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SNAD is an international project with a primary focus on detecting astronomical anomalies within large-scale surveys, using active learning and other machine learning algorithms. The work carried out by SNAD not only contributes to the discovery and classification of various astronomical phenomena but also enhances our understanding and implementation of machine learning techniques within the field of astrophysics. This paper provides a review of the SNAD project and summarizes the advancements and achievements made by the team over several years., Comment: 14 pages, 4 figures

This paper introduces the Bayesian Confidence Estimator (BACON) for deep neural networks. Current practice of interpreting Softmax values in the output layer as probabilities of outcomes is prone to extreme predictions of class probability. In this work we extend Waagen's method of representing the terminal layers with a geometric model, where the probability associated with an output vector is estimated with Bayes' Rule using validation data to provide likelihood and normalization values. This estimator provides superior ECE and ACE calibration error compared to Softmax for ResNet-18 at 85% network accuracy, and EfficientNet-B0 at 95% network accuracy, on the CIFAR-10 dataset with an imbalanced test set, except for very high accuracy edge cases. In addition, when using the ACE metric, BACON demonstrated improved calibration error when estimating probabilities for the imbalanced test set when using actual class distribution fractions., Comment: 14 pages, 15 figures (10 of which include sub-figures)

The composition of protoplanetary disks, and hence the initial conditions of planet formation, may be strongly influenced by the infall and thermal processing of material during the protostellar phase. Composition of dust and ice in protostellar envelopes, shaped by energetic processes driven by the protostar, serves as the fundamental building material for planets and complex organic molecules. As part of the JWST GO program, "Investigating Protostellar Accretion" (IPA), we observed an intermediate-mass protostar HOPS 370 (OMC2-FIR3) using NIRSpec/IFU and MIRI/MRS. This study presents the gas and ice phase chemical inventory revealed with the JWST in the spectral range of $\sim$2.9 to 28 $\mu$m and explores the spatial variation of volatile ice species in the protostellar envelope. We find evidence for thermal processing of ice species throughout the inner envelope. We present the first high-spatial resolution ($\sim 80$ au) maps of key volatile ice species H$_{2}$O, CO$_{2}$, $^{13}$CO$_2$, CO, and OCN$^-$, which reveal a highly structured and inhomogeneous density distribution of the protostellar envelope, with a deficiency of ice column density that coincides with the jet/outflow shocked knots. Further, we observe high relative crystallinity of H$_{2}$O ice around the shocked knot seen in the H$_2$ and OH wind/outflow, which can be explained by a lack of outer colder material in the envelope along the line of sight due to the irregular structure of the envelope. These observations show clear evidence of thermal processing of the ices in the inner envelope, close to the outflow cavity walls, heated by the luminous protostar., Comment: Submitted to ApJ. Main text:16 pages with 11 figures

We describe AthenaK: a new implementation of the Athena++ block-based adaptive mesh refinement (AMR) framework using the Kokkos programming model. Finite volume methods for Newtonian, special relativistic (SR), and general relativistic (GR) hydrodynamics and magnetohydrodynamics (MHD), and GR-radiation hydrodynamics and MHD, as well as a module for evolving Lagrangian tracer or charged test particles (e.g., cosmic rays) are implemented using the framework. In two companion papers we describe (1) a new solver for the Einstein equations based on the Z4c formalism and (2) a GRMHD solver in dynamical spacetimes also implemented using the framework, enabling new applications in numerical relativity. By adopting Kokkos, the code can be run on virtually any hardware, including CPUs, GPUs from multiple vendors, and emerging ARM processors. AthenaK shows excellent performance and weak scaling, achieving over one billion cell updates per second for hydrodynamics in three-dimensions on a single NVIDIA Grace Hopper processor and with a typical parallel efficiency of 80% on 65536 AMD GPUs on the OLCF Frontier system. Such performance portability enables AthenaK to leverage modern exascale computing systems for challenging applications in astrophysical fluid dynamics, numerical relativity, and multimessenger astrophysics., Comment: Submitted to ApJS

