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Simplification of the Free Application for Federal Student Aid (FAFSA) entails significant changes to the FAFSA and the methodology for determining eligibility for federal financial aid for the 2024-25 academic year. The changes to the FAFSA form that were mandated by the Simplification Act delayed implementation and shifted the timeline for release of the 2024-25 FAFSA from October to December 2023. This shift has also led to delays in processing the FAFSA. Through a partnership with the National Association of State Student Grant and Aid Programs (NASSGAP), SHEEO initially convened 12 states from across the country (now expanded to 17 states) in 2022 to participate in a learning community. The learning community provided states with opportunities to examine the impact of FAFSA simplification on state financial aid programs and to take advantage of the open policy window to reconsider state financial aid policies and processes. Feedback from state members has confirmed that, despite the challenges and uncertainties around the rollout of the new FAFSA, states were as prepared as possible to implement the new FAFSA due in part to their participation in the learning community. As the first phase of the learning community concludes, SHEEO staff have conducted case-study interviews with state members of the learning community and the larger SHEEO membership. While all states have worked diligently to help students complete the new FAFSA, the four states selected -- Alabama, Illinois, Louisiana, and Minnesota -- were chosen to represent states that implemented successful strategies for taking advantage of the policy window (Minnesota), employing FAFSA completion initiatives (Alabama, Illinois, and Louisiana), and preparing for the new FAFSA (all states).

Direct Admissions policies, first pioneered by Idaho in 2015, aim to simplify the path to college for high school students by proactively admitting students to state colleges and universities. Idaho's decision to implement Direct Admissions was motivated by a desire to boost its relatively low college-going rates and ensure that more of its high school graduates pursue higher education, particularly at state institutions. Idaho's Direct Admissions system automatically qualified all 2016 public high school seniors for admission to participating colleges and universities based on their academic performance such as standardized test scores, GPA, and high school course credits, without requiring them to undergo the traditional application process. Using the student's SAT score and GPA, the Idaho Office of the State Board of Education (OSBE) proactively admits high school students to the "Letter of 6" or "Letter of 8." Students receiving the Letter of 8 are admitted to all of Idaho's public higher education institutions, while students receiving the Letter of 6 are admitted to all except Boise State University and the University of Idaho, the two more selective institutions in the state. Once a student is guaranteed a seat at any of the colleges listed in their Direct Admissions letter, students then apply to the institutions of choice to verify their enrollment intentions. Direct Admissions is designed to demystify the college application process, reduce barriers to entry, and encourage a higher rate of postsecondary enrollment. Since its implementation, the policy has garnered attention for its role in increasing postsecondary applications and enrollments. It has also emerged as a potential model for other states considering similar reforms. Previous research on Direct Admissions policies in Idaho has examined the policy's effectiveness on institutional applications and enrollment outcomes. This paper uses data on the receipt of a Letter of 6 and receipt of a Letter of 8 to understand how Direct Admissions policies influence student choice in institutional selectivity.

In this paper, we introduce ChatCite, a novel method leveraging large language models (LLMs) for generating comparative literature summaries. The ability to summarize research papers with a focus on key comparisons between studies is an essential task in academic research. Existing summarization models, while effective at generating concise summaries, fail to provide deep comparative insights. ChatCite addresses this limitation by incorporating a multi-step reasoning mechanism that extracts critical elements from papers, incrementally builds a comparative summary, and refines the output through a reflective memory process. We evaluate ChatCite on a custom dataset, CompLit-LongContext, consisting of 1000 research papers with annotated comparative summaries. Experimental results show that ChatCite outperforms several baseline methods, including GPT-4, BART, T5, and CoT, across various automatic evaluation metrics such as ROUGE and the newly proposed G-Score. Human evaluation further confirms that ChatCite generates more coherent, insightful, and fluent summaries compared to these baseline models. Our method provides a significant advancement in automatic literature review generation, offering researchers a powerful tool for efficiently comparing and synthesizing scientific research., Comment: 8 pages

Real world planning problems are often too complex to be effectively tackled by a single unaided human. To alleviate this, some recent work has focused on developing a collaborative planning system to assist humans in complex domains, with bridging the gap between the system's problem representation and the real world being a key consideration. Transferring the speed and correctness formal planners provide to real-world planning problems is greatly complicated by the dynamic and online nature of such tasks. Formal specifications of task and environment dynamics frequently lack constraints on some behaviors or goal conditions relevant to the way a human operator prefers a plan to be carried out. While adding constraints to the representation with the objective of increasing its realism risks slowing down the planner, we posit that the same benefits can be realized without sacrificing speed by modeling this problem as an online preference learning task. As part of a broader cooperative planning system, we present a feedback-driven plan critic. This method makes use of reinforcement learning with human feedback in conjunction with a genetic algorithm to directly optimize a plan with respect to natural-language user preferences despite the non-differentiability of traditional planners. Directly optimizing the plan bridges the gap between research into more efficient planners and research into planning with language models by utilizing the convenience of natural language to guide the output of formal planners. We demonstrate the effectiveness of our plan critic at adhering to user preferences on a disaster recovery task, and observe improved performance compared to an llm-only neurosymbolic approach., Comment: 5 pages, 3 figures

