Search

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.

Combined, joint, intra-governmental, inter-agency and multinational (CJIIM) operations require rapid data sharing without the bottlenecks of metadata curation and alignment. Curation and alignment is particularly infeasible for external open source information (OSINF), e.g., social media, which has become increasingly valuable in understanding unfolding situations. Large language models (transformers) facilitate semantic data and metadata alignment but are inefficient in CJIIM settings characterised as denied, degraded, intermittent and low bandwidth (DDIL). Vector symbolic architectures (VSA) support semantic information processing using highly compact binary vectors, typically 1-10k bits, suitable in a DDIL setting. We demonstrate a novel integration of transformer models with VSA, combining the power of the former for semantic matching with the compactness and representational structure of the latter. The approach is illustrated via a proof-of-concept OSINF data discovery portal that allows partners in a CJIIM operation to share data sources with minimal metadata curation and low communications bandwidth. This work was carried out as a bridge between previous low technology readiness level (TRL) research and future higher-TRL technology demonstration and deployment.

Large language model (LLM) chatbots are susceptible to biases and hallucinations, but current evaluations of mental wellness technologies lack comprehensive case studies to evaluate their practical applications. Here, we address this gap by introducing the MHealth-EVAL framework, a new role-play based interactive evaluation method designed specifically for evaluating the appropriateness, trustworthiness, and safety of mental wellness chatbots. We also introduce Psyfy, a new chatbot leveraging LLMs to facilitate transdiagnostic Cognitive Behavioral Therapy (CBT). We demonstrate the MHealth-EVAL framework's utility through a comparative study of two versions of Psyfy against standard baseline chatbots. Our results showed that Psyfy chatbots outperformed the baseline chatbots in delivering appropriate responses, engaging users, and avoiding untrustworthy responses. However, both Psyfy and the baseline chatbots exhibited some limitations, such as providing predominantly US-centric resources. While Psyfy chatbots were able to identify most unsafe situations and avoid giving unsafe responses, they sometimes struggled to recognize subtle harmful intentions when prompted in role play scenarios. Our study demonstrates a practical application of the MHealth-EVAL framework and showcases Psyfy's utility in harnessing LLMs to enhance user engagement and provide flexible and appropriate responses aligned with an evidence-based CBT approach.

We propose that gamma-ray burst pulses are produced when highly-relativistic jets sweep across an observer's line-of-sight. We hypothesize that axisymmetric jet profiles, coupled with special relativistic effects, produce the time-reversed properties of gamma-ray burst pulses. Curvature resulting from rapid jet expansion is responsible for much of the observed pulse asymmetry and hard-to-soft evolution. The relative obliqueness with which the jet crosses the line-of-sight explains the known GRB pulse morphological types. We explore two scenarios: one in which a rigid/semi-rigid jet moves laterally, and the other in which a ballistic jet sprays material from a laterally-moving nozzle. The ballistic jet model is favored based upon its consistency with standard emission mechanisms., Comment: 18 pages, 13 figures, accepted for publication in The Astrophysical Journal

Concept Bottleneck Models (CBMs) are regarded as inherently interpretable because they first predict a set of human-defined concepts which are used to predict a task label. For inherent interpretability to be fully realised, and ensure trust in a model's output, it's desirable for concept predictions to use semantically meaningful input features. For instance, in an image, pixels representing a broken bone should contribute to predicting a fracture. However, current literature suggests that concept predictions often rely on irrelevant input features. We hypothesise that this occurs when dataset labels include inaccurate concept annotations, or the relationship between input features and concepts is unclear. In general, the effect of dataset labelling on concept representations remains an understudied area. In this paper, we demonstrate that CBMs can learn to map concepts to semantically meaningful input features, by utilising datasets with a clear link between the input features and the desired concept predictions. This is achieved, for instance, by ensuring multiple concepts do not always co-occur and, therefore provide a clear training signal for the CBM to distinguish the relevant input features for each concept. We validate our hypothesis on both synthetic and real-world image datasets, and demonstrate under the correct conditions, CBMs can learn to attribute semantically meaningful input features to the correct concept predictions., Comment: Main paper: 8 pages, 9 figures, Appendix: 14 pages, 21 figures. This paper is a preprint