The cell is arguably the most fundamental unit of life and is central to understanding biology. Accurate modeling of cells is important for this understanding as well as for determining the root causes of disease. Recent advances in artificial intelligence (AI), combined with the ability to generate large-scale experimental data, present novel opportunities to model cells. Here we propose a vision of leveraging advances in AI to construct virtual cells, high-fidelity simulations of cells and cellular systems under different conditions that are directly learned from biological data across measurements and scales. We discuss desired capabilities of such AI Virtual Cells, including generating universal representations of biological entities across scales, and facilitating interpretable in silico experiments to predict and understand their behavior using virtual instruments. We further address the challenges, opportunities and requirements to realize this vision including data needs, evaluation strategies, and community standards and engagement to ensure biological accuracy and broad utility. We envision a future where AI Virtual Cells help identify new drug targets, predict cellular responses to perturbations, as well as scale hypothesis exploration. With open science collaborations across the biomedical ecosystem that includes academia, philanthropy, and the biopharma and AI industries, a comprehensive predictive understanding of cell mechanisms and interactions has come into reach.

We examine the prospect of observing genuine lepton number violating (LNV) signals at hadron colliders in the context of the Type II seesaw mechanism. The model features smoking gun signals involving same-sign di-leptons and jets that may be the primary observable channel in certain regions of the parameter space. The flavour composition of final-state charged leptons in the minimal model is related to the origin of neutrino masses and is correlated with other rare processes, such as neutrinoless double beta decay. We review existing collider limits and provide sensitivity estimates from LNV signals at upcoming runs of the LHC, for zero and non-zero mass splittings between the scalar triplet components., Comment: 7 pages, 7 figures

Stroke poses a significant global health threat, with millions affected annually, leading to substantial morbidity and mortality. Current stroke risk assessment for the general population relies on markers such as demographics, blood tests, and comorbidities. A minimally invasive, clinically scalable, and cost-effective way to directly measure cerebral blood flow presents an opportunity. This opportunity has potential to positively impact effective stroke risk assessment prevention and intervention. Physiological changes in the cerebral vascular system, particularly in response to carbon dioxide level changes and oxygen deprivation, such as during breath-holding, can offer insights into stroke risk assessment. However, existing methods for measuring cerebral perfusion reserve, such as blood flow and blood volume changes, are limited by either invasiveness or impracticality. Here, we propose a transcranial approach using speckle contrast optical spectroscopy (SCOS) to non-invasively monitor regional changes in brain blood flow and volume during breath-holding. Our study, conducted on 50 individuals classified into two groups (low-risk and higher-risk for stroke), shows significant differences in blood dynamic changes during breath-holding between the two groups, providing physiological insights for stroke risk assessment using a non-invasive quantification paradigm. Given its cost-effectiveness, scalability, portability, and simplicity, this laser-centric tool has significant potential in enhancing the pre-screening of stroke and mitigating strokes in the general population through early diagnosis and intervention., Comment: 12 pages, 4 figures

In this article we report on an initial exploration to assess the viability of using the general large language models (LLMs), recently made public, to classify mathematical documents. Automated classification would be useful from the applied perspective of improving the navigation of the literature and the more open-ended goal of identifying relations among mathematical results. The Mathematical Subject Classification MSC 2020, from MathSciNet and zbMATH, is widely used and there is a significant corpus of ground truth material in the open literature. We have evaluated the classification of preprint articles from arXiv.org according to MSC 2020. The experiment used only the title and abstract alone -- not the entire paper. Since this was early in the use of chatbots and the development of their APIs, we report here on what was carried out by hand. Of course, the automation of the process will have to follow if it is to be generally useful. We found that in about 60% of our sample the LLM produced a primary classification matching that already reported on arXiv. In about half of those instances, there were additional primary classifications that were not detected. In about 40% of our sample, the LLM suggested a different classification than what was provided. A detailed examination of these cases, however, showed that the LLM-suggested classifications were in most cases better than those provided.