The short gamma-ray burst (sGRB), GRB~170817A, is often considered a rare event. However, its inferred event rate, $\mathcal{O}(100s)\ \text{Gpc}^{-3}\ \text{yr}^{-1}$, exceeds cosmic sGRB rate estimates from high-redshift samples by an order of magnitude. This discrepancy can be explained by geometric effects related to the structure of the relativistic jet. We first illustrate how adopting a detector flux threshold point estimate rather than an efficiency function, can lead to a large variation in rate estimates. Simulating the Fermi-GBM sGRB detection efficiency, we then show that for a given a universal structured jet profile, one can model a geometric bias with redshift. Assuming different jet profiles, we show a geometrically scaled rate of GRB~170817A is consistent with the cosmic beaming uncorrected rate estimates of short $\gamma$-ray bursts (sGRBs) and that geometry can boost observational rates within $\mathcal{O}(100s)$\,Mpc. We find an apparent GRB~170817A rate of $303_{-300}^{+1580}$ $\mathrm{Gpc}^{-3}\, \mathrm{yr}^{-1} $ which when corrected for geometry yields $6.15_{-6.06}^{+31.2}$ $\mathrm{Gpc}^{-3}\, \mathrm{yr}^{-1} $ and $3.34_{-3.29}^{+16.7}$ $\mathrm{Gpc}^{-3}\, \mathrm{yr}^{-1} $ for two different jet profiles, consistent with pre-2017 estimates of the isotropic sGRB rate. Our study shows how jet structure can impact rate estimations and could allow one to test structured jet profiles. We finally show that modelling the maximum structured jet viewing angle with redshift can transform a cosmic beaming uncorrected rate to a representative estimate of the binary neutron star merger rate. We suggest this framework can be used to demonstrate parity with merger rates or to yield estimates of the successful jet fraction of sGRBs., Comment: Submitted to MNRAS

Magnetar Giant Flares (MGFs) are the most energetic non-catastrophic transients known to originate from stellar objects. The first discovered events were nearby. In recent years, several extragalactic events have been identified, implying an extremely high volumetric rate. We show that future instruments with a sensitivity $\lesssim 5\times 10^{-9}$ erg cm$^{-2}$ at $\sim 1$ MeV will be dominated by extragalactic MGFs over short gamma-ray bursts (sGRBs). Clear discrimination of MGFs requires intrinsic GRB localization capability to identify host galaxies. As MGFs involve a release of a sizable fraction of the neutron star's magnetic free energy reservoir in a single event, they provide us with invaluable tools for better understanding magnetar birth properties and the evolution of their magnetic fields. A major obstacle is to identify a (currently) small sub-population of MGFs in a larger sample of more energetic and distant sGRBs. We develop the tools to analyze the properties of detected events and their occurrence rate relative to sGRBs. Even with the current (limited) number of events, we can constrain the initial internal magnetic field of a typical magnetar at formation to be $B_0\approx 3\times 10^{14}-2\times 10^{15}$\,G. Larger samples will constrain the distribution of birth fields. We also estimate the contribution of MGFs to the gravitational wave (GW) stochastic background. Depending on the acceleration time of baryon-loaded ejecta involved in MGFs, their GW emission may reach beyond 10~kHz and, if so, will likely dominate over other conventional astrophysical sources in that frequency range., Comment: To be submitted in a few days. Comments welcome!

The FASTSUM Collaboration has developed a comprehensive research programme in thermal lattice QCD using 2+1 flavour ensembles. We review our recent hadron spectrum analyses of open charm mesons and charm baryons at non-zero temperature. We also detail our determination of the interquark potential in the bottomonium system using NRQCD quarks. All of our work uses anisotropic lattices where the temporal lattice spacing is considerably finer than the spatial one allowing better resolution of temporal correlation functions., Comment: 6 pages. Contribution to 42nd International Conference on High Energy Physics (ICHEP2024), 18-24 July 2024, Prague, Czech Republic

We address the issue of the exploding computational requirements of recent State-of-the-art (SOTA) open set multimodel 3D mapping (dense 3D mapping) algorithms and present Voxel-Aggregated Feature Synthesis (VAFS), a novel approach to dense 3D mapping in simulation. Dense 3D mapping involves segmenting and embedding sequential RGBD frames which are then fused into 3D. This leads to redundant computation as the differences between frames are small but all are individually segmented and embedded. This makes dense 3D mapping impractical for research involving embodied agents in which the environment, and thus the mapping, must be modified with regularity. VAFS drastically reduces this computation by using the segmented point cloud computed by a simulator's physics engine and synthesizing views of each region. This reduces the number of features to embed from the number of captured RGBD frames to the number of objects in the scene, effectively allowing a "ground truth" semantic map to be computed an order of magnitude faster than traditional methods. We test the resulting representation by assessing the IoU scores of semantic queries for different objects in the simulated scene, and find that VAFS exceeds the accuracy and speed of prior dense 3D mapping techniques., Comment: 6 pages, 2 figures, CVPR 2025

