earnings and unemployment disparities experienced among racial minorities and immigrants may diminish if they pursue majors closely tied to jobs in the labor market and secure jobs related to their college majors.

Computer models (simulators) are vital tools for investigating physical processes. Despite their utility, the prohibitive run-time of simulators hinders their direct application for uncertainty quantification. Gaussian process emulators (GPEs) have been used extensively to circumvent the cost of the simulator and are known to perform well on simulators with smooth, stationary output. In reality, many simulators violate these assumptions. Motivated by a finite element simulator which models early stage corrosion of uranium in water vapor, we propose an adaption of the GPE, called the double emulator, specifically for simulators which 'ground' in a considerable volume of their input space. Grounding is the process by which a simulator attains its minimum and can result in violation of the stationarity and smoothness assumptions used in the conventional GPE. We perform numerical experiments comparing the performance of the GPE and double emulator on both the corrosion simulator and synthetic examples., Comment: 29 pages, 12 figures

LLMs have performed well on several reasoning benchmarks, including ones that test analogical reasoning abilities. However, there is debate on the extent to which they are performing general abstract reasoning versus employing non-robust processes, e.g., that overly rely on similarity to pre-training data. Here we investigate the robustness of analogy-making abilities previously claimed for LLMs on three of four domains studied by Webb, Holyoak, and Lu (2023): letter-string analogies, digit matrices, and story analogies. For each domain we test humans and GPT models on robustness to variants of the original analogy problems that test the same abstract reasoning abilities but are likely dissimilar from tasks in the pre-training data. The performance of a system that uses robust abstract reasoning should not decline substantially on these variants. On simple letter-string analogies, we find that while the performance of humans remains high for two types of variants we tested, the GPT models' performance declines sharply. This pattern is less pronounced as the complexity of these problems is increased, as both humans and GPT models perform poorly on both the original and variant problems requiring more complex analogies. On digit-matrix problems, we find a similar pattern but only on one out of the two types of variants we tested. On story-based analogy problems, we find that, unlike humans, the performance of GPT models are susceptible to answer-order effects, and that GPT models also may be more sensitive than humans to paraphrasing. This work provides evidence that LLMs often lack the robustness of zero-shot human analogy-making, exhibiting brittleness on most of the variations we tested. More generally, this work points to the importance of carefully evaluating AI systems not only for accuracy but also robustness when testing their cognitive capabilities., Comment: 31 pages, 13 figures. arXiv admin note: text overlap with arXiv:2402.08955

We investigate the Demazure product in a double affine setting. Work by Muthiah and Pusk\'as gives a conjectural way to define this in terms of the $q=0$ specialisation of these Hecke algebras. We instead take a different approach generalising work by Felix Schremmer, who gave an equivalent formula for the (single) affine Demazure product in terms of the quantum Bruhat graph. We focus on type $\widehat{SL}_2$, where we prove that the quantum Bruhat graph of this type satisfies some nice properties, which allows us to construct a well-defined associative Demazure product for the double affine Weyl semigroup $W_{\mathcal{T}}$ (for level greater than one). We give results regarding the Demazure product and Muthiah and Orr's length function for $W_{\mathcal{T}}$, and we verify that our proposal matches specific examples computed by Muthiah and Pusk\'as using the Kac-Moody affine Hecke algebra, Comment: 25 pages. Comments welcome

We report measurements of the absolute branching fractions $\mathcal{B}(B_s^0 \to D_s^{\pm} X)$, $\mathcal{B}(B_s^0 \to D^0/\bar{D}^0 X)$, and $\mathcal{B}(B_s^0 \to D^{\pm} X)$, where the latter is measured for the first time. The results are based on a 121.4\,fb$^{-1}$ data sample collected at the $\Upsilon(10860)$ resonance by the Belle detector at the KEKB asymmetric-energy $e^+ e^-$ collider. We reconstruct one $B_s^0$ meson in $e^+e^- \to \Upsilon(10860) \to B_s^{*} \bar{B}_s^{*}$ events and measure yields of $D_s^+$, $D^0$, and $D^+$ mesons in the rest of the event. We obtain $\mathcal{B}(B_s^0 \to D_s^{\pm} X) = (68.6 \pm 7.2 \pm 4.0)\%$, $\mathcal{B}(B_s^0 \to D^0/\bar{D}^0 X) = (21.5 \pm 6.1 \pm 1.8)\%$, and $\mathcal{B}(B_s^0 \to D^{\pm} X) = (12.6 \pm 4.6 \pm 1.3)\%$, where the first uncertainty is statistical and the second is systematic. Averaging with previous Belle measurements gives $\mathcal{B}(B_s^0 \to D_s^{\pm} X) = (63.4 \pm 4.5 \pm 2.2)\%$ and $\mathcal{B}(B_s^0 \to D^0/\bar{D}^0 X) = (23.9 \pm 4.1 \pm 1.8)\%$. For the $B_s^0$ production fraction at the $\Upsilon(10860)$, we find $f_s = (21.4^{+1.5}_{-1.7})\%$., Comment: 23 pages, 9 figures, submitted to JHEP