Optical bottle beams, characterized by their unique three-dimensional dark core, have garnered substantial interest due to their potential applications across multiple domains of science and technology. This paper delves into the current methods used to create these beams and provides a method to obscure their nodal planes through coaxial non-interfering orthogonally polarized beams to generate bottle beams with enhanced uniformity. Experimental and theoretical results show the enhanced vector bottle beam maintains a smaller, more spherically uniform potential well and interesting quasi-particle polarization characteristics.

We explore fitting gamma-ray burst spectra with three physically-motivated models, and thus revisit the viability of synchrotron radiation as the primary source of GRB prompt emission. We pick a sample of 100 bright GRBs observed by the Fermi Gamma-ray Burst Monitor (GBM), based on their energy flux values. In addition to the standard empirical spectral models used in previous GBM spectroscopy catalogs, we also consider three physically-motivated models; (a) a Thermal Synchrotron model, (b) a Band model with a High-energy Cutoff, and (c) a Smoothly Broken Power Law (SBPL) model with a Multiplicative Broken Power Law (MBPL). We then adopt the Bayesian information criterion (BIC) to compare the fits obtained and choose the best model. We find that 42% of the GRBs from the fluence spectra and 23% of GRBs from the peak-flux spectra have one of the three physically-motivated models as their preferred one. From the peak-flux spectral fits, we find that the low-energy index distributions from the empirical model fits for long GRBs peak around the synchrotron value of -2/3, while the two low-energy indices from the SBPL+MBPL fits of long GRBs peak close to the -2/3 and -3/2 values expected for a synchrotron spectrum below and above the cooling frequency., Comment: arXiv admin note: text overlap with arXiv:2103.13528

This work reveals an evidential signal that emerges from the uncertainty value in Evidential Deep Learning (EDL). EDL is one example of a class of uncertainty-aware deep learning approaches designed to provide confidence (or epistemic uncertainty) about the current test sample. In particular for computer vision and bidirectional encoder large language models, the `evidential signal' arising from the Dirichlet strength in EDL can, in some cases, discriminate between classes, which is particularly strong when using large language models. We hypothesise that the KL regularisation term causes EDL to couple aleatoric and epistemic uncertainty. In this paper, we empirically investigate the correlations between misclassification and evaluated uncertainty, and show that EDL's `evidential signal' is due to misclassification bias. We critically evaluate EDL with other Dirichlet-based approaches, namely Generative Evidential Neural Networks (EDL-GEN) and Prior Networks, and show theoretically and empirically the differences between these loss functions. We conclude that EDL's coupling of uncertainty arises from these differences due to the use (or lack) of out-of-distribution samples during training.

Accelerated muon beams have been considered for next-generation studies of high-energy lepton-antilepton collisions and neutrino oscillations. However, high-brightness muon beams have not yet been produced. The main challenge for muon acceleration and storage stems from the large phase-space volume occupied by the beam, derived from the muon production mechanism through the decay of pions from proton collisions. Ionization cooling is the technique proposed to decrease the muon beam phase-space volume. Here we demonstrate a clear signal of ionization cooling through the observation of transverse emittance reduction in beams that traverse lithium hydride or liquid hydrogen absorbers in the Muon Ionization Cooling Experiment (MICE). The measurement is well reproduced by the simulation of the experiment and the theoretical model. The results shown here represent a substantial advance towards the realization of muon-based facilities that could operate at the energy and intensity frontiers., Comment: 23 pages and 5 figures

The recent discovery of a kilonova from the long duration gamma-ray burst, GRB 211211A, challenges classification schemes based on temporal information alone. Gamma-ray properties of GRB 211211A reveal an extreme event, which stands out among both short and long GRBs. We find very short variations (few ms) in the lightcurve of GRB 211211A and estimate ~1000 for the Lorentz factor of the outflow. We discuss the relevance of the short variations in identifying similar long GRBs resulting from compact mergers. Our findings indicate that in future gravitational wave follow-up campaigns, some long duration GRBs should be treated as possible strong gravitational wave counterparts., Comment: 10 pages 5 figures, submitted to AAS journals