In the past few years, the improved sensitivity and cadence of wide-field optical surveys have enabled the discovery of several afterglows without associated detected gamma-ray bursts (GRBs). We present the identification, observations, and multiwavelength modeling of a recent such afterglow (AT2023lcr), and model three literature events (AT2020blt, AT2021any, and AT2021lfa) in a consistent fashion. For each event, we consider the following possibilities as to why a GRB was not observed: 1) the jet was off-axis; 2) the jet had a low initial Lorentz factor; and 3) the afterglow was the result of an on-axis classical GRB (on-axis jet with physical parameters typical of the GRB population), but the emission was undetected by gamma-ray satellites. We estimate all physical parameters using afterglowpy and Markov Chain Monte Carlo methods from emcee. We find that AT2023lcr, AT2020blt, and AT2021any are consistent with on-axis classical GRBs, and AT2021lfa is consistent with both on-axis low Lorentz factor ($\Gamma_0 \approx 5 - 13$) and off-axis ($\theta_\text{obs}=2\theta_\text{jet}$) high Lorentz factor ($\Gamma_0 \approx 100$) jets., Comment: 40 pages, 18 figures, 20 tables

The susceptibility of timestepping algorithms to numerical instabilities is an important consideration when simulating partial differential equations (PDEs). Here we identify and analyze a pernicious numerical instability arising in pseudospectral simulations of nonlinear wave propagation resulting in finite-time blow-up. The blow-up time scale is independent of the spatial resolution and spectral basis but sensitive to the timestepping scheme and the timestep size. The instability appears in multi-step and multi-stage implicit-explicit (IMEX) timestepping schemes of different orders of accuracy and has been found to manifest in simulations of soliton solutions of the Korteweg-de Vries (KdV) equation and traveling wave solutions of a nonlinear generalized Klein-Gordon equation. Focusing on the case of KdV solitons, we show that modal predictions from linear stability theory are unable to explain the instability because the spurious growth from linear dispersion is small and nonlinear sources of error growth converge too slowly in the limit of small timestep size. We then develop a novel multi-scale asymptotic framework that captures the slow, nonlinear accumulation of timestepping errors. The framework allows the solution to vary with respect to multiple time scales related to the timestep size and thus recovers the instability as a function of a slow time scale dictated by the order of accuracy of the timestepping scheme. We show that this approach correctly describes our simulations of solitons by making accurate predictions of the blow-up time scale and transient features of the instability. Our work demonstrates that studies of long-time simulations of nonlinear waves should exercise caution when validating their timestepping schemes., Comment: 26 pages, 13 figures, 3 tables

Large language models (LLMs) have shown remarkable progress in encoding clinical knowledge and responding to complex medical queries with appropriate clinical reasoning. However, their applicability in subspecialist or complex medical settings remains underexplored. In this work, we probe the performance of AMIE, a research conversational diagnostic AI system, in the subspecialist domain of breast oncology care without specific fine-tuning to this challenging domain. To perform this evaluation, we curated a set of 50 synthetic breast cancer vignettes representing a range of treatment-naive and treatment-refractory cases and mirroring the key information available to a multidisciplinary tumor board for decision-making (openly released with this work). We developed a detailed clinical rubric for evaluating management plans, including axes such as the quality of case summarization, safety of the proposed care plan, and recommendations for chemotherapy, radiotherapy, surgery and hormonal therapy. To improve performance, we enhanced AMIE with the inference-time ability to perform web search retrieval to gather relevant and up-to-date clinical knowledge and refine its responses with a multi-stage self-critique pipeline. We compare response quality of AMIE with internal medicine trainees, oncology fellows, and general oncology attendings under both automated and specialist clinician evaluations. In our evaluations, AMIE outperformed trainees and fellows demonstrating the potential of the system in this challenging and important domain. We further demonstrate through qualitative examples, how systems such as AMIE might facilitate conversational interactions to assist clinicians in their decision making. However, AMIE's performance was overall inferior to attending oncologists suggesting that further research is needed prior to consideration of prospective uses.

In recent years, imitation learning from large-scale human demonstrations has emerged as a promising paradigm for training robot policies. However, the burden of collecting large quantities of human demonstrations is significant in terms of collection time and the need for access to expert operators. We introduce a new data collection paradigm, RoboCrowd, which distributes the workload by utilizing crowdsourcing principles and incentive design. RoboCrowd helps enable scalable data collection and facilitates more efficient learning of robot policies. We build RoboCrowd on top of ALOHA (Zhao et al. 2023) -- a bimanual platform that supports data collection via puppeteering -- to explore the design space for crowdsourcing in-person demonstrations in a public environment. We propose three classes of incentive mechanisms to appeal to users' varying sources of motivation for interacting with the system: material rewards, intrinsic interest, and social comparison. We instantiate these incentives through tasks that include physical rewards, engaging or challenging manipulations, as well as gamification elements such as a leaderboard. We conduct a large-scale, two-week field experiment in which the platform is situated in a university cafe. We observe significant engagement with the system -- over 200 individuals independently volunteered to provide a total of over 800 interaction episodes. Our findings validate the proposed incentives as mechanisms for shaping users' data quantity and quality. Further, we demonstrate that the crowdsourced data can serve as useful pre-training data for policies fine-tuned on expert demonstrations -- boosting performance up to 20% compared to when this data is not available. These results suggest the potential for RoboCrowd to reduce the burden of robot data collection by carefully implementing crowdsourcing and incentive design principles., Comment: 21 pages, 25 figures

