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Large language models are increasingly becoming a cornerstone technology in artificial intelligence, the sciences, and society as a whole, yet the optimal strategies for dataset composition and filtering remain largely elusive. Many of the top-performing models lack transparency in their dataset curation and model development processes, posing an obstacle to the development of fully open language models. In this paper, we identify three core data-related challenges that must be addressed to advance open-source language models. These include (1) transparency in model development, including the data curation process, (2) access to large quantities of high-quality data, and (3) availability of artifacts and metadata for dataset curation and analysis. To address these challenges, we release RedPajama-V1, an open reproduction of the LLaMA training dataset. In addition, we release RedPajama-V2, a massive web-only dataset consisting of raw, unfiltered text data together with quality signals and metadata. Together, the RedPajama datasets comprise over 100 trillion tokens spanning multiple domains and with their quality signals facilitate the filtering of data, aiming to inspire the development of numerous new datasets. To date, these datasets have already been used in the training of strong language models used in production, such as Snowflake Arctic, Salesforce's XGen and AI2's OLMo. To provide insight into the quality of RedPajama, we present a series of analyses and ablation studies with decoder-only language models with up to 1.6B parameters. Our findings demonstrate how quality signals for web data can be effectively leveraged to curate high-quality subsets of the dataset, underscoring the potential of RedPajama to advance the development of transparent and high-performing language models at scale., Comment: 38th Conference on Neural Information Processing Systems (NeurIPS 2024) Track on Datasets and Benchmarks

We analyzed the 7.92$\times 10^{11}$ cosmic-ray-induced muon events collected by the IceCube Neutrino Observatory from May 13, 2011, when the fully constructed experiment started to take data, to May 12, 2023. This dataset provides an up-to-date cosmic-ray arrival direction distribution in the Southern Hemisphere with unprecedented statistical accuracy covering more than a full period length of a solar cycle. Improvements in Monte Carlo event simulation and better handling of year-to-year differences in data processing significantly reduce systematic uncertainties below the level of statistical fluctuations compared to the previously published results. We confirm the observation of a change in the angular structure of the cosmic-ray anisotropy between 10 TeV and 1 PeV, more specifically in the 100-300 TeV energy range.

We report on the coherent creation, control and read-out of a single photonic qutrit in a Rydberg ensemble. In each measurement, an optical photon is stored as a Rydberg polariton through electromagnetically induced transparency. Employing two microwave fields, the polariton is driven into an arbitrary superposition of three collective states, each encoded in a Rydberg state. The collective state is mapped into a photonic time-bin qutrit with the microwave field and read out sequentially. The complete sequence, including preparation, control, and read-out, is less than 1.8~$\mu$s, which mitigates decoherence significantly. We measure the coherence of the qutrit with non-destructive Ramsey interferometry, which is preferable for quantum information processing, and find good quantitative agreement with the theoretical model. The ability to write, process and read out the single photonic qutrit on microsecond time scales with microwave coupled Rydberg states demonstrates the coherent connectivity among the high Hilbert space of the qutrit.Our study is an important step in exploring qutrit based quantum information processes and quantum simulation of topological physics with microwave coupled Rydberg atom ensembles., Comment: 7 pages, 4 figures

We present numerous aspects of the evolution of the LP 890-9 (SPECULOOS-2/TOI-4306) planetary system, focusing on the likelihood that planet c can support life. We find that the host star reaches the main sequence in 1 Gyr and that planet c lies close to the inner boundary of the habitable zone. We find the magma ocean stage can last up to 50 Myr, remove 8 Earth-oceans of water, and leave up to 2000 bars of oxygen in the atmosphere. However, if the planet forms with a hydrogen envelope as small as 0.1 Earth-masses, no water will be lost during the star's pre-main sequence phase from thermal escape processes. We find that the planets are unlikely to be in a 3:1 mean motion resonance and that both planets tidally circularize within 0.5 Gyr when tidal dissipation is held constant. However, if tidal dissipation is a function of mantle temperature and rheology, then we find that planet c's orbit may require more than 7 Gyr to circularize, during which time tidal heating may reach hundreds of terawatts. We thus conclude that the habitability of planet c depends most strongly on the initial volatile content and internal properties, but no data yet preclude the viability of an active biosphere on the planet., Comment: 16 pages, 9 figures, accepted to PSJ

The common theory is that human pilot's performance degrades when responsible for an increased number of uncrewed aircraft systems (UAS). This theory was developed in the early 2010's for ground robots and not highly autonomous UAS. It has been shown that increasing autonomy can mitigate some performance impacts associated with increasing the number of UAS. Overall, the Oregon State University-Wing collaboration seeks to understand what factors negatively impact a pilot's ability to maintain responsibility and control over an assigned set of active UAS. The Phase I evaluation establishes baseline data focused on the number of UAS and the number of nests increase. This evaluation focuses on nominal operations as well as crewed aircraft encounters and adverse weather changes. The results demonstrate that the pilots were actively engaged and had very good situation awareness. Manipulation of the conditions did not result in any significant differences in overall workload. The overall results debunk the theory that increasing the number of UAS is detrimental to pilot's performance., Comment: 45 pages, 10 figures, 21 tables