Concept Bottleneck Models (CBMs) first map raw input(s) to a vector of human-defined concepts, before using this vector to predict a final classification. We might therefore expect CBMs capable of predicting concepts based on distinct regions of an input. In doing so, this would support human interpretation when generating explanations of the model's outputs to visualise input features corresponding to concepts. The contribution of this paper is threefold: Firstly, we expand on existing literature by looking at relevance both from the input to the concept vector, confirming that relevance is distributed among the input features, and from the concept vector to the final classification where, for the most part, the final classification is made using concepts predicted as present. Secondly, we report a quantitative evaluation to measure the distance between the maximum input feature relevance and the ground truth location; we perform this with the techniques, Layer-wise Relevance Propagation (LRP), Integrated Gradients (IG) and a baseline gradient approach, finding LRP has a lower average distance than IG. Thirdly, we propose using the proportion of relevance as a measurement for explaining concept importance., Comment: Accepted into the AAAI-23 workshop Representation Learning for Responsible Human-Centric AI (R2HCAI) as a 4 page paper. This version also includes an additional 47 pages for the appendix and contains additional figures and tables

Working from a model of Gaussian pixel noise, we present and unify over twenty-five years of developments in the statistical analysis of the photon transfer conversion gain measurement. We then study a two-sample estimator of the conversion gain that accounts for the general case of non-negligible dark noise. The moments of this estimator are ill-defined (their integral representations diverge) and so we propose a method for assigning pseudomoments, which are shown to agree with actual sample moments under mild conditions. A definition of optimal sample size pairs for this two-sample estimator is proposed and used to find approximate optimal sample size pairs that allow experimenters to achieve a predetermined measurement uncertainty with as little data as possible. The conditions under which these approximations hold are also discussed. Design and control of experiment procedures are developed and used to optimally estimate a per-pixel conversion gain map of a real image sensor. Experimental results show excellent agreement with theoretical predictions and are backed up with Monte Carlo simulation. The per-pixel conversion gain estimates are then applied in a demonstration of per-pixel read noise estimation of the same image sensor. The results of this work open the door to a comprehensive pixel-level adaptation of the photon transfer method., Comment: 16 pages, 5 figures

Short gamma-ray bursts are associated with binary neutron star mergers, which are multimessenger astronomical events that have been observed both in gravitational waves and in the multiband electromagnetic spectrum. Depending on the masses of the stars in the binary and on details of their largely unknown equation of state, a dynamically evolving and short-lived neutron star may be formed after the merger, existing for approximately 10-300 ms before collapsing to a black hole. Numerical relativity simulations across different groups consistently show broad power spectral features in the 1-5 kHz range in the post-merger gravitational wave signal, which is inaccessible by current gravitational-wave detectors but could be seen by future third generation ground-based detectors in the next decade. This implies the possibility of quasiperiodic modulation of the emitted gamma-rays in a subset of events where a neutron star is formed shortly prior to the final collapse to a black hole. Here we present two such signals identified in the short bursts GRB 910711 and GRB 931101B from archival BATSE data, which are compatible with the predictions from numerical relativity., Comment: 20 pages, 11 figures, 6 tables. Version accepted for publication in Nature

We present evolutionary pathways for creating hot subdwarf OB (sdOB) stars from hierarchical triple configurations. We use the population synthesis code Multiple Stellar Evolution (MSE) to follow the stellar, binary, and gravitational dynamical evolution of triple-star systems. To ascertain the effect of the outer tertiary, we also consider the evolution of the inner binary with the tertiary component removed. We find we are able to create sdOB stars in single, binary and triple configurations. We also demonstrate that it is possible to form sdOBs in systems which undergo triple common envelope evolution, when the tertiary star undergoes unstable mass transfer onto the inner binary. We are unable to create single or wide sdOB systems without involving a merger earlier in the evolution. The triples can produce sdOBs in binaries with wide, non-interacting companions through binary interactions, which is impossible in isolated binaries. Owing to the closeness of the inner binary in hierarchical triples the formation channels associated with stable mass transfer are suppressed when compared to the isolated binary case., Comment: 10 Pages, 10 Figures, Accepted for publication