We explore long-lived particle (LLP) searches using non-pointing photons at the LHC as a probe for sterile-to-sterile and active-to-sterile transition magnetic dipole moments of sterile neutrinos. We consider heavy sterile neutrinos with masses ranging from a few~GeV to several hundreds of GeV. We discuss transition magnetic dipole moments using the Standard Model effective field theory and low-energy effective field theory extended by sterile neutrinos ($N_R$SMEFT and $N_R$LEFT) and also provide a simplified UV-complete model example. LLP searches at the LHC using non-pointing photons will probe sterile-to-sterile dipole moments two orders of magnitude below the current best constraints from LEP, while an unprecedented sensitivity to sterile neutrino mass of about 700 GeV is expected for active-to-sterile dipole moments. For the UV model example with one-loop transition magnetic moments, the searches for charged lepton flavour violating processes in synergy with LLP searches at the LHC can probe new physics at several TeV mass scales and provide valuable insights into the lepton flavour structure of new physics couplings., Comment: New version matches the journal published version

The envelopes and disks that surround protostars reflect the initial conditions of star and planet formation and govern the assembly of stellar masses. Characterizing these structures requires observations that span the near-infrared to centimeter wavelengths. Consequently, the past two decades have seen progress driven by numerous advances in observational facilities across this spectrum, including the \textit{Spitzer Space Telescope}, \textit{Herschel Space Observatory}, the Atacama Large Millimeter/submillimeter Array, and a host of other ground-based interferometers and single-dish radio telescopes. Nearly all protostars appear to have well-formed circumstellar disks that are likely to be rotationally-supported; the ability to detect a disk around a protostar is more a question of spatial resolution than whether or not a disk is present. The disks around protostars have inherently higher millimeter/submillimeter luminosities as compared to disks around more-evolved pre-main sequence stars, though there may be systematic variations between star forming regions. The envelopes around protostars are inherently asymmetric and streamers emphasize that mass flow through the envelopes to the disks may not be homogeneous. The current mass distribution of protostars may be impacted by selection bias given that it is skewed toward solar-mass protostars, inconsistent with the stellar initial mass function., Comment: To appear in Annual Reviews in Astronomy and Astrophysics; 42 pages, 12 Figures, 1 Table

The recent Belle II observation of $B \to K E_{\rm miss}$ challenges theoretical interpretations in terms of Standard Model neutrino final states. Instead, we consider new physics scenarios where up to two new light-invisible particles of spin 0 up to 3/2 are present in the final state. We identify viable scenarios by reconstructing the (binned) likelihoods of the relevant $B \to K^{(*)} E_{\rm miss}$ and also $B_s \to E_{\rm miss}$ experimental analyses and present preferred regions of couplings and masses. In particular, we find that the current data prefers two-body decay kinematics involving the emission of a single massive scalar or a vector particle, or alternatively, three-body decays involving pairs of massive scalars or spin 1/2 fermions. When applicable, we compare our findings with existing literature and briefly discuss some model-building implications., Comment: 16 pages, 10 figures

We present a statistical characterization of circumstellar disk orientations toward 12 protostellar multiple systems in the Perseus molecular cloud using the Atacama Large Millimeter/submillimeter Array at Band 6 (1.3 mm) with a resolution of 25 mas (8 au). This exquisite resolution enabled us to resolve the compact inner disk structures surrounding the components of each multiple system and to determine the projected 3-D orientation of the disks (position angle and inclination) to high precision. We performed a statistical analysis on the relative alignment of disk pairs to determine whether the disks are preferentially aligned or randomly distributed. We considered three subsamples of the observations selected by the companion separations, a <100 au, a >500 au, and a < 10,000 au. We found for the compact (< 100 au) subsample, the distribution of orientation angles is best described by an underlying distribution of preferentially aligned sources (within 30deg) but does not rule out distributions with 40% misaligned sources. The wide companion (>500 au) subsample appears to be consistent with a distribution of 40%-80% preferentially aligned sources. Similarly, the full sample of systems with companions (a< 10, 000 au) is most consistent with a fractional ratio of at most 80% preferentially aligned source and rules out purely randomly aligned distributions. Thus our results imply the compact sources (<100 au) and the wide companions (>500 au) are statistically different.