Consider a large system of $N$ Brownian motions in $\R ^d$ fixed on a time interval $[0,\beta]$ with symmetrized initial and terminal conditions, under the influence of a trap potential. Such systems describe systems of bosons at positive temperatures confined in a spatial domain. We describe the large $N$ behavior of the averaged path (that is, their empirical path measure) and its connection with a well known optimal transport problem formulated by Erwin Schr\"odinger. We also explore the asymptotic behavior of the Brownian motions in terms of Large Deviations. In particular, the rate function that governs the mean of occupation measures turns out to be the well-known Donsker-Varadhan rate function. We therefore prove a simple formula for the large $N$ asymptotic of the symmetrized trace of $e^{-\beta \Hcal_N}$, where $\Hcal_N$ is an $N$ particle Hamilton operator in a trap

Liver transplant can be a life-saving procedure for patients with end-stage liver disease. With the introduction of modern immunosuppressive therapies, short-term survival has significantly improved. However, long-term survival has not substantially improved in decades. Consequently, causes of death are now more likely to be due to the toxicities and side-effects of long-term immunosuppression rather than rejection. In order to study the balance of immunosuppression and rejection, we developed the first mechanistic mathematical model of liver transplant and immune system dynamics. We determined key cells and interactions in the model using literature information; we then used sensitivity analysis to determine key pathways driving the health status of the transplanted liver. We found that dynamics related to cytotoxic T cells and IL-2, in addition to the liver itself, are key determinants of liver graft injury. This has significant implications for the use of tests to monitor patients, and therapeutic strategies to prevent or treat liver transplantation rejection. Future work to collect appropriate data and parametrize the model would be valuable in improving our understanding of the dynamics of this system. We also note that our model could be tailored to model transplant of other organs., Comment: 34 pages, 5 figures

Cyber-attacks pose a security threat to military command and control networks, Intelligence, Surveillance, and Reconnaissance (ISR) systems, and civilian critical national infrastructure. The use of artificial intelligence and autonomous agents in these attacks increases the scale, range, and complexity of this threat and the subsequent disruption they cause. Autonomous Cyber Defence (ACD) agents aim to mitigate this threat by responding at machine speed and at the scale required to address the problem. Sequential decision-making algorithms such as Deep Reinforcement Learning (RL) provide a promising route to create ACD agents. These algorithms focus on a single objective such as minimizing the intrusion of red agents on the network, by using a handcrafted weighted sum of rewards. This approach removes the ability to adapt the model during inference, and fails to address the many competing objectives present when operating and protecting these networks. Conflicting objectives, such as restoring a machine from a back-up image, must be carefully balanced with the cost of associated down-time, or the disruption to network traffic or services that might result. Instead of pursing a Single-Objective RL (SORL) approach, here we present a simple example of a multi-objective network defence game that requires consideration of both defending the network against red-agents and maintaining critical functionality of green-agents. Two Multi-Objective Reinforcement Learning (MORL) algorithms, namely Multi-Objective Proximal Policy Optimization (MOPPO), and Pareto-Conditioned Networks (PCN), are used to create two trained ACD agents whose performance is compared on our Multi-Objective Cyber Defence game. The benefits and limitations of MORL ACD agents in comparison to SORL ACD agents are discussed based on the investigations of this game., Comment: 9 pages, 9 figures

Examining reflected light from exoplanets aids in our understanding of the scattering properties of their atmospheres and will be a primary task of future flagship space- and ground-based telescopes. We introduce an enhanced capability of Planetary Intensity Code for Atmospheric Scattering Observations (PICASO), an open-source radiative transfer model used for exoplanet and brown dwarf atmospheres, to produce reflected light phase curves from three-dimensional atmospheric models. Since PICASO is coupled to the cloud code Virga, we produce phase curves for different cloud condensate species and varying sedimentation efficiencies (fsed) and apply this new functionality to Kepler-7b, a hot Jupiter with phase curve measurements dominated by reflected starlight. We model three different cloud scenarios for Kepler-7b: MgSiO3 clouds only, Mg2SiO4 clouds only, and Mg2SiO4, Al2O3, and TiO2 clouds. All our Virga models reproduce the cloudy region west of the substellar point expected from previous studies, as well as clouds at high latitudes and near the eastern limb, which are primarily composed of magnesium silicates. Al2O3 and TiO2 clouds dominate near the substellar point. We then compare our modeled reflected light phase curves to Kepler observations and find that models with all three cloud condensate species and low sedimentation efficiencies (0.03 - 0.1) match best, though our reflected light phase curves show intensities approximately one-third of those observed by Kepler. We conclude that a better understanding of zonal transport, cloud radiative feedback, and particle scattering properties is needed to further explain the differences between the modeled and observed reflected light fluxes.