This work theoretically investigates the transition from topology to chaos in a periodically driven system consisting of a quantum top coupled to a spin-1/2 particle. The system is driven by two alternating interaction kicks per period. For small kick strengths, localized topologically protected bound states exist, and as the kick strengths increase, these states proliferate. However, at large kick strengths they gradually delocalize in stages, eventually becoming random orthonormal vectors as chaos emerges. We identify the delocalization of the bound states as a finite size effect where their proliferation leads to their eventual overlap. This insight allows us to make analytic predictions for the onset and full emergence of chaos which are supported by numerical results of the quasi-energy level spacing ratio and R\'{e}nyi entropy. A dynamical probe is also proposed to distinguish chaotic from regular behavior., Comment: 9 pages, 5 figures

Grading assessments is time-consuming and prone to human bias. Students may experience delays in receiving feedback that may not be tailored to their expectations or needs. Harnessing AI in education can be effective for grading undergraduate physics problems, enhancing the efficiency of undergraduate-level physics learning and teaching, and helping students understand concepts with the help of a constantly available tutor. This report devises a simple empirical procedure to investigate and quantify how well large language model (LLM) based AI chatbots can grade solutions to undergraduate physics problems in Classical Mechanics, Electromagnetic Theory and Quantum Mechanics, comparing humans against AI grading. The following LLMs were tested: Gemini 1.5 Pro, GPT-4, GPT-4o and Claude 3.5 Sonnet. The results show AI grading is prone to mathematical errors and hallucinations, which render it less effective than human grading, but when given a mark scheme, there is substantial improvement in grading quality, which becomes closer to the level of human performance - promising for future AI implementation. Evidence indicates that the grading ability of LLM is correlated with its problem-solving ability. Through unsupervised clustering, it is shown that Classical Mechanics problems may be graded differently from other topics. The method developed can be applied to investigate AI grading performance in other STEM fields., Comment: 16 pages + appendices

We present a detailed study of the large-scale shock front in Stephan's Quintet, a byproduct of past and ongoing interactions. Using integral-field spectroscopy from the new William Herschel Telescope Enhanced Area Velocity Explorer (WEAVE), recent 144 MHz observations from the LOFAR Two-metre Sky Survey (LoTSS), and archival data from the Very Large Array and James Webb Space Telescope (JWST), we obtain new measurements of key shock properties and determine its impact on the system. Harnessing the WEAVE large integral field unit's (LIFU) field of view (90 $\times$ 78 arcsec$^{2}$), spectral resolution ($R\sim2500$) and continuous wavelength coverage across the optical band, we perform robust emission line modeling and dynamically locate the shock within the multi-phase intergalactic medium (IGM) with higher precision than previously possible. The shocking of the cold gas phase is hypersonic, and comparisons with shock models show that it can readily account for the observed emission line ratios. In contrast, we demonstrate that the shock is relatively weak in the hot plasma visible in X-rays (with Mach number of $\mathcal{M} \sim 2 - 4$), making it inefficient at producing the relativistic particles needed to explain the observed synchrotron emission. Instead, we propose that it has led to an adiabatic compression of the medium, which has increased the radio luminosity ten-fold. Comparison of the Balmer line-derived extinction map with the molecular gas and hot dust observed with JWST suggests that pre-existing dust may have survived the collision, allowing the condensation of H$_{2}$ - a key channel for dissipating the shock energy., Comment: 23 pages, 15 figures, accepted for publication in MNRAS

Transposons are tiny intragenomic parasites found in every branch of life. Often, one transposon will hyperparasitize another, forming an intracellular ecosystem. In some species these ecosystems thrive, while in others they go extinct, yet little is known about when or why this occurs. Here, we present a stochastic model for these ecosystems and discover a dynamical phase transition from stable coexistence to population collapse when the propensity for a transposon to replicate comes to exceed that of its hyperparasites. Our model also predicts that replication rates should be low in equilibrium, which appears to be true of many transposons in nature.