The US Department of Energys Office of Nuclear Energy is planning for an integrated waste management approach to transport, store, and eventually dispose of spent nuclear fuel and other high-level radioactive waste as part of the Integrated Waste Management program. In support of this effort, the Stakeholder Tool for Assessing Radioactive Transportation is being developed within the IWM program. This is a web-based decision support tool that can be used to analyze geospatial data related to the transportation of SNF and HLW., Comment: Presented at the '2023 ANS Winter Conference and Expo'

We are developing an economic model to explore multiple topics in Australian youth mental health policy. We want that model to be readily transferable to other jurisdictions. We developed a software framework for authoring transparent, reusable and updatable Computational Health Economic Models (CHEMs) (the software files that implement health economic models). We specified framework user requirements of a template CHEM module that facilitates modular model implementations, a simple programming syntax and tools for authoring new CHEM modules, supplying CHEMs with data, reporting reproducible CHEM analyses, searching for CHEM modules and maintaining a CHEM project website. We implemented the framework as six development version code libraries in the programming language R that integrate with online services for software development and research data archiving. We used the framework to author five development version R libraries of CHEM modules focused on utility mapping in youth mental health. These modules provide tools for variable validation, dataset description, multi-attribute instrument scoring, construction of mapping models, reporting of mapping studies and making out of sample predictions. We assessed these CHEM module libraries as mostly meeting transparency, reusability and updatability criteria that we have previously developed, but requiring more detailed documentation and unit testing of individual modules. Our software framework has potential value as a prototype for future tools to support the development of transferable CHEMs., Comment: 16 pages, 3 tables, 1 figure

High-resolution, millimeter observations of disks at the protoplanetary stage reveal substructures such as gaps, rings, arcs, spirals, and cavities. While many protoplanetary disks host such substructures, only a few at the younger protostellar stage have shown similar features. We present a detailed search for early disk substructures in ALMA 1.3 and 0.87~mm observations of ten protostellar disks in the Ophiuchus star-forming region. Of this sample, four disks have identified substructure, two appear to be smooth disks, and four are considered ambiguous. The structured disks have wide Gaussian-like rings ($\sigma_R/R_{\mathrm{disk}}\sim0.26$) with low contrasts ($C<0.2$) above a smooth disk profile, in comparison to protoplanetary disks where rings tend to be narrow and have a wide variety of contrasts ($\sigma_R/R_{\mathrm{disk}}\sim0.08$ and $C$ ranges from $0-1$). The four protostellar disks with the identified substructures are among the brightest sources in the Ophiuchus sample, in agreement with trends observed for protoplanetary disks. These observations indicate that substructures in protostellar disks may be common in brighter disks. The presence of substructures at the earliest stages suggests an early start for dust grain growth and, subsequently, planet formation. The evolution of these protostellar substructures is hypothesized in two potential pathways: (1) the rings are the sites of early planet formation, and the later observed protoplanetary disk ring-gap pairs are secondary features, or (2) the rings evolve over the disk lifetime to become those observed at the protoplanetary disk stage., Comment: Accepted by ApJ, 22 pages, 10 figures

Studying the physical and chemical conditions of young embedded disks is crucial to constrain the initial conditions for planet formation. Here, we present Atacama Large Millimeter/submillimeter Array (ALMA) observations of dust continuum at $\sim$0.06" (8 au) resolution and molecular line emission at $\sim$0.17" (24 au) resolution toward the Class 0 protostar L1527 IRS from the Large Program eDisk (Early Planet Formation in Embedded Disks). The continuum emission is smooth without substructures, but asymmetric along both the major and minor axes of the disk as previously observed. The detected lines of $^{12}$CO, $^{13}$CO, C$^{18}$O, H$_2$CO, c-C$_3$H$_2$, SO, SiO, and DCN trace different components of the protostellar system, with a disk wind potentially visible in $^{12}$CO. The $^{13}$CO brightness temperature and the H$_2$CO line ratio confirm that the disk is too warm for CO freeze out, with the snowline located at $\sim$350 au in the envelope. Both molecules show potential evidence of a temperature increase around the disk-envelope interface. SO seems to originate predominantly in UV-irradiated regions such as the disk surface and the outflow cavity walls rather than at the disk-envelope interface as previously suggested. Finally, the continuum asymmetry along the minor axis is consistent with the inclination derived from the large-scale (100" or 14,000 au) outflow, but opposite to that based on the molecular jet and envelope emission, suggesting a misalignment in the system. Overall, these results highlight the importance of observing multiple molecular species in multiple transitions to characterize the physical and chemical environment of young disks., Comment: 27 pages, 16 figures, 2 tables, 10 pages appendix with 12 figures. Accepted for publication in ApJ as one of the first-look papers of the eDisk ALMA Large Program