From transmission electron microscopy and other laboratory studies of presolar grains, the implicit condensation sequence of carbon-bearing condensates in circumstellar envelopes of carbon stars is (from first to last) TiC-graphite-SiC. We use thermochemical equilibrium condensation calculations and show that the condensation sequence of TiC, graphite, and SiC depends on metallicity in addition to C/O ratio and total pressure. Calculations were performed for a characteristic carbon star ratio of C/O = 1.2 from 1E-10 to 1E-4 bars total pressure and for uniform metallicity variations ranging from 0.01 to 100 times solar elemental abundances. TiC always condenses before SiC, and the carbide condensation temperatures increase with increasing metallicity and total pressure. Graphite, however, can condense in a cooling circumstellar envelope before TiC, between TiC and SiC, or after SiC, depending on the carbon-bearing gas chemistry, which is dependent on metallicity and total pressure. Analytical expressions for the graphite, TiC, and SiC condensation temperatures as functions of metallicity and total pressure are presented. The inferred sequence from laboratory presolar grain studies, TiC-graphite-SiC, is favored under equilibrium conditions at solar and subsolar metallicities between ~1E-5 to 1E-8 bar total pressure within circumstellar envelopes of carbon stars with nominal C/O = 1.2. We also explored the dependence of the sequence at C/O ratios of 1.1 and 3.0 and found that as the C/O ratio increases, the TiC-graphite-SiC region shifts towards higher total pressures and lower metallicities., Comment: 33 pages, 9 figures, 2 tables. Preprint submitted to The Astrophysical Journal, November 2024

The observed star formation rates of galaxies in the Local Universe suggests that they are replenishing their gas reservoir across cosmic time. Cosmological simulations predict that this accretion of fresh gas can occur in a hot or a cold mode, yet the existence of low column density ($\sim10^{17}$ cm$^{-2}$) neutral atomic hydrogen (HI) tracing the cold mode has not been unambiguously confirmed by observations. We present the application of unconstrained spectral stacking to attempt to detect the emission from this HI in the Circum-Galactic Medium (CGM) and Inter-Galactic Medium (IGM) of 6 nearby star forming galaxies from the MHONGOOSE sample for which full-depth observations are available. Our stacking procedure consists of a standard spectral stacking algorithm coupled with a one-dimensional spectral line finder designed to extract reliable signal close to the noise level. In agreement with previous studies, we found that the amount of signal detected outside the HI disk is much smaller than implied by simulations. Furthermore, the column density limit that we achieve via stacking ($\sim10^{17}$ cm$^{-2}$) suggests that direct detection of the neutral CGM/IGM component might be challenging in the future, even with the next generation of radio telescopes., Comment: Accepted for publication in Astronomy & Astrophysics

Abundant geomorphological and geochemical evidence of liquid water on the surface of early Mars during the late Noachian and early Hesperian periods needs to be reconciled with a fainter young Sun. While a dense CO2 atmosphere and related warming mechanisms are potential solutions to the early Mars climate problem, further investigation is warranted. Here, we complete a comprehensive survey of the warming potential of all known greenhouse gases and perform detailed calculations for 15 different minor gas species under early Martian conditions. We find that of these 15 species, H2O2, HNO3, NH3, SO2, and C2H4 cause significant greenhouse warming at concentrations of ~0.1 ppmv or greater. However, the most highly effective greenhouse gas species also tend to be more condensable, soluble and vulnerable to photolytic destruction. To provide a reference for future atmospheric evolution and photochemical studies, we have made our warming potential database freely available online., Comment: 14 pages, 12 figures, published in JGR Planets

The precise characterization and mitigation of systematic effects is one of the biggest roadblocks impeding the detection of the fluctuations of cosmological 21cm signals. Missing data in radio cosmological experiments, often due to radio frequency interference (RFI), poses a particular challenge to power spectrum analysis as it could lead to the ringing of bright foreground modes in Fourier space, heavily contaminating the cosmological signals. Here we show that the problem of missing data becomes even more arduous in the presence of systematic effects. Using a realistic numerical simulation, we demonstrate that partially flagged data combined with systematic effects can introduce significant foreground ringing. We show that such an effect can be mitigated through inpainting the missing data. We present a rigorous statistical framework that incorporates the process of inpainting missing data into a quadratic estimator of the 21cm power spectrum. Under this framework, the uncertainties associated with our inpainting method and its impact on power spectrum statistics can be understood. These results are applied to the latest Phase II observations taken by the Hydrogen Epoch of Reionization Array, forming a crucial component in power spectrum analyses as we move toward detecting 21cm signals in the ever more noisy RFI environment., Comment: 25 pages, 11 figures, submitted to ApJ