We present measurements of $B \to K{}^{*}(892)\gamma$ decays using $365\,{\rm fb}^{-1}$ of data collected from 2019 to 2022 by the Belle~II experiment at the SuperKEKB asymmetric-energy $e^+e^-$ collider. The data sample contains $(387 \pm 6) \times 10^6$ $B\overline{B}$ events. We measure branching fractions ($\mathcal{B}$) and $C\!P$ asymmetries ($\mathcal{A}_{C\!P}$) for both $B^{0}\to K{}^{*0}\gamma$ and $B^{+}\to K{}^{*+}\gamma$ decays. The difference in $C\!P$ asymmetries ($\Delta \mathcal{A}_{C\!P}$) and the isospin asymmetry ($\Delta_{0+}$) between these neutral and charged channels are also measured. We obtain the following branching fractions and $C\!P$ asymmetries: $\mathcal{B} (B^{0} \to K{}^{*0}\gamma) = (4.14 \pm 0.10 \pm 0.11 ) \times 10^{-5}$, $\mathcal{B} (B^{+} \to K{}^{*+}\gamma) = (4.02 \pm 0.13 \pm 0.13 )\times 10^{-5}$, $\mathcal{A}_{C\!P} (B^{0} \to K{}^{*0}\gamma) = (-3.3 \pm 2.3 \pm 0.4 )\%$, and $\mathcal{A}_{C\!P} (B^{+} \to K{}^{*+}\gamma) = (-0.7 \pm 2.9 \pm 0.6 )\%$. The measured difference in $C\!P$ asymmetries is $\Delta \mathcal{A}_{C\!P} = (+2.6 \pm 3.8 \pm 0.7 )\%$, and the measured isospin asymmetry is $\Delta_{0+} = (+5.0 \pm 2.0 \pm 1.5 )\%$. The first uncertainties listed are statistical and the second are systematic. These results are consistent with world-average values and theory predictions.

Unconventional superconductivity, where electron pairing does not involve electron-phonon interactions, is often attributed to magnetic correlations in a material. Well known examples include high-T_c cuprates and uranium-based heavy fermion superconductors. Less explored are unconventional superconductors with strong spin-orbit coupling, where interactions between spin-polarised electrons and external magnetic field can result in multiple superconducting phases and field-induced transitions between them, a rare phenomenon in the superconducting state. Here we report a magnetic-field driven phase transition in \beta-PdBi2, a layered non-magnetic superconductor. Our tunnelling spectroscopy on thin PdBi2 monocrystals incorporated in planar superconductor-insulator-normal metal junctions reveals a marked discontinuity in the superconducting properties with increasing in-plane field, which is consistent with a transition from conventional (s-wave) to nodal pairing. Our theoretical analysis suggests that this phase transition may arise from spin polarisation and spin-momentum locking caused by locally broken inversion symmetry, with p-wave pairing becoming energetically favourable in high fields. Our findings also reconcile earlier predictions of unconventional multigap superconductivity in \beta-PdBi2 with previous experiments where only a single s-wave gap could be detected., Comment: 29 pages, including 4 main Figures, Methods, 8 Supplementary Figures and 5 Supplementary Notes

Let $G$ be a finite group, and let $d$ be the degree of an irreducible character of $G$ such that $|G|=d(d+e)$ for some $e>1$. Consider the case when $G$ is solvable, $d$ is square-free, and $(d,d+e)=1$. We wish to explore an equivalent condition on $G$ when $d\in\text{cd}(G)$. We show that if $d\in\text{cd}(G)$ then there is a sequence of congruences relating the prime power factors of $d+e$ to the product of prime factors of $d$ such that the product of the moduli in this sequence of congruences is $d$. Moreover, the argument will hold in both directions.

As globular clusters (GCs) orbit the Milky Way, their stars are tidally stripped forming tidal tails that follow the orbit of the clusters around the Galaxy. The morphology of these tails is complex and shows correlations with the phase of the orbit and the orbital angular velocity, especially for GCs on eccentric orbits. Here, we focus on two GCs, NGC 1261 and NGC 1904, that have potentially been accreted alongside Gaia-Enceladus and that have shown signatures of having, in addition of tidal tails, structures formed by distributions of extra-tidal stars that are misaligned with the general direction of the clusters' respective orbits. To provide an explanation for the formation of these structures, we make use of spectroscopic measurements from the Southern Stellar Stream Spectroscopic Survey ($S^5$) as well as proper motion measurements from Gaia's third data release (DR3), and apply a Bayesian mixture modeling approach to isolate high-probability member stars. We recover extra-tidal features similar to those found in Shipp et al. (2018) surrounding each cluster. We conduct N-body simulations and compare the expected distribution and variation in the dynamical parameters along the orbit with those of our potential member sample. Furthermore, we use Dark Energy Camera (DECam) photometry to inspect the distribution of the member stars in the color-magnitude diagram (CMD). We find that the potential members agree reasonably with the N-body simulations and that the majority of them follow a simple stellar population-like distribution in the CMD which is characteristic of GCs. In the case of NGC 1904, we clearly detect the tidal debris escaping the inner and outer Lagrange points which are expected to be prominent when at or close to the apocenter of its orbit. Our analysis allows for further exploration of other GCs in the Milky Way that exhibit similar extra-tidal features.