Software is vital for the advancement of biology and medicine. Analysis of usage and impact metrics can help developers determine user and community engagement, justify additional funding, encourage additional use, identify unanticipated use cases, and help define improvement areas. However, there are challenges associated with these analyses including distorted or misleading metrics, as well as ethical and security concerns. More attention to the nuances involved in capturing impact across the spectrum of biological software is needed. Furthermore, some tools may be especially beneficial to a small audience, yet may not have compelling typical usage metrics. We propose more general guidelines, as well as strategies for more specific types of software. We highlight outstanding issues regarding how communities measure or evaluate software impact. To get a deeper understanding of current practices for software evaluations, we performed a survey of participants in the Informatics Technology for Cancer Research (ITCR) program funded by the National Cancer Institute (NCI). We also investigated software among this community and others to assess how often infrastructure that supports such evaluations is implemented and how this impacts rates of papers describing usage of the software. We find that developers recognize the utility of analyzing software usage, but struggle to find the time or funding for such analyses. We also find that infrastructure such as social media presence, more in-depth documentation, the presence of software health metrics, and clear information on how to contact developers seem to be associated with increased usage rates. Our findings can help scientific software developers make the most out of evaluations of their software., Comment: 25 total pages (17 pages for manuscript and 8 pages for the supplement). There are 2 figures

Substantial effort has been devoted to the characterization of transient phenomena from photometric information. Automated approaches to this problem have taken advantage of complete phase-coverage of an event, limiting their use for triggering rapid follow-up of ongoing phenomena. In this work, we introduce a neural network with a single recurrent layer designed explicitly for early photometric classification of supernovae. Our algorithm leverages transfer learning to account for model misspecification, host galaxy photometry to solve the data scarcity problem soon after discovery, and a custom weighted loss to prioritize accurate early classification. We first train our algorithm using state-of-the-art transient and host galaxy simulations, then adapt its weights and validate it on the spectroscopically-confirmed SNe Ia, SNe II, and SNe Ib/c from the Zwicky Transient Facility Bright Transient Survey. On observed data, our method achieves an overall accuracy of $82 \pm 2$% within 3 days of an event's discovery, and an accuracy of $87 \pm 5$% within 30 days of discovery. At both early and late phases, our method achieves comparable or superior results to the leading classification algorithms with a simpler network architecture. These results help pave the way for rapid photometric and spectroscopic follow-up of scientifically-valuable transients discovered in massive synoptic surveys., Comment: 24 pages, 8 figures. Accepted to ApJ

We introduce Mahakala, a Python-based, modular, radiative ray-tracing code for curved space-times. We employ Google's JAX framework for accelerated automatic differentiation, which can efficiently compute Christoffel symbols directly from the metric, allowing the user to easily and quickly simulate photon trajectories through non-Kerr metrics. JAX also enables Mahakala to run in parallel on both CPUs and GPUs and achieve speeds comparable to C-based codes. Mahakala natively uses the Cartesian Kerr-Schild coordinate system, which avoids numerical issues caused by the "pole" of spherical coordinates. We demonstrate Mahakala's capabilities by simulating the 1.3 mm wavelength images (the wavelength of Event Horizon Telescope observations) of general relativistic magnetohydrodynamic simulations of low-accretion rate supermassive black holes. The modular nature of Mahakala allows us to easily quantify the relative contribution of different regions of the flow to image features. We show that most of the emission seen in 1.3 mm images originates close to the black hole. We also quantify the relative contribution of the disk, forward jet, and counter jet to 1.3 mm images., Comment: 15 pages, 11 figures