Let $G$ be a compact, connected metric graph and let $X\subseteq G$ be a subset. If $X$ is sufficiently dense in $G$, we show that the Gromov--Hausdorff distance matches the Hausdorff distance, namely $d_{GH}(G,X)=d_{H}(G,X)$. In a recent study, when the metric graph is the circle $G=S^1$ with circumference $2\pi$, the equality $d_{GH}(S^1,X)=d_{H}(S^1,X)$ was established whenever $d_{GH}(S^1,X)<\frac{\pi}{6}$. Our result for general metric graphs relaxes this hypothesis in the circle case to $d_{GH}(S^1,X)<\frac{\pi}{3}$, and furthermore, we give an example showing that the constant $\frac{\pi}{3}$ is the best possible. We lower bound the Gromov--Hausdorff distance $d_{GH}(G,X)$ by the Hausdorff distance $d_{H}(G,X)$ via a simple topological obstruction: showing a correspondence with too small distortion contradicts the connectedness of $G$. Moreover, for two sufficiently dense subsets $X,Y\subseteq G$, we provide new lower bounds on $d_{GH}(X,Y)$ in terms of the Hausdorff distance $d_{H}(X,Y)$, which is $O(n^2)$-time computable if the subsets have at most $n$ points.

Light-induced phase transitions offer a method to dynamically modulate topological states in bulk complex materials. Yet, next-generation devices demand nanoscale architectures with contact resistances near the quantum limit and precise control over local electronic properties. The layered material WTe$_2$ has gained attention as a likely Weyl semimetal, with topologically protected linear electronic band crossings hosting massless chiral fermions. Here, we demonstrate a topological phase transition facilitated by light-induced shear motion of a single atomic layer at the surface of bulk WTe$_2$, thereby opening the door to nanoscale device concepts. Ultrafast terahertz fields enhanced at the apex of an atomically sharp tip resonantly couple to the key interlayer shear mode of WTe$_2$ via a ferroelectric dipole at the interface, inducing a structural phase transition at the surface to a metastable state. Subatomically resolved differential imaging, combined with hybrid-level density functional theory, reveals a shift of 7 $\pm$ 3 picometres in the top atomic plane. Tunnelling spectroscopy links electronic changes across the phase transition with the electron and hole pockets in the band structure, suggesting a reversible, light-induced annihilation of the topologically-protected Fermi arc surface states in the top atomic layer.

We conduct a large-scale empirical user study in a live setup to evaluate the acceptance of LLM-generated comments and their impact on the review process. This user study was performed in two organizations, Mozilla (which has its codebase available as open source) and Ubisoft (fully closed-source). Inside their usual review environment, participants were given access to RevMate, an LLM-based assistive tool suggesting generated review comments using an off-the-shelf LLM with Retrieval Augmented Generation to provide extra code and review context, combined with LLM-as-a-Judge, to auto-evaluate the generated comments and discard irrelevant cases. Based on more than 587 patch reviews provided by RevMate, we observed that 8.1% and 7.2%, respectively, of LLM-generated comments were accepted by reviewers in each organization, while 14.6% and 20.5% other comments were still marked as valuable as review or development tips. Refactoring-related comments are more likely to be accepted than Functional comments (18.2% and 18.6% compared to 4.8% and 5.2%). The extra time spent by reviewers to inspect generated comments or edit accepted ones (36/119), yielding an overall median of 43s per patch, is reasonable. The accepted generated comments are as likely to yield future revisions of the revised patch as human-written comments (74% vs 73% at chunk-level)., Comment: 12pages

Portable, low-field Magnetic Resonance Imaging (MRI) scanners are increasingly being deployed in clinical settings. However, critical barriers to their widespread use include low signal-to-noise ratio (SNR), generally low image quality, and long scan duration. As these systems can operate in unusual environments, the level and spectral characteristics of the environmental electromagnetic inference (EMI) noise can change substantially across sites and scans, further reducing image quality. Methods for accelerating acquisition and boosting image quality are of critical importance to enable clinically actionable high-quality imaging in these systems. Despite the role that compressed sensing (CS) and artificial intelligence (AI)-based methods have had in improving image quality for high-field MRI, their adoption for low-field imaging is in its infancy, and it is unclear how robust these methods are in low SNR regimes. Here, we investigate and compare leading CS and AI-based methods for image reconstruction from subsampled data and perform a thorough analysis of their performance across a range of SNR values. We compare classical L1-wavelet CS with leading data-driven and model-driven AI methods. Experiments are performed using publicly available datasets and our own low-field and high-field experimental data. Specifically, we apply an unrolled AI network to low-field MRI, and find it outperforms competing reconstruction methods. We prospectively deploy our undersampling methods to accelerate imaging on a 6.5 mT MRI scanner. This work highlights the potential and pitfalls of advanced reconstruction techniques in low-field MRI, paving the way for broader clinical applications.