As the debate over the future of transportation continues in the midst of the COVID-19 pandemic as a deepening global crisis, taxi industry seems to be not spared by the quick and disrupting changes that may arise from the pandemic. The impact is relatively higher in major cities because of the high-density population and transportation congestion. In this study, we used spatial analysis and visualization to investigate the impact of the pandemic on the economics of the taxi industry and travel behavior using trip-by-trip data from the year of 2014 to 2020 in Chicago, IL. Results show that there is a drastic decline in the trips in the central city and airport areas. During the pandemic, people tended to travel longer distances, but travel times were considerably less because of the significant reduction in traffic volumes. Results also showed that the top twenty most popular pick-up and drop-off locations only included Chicago Downtown and OHare International Airport before the pandemic. However, during the pandemic, the top twenty most popular pick-up and drop-off locations is distributed between the Airport, the Downtown, as well as many other areas along Chicago Eastside.

We introduce Edify 3D, an advanced solution designed for high-quality 3D asset generation. Our method first synthesizes RGB and surface normal images of the described object at multiple viewpoints using a diffusion model. The multi-view observations are then used to reconstruct the shape, texture, and PBR materials of the object. Our method can generate high-quality 3D assets with detailed geometry, clean shape topologies, high-resolution textures, and materials within 2 minutes of runtime., Comment: Project website: https://research.nvidia.com/labs/dir/edify-3d

We introduce Edify Image, a family of diffusion models capable of generating photorealistic image content with pixel-perfect accuracy. Edify Image utilizes cascaded pixel-space diffusion models trained using a novel Laplacian diffusion process, in which image signals at different frequency bands are attenuated at varying rates. Edify Image supports a wide range of applications, including text-to-image synthesis, 4K upsampling, ControlNets, 360 HDR panorama generation, and finetuning for image customization.

We extend our time-dependent hydrogen ionization simulations of diffuse ionized gas to include metals important for collisional cooling and diagnostic emission lines. The combination of heating from supernovae and time-dependent collisional and photoionization from midplane OB stars produces emission line intensities (and emission line ratios) that follow the trends observed in the Milky Way and other edge-on galaxies. The long recombination times in low density gas result in persistent large volumes of ions with high ionization potentials, such as O III and Ne III. In particular, the vertically extended layers of Ne III in our time-dependent simulations result in [Ne III] 15$\mu$m/[Ne II] 12$\mu$m emission line ratios in agreement with observations of the edge-on galaxy NGC 891. Simulations adopting ionization equilibrium do not allow for the persistence of ions with high ionization states and therefore cannot reproduce the observed emission lines from low density gas at high altitudes., Comment: 14 pages, 16 figures, accepted for publication in MNRAS

Brown dwarfs with measured dynamical masses and spectra from direct imaging are benchmarks that anchor substellar atmosphere cooling and evolution models. We present Subaru SCExAO/CHARIS infrared spectroscopy of HIP 93398 B, a brown dwarf companion recently discovered by Li et al. 2023 as part of an informed survey using the Hipparcos-Gaia Catalog of Accelerations. This object was previously classified as a T6 dwarf based on its luminosity, with its independently-derived age and dynamical mass in tension with existing models of brown dwarf evolution. Spectral typing via empirical standard spectra, temperatures derived by fitting substellar atmosphere models, and J-H, J-K and H-L' colors all suggest that this object has a substantially higher temperature and luminosity, consistent with classification as a late-L dwarf near the L/T transition (T = 1200$^{+140}_{-119}$ K) with moderate to thick clouds possibly present in its atmosphere. When compared with the latest generation of evolution models that account for clouds with our revised luminosity and temperature for the object, the tension between the model-independent mass/age and model predictions is resolved., Comment: Accepted to AJ, 19 pages

The development of large language models (LLMs) has expanded to multi-modal systems capable of processing text, images, and speech within a unified framework. Training these models demands significantly larger datasets and computational resources compared to text-only LLMs. To address the scaling challenges, we introduce Mixture-of-Transformers (MoT), a sparse multi-modal transformer architecture that significantly reduces pretraining computational costs. MoT decouples non-embedding parameters of the model by modality -- including feed-forward networks, attention matrices, and layer normalization -- enabling modality-specific processing with global self-attention over the full input sequence. We evaluate MoT across multiple settings and model scales. In the Chameleon 7B setting (autoregressive text-and-image generation), MoT matches the dense baseline's performance using only 55.8\% of the FLOPs. When extended to include speech, MoT reaches speech performance comparable to the dense baseline with only 37.2\% of the FLOPs. In the Transfusion setting, where text and image are trained with different objectives, a 7B MoT model matches the image modality performance of the dense baseline with one third of the FLOPs, and a 760M MoT model outperforms a 1.4B dense baseline across key image generation metrics. System profiling further highlights MoT's practical benefits, achieving dense baseline image quality in 47.2\% of the wall-clock time and text quality in 75.6\% of the wall-clock time (measured on AWS p4de.24xlarge instances with NVIDIA A100 GPUs).