Multiple Coulomb Scattering (MCS) is a well known phenomenon occurring when charged particles traverse materials. Measurements of muons traversing low $Z$ materials made in the MuScat experiment showed that theoretical models and simulation codes, such as GEANT4 (v7.0), over-estimated the scattering. The Muon Ionization Cooling Experiment (MICE) measured the cooling of a muon beam traversing a liquid hydrogen or lithium hydride (LiH) energy absorber as part of a programme to develop muon accelerator facilities, such as a Neutrino Factory or a Muon Collider. The energy loss and MCS that occur in the absorber material are competing effects that alter the performance of the cooling channel. Therefore measurements of MCS are required in order to validate the simulations used to predict the cooling performance in future accelerator facilities. We report measurements made in the MICE apparatus of MCS using a LiH absorber and muons within the momentum range 160 to 245 MeV/c. The measured RMS scattering width is about 9% smaller than that predicted by the approximate formula proposed by the Particle Data Group. Data at 172, 200 and 240 MeV/c are compared to the GEANT4 (v9.6) default scattering model. These measurements show agreement with this more recent GEANT4 (v9.6) version over the range of incident muon momenta., Comment: 20 pages, 14 figures, journal

The LUX-ZEPLIN experiment is a dark matter detector centered on a dual-phase xenon time projection chamber operating at the Sanford Underground Research Facility in Lead, South Dakota, USA. This Letter reports results from LUX-ZEPLIN's first search for weakly interacting massive particles (WIMPs) with an exposure of 60~live days using a fiducial mass of 5.5 t. A profile-likelihood ratio analysis shows the data to be consistent with a background-only hypothesis, setting new limits on spin-independent WIMP-nucleon, spin-dependent WIMP-neutron, and spin-dependent WIMP-proton cross sections for WIMP masses above 9 GeV/c$^2$. The most stringent limit is set for spin-independent scattering at 36 GeV/c$^2$, rejecting cross sections above 9.2$\times 10^{-48}$ cm$^2$ at the 90% confidence level., Comment: 9 pages, 8 figures. See https://doi.org/10.1103/PhysRevLett.131.041002 for a data release related to this paper

Time-based dynamic models of cascading failures have been recognized as one of the most comprehensive methods of representing detailed cascading information and are often used for benchmarking and validation. This paper provides an overview of the progress in the field of dynamic analysis of cascading failures in power systems and outlines the benefits and challenges of dynamic simulations in future grids. The benefits include the ability to capture temporal characteristics of system dynamics and provide timing information to facilitate control actions for blackout mitigation. The greatest barriers to dynamic modelling of cascading failures are the computational burden, and the extensive but often unavailable data requirements for dynamic representation of a power system. These factors are discussed in detail in this paper and the need for in-depth research into dynamic modelling of cascading failures is highlighted. Furthermore, case studies of dynamic cascading simulation of 200-bus and 2000-bus benchmark systems provide initial guidance for the selection of critical parameters to enhance simulation efficiency. Finally, cross-validation and comparison against a quasi-steady state DC power flow model is performed, with various metrics compared., Comment: In proceedings of the 11th Bulk Power Systems Dynamics and Control Symposium (IREP 2022), July 25-30, 2022, Banff, Canada

Optical tweezers are tools made of light that enable contactless pushing, trapping, and manipulation of objects ranging from atoms to space light sails. Since the pioneering work by Arthur Ashkin in the 1970s, optical tweezers have evolved into sophisticated instruments and have been employed in a broad range of applications in life sciences, physics, and engineering. These include accurate force and torque measurement at the femtonewton level, microrheology of complex fluids, single micro- and nanoparticle spectroscopy, single-cell analysis, and statistical-physics experiments. This roadmap provides insights into current investigations involving optical forces and optical tweezers from their theoretical foundations to designs and setups. It also offers perspectives for applications to a wide range of research fields, from biophysics to space exploration., Comment: 181 pages, 61 figures