We address the question of how to connect predictions by hydrodynamic models of how sea lice move in water to observable measures that count the number of lice on each fish in a cage in the water. This question is important for management and regulation of aquacultural practice that tries to maximise food production and minimise risk to the environment. We do this through a simple rule-based model of interaction between sea lice and caged fish. The model is simple: sea lice can attach and detach from a fish. The model has a novel feature, encoding what is known as a master equation producing a time-series of distributions of lice on fish that one might expect to find if a cage full of fish were placed at any given location. To demonstrate how this works, and to arrive at a rough estimate of the interaction rates, we fit a simplified version of the model with three free parameters to publicly available data about an experiment with sentinel cages in Loch Linnhe in Scotland. Our construction, coupled to the hydrodynamic models driven by surveillance data from industrial farms, quantifies the environmental impact as: what would the infection burden look like in a notional cage at any location and how does it change with time?

In this paper we share the experience of the U.S. National Science Foundation (NSF) National Solar Observatory (NSO) scientists, educators and public outreach officers organizing an eclipse viewing party at a sports complex stadium on the US/Mexico border in Eagle Pass, TX in collaboration with educators from Eagle Pass and Uvalde areas. We describe reasons we chose Eagle Pass, contacts we established with the local community, preparations for and activities set up during the eclipse viewing party, the eclipse day on April 8 2024 and lessons learned from organizing our event., Comment: 17 pages, 9 figures, submitted to Bulletin of the AAS: Celebrating the Wonder of Science in the Shadow II

Galaxy mergers are a key driver of galaxy formation and evolution, including the triggering of AGN and star formation to a still unknown degree. We thus investigate the impact of galaxy mergers on star formation and AGN activity using a sample of 3,330 galaxies at $z = [4.5, 8.5]$ from eight JWST fields (CEERS, JADES GOODS-S, NEP-TDF, NGDEEP, GLASS, El-Gordo, SMACS-0723, and MACS-0416), collectively covering an unmasked area of 189 arcmin$^2$. We focuses on star formation rate (SFR) enhancement, AGN fraction, and AGN excess in major merger ($\mu > 1/4$) close-pair samples, defined by $\Delta z < 0.3$ and projected separations $r_p < 100$ kpc, compared to non-merger samples. We find that SFR enhancement occurs only at $r_p < 20$ kpc, with values of $0.25 \pm 0.10$ dex and $0.26 \pm 0.11$ dex above the non-merger medians for $z = [4.5, 6.5]$ and $z = [6.5, 8.5]$, respectively. No other statistically significant enhancements in galaxy sSFR or stellar mass are observed at any projected separation or redshift bin. We also compare our observational results with predictions from the SC-SAM simulation and find no evidence of star formation enhancement in the simulations at any separation range. Finally, we examine the AGN fraction and AGN excess, finding that the fraction of AGNs in AGN-galaxy pairs, relative to the total AGN population, is $3.25^{+1.50}_{-1.06}$ times greater than the fraction of galaxy pairs relative to the overall galaxy population at the same redshift. We find that nearly all AGNs have a companion within 100 kpc and observe an excess AGN fraction in close-pair samples compared to non-merger samples. This excess is found to be $1.26 \pm 0.06$ and $1.34 \pm 0.06$ for AGNs identified via the inferred BPT diagram and photometric SED selection, respectively., Comment: 17 Pages, 7 Figures, Submitted to MNRAS

Floquet systems are periodically driven systems. In this framework, the system Hamiltonian and associated spectra of interest are modified, giving rise to new quantum phases of matter and nonequilibrium dynamics without static counterparts. Here we experimentally demonstrate a self-induced Floquet system in the interacting Rydberg gas. This originates from the photoionization of thermal Rydberg gases in a static magnetic field. Importantly, by leveraging the Rydberg electromagnetically induced transparency spectrum, we probe the nonequilibrium dynamics in the bistable regime and identify the emergence of a discrete time crystalline phase. Our work fills the experimental gap in the understanding the relation of multistability and dissipative discrete time crystalline phase. In this regard, it constitutes a highly controlled platform for exploring exotic nonequilibrium physics in dissipative interacting systems., Comment: 6 pages, 4 figures

We present the first broadband near- to mid-infrared (3-12 microns) transmission spectrum of the highly-irradiated (T_eq = 981 K) M dwarf rocky planet L 168-9 b (TOI-134 b) observed with the NIRSpec and MIRI instruments aboard JWST. We measure the near-infrared transit depths to a combined median precision of 20 ppm across the three visits in 54 spectroscopic channels with uniform widths of 60 pixels (~0.2 microns wide; R~100), and the mid-infrared transit depths to 61 ppm median precision in 48 wavelength bins (~0.15 microns wide; R~50). We compare the transmission spectrum of L 168-9 b to a grid of 1D thermochemical equilibrium forward models, and rule out atmospheric metallicities of less than 100x solar (mean molecular weights <4 g mol$^{-1}$) to 3-sigma confidence assuming high surface pressure (>1 bar), cloudless atmospheres. Based on photoevaporation models for L 168-9 b with initial atmospheric mass fractions ranging from 2-100%, we find that this planet could not have retained a primordial H/He atmosphere beyond the first 200 Myr of its lifetime. Follow-up MIRI eclipse observations at 15 microns could make it possible to confidently identify a CO2-dominated atmosphere on this planet if one exists., Comment: 19 pages, 11 figures, accepted for publication in The Astronomical Journal