We investigate ultra slow-roll inflation in a black hole background finding a correspondence between scalar solutions of ultra slow-roll inflation and quasi-normal modes of the cosmological black hole spacetime. Transitions from slow-roll to ultra slow-roll can enhance the peak of the primordial power spectrum increasing the likelihood of primordial black hole formation. By following such a transition in a black hole background, we observe a decay of the slow-roll attractor solution into the quasi-normal modes of the system. With a large black hole, the ringing modes dominate, which could have implications for the background of cosmological scalar perturbations and peak enhancement., Comment: 34 pages, 10 figures

Dispersion measures (DM) of fast radio bursts (FRBs) probe the density of electrons in the intergalactic medium (IGM) along their lines-of-sight, including the average density versus distance to the source and its variations in direction. While previous study focused on low-redshift, FRBs are potentially detectable out to high redshift, where their DMs can, in principle, probe the epoch of reionization (EOR) and its patchiness. We present the first predictions from large-scale, radiation-hydrodynamical simulation of fully-coupled galaxy formation and reionization, using Cosmic Dawn (``CoDa")~II to model the density and ionization fields of the universe down to redshifts through the end of the EOR at $z_{re}\approx6.1$. Combining this with an N-body simulation CoDa~II--Dark Matter of the fully-ionized epoch from the EOR to the present, we calculate the mean and standard deviation of FRB DMs as functions of their source redshift. The mean and standard deviation of DM increase with redshift, reaching a plateau by $z(x_{HII}\lesssim0.25)\gtrsim8$, i.e. well above $z_{re}$. The mean-DM asymptote $\mathcal{DM}_{max} \approx 5900~\mathrm{pc\, cm^{-3}}$ reflects the end of the EOR and its duration. The standard deviation there is $\sigma_{DM, max}\approx497 ~\mathrm{pc\, cm^{-3}}$, reflecting inhomogeneities of both patchy reionization and density. Inhomogeneities in ionization during the EOR contribute $\mathcal{O}(1$ per cent) of this value of $\sigma_{DM,max}$ from FRBs at redshifts $z\gtrsim 8$. Current estimates of FRB rates suggest this may be detectable within a few years of observation., Comment: 14 pages, 10 figures, 2 tables, 2 appendices

In this paper we first make and discuss a conjecture concerning Newtonian potentials in Euclidean n space which have all their mass on the unit sphere about the origin, and are normalized to be one at the origin. The conjecture essentially divides these potentials into subclasses whose criteria for membership is that a given member have its maximum on the closed unit ball at most M and its minimum at least d. It then lists the extremal potential in each subclass which is conjectured to solve certain extremal problems. In Theorem 1.1 we show existence of these extremal potentials. In Theorem 1.2 we prove an integral inequality on spheres about the origin, involving so called extremal potentials, which lends credence to the conjecture., Comment: 22 pages

One Health issues, such as the spread of highly pathogenic avian influenza (HPAI), present significant challenges at the intersection of human, animal, and environmental health. Recent H5N1 outbreaks underscore the need for comprehensive modeling that capture the complex interactions between various entities in these interconnected ecosystems, encompassing livestock, wild birds, and human populations. To support such efforts, we present a synthetic spatiotemporal gridded dataset for the contiguous United States, referred to as a digital similar. The methodology for constructing this digital similar involves fusing diverse datasets using statistical and optimization techniques. The livestock component includes farm-level representations of multiple livestock types -- cattle, poultry, hogs, and sheep -- including further categorization into subtypes, such as milk and beef cows, chicken, turkeys, ducks, etc. It also includes location-level data for livestock-product processing centers. Weekly abundance data for key wild bird species involved in avian flu transmission are included along with temporal networks of movements. Gridded distributions of the human population, along with demographic and occupational features, capture the placement of agricultural workers and the general population. The digital similar is verified and validated in multiple ways.This dataset aims to provide a comprehensive basis for modeling complex phenomena at the wild-domestic-human interfaces.