Southeast Asia is a geopolitically and socio-economically significant region with unique challenges and opportunities. Intensifying progress in generative AI against a backdrop of existing health security threats makes applications of AI to mitigate such threats attractive but also risky if done without due caution. This paper provides a brief sketch of some of the applications of AI for health security and the regional policy and governance landscape. I focus on policy and governance activities of the Association of Southeast Asian Nations (ASEAN), an international body whose member states represent 691 million people. I conclude by identifying sustainability as an area of opportunity for policymakers and recommend priority areas for generative AI researchers to make the most impact with their work., Comment: 13 pages, 1 appendix; accepted to GenAI for Health: Potential, Trust and Policy Compliance workshop at NeurIPS 2024

For over 25 years, the origin of long-duration gamma-ray bursts (lGRBs) has been linked to the collapse of rotating massive stars. However, we have yet to pinpoint the stellar progenitor powering these transients. Moreover, the dominant engine powering the explosions remains open to debate. Observations of both lGRBs, supernovae associated with these GRBs, such as broad-line (BL) stripped-envelope (type Ic) supernovae (hereafter, Ic-BL) supernovae (SNe) and perhaps superluminous SNe, fast blue optical transients, and fast x-ray transients, may provide clues to both engines and progenitors. In this paper, we conduct a detailed study of the tight-binary formation scenario for lGRBs, comparing this scenario to other leading progenitor models. Combining this progenitor scenario with different lGRB engines, we can compare to existing data and make predictions for future observational tests. We find that the combination of the tight-binary progenitor scenario with the black hole accretion disk (BHAD) engine can explain lGRBs, low-luminosity GRBs, ultra-long GRBs, and Ic-BL. We discuss the various progenitor properties required for these different subclasses and note such systems would be future gravitational wave merger sources. We show that the current literature on other progenitor-engine scenarios cannot explain all of these transient classes with a single origin, motivating additional work. We find that the tight-binary progenitor with a magnetar engine is excluded by existing observations. The observations can be used to constrain the properties of stellar evolution, the nature of the GRB and the associated SN engines in lGRBs and Ic-BL. We discuss the future observations needed to constrain our understanding of these rare, but powerful, explosions., Comment: 20 pages, 10 figures, submitted to ApJ

The Axion Dark Matter eXperiment is sensitive to narrow axion flows, given axions compose a fraction of the dark matter with a non-negligible local density. Detecting these low-velocity dispersion flows requires a high spectral resolution and careful attention to the expected signal modulation due to Earth's motion. We report an exclusion on the local axion dark matter density in narrow flows of $\rho_a \gtrsim 0.03\,\mathrm{GeV/cm^3}$ and $\rho_a \gtrsim 0.004\,\mathrm{GeV/cm^3}$ for Dine-Fischler-Srednicki-Zhitnitski and Kim-Shifman-Vainshtein-Zakharov axion-photon couplings, respectively, over the mass range $3.3-4.2\,\mu\text{eV}$. Measurements were made at selected resolving powers to allow for a range of possible velocity dispersions., Comment: 7 pages, 3 figures

This paper presents the NSX front-end ASIC, being developed to read charge signals from the HEMA and WFM X-ray detectors for the STROBE-X mission. The ASIC reads out signals from up to 64 anodes of linear Silicon Drift Detectors (SDDs). When unloaded, the ASIC channel has a charge resolution, expressed in Equivalent Noise Charge (ENC) of about 2.8 e-. Once connected to the SDD anode we anticipate, for the 80 keV energy range, a ENC of about 10.7 e- at a leakage current of 2 pA, which corresponds to a FWHM of about 145 eV at 6 keV once the Fano-limited statistics from charge generation in Si is included. The acquisition is event-triggered and, for events exceeding the threshold, the ASIC measures the peak amplitude and stores it in an analog memory for subsequent readout. The ASIC can also force the measurement of the sub-threshold channels neighboring the triggered channel, including the ones that belong to neighbor chips by using bi-directional differential inter-chip communication. Alternatively, the ASIC can measure the amplitudes of all channels at the time of the first detected peak. Additional features include a high-resolution option, channel power down and skip function, a low-noise pulse generator, a temperature sensor, and the monitoring of the channel analog output and trimmed threshold. The power consumption of the individual channel is ~590 $\mu$W and, when including all shared circuits, it averages to ~670 $\mu$W / channel., Comment: 16 pages, 12 figures, accepted for publication in JATIS

Neural network (NN) emulators of the global 21 cm signal need emulation error much less than the observational noise in order to be used to perform unbiased Bayesian parameter inference. To this end, we introduce $\texttt{21cmLSTM}$ -- a long short-term memory (LSTM) NN emulator of the global 21 cm signal that leverages the intrinsic correlation between frequency channels to achieve exceptional accuracy compared to previous emulators, which are all feedforward, fully connected NNs. LSTM NNs are a type of recurrent NN designed to capture long-term dependencies in sequential data. When trained and tested on the same simulated set of global 21 cm signals as the best previous emulators, $\texttt{21cmLSTM}$ has average relative rms error of 0.22% -- equivalently 0.39 mK -- and comparably fast evaluation time. We perform seven-dimensional Bayesian parameter estimation analyses using $\texttt{21cmLSTM}$ to fit global 21 cm signal mock data with different adopted observational noise levels, $\sigma_{21}$. The posterior $1\sigma$ rms error is $\approx3\times$ less than $\sigma_{21}$ for each fit and consistently decreases for tighter noise levels, showing that $\texttt{21cmLSTM}$ can sufficiently exploit even very optimistic measurements of the global 21 cm signal. We made the emulator, code, and data sets publicly available so that $\texttt{21cmLSTM}$ can be independently tested and used to retrain and constrain other 21 cm models., Comment: 15 pages, 8 figures, 3 tables. Accepted by ApJ