Code translation aims to convert a program from one programming language (PL) to another. This long-standing software engineering task is crucial for modernizing legacy systems, ensuring cross-platform compatibility, enhancing performance, and more. However, automating this process remains challenging due to many syntactic and semantic differences between PLs. Recent studies show that even advanced techniques such as large language models (LLMs), especially open-source LLMs, still struggle with the task. Currently, code LLMs are trained with source code from multiple programming languages, thus presenting multilingual capabilities. In this paper, we investigate whether such multilingual capabilities can be harnessed to enhance code translation. To achieve this goal, we introduce InterTrans, an LLM-based automated code translation approach that, in contrast to existing approaches, leverages intermediate translations across PLs to bridge the syntactic and semantic gaps between source and target PLs. InterTrans contains two stages. It first utilizes a novel Tree of Code Translation (ToCT) algorithm to plan transitive intermediate translation sequences between a given source and target PL, then validates them in a specific order. We evaluate InterTrans with three open LLMs on three benchmarks (i.e., CodeNet, HumanEval-X, and TransCoder) involving six PLs. Results show an absolute improvement between 18.3% to 43.3% in Computation Accuracy (CA) for InterTrans over Direct Translation with 10 attempts. The best-performing variant of InterTrans (with Magicoder LLM) achieved an average CA of 87.3%-95.4% on three benchmarks.

To help MLOps engineers decide which operator to use in which deployment scenario, this study aims to empirically assess the accuracy vs latency trade-off of white-box (training-based) and black-box operators (non-training-based) and their combinations in an Edge AI setup. We perform inference experiments including 3 white-box (i.e., QAT, Pruning, Knowledge Distillation), 2 black-box (i.e., Partition, SPTQ), and their combined operators (i.e., Distilled SPTQ, SPTQ Partition) across 3 tiers (i.e., Mobile, Edge, Cloud) on 4 commonly-used Computer Vision and Natural Language Processing models to identify the effective strategies, considering the perspective of MLOps Engineers. Our Results indicate that the combination of Distillation and SPTQ operators (i.e., DSPTQ) should be preferred over non-hybrid operators when lower latency is required in the edge at small to medium accuracy drop. Among the non-hybrid operators, the Distilled operator is a better alternative in both mobile and edge tiers for lower latency performance at the cost of small to medium accuracy loss. Moreover, the operators involving distillation show lower latency in resource-constrained tiers (Mobile, Edge) compared to the operators involving Partitioning across Mobile and Edge tiers. For textual subject models, which have low input data size requirements, the Cloud tier is a better alternative for the deployment of operators than the Mobile, Edge, or Mobile-Edge tier (the latter being used for operators involving partitioning). In contrast, for image-based subject models, which have high input data size requirements, the Edge tier is a better alternative for operators than Mobile, Edge, or their combination.

A likelihood analysis of the observables in deeply virtual exclusive photoproduction off a proton target, $ep \rightarrow e' p' \gamma'$, is presented. Two processes contribute to the reaction: deeply virtual Compton scattering, where the photon is produced at the proton vertex, and the Bether-Heitler process, where the photon is radiated from the electron. We consider the unpolarized process for which the largest amount of data with all the kinematic dependences are available from corresponding datasets with unpolarized beams and unpolarized targets from Jefferson Lab. We provide and use a method which derives a joint likelihood of the Compton form factors, which parametrize the deeply virtual Compton scattering amplitude in QCD, for each observed combination of the kinematic variables defining the reaction. The unpolarized twist-two cross section likelihood fully constrains only three of the Compton form factors (CFFs). The impact of the twist-three corrections to the analysis is also explored. The derived likelihoods are explored using Markov chain Monte Carlo (MCMC) methods. Using our proposed method we derive CFF error bars and covariances. Additionally, we explore methods which may reduce the magnitude of error bars/contours in the future., Comment: 22 pages, 11 figures

A non-planar graph is almost-planar if either deleting or contracting any edge makes it planar. A graph with $n$ vertices is pancyclic if it contains a cycle of every length from $3$ to $n$, and it is Hamiltonian if it contains a cycle of length $n$. A Hamiltonian path is a path of length $n$ and a graph with a Hamiltonian path between every pair of vertices is called Hamiltonian-connected. In 1990, Gubser characterized the class of almost-planar graphs. This paper explores the pancyclicity of these graphs. We prove that a $3$-connected almost-planar graph is pancyclic if and only if it has a cycle of length 3. Furthermore, we prove that a 4-connected almost-planar graph is both pancyclic and Hamiltonian-connected., Comment: 15 pages, 11 figures