Social media platforms have led to online consumption communities, or fandoms, that involve complex networks of ancillary creators and consumers focused on some core product or intellectual property. For example, video game communities include networks of players and content creators centered around a specific video game. These networks are complex in that video game publishers often sponsor creators, but creators and publishers may have divergent incentives. Specifically, creators can potentially benefit from content that builds their own following at the expense of the core game. Our research investigates the relationship between consuming live-streamed content and engagement with a specific video game. We examine the causal effect of viewing live-streamed content on subsequent gameplay for a specific game, using an unexpected service interruption of the livestreaming platform and time zone differences among users. We find live-streamed content significantly increases gameplay as a 10% increase in live-streamed viewing minutes results in a 3.08% increase in gameplay minutes. We also explore how this effect varies by user loyalty to different types of streamer channels (firm-owned, mega, and micro). The positive effects of live-streamed content are greatest for micro-streamers and smallest for mega-streamers. These findings are salient for firms allocating sponsorship resources., Comment: 51 pages, 9 Tables, 6 Figures

Variations in individuals' perceptions of vaccination and decision-making processes can give rise to poor vaccination coverage. The future vaccination promotion programs will benefit from understanding this heterogeneity amongst groups within a population and, accordingly, tailoring the communication strategies. Motivated by this, we developed a mechanistic model consisting of a system of ordinary differential equations that categorizes individuals based on two factors: (i) perceived payoff gains for vaccination and (ii} decision-making strategies where we assumed that individuals may behave as either myopic rationalists, going for a dose of vaccine if doing so maximizes their perceived payoff gain, or success-based learners, waiting to observe feedback on vaccination before deciding. We then investigated the global identifiability of group proportions and perceived payoff gains, that is, the possibility of globally retrieving these parameters by observing the error-free cumulative proportion of vaccinated individuals over time. To do so, for each group, we assumed a piecewise constant payoff gain and, for each time interval, obtained the so-called generalized input-output equation. We then proved the global identifiability of these parameters under certain conditions. Global identifiability opens the door to reliable estimations of the group proportions and their perceived payoffs.

Computational fluid dynamics (CFD) is a specialised branch of fluid mechanics that utilises numerical methods and algorithms to solve and analyze fluid-flow problems. One promising avenue to enhance CFD is the use of quantum computing, which has the potential to resolve nonlinear differential equations more efficiently than classical computers. Here, we try to answer the question of which regimes of nonlinear partial differential equations (PDEs) for fluid dynamics can have an efficient quantum algorithm. We propose a connection between the numerical parameter, $R$, that guarantees efficiency in the truncation of the Carleman linearisation, and the physical parameters that describe the fluid flow. This link can be made thanks to the Kolmogorov scale, which determines the minimum size of the grid needed to properly resolve the energy cascade induced by the nonlinear term. Additionally, we introduce the formalism for vector field simulation in different spatial dimensions, providing the discretisation of the operators and the boundary conditions.

This study evaluates the generalisation capabilities of state-of-the-art histopathology foundation models on out-of-distribution multi-stain autoimmune Immunohistochemistry datasets. We compare 13 feature extractor models, including ImageNet-pretrained networks, and histopathology foundation models trained on both public and proprietary data, on Rheumatoid Arthritis subtyping and Sjogren's Disease detection tasks. Using a simple Attention-Based Multiple Instance Learning classifier, we assess the transferability of learned representations from cancer H&E images to autoimmune IHC images. Contrary to expectations, histopathology-pretrained models did not significantly outperform ImageNet-pretrained models. Furthermore, there was evidence of both autoimmune feature misinterpretation and biased feature importance. Our findings highlight the challenges in transferring knowledge from cancer to autoimmune histopathology and emphasise the need for careful evaluation of AI models across diverse histopathological tasks. The code to run this benchmark is available at https://github.com/AmayaGS/ImmunoHistoBench., Comment: Accepted at Workshop on Advancements In Medical Foundation Models (NeurIPS 2024)

We show by an explicit example that the Garsia--Remmel $q$-rook numbers of Ferrers boards do not all have unimodal sequences of coefficients. This resolves in the negative a question from 1986 by the aforementioned authors., Comment: 6 pages

Ballots are the core records of elections. Electronic records of actual ballots cast (cast vote records) are available to the public in some jurisdictions. However, they have been released in a variety of formats and have not been independently evaluated. Here we introduce a database of cast vote records from the 2020 U.S. general election. We downloaded publicly available unstandardized cast vote records, standardized them into a multi-state database, and extensively compared their totals to certified election results. Our release includes vote records for President, Governor, U.S. Senate and House, and state upper and lower chambers -- covering 42.7 million voters in 20 states who voted for more than 2,204 candidates. This database serves as a uniquely granular administrative dataset for studying voting behavior and election administration. Using this data, we show that in battleground states, 1.9 percent of solid Republicans (as defined by their congressional and state legislative voting) in our database split their ticket for Joe Biden, while 1.2 percent of solid Democrats split their ticket for Donald Trump., Comment: 26 pages and appendix