Type II supernovae (SNeII) mark the endpoint in the lives of hydrogen-rich massive stars. Their large explosion energies and luminosities allow us to measure distances, metallicities, and star formation rates into the distant Universe. To fully exploit their use in answering different astrophysical problems, high-quality low-redshift data sets are required. Such samples are vital to understand the physics of SNeII, but also to serve as calibrators for distinct - and often lower-quality - samples. We present uBgVri optical and YJH near-infrared (NIR) photometry for 94 low-redshift SNeII observed by the Carnegie Supernova Project (CSP). A total of 9817 optical and 1872 NIR photometric data points are released, leading to a sample of high-quality SNII light curves during the first ~150 days post explosion on a well-calibrated photometric system. The sample is presented and its properties are analysed and discussed through comparison to literature events. We also focus on individual SNeII as examples of classically defined subtypes and outlier objects. Making a cut in the plateau decline rate of our sample (s2), a new subsample of fast-declining SNeII is presented. The sample has a median redshift of 0.015, with the nearest event at 0.001 and the most distant at 0.07. At optical wavelengths (V), the sample has a median cadence of 4.7 days over the course of a median coverage of 80 days. In the NIR (J), the median cadence is 7.2 days over the course of 59 days. The fast-declining subsample is more luminous than the full sample and shows shorter plateau phases. Of the non-standard SNeII highlighted, SN2009A particularly stands out with a steeply declining then rising light curve, together with what appears to be two superimposed P-Cygni profiles of H-alpha in its spectra. We outline the significant utility of these data, and finally provide an outlook of future SNII science., Comment: Accepted for publication in A&A. Photometric data will be uploaded to the CDS and the CSP website, and can also be requested from the first author

Analog dynamical accelerators (DXs) are a growing sub-field in computer architecture research, offering order-of-magnitude gains in power efficiency and latency over traditional digital methods in several machine learning, optimization, and sampling tasks. However, limited-capacity accelerators require hybrid analog/digital algorithms to solve real-world problems, commonly using large-neighborhood local search (LNLS) frameworks. Unlike fully digital algorithms, hybrid LNLS has no non-asymptotic convergence guarantees and no principled hyperparameter selection schemes, particularly limiting cross-device training and inference. In this work, we provide non-asymptotic convergence guarantees for hybrid LNLS by reducing to block Langevin Diffusion (BLD) algorithms. Adapting tools from classical sampling theory, we prove exponential KL-divergence convergence for randomized and cyclic block selection strategies using ideal DXs. With finite device variation, we provide explicit bounds on the 2-Wasserstein bias in terms of step duration, noise strength, and function parameters. Our BLD model provides a key link between established theory and novel computing platforms, and our theoretical results provide a closed-form expression linking device variation, algorithm hyperparameters, and performance., Comment: 31 pages, 2 figures

We consider the process of precipitation in binary alloys in the presence of mechanical deformation. It is commonly observed that mechanical deformation prior to or during precipitation leads to microstructure with excess defects, which allows for enhanced precipitate nucleation and growth rates. To investigate this phenomenon, we employ a two-dimensional phase-field crystal alloy model endowed with a temperature dependent mobility, making it capable of recovering isothermal transformation (TTT) diagrams with a characteristic inflection point (nose) about a critical temperature. We examine the variation in the time-scale of precipitation and its connection to the time-scale of the applied deformation, focusing on the roles of atomic defects in the processes involved. Our results indicate that precipitation is initially delayed through application of a deformation until a critical strain is achieved, beyond which precipitation proceeds more rapidly, assisted by plastic deformation such as grain boundary buckling or dislocation nucleation. We show that the evolution of the precipitated fraction, $f(t)$, departs from classical Avrami behaviour. Specifically, $df/dt$ develops two peaks indicative of a ``plateau"-like inflection in $f(t)$, signalling the transition to defect assisted precipitate nucleation. We analyze these plateaus as a function of the deformation rate and demonstrate that the they exhibit a discontinuous bifurcation as the time-scale of applied deformation is increased. These findings are compared to and found to be consistent with experiments., Comment: Main text: 6 pages, 5 figures, Supplemental Material: 2 pages, 1 figure submitted to Physical Review Letters

The advancements of language language models (LLMs) have piqued growing interest in developing LLM-based language agents to automate scientific discovery end-to-end, which has sparked both excitement and skepticism about their true capabilities. In this work, we call for rigorous assessment of agents on individual tasks in a scientific workflow before making bold claims on end-to-end automation. To ensure the scientific authenticity and real-world relevance of our benchmark, we extract 102 tasks from 44 peer-reviewed publications in four disciplines and engage nine subject matter experts to validate them. We unify the target output for every task to a self-contained Python program file and employ an array of evaluation metrics to examine the generated programs, execution results, and costs. Each task goes through multiple rounds of manual validation by annotators and subject matter experts to ensure its annotation quality and scientific plausibility. We also propose two effective strategies to mitigate data contamination concerns. Using our benchmark, we evaluate five open-weight and proprietary LLMs, each with three frameworks: direct prompting, OpenHands CodeAct, and self-debug. Given three attempts for each task, the best-performing agent can only solve 32.4% of the tasks independently and 34.3% with expert-provided knowledge. In addition, we evaluate OpenAI o1 with direct prompting and self-debug, which demonstrates the effectiveness of increasing inference-time compute. Still, our results underscore the limitations of current language agents in generating code for data-driven discovery, let alone end-to-end automation for scientific research., Comment: 57 pages