We present an updated prescription for the equilibrium tides suitable for population synthesis codes. A grid of 1D evolutionary models was created and the viscous time-scale was calculated for each detailed model. A metallicity dependent power-law relation was fitted to both the convective cores and convective envelopes of the models. The prescription was implemented into the population synthesis code BSE and predicts an 16.5% reduction in the overall number of merges, with those involving main-sequence stars most affected. The new prescription also reduces the overall supernova rate by 3.6% with individual channels being differently affected. The single degenerate Ia supernova occurrence is reduced by 12.8%. The merging of two Carbon Oxygen white dwarfs to cause a Ia supernova occurs 16% less frequently. The number of sub-synchronously rotating stars in close binaries is substantially increased with our prescription, as is the number of non-circularized systems at the start of common-envelope evolution., Comment: 22 pages, 17 Figures, Accepted for publication 13/05/22

We present, for the first time, the relationship between local stellar mass surface density, $\mathrm{\Sigma_{*}}$, and N/O derived from SDSS-IV MaNGA data, using a sample of $792765$ high signal-to-noise ratio star-forming spaxels. Using a combination of phenomenological modelling and partial correlation analysis, we find that $\mathrm{\Sigma_{*}}$ alone is insufficient to predict the N/O in MaNGA spaxels, and that there is an additional dependence on the local star formation rate surface density, $\mathrm{\Sigma_{SFR}}$. This effect is a factor of $3$ stronger than the dependence of 12+log(O/H) on $\mathrm{\Sigma_{SFR}}$. Surprisingly, we find that the local N/O scaling relations also depend on the total galaxy stellar mass at fixed $\Sigma_{*}$ as well as the galaxy size at fixed stellar mass. We find that more compact galaxies are more nitrogen rich, even when $\mathrm{\Sigma_{*}}$ and $\mathrm{\Sigma_{SFR}}$ are controlled for. We show that $\sim50\%$ of the variance of N/O is explained by the total stellar mass and size. Thus, the evolution of nitrogen in galaxies is set by more than just local effects and does not simply track the build up of oxygen in galaxies. The precise form of the N/O-O/H relation is therefore sensitive to the sample of galaxies from which it is derived. This result casts doubt on the universal applicability of nitrogen-based strong-line metallicity indicators derived in the local universe., Comment: 22 pages, 14 figures. Accepted for publication in the Astrophysical Journal

Gamma-rays, the most energetic photons, carry information from the far reaches of extragalactic space with minimal interaction or loss of information. They bring messages about particle acceleration in environments so extreme they cannot be reproduced on earth for a closer look. Gamma-ray astrophysics is so complementary with collider work that particle physicists and astroparticle physicists are often one in the same. Gamma-ray instruments, especially the Fermi Gamma-ray Space Telescope, have been pivotal in major multi-messenger discoveries over the past decade. There is presently a great deal of interest and scientific expertise available to push forward new technologies, to plan and build space- and ground-based gamma-ray facilities, and to build multi-messenger networks with gamma rays at their core. It is therefore concerning that before the community comes together for planning exercises again, much of that infrastructure could be lost to a lack of long-term planning for support of gamma-ray astrophysics. Gamma-rays with energies from the MeV to the EeV band are therefore central to multiwavelength and multi-messenger studies to everything from astroparticle physics with compact objects, to dark matter studies with diffuse large scale structure. These goals and new discoveries have generated a wave of new gamma-ray facility proposals and programs. This paper highlights new and proposed gamma-ray technologies and facilities that have each been designed to address specific needs in the measurement of extreme astrophysical sources that probe some of the most pressing questions in fundamental physics for the next decade. The proposed instrumentation would also address the priorities laid out in the recent Astro2020 Decadal Survey, a complementary study by the astrophysics community that provides opportunities also relevant to Snowmass., Comment: Contribution to Snowmass 2021