Detached eclipsing binaries (DEBs) allow for the possibility of precise characterization of its stellar components. They offer a unique opportunity to derive their physical parameters in a near-model-independent way for a number of systems consisting of late-type giant stars. Here we aim to expand the sample of low-metallicity late-type giant stars with precise parameters determined. We aim to determine the fundamental parameters like the mass, radius, or effective temperature for three long-period late-type eclipsing binaries from the Large Magellanic Cloud: OGLE-LMC-ECL-25304, OGLE-LMC-ECL-28283, and OGLE-IV LMC554.19.81. Subsequently we aim to determine the evolutionary stages of the systems. We fit the light curves from the OGLE project and radial velocity curves from high resolution spectrographs using the Wilson-Devinney code. The spectral analysis was performed with the GSSP code and resulted in the determination of atmospheric parameters such as effective temperatures and metallicities. We used isochrones provided by the MIST models based on the MESA code to derive evolutionary status of the stars. We present the first analysis of three DEBs composed of similar He-burning late-type stars passing through the blue loop. Estimated masses for OGLE-LMC-ECL-29293 (G4III + G4III) are $M_1=2.898\pm0.031$ and $M_2=3.153\pm0.038$ $M_\odot$, stellar radii are $R_1=19.43\pm0.31$ and $R_2=19.30\pm0.31$ $R_\odot$. OGLE-LMC-ECL-25304 (G4III + G5III) has stellar masses of $M_1=3.267\pm0.028$ and $M_2=3.229\pm0.029$ $M_\odot$, radii of $R_1=23.62\pm0.42$ and $R_2=25.10\pm0.43$ $R_\odot$. OGLE-IV LMC554.19.81 (G2III + G2III) have masses of $M_1=3.165\pm0.020$ and $M_2=3.184\pm0.020$ $M_\odot$, radii of $R_1=18.86\pm0.26$ and $R_2=19.64\pm0.26$ $R_\odot$. All masses were determined with a precision better than 2\% and radii better than 1.5\%. The ages of the stars are in the range of 270-341 Myr., Comment: 15 pages, 15 figures. Accepted for publication in A&A

Aerosols are a ubiquitous feature of planetary atmospheres and leave clear spectral imprints in exoplanet spectra. Pre-JWST, exoplanet retrieval frameworks mostly adopted simple parametric approximations. With JWST, we now have access to mid-infrared wavelengths where aerosols have detectable composition-specific resonance features. Here, we implement new features into the open-source atmospheric retrieval code POSEIDON to account for the complex scattering, reflection, and absorption properties of Mie scattering aerosols. We provide an open-source database of these Mie scattering cross sections and optical properties. We also extend the radiative transfer and retrieval functionality in POSEIDON to include multiple scattering reflection and emission spectroscopy. We demonstrate these new retrieval capabilities on archival Hubble and Spitzer transmission and secondary eclipse spectra of the hot Jupiter HD 189733 b. We find that a high-altitude, low-density, thin slab composed of sub-micron particles is necessary to fit HD 189733 b's transmission spectrum, with multiple aerosol species providing a good fit. We additionally retrieve a sub-solar H$_2$O abundance, a sub-solar K abundance, and do not detect CO$_2$. Our joint thermal and reflection retrievals of HD 189733 b's secondary eclipse spectrum, however, finds no evidence of dayside aerosols, a sub-solar dayside H$_2$O abundance, enhanced CO$_2$, and slighty sub-solar alkali abundances. We additionally explore how retrieval model choices, such as cloud parameterization, aerosol species and properties, and thermal structure parameterization affect retrieved atmospheric properties. Upcoming JWST data for hot Jupiters like HD 189733 b will be well suited to enable deeper exploration of aerosol properties, allowing the formulation of a self-consistent, multi-dimensional picture of cloud formation processes., Comment: 51 pages, 17 figures, 13 tables. Accepted for publication in ApJ (October 2024)

Let $D: \mathbb{Z}_m^n \to \mathbb{Z}_m^n$ be defined so \[D(x_1, x_2, ..., x_n)=(x_1+x_2 \; \text{mod} \; m, x_2+x_3 \; \text{mod} \; m, ..., x_n+x_1 \; \text{mod} \; m).\] $D$ is known as the Ducci function and for $\mathbf{u} \in \mathbb{Z}_m^n$, $\{D^{\alpha}(\mathbf{u})\}_{\alpha=0}^{\infty}$ is the Ducci sequence of $\mathbf{u}$. Every Ducci sequence enters a cycle because $\mathbb{Z}_m^n$ is finite. In this paper, we aim to establish an upper bound for how long it will take for a Ducci sequence in $\mathbb{Z}_m^n$ to enter its cycle when $n$ is even.