The Time-Domain And MultiMessenger (TDAMM) Communications Science Analysis Group (TDAMMCommSAG) was formulated to describe the unique technical challenges of communicating rapidly to and from NASA astrophysics missions studying the most variable, transient, and extreme objects in the Universe. This report describes the study of if and how the transition from current NASA-operated space and ground relays to commercial services will adequately serve these missions. Depending on the individual mission requirements and Concept of Operations (ConOps), TDAMM missions may utilize a rapid low-rate demand access service, a low-rate continuous contact service, low-latency downlink upon demand, or a higher-latency but regular relay service. The specific implementations can vary via space relay or direct to Earth, but requires flexibility and adaptability using modern software infrastructure. The study team reviewed the current state of NASA communications services and future commercial and NASA communications services under study and in development. We explored the communications capabilities driving from the behavior of the astrophysical objects themselves., Comment: 20 page, 1 figure

We investigate the Lyman-$\alpha$ (Ly$\alpha$) and Lyman continuum (LyC) properties of the Sunburst Arc, a $z=2.37$ gravitationally lensed galaxy with a multiply-imaged, compact region leaking LyC and a triple-peaked Ly$\alpha$ profile indicating direct Ly$\alpha$ escape. Non-LyC-leaking regions show a redshifted Ly$\alpha$ peak, a redshifted and central Ly$\alpha$ peak, or a triple-peaked Ly$\alpha$ profile. We measure the properties of the Ly$\alpha$ profile from different regions of the galaxy using $R\sim5000$ Magellan/MagE spectra. We compare the Ly$\alpha$ spectral properties to LyC and narrowband Ly$\alpha$ maps from Hubble Space Telescope (HST) imaging to explore the subgalactic Ly$\alpha-$LyC connection. We find strong correlations (Pearson correlation coefficient $r>0.6$) between the LyC escape fraction ($f_{\rm esc}^{\rm LyC}$) and Ly$\alpha$ (1) peak separation $v_{\rm{sep}}$, (2) ratio of the minimum flux density between the redshifted and blueshifted Ly$\alpha$ peaks to continuum flux density $f_{\rm{min}}/f_{\rm{cont}}$, and (3) equivalent width. We favor a complex \ion{H}{1} geometry to explain the Ly$\alpha$ profiles from non-LyC-leaking regions and suggest two \ion{H}{1} geometries that could diffuse and/or rescatter the central Ly$\alpha$ peak from the LyC-leaking region into our sightline across transverse distances of several hundred parsecs. Our results emphasize the complexity of Ly$\alpha$ radiative transfer and its sensitivity to the anisotropies of \ion{H}{1} gas on subgalactic scales. Large differences in the physical scales on which we observe spatially variable direct escape Ly$\alpha$, blueshifted Ly$\alpha$, and escaping LyC photons in the Sunburst Arc underscore the importance of resolving the physical scales that govern Ly$\alpha$ and LyC escape., Comment: Submitted to The Astrophysical Journal with revisions from the first referee report. Comments welcome

In the 2022-23 school year, Arizona began implementation of a "universal voucher" program through which all school-age students are eligible for a voucher, and families can use public funding to underwrite private or homeschool education for their children. Universal vouchers in Arizona are an expansion of the existing Empowerment Scholarship Account (ESA) program, which was targeted to students with special education needs or in specific circumstances. To better understand this program's impact on Arizona public schools, this report undertook a financial review of the expanded Arizona ESA program using publicly available data from the state budget, which details total state expenditures and student enrollment; Arizona Department of Education (ADE) quarterly reports to the State Board of Education, which detail the number of ESA applications received, approved, and denied; and ADE enrollment figures. The authors analyzed student enrollment in the program, the combined cost of the earlier enacted ESA program and the new universal voucher program, and their effects on education funding in the state. This report outlines the cost estimates and calculations in detail.

Public higher education leaders have entered 2024 aided by tailwinds of fiscal stability in many states and a strong national economy, but some challenges of the post-pandemic era remain, including strengthening the value proposition of higher education, building public trust, and meeting changing economic and workforce needs. This paper presents the top state policy priorities for 2024 based on a survey of members of the State Higher Education Executive Officers Association (SHEEO) during the first half of November 2023. This paper is not an exhaustive list of state higher education policy issues for 2024 but represents those most likely to affect state higher education communities in the year ahead. College affordability, for example, remains a long-term concern, while other topics, such as enrollment decline, are driven by the current higher education context. Additional information and context for these issues and trends has been provided through scans of state legislative activity, policy reports, and news articles.