Current image watermarking methods are vulnerable to advanced image editing techniques enabled by large-scale text-to-image models. These models can distort embedded watermarks during editing, posing significant challenges to copyright protection. In this work, we introduce W-Bench, the first comprehensive benchmark designed to evaluate the robustness of watermarking methods against a wide range of image editing techniques, including image regeneration, global editing, local editing, and image-to-video generation. Through extensive evaluations of eleven representative watermarking methods against prevalent editing techniques, we demonstrate that most methods fail to detect watermarks after such edits. To address this limitation, we propose VINE, a watermarking method that significantly enhances robustness against various image editing techniques while maintaining high image quality. Our approach involves two key innovations: (1) we analyze the frequency characteristics of image editing and identify that blurring distortions exhibit similar frequency properties, which allows us to use them as surrogate attacks during training to bolster watermark robustness; (2) we leverage a large-scale pretrained diffusion model SDXL-Turbo, adapting it for the watermarking task to achieve more imperceptible and robust watermark embedding. Experimental results show that our method achieves outstanding watermarking performance under various image editing techniques, outperforming existing methods in both image quality and robustness. Code is available at https://github.com/Shilin-LU/VINE.

Engineering molecules to exhibit precise 3D intermolecular interactions with their environment forms the basis of chemical design. In ligand-based drug design, bioisosteric analogues of known bioactive hits are often identified by virtually screening chemical libraries with shape, electrostatic, and pharmacophore similarity scoring functions. We instead hypothesize that a generative model which learns the joint distribution over 3D molecular structures and their interaction profiles may facilitate 3D interaction-aware chemical design. We specifically design ShEPhERD, an SE(3)-equivariant diffusion model which jointly diffuses/denoises 3D molecular graphs and representations of their shapes, electrostatic potential surfaces, and (directional) pharmacophores to/from Gaussian noise. Inspired by traditional ligand discovery, we compose 3D similarity scoring functions to assess ShEPhERD's ability to conditionally generate novel molecules with desired interaction profiles. We demonstrate ShEPhERD's potential for impact via exemplary drug design tasks including natural product ligand hopping, protein-blind bioactive hit diversification, and bioisosteric fragment merging.

The Particle X-ray Coincidence Technique (PXCT) was originally developed to measure average lifetimes in the $10^{-17}-10^{-15}$~s range for proton-unbound states populated by electron capture (EC). We have designed and built the Lifetimes and Branching Ratios Apparatus (LIBRA) to be used in the stopped-beam area at the Facility for Rare Isotope Beams that extends PXCT to measure both lifetimes and decay branching ratios of resonances populated by EC/$\beta^+$ decay. The first application of LIBRA aims to obtain essential nuclear data from $^{60}$Ga EC/$\beta^+$ decay to constrain the thermonuclear rates of the $^{59}$Cu$(p,\gamma)^{60}$Zn and $^{59}$Cu$(p,\alpha)^{56}$Ni reactions, and in turn, the strength of the NiCu nucleosynthesis cycle, which is predicted to significantly impact the modeling of Type I X-ray burst light curves and the composition of the burst ashes. Detailed theoretical calculations, Monte Carlo simulations, and performance tests with radioactive sources have been conducted to validate the feasibility of employing LIBRA for the $^{60}$Ga experiment. The method introduced with LIBRA has the potential to measure nearly all essential ingredients for thermonuclear reaction rate calculations in a single experiment, in the absence of direct measurements, which are often impractical for radioactive reactants.

For the first time in history, humankind might conceivably begin to imagine itself as a multi-planetary species. This goal will entail technical innovation in a number of contexts, including that of healthcare. All life on Earth shares an evolution that is coupled to specific environmental conditions, including gravitational and magnetic fields. While the human body may be able to adjust to short term disruption of these fields during space flights, any long term settlement would have to take into consideration the effects that different fields will have on biological systems, within the space of one lifetime, but also across generations. Magnetic fields, for example, influence the growth of stem cells in regenerative processes. Circadian rhythms are profoundly influenced by magnetic fields, a fact that will likely have an effect on mental as well as physical health. Even the brain responds to small perturbations of this field. One possible mechanism for the effects of weak magnetic fields on biological systems has been suggested to be the radical pair mechanism. The radical pair mechanism originated in the context of spin chemistry to describe how magnetic fields influence the yields of chemical reactions. This mechanism was subsequently incorporated into the field of quantum biology. Quantum biology, most generally, is the study of whether non-trivial quantum effects play any meaningful role in biological systems. The radical pair mechanism has been used most consistently in this context to describe the avian compass. Recently, however, a number of studies have investigated other biological contexts in which the radical pair might play a role, from the action of anaesthetics and antidepressants, to microtubule development and the proper function of the circadian clock... (full abstract in the manuscript), Comment: 18 pages, 9 figures