We introduce a new class of billiard-like system, ``bouncing outer billiards" which are 3-dimensional cousins of outer billiards of Neumann and Moser. We prove that bouncing outer billiard on a smooth convex body has at least four 1-parameter families of fixed points. We also fully describe dynamics of bouncing outer billiard on a line segment. Finally we carry out numerical experiments suggesting very complicated (non-ergodic) behavior for several shapes including the square and an ellipse.

Warm Saturn type exoplanets orbiting M-dwarfs are particularly suitable for in-depth cloud characterisation through transmission spectroscopy due to their favourable stellar to planetary radius contrast. However, modelling cloud formation consistently within the 3D atmosphere remains computationally challenging. The aim is to explore the combined atmospheric and micro-physical cloud structure, and the kinetic gas-phase chemistry for the warm Saturn HATS0-6b orbiting an M-dwarf. A combined 3D cloudy atmosphere model is constructed by iteratively executing the 3D General Circulation Model (GCM) expeRT/MITgcm and a kinetic cloud formation model, each in its full complexity. Resulting cloud particle number densities, sizes, and compositions are used to derive the local cloud opacity which is then utilised in the next GCM iteration. The disequilibrium H/C/O/N gas-phase chemistry is calculated for each iteration to assess the resulting transmission spectrum in post-processing. The cloud opacity feedback causes a temperature inversion at the sub-stellar point and at the evening terminator at gas pressures higher than 0.01 bar. Furthermore, clouds cool the atmosphere between 0.01 bar and 10 bar, and narrow the equatorial wind jet. The transmission spectrum shows muted gas-phase absorption and a cloud particle silicate feature at approximately 10 micron. The combined atmosphere-cloud model retains the full physical complexity of each component and therefore enables a detailed physical interpretation with JWST NIRSpec and MIRI LRS observational accuracy. The model shows that warm Saturn type exoplanets around M-dwarfs are ideal candidates to search for limb asymmetries in clouds and chemistry, identify cloud particle composition by observing their spectral features, and identify the cloud-induced strong thermal inversion that arises on these planets specifically., Comment: 21 pages, 15 figures, Accepted by A&A

Ultraviolet wavelengths offer unique insights into aerosols in exoplanetary atmospheres. However, only a handful of exoplanets have been observed in the ultraviolet to date. Here, we present the ultraviolet-visible transmission spectrum of the inflated hot Jupiter WASP-127b. We observed one transit of WASP-127b with WFC3/UVIS G280 as part of the Hubble Ultraviolet-optical Survey of Transiting Legacy Exoplanets (HUSTLE), obtaining a transmission spectrum from 200-800 nm. Our reductions yielded a broad-band transit depth precision of 91 ppm and a median precision of 240 ppm across 59 spectral channels. Our observations are suggestive of a high-altitude cloud layer with forward modeling showing they are composed of sub-micron particles and retrievals indicating a high opacity patchy cloud. While our UVIS/G280 data only offers weak evidence for Na, adding archival HST WFC3/IR and STIS observations raises the overall Na detection significance to 4.1-sigma. Our work demonstrates the capabilities of HST WFC3/UVIS G280 observations to probe the aerosols and atmospheric composition of transiting hot Jupiters with comparable precision to HST STIS., Comment: 25 pages, 8 figures, 6 tables

Chemical abundances of stellar streams can be used to determine the nature of a stream's progenitor. Here we study the progenitor of the recently discovered Leiptr stellar stream, which was previously suggested to be a tidally disrupted halo globular cluster. We obtain high-resolution spectra of five red giant branch stars selected from the Gaia DR2 STREAMFINDER catalog with Magellan/MIKE. One star is a clear non-member. The remaining four stars display chemical abundances consistent with those of a low-mass dwarf galaxy: they have a low mean metallicity, $\langle{\rm[Fe/H]}\rangle = -2.2$; they do not all have identical metallicities; and they display low [$\alpha$/Fe] $\sim 0$ and [Sr/Fe] and [Ba/Fe] $\sim -1$. This pattern of low $\alpha$ and neutron-capture element abundances is only found in intact dwarf galaxies with stellar mass $\lesssim 10^5 M_\odot$. Although more data are needed to be certain, Leiptr's chemistry is consistent with being the lowest-mass dwarf galaxy stream without a known intact progenitor, possibly in the mass range of ultra-faint dwarf galaxies. Leiptr thus preserves a record of one of the lowest-mass early accretion events into the Milky Way., Comment: 18 pages, 12 figures, 8 tables, to be submitted to The Open Journal of Astrophysics