The prompt spectra of gamma-ray bursts are known to follow broadband continuum behavior over decades in energy. GRB 221009A, given the moniker the brightest of all time (BOAT), is the brightest gamma-ray burst identified in half a century of observations, and was first identified by the Fermi Gamma-ray Burst Monitor (GBM). On behalf of the Fermi-GBM Team, Lesage et al. (2023) described the initial GBM analysis. Ravasio et al. (2024) report the identification of a spectral line in part of the prompt emission of this burst, which they describe as evolving over 80 s from $\sim$12 MeV to 6 MeV. We report a GBM Team analysis on the Ravasio Line: 1) We cannot identify an instrumental effect that could have produced this signal, and 2) our method of calculating the statistical significance of the line shows it easily exceeds the 5$\sigma$ discovery threshold. We additionally comment on the claim of the line beginning at earlier time intervals, up to 37 MeV, as reported in Zhang et al. (2024). We find that it is reasonable to utilize these measurements for characterization of the line evolution, with caution. We encourage theoretical studies exploring this newly discovered gamma-ray burst spectral feature, unless any rigorous alternative explanation unrelated to the emission from GRB 221009A is identified.

In the rapidly rotating limit, we derive a balanced set of reduced equations governing the strongly nonlinear development of the convective wall-mode instability in the interior of a general container. The model illustrates that wall-mode convection is a multiscale phenomenon where the dynamics of the bulk interior diagnostically determine the small-scale dynamics within Stewartson boundary layers at the sidewalls. The sidewall boundary layers feedback on the interior via a nonlinear lateral heat-flux boundary condition, providing a closed system. Outside the asymptotically thin boundary layer, the convective modes connect to a dynamical interior that maintains scales set by the domain geometry. In many ways, the final system of equations resembles boundary-forced planetary geostrophic baroclinic dynamics coupled with barotropic quasi-geostrophic vorticity. The reduced system contains the results from previous linear instability theory but captured in an elementary fashion, providing a new avenue for investigating wall-mode convection in the strongly nonlinear regime. We also derive the dominant Ekman-flux correction to the onset Rayleigh number for large Taylor number, Ra ~ 31.8 Ta^(1/2) - 4.43 Ta^(5/12) for no-slip boundaries. We demonstrate some of the reduced model's nonlinear dynamics with numerical simulations in a cylindrical container., Comment: 40 pages, 13 figures

We present the detection and analysis of GRB 231115A, a candidate extragalactic magnetar giant flare (MGF) observed by Fermi/GBM and localized by INTEGRAL to the starburst galaxy M82. This burst exhibits distinctive temporal and spectral characteristics that align with known MGFs, including a short duration and a high peak energy. Gamma-ray analyses reveal significant insights into this burst, supporting conclusions already established in the literature: our time-resolved spectral studies provide further evidence that GRB 231115A is indeed a MGF. Significance calculations also suggest a robust association with M82, further supported by a high Bayes factor that minimizes the probability of chance alignment with a neutron star merger. Despite extensive follow-up efforts, no contemporaneous gravitational wave or radio emissions were detected. The lack of radio emission sets stringent upper limits on possible radio luminosity. Constraints from our analysis show no fast radio bursts (FRBs) associated with two MGFs. X-ray observations conducted post-burst by Swift/XRT and XMM/Newton provided additional data, though no persistent counterparts were identified. Our study underscores the importance of coordinated multi-wavelength follow-up and highlights the potential of MGFs to enhance our understanding of short GRBs and magnetar activities in the cosmos. Current MGF identification and follow-up implementation are insufficient for detecting expected counterparts; however, improvements in these areas may allow for the recovery of follow-up signals with existing instruments. Future advancements in observational technologies and methodologies will be crucial in furthering these studies.

We present a complete analysis of Fermi Large Area Telescope (LAT) data of GRB 221009A, the brightest Gamma-Ray Burst (GRB) ever detected. The burst emission above 30 MeV detected by the LAT preceded by 1 s the low-energy (< 10 MeV) pulse that triggered the Fermi Gamma-Ray Burst Monitor (GBM), as has been observed in other GRBs. The prompt phase of GRB 221009A lasted a few hundred seconds. It was so bright that we identify a Bad Time Interval (BTI) of 64 seconds caused by the extremely high flux of hard X-rays and soft gamma rays, during which the event reconstruction efficiency was poor and the dead time fraction quite high. The late-time emission decayed as a power law, but the extrapolation of the late-time emission during the first 450 seconds suggests that the afterglow started during the prompt emission. We also found that high-energy events observed by the LAT are incompatible with synchrotron origin, and, during the prompt emission, are more likely related to an extra component identified as synchrotron self-Compton (SSC). A remarkable 400 GeV photon, detected by the LAT 33 ks after the GBM trigger and directionally consistent with the location of GRB 221009A, is hard to explain as a product of SSC or TeV electromagnetic cascades, and the process responsible for its origin is uncertain. Because of its proximity and energetic nature, GRB 221009A is an extremely rare event., Comment: 60 pages, 38 figures, 9 tables

Observable estimation is a core primitive in NISQ-era algorithms targeting quantum chemistry applications. To reduce the state preparation overhead required for accurate estimation, recent works have proposed various simultaneous measurement schemes to lower estimator variance. Two primary grouping schemes have been proposed: fully commutativity (FC) and qubit-wise commutativity (QWC), with no compelling means of interpolation. In this work we propose a generalized framework for designing and analyzing context-aware hybrid FC/QWC commutativity relations. We use our framework to propose a noise-and-connectivity aware grouping strategy: Generalized backend-Aware pauLI Commutation (GALIC). We demonstrate how GALIC interpolates between FC and QWC, maintaining estimator accuracy in Hamiltonian estimation while lowering variance by an average of 20\% compared to QWC. We also explore the design space of near-term quantum devices using the GALIC framework, specifically comparing device noise levels and connectivity. We find that error suppression has a more than $10\times$ larger impact on device-aware estimator variance than qubit connectivity with even larger correlation differences in estimator biases., Comment: 37 pages, 7 figures