The Hausdorff distance measures how far apart two sets are in a common metric space. By contrast, the Gromov-Hausdorff distance provides a notion of distance between two abstract metric spaces. How do these distances behave for quotients of spaces under group actions? Suppose a group $G$ acts by isometries on two metric spaces $X$ and $Y$. In this article, we study how the Hausdorff and Gromov-Hausdorff distances between $X$ and $Y$ and their quotient spaces $X/G$ and $Y/G$ are related. For the Hausdorff distance, we show that if $X$ and $Y$ are $G$-invariant subsets of a common metric space, then we have $d_{\mathrm{H}}(X,Y)=d_{\mathrm{H}}(X/G,Y/G)$. However, the Gromov-Hausdorff distance does not preserve this relationship: we show how to make the ratio $\frac{d_{\mathrm{GH}}(X/G,Y/G)}{d_{\mathrm{GH}}(X,Y)}$ both arbitrarily large and arbitrarily small, even if $X$ is an arbitrarily dense $G$-invariant subset of $Y$.

Let $G(\mathbb{R})$ be a real reductive group. Suppose $\pi$ is an irreducible representation of $G(\mathbb{R})$ having a Whittaker model, and consider three invariants of $\pi$ related to nilpotents elements of the Lie algebra of $G$ (or its dual): the associated variety, the wave-front set, and the set of Whittaker data for which $\pi$ has a Whittaker model. If $\pi$ is a discrete series representation, these invariants are known to determine each other. We provide a self-contained account of this and related results, including an elementary proof that passage from $\pi$ to the three invariants defines natural bijections between the generic discrete series in an $L$-packet, the possible Whittaker data for $G(\mathbb{R})$, and the appropriate sets of nilpotent orbits. Given one of the three invariants, we also explain how to reconstruct the other two. Many of the results were known: we give simplified proofs for several of them, for instance a simple proof (for generic discrete series) that the associated variety and the wave-front set are related by the Kostant-Sekiguchi correspondence., Comment: 23 pages

Mechanical meta-materials are solids whose geometric structure results in exotic nonlinear behaviors that are not typically achievable via homogeneous materials. We show how to drastically expand the design space of a class of mechanical meta-materials known as cellular solids, by generalizing beyond translational symmetry. This is made possible by transforming a reference geometry according to a divergence free flow that is parameterized by a neural network and equivariant under the relevant symmetry group. We show how to construct flows equivariant to the space groups, despite the fact that these groups are not compact. Coupling this flow with a differentiable nonlinear mechanics simulator allows us to represent a much richer set of cellular solids than was previously possible. These materials can be optimized to exhibit desirable mechanical properties such as negative Poisson's ratios or to match target stress-strain curves. We validate these new designs in simulation and by fabricating real-world prototypes. We find that designs with higher-order symmetries can exhibit a wider range of behaviors.

Superfast rotators (SFRs) are small solar system objects that rotate faster than generally possible for a cohesionless rubble pile. Their rotational characteristics allow us to make inferences about their interior structure and composition. Here, we present the methods and results from a preliminary search for SFRs in the DECam Ecliptic Exploration Project (DEEP) data set. We find three SFRs from a sample of 686 main-belt asteroids, implying an occurrence rate of 0.4 -0.3/+0.1 percent - a higher incidence rate than has been measured by previous studies. We suggest that this high occurrence rate is due to the small sub-kilometer size regime to which DEEP has access: the objects searched here were as small as 500 m. We compute the minimum required cohesive strength for each of these SFRs and discuss the implications of these strengths in the context of likely evolution mechanisms. We find that all three of these SFRs require strengths that are more than that of weak regolith but consistent with many cohesive asteroid strengths reported in the literature. Across the full DEEP data set, we have identified ~70,000 Main-Belt Asteroids and expect ~300 SFRs - a result that will be assessed in a future paper.

The fundamental functional summary statistics used for studying spatial point patterns are developed for marked homogeneous and inhomogeneous point processes on the surface of a sphere. These are extended to point processes on the surface of three dimensional convex shapes given the bijective mapping from the shape to the sphere is known. These functional summary statistics are used to test for independence between the marginals of multi-type spatial point processes with methods for sampling the null distribution proposed and discussed. This is illustrated on both simulated data and the RNGC galaxy point pattern, revealing attractive dependencies between different galaxy types.

The evolution of artificial intelligence (AI) presents an unprecedented opportunity for Historically Black Colleges and Universities (HBCUs) to lead in an era characterized by rapid technological advancement and societal transformation. This report explores the integral role HBCUs--with their history of academic excellence and commitment to inclusivity--can play in steering the AI revolution, ensuring that the Black community remains at the forefront of educational, economic, and social progress. Institutional leaders, faculty and instructors, and instructional support staff can benefit from the findings of this report, which is presented in the following sections: (1) Why AI Matters and the Unique Role of HBCUs in the AI Revolution; (2) An AI Policy and Practice Framework for Institutional Development; (3) AI and Curricular Innovation; (4) The Importance of Industry Partnerships and Student Development; and (5) AI at HBCUs: A Path to the Future. [This report was created in collaboration with the Thurgood Marshall College Fund.]