In 21-cm experimental cosmology, accurate characterization of a radio telescope's antenna beam response is essential to measure the 21-cm signal. Computational electromagnetic (CEM) simulations estimate the antenna beam pattern and frequency response by subjecting the EM model to different dependencies, or beam hyper-parameters, such as soil dielectric constant or orientation with the environment. However, it is computationally expensive to search all possible parameter spaces to optimize the antenna design or accurately represent the beam to the level required for use as a systematic model in 21-cm cosmology. We therefore present $\texttt{MEDEA}$, an emulator which rapidly and accurately generates farfield radiation patterns over a large hyper-parameter space. $\texttt{MEDEA}$ takes a subset of beams simulated by CEM software, spatially decomposes them into coefficients in a complete, linear basis, and then interpolates them to form new beams at arbitrary hyper-parameters. We test $\texttt{MEDEA}$ on an analytical dipole and two numerical beams motivated by upcoming lunar lander missions, and then employ $\texttt{MEDEA}$ as a model to fit mock radio spectrometer data to extract covariances on the input beam hyper-parameters. We find that the interpolated beams have RMS relative errors of at most $10^{-2}$ using 20 input beams or less, and that fits to mock data are able to recover the input beam hyper-parameters when the model and mock derive from the same set of beams. When a systematic bias is introduced into the mock data, extracted beam hyper-parameters exhibit bias, as expected. We propose several future extensions to $\texttt{MEDEA}$ to potentially account for such bias., Comment: 23 pages, 12 figures, accepted for publication in ApJ

Quadrotor-based multimodal hopping and flying locomotion significantly improves efficiency and operation time as compared to purely flying systems. However, effective control necessitates continuous estimation of the vertical states, as thrust (insufficient for flight) in the aerial phase creates non-ballistic behavior. A single hopping continuous state estimator has been shown (Kang 2024), in which two vertical states (position, acceleration) are measured and velocity is estimated through a technique requiring multiple sensors (IMU, lidar, depth camera, contact force sensor), and computationally intensive calculations (12-core, 5 GHz processor), for a maximum hop height of ~0.6 m at 3.65 kg. This poses a significant challenge to the development of light-weight, high-performance, low observable, jamming and electronic interference resistant hopping systems; especially in perceptually degraded environments (e.g., dust, smoke). Here we show a trained Kalman filter based hopping vertical state estimator (HVSE), requiring only vertical acceleration measurements. The training uses hopping data from the robot and a motion capture system to adapt a general framework to the specific system; including high impact behaviors. Our results show the HVSE can estimate more states (position, velocity) with 32% of the mean-absolute-percentage-error in the hop apex height (height error/ground truth) of the next best inertial navigation technique (12.5%), running ~4.2x faster (840 Hz) on a substantially less powerful processor (dual-core 240 MHz) with over ~6.7x the hopping height (4.02 m) at 20% of the mass (672 g). The presented general HVSE, and training procedure make the methodology broadly applicable to other robots., Comment: 15 pages, 7 figures, 6 tables

In a recent class of phase field crystal (PFC) models, the density order parameter is coupled to powers of its mean field. This effectively introduces a phenomenology of higher-order direct correlation functions acting on long wavelengths, which is required for modelling solid-liquid-vapor systems. The present work generalizes these models by incorporating, into a single-field theory, higher-order direct correlations, systematically constructed in reciprocal space to operate across long {\it and} short wavelengths. The correlation kernels introduced are also readily adaptable to describe distinct crystal structures. We examine the three-phase equilibrium properties and phase diagrams of the proposed model, and reproduce parts of the aluminum phase diagram as an example of its versatile parametrization. We assess the dynamics of the model, showing that it allows robust control of the interface energy between the vapor and condensed phases (liquid and solid). We also examine the dynamics of solid-vapor interfaces over a wide range of parameters and find that dynamical artifacts reported in previous PFC models do not occur in the present formalism. Additionally, we demonstrate the capacity of the proposed formalism for computing complex microstructures and defects such as dislocations, grain boundaries, and voids in solid-liquid-vapor systems, all of which are expected to be crucial for investigating rapid solidification processes.

Strong optomechanical coupling -- a regime where mechanical motion is damped by environmental radiation -- has traditionally required demanding experimental ingredients such as superconducting resonators, high-quality optical cavities, or large magnetic fields. Here we demonstrate a room temperature, cavity-free, all-electric device reaching this regime at radio frequencies, enabled by a mechanically compliant parallel-plate capacitor with a nanoscale plate separation and an aspect ratio exceeding 1,000. The device has four orders of magnitude lower insertion loss than a comparable commercial quartz crystal, and achieves a position imprecision rivaling an optical interferometer. With the help of a back-action isolation scheme, we observe radiative cooling of mechanical motion by a remote cryogenic load. This work provides a technologically accessible route to high-precision sensing, transduction, and signal processing., Comment: 19+13 pages, 5+2 figures