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The explosive demand for artificial intelligence (AI) workloads has led to a significant increase in silicon area dedicated to lower-precision computations on recent high-performance computing hardware designs. However, mixed-precision capabilities, which can achieve performance improvements of 8x compared to double-precision in extreme compute-intensive workloads, remain largely untapped in most scientific applications. A growing number of efforts have shown that mixed-precision algorithmic innovations can deliver superior performance without sacrificing accuracy. These developments should prompt computational scientists to seriously consider whether their scientific modeling and simulation applications could benefit from the acceleration offered by new hardware and mixed-precision algorithms. In this article, we review the literature on relevant applications, existing mixed-precision algorithms, theories, and the available software infrastructure. We then offer our perspective and recommendations on the potential of mixed-precision algorithms to enhance the performance of scientific simulation applications. Broadly, we find that mixed-precision methods can have a large impact on computational science in terms of time-to-solution and energy consumption. This is true not only for a few arithmetic-dominated applications but also, to a more moderate extent, to the many memory bandwidth-bound applications. In many cases, though, the choice of algorithms and regions of applicability will be domain-specific, and thus require input from domain experts. It is helpful to identify cross-cutting computational motifs and their mixed-precision algorithms in this regard. Finally, there are new algorithms being developed to utilize AI hardware and and AI methods to accelerate first-principles computational science, and these should be closely watched as hardware platforms evolve., Comment: Submitted to IJHPCA

We use hierarchical Bayesian modelling to calibrate a network of 32 all-sky faint DA white dwarf (DA WD) spectrophotometric standards ($16.5 < V < 19.5$) alongside the three CALSPEC standards, from 912 \r{A} to 32 $\mu$m. The framework is the first of its kind to jointly infer photometric zeropoints and WD parameters ($\log g$, $T_{\text{eff}}$, $A_V$, $R_V$) by simultaneously modelling both photometric and spectroscopic data. We model panchromatic HST/WFC3 UVIS and IR fluxes, HST/STIS UV spectroscopy and ground-based optical spectroscopy to sub-percent precision. Photometric residuals for the sample are the lowest yet yielding $<0.004$ mag RMS on average from the UV to the NIR, achieved by jointly inferring time-dependent changes in system sensitivity and WFC3/IR count-rate nonlinearity. Our GPU-accelerated implementation enables efficient sampling via Hamiltonian Monte Carlo, critical for exploring the high-dimensional posterior space. The hierarchical nature of the model enables population analysis of intrinsic WD and dust parameters. Inferred SEDs from this model will be essential for calibrating the James Webb Space Telescope as well as next-generation surveys, including Vera Rubin Observatory's Legacy Survey of Space and Time, and the Nancy Grace Roman Space Telescope., Comment: 32 pages, 24 figures, 5 tables, submitted to MNRAS

Fainter standard stars are essential for the calibration of larger telescopes. This work adds to the CALSPEC (calibration spectra) database 19 faint white dwarfs (WDs) with all-sky coverage and V magnitudes between 16.5 and 18.7. Included for these stars is new UV (ultraviolet) HST (Hubble Space Telescope) STIS (Space Telescope Imaging Spectrometer) spectrophotometry between 1150 and 3000~\AA\ with a resolution of $\sim$500. Pure hydrogen WD models are fit to these UV spectra and to six-band HST/WFC3 (Wide Field Camera 3) photometry at 0.28 to 1.6~\micron\ to construct predicted model SEDs (spectral energy distributions) covering wavelengths from 900~\AA\ to the JWST (James Webb Space Telescope) limit of 30~\micron\ using well-established CALSPEC procedures for producing flux standards with the goal of 1\% accuracy.

We introduce a pipeline that performs rapid image subtraction and source selection to detect transients, with a focus on identifying gravitational wave optical counterparts using the Dark Energy Camera (DECam). In this work, we present the pipeline steps from processing raw data to identification of astrophysical transients on individual exposures. We process DECam data and build difference images using the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) Science Pipelines software, and we use flags and principal component analysis to select transients on a per-exposure basis, without associating the results from different exposures. Those candidates will be sent to brokers for further classification and alert distribution. We validate our pipeline using archival exposures that cover various types of objects, and the tested targets include a kilonova (GW170817), supernovae, stellar flares, variable stars (in a resolved galaxy or the Milky Way Bulge), and serendipitous objects. Overall, the data processing produces clean light curves that are comparable with published results, demonstrating the photometric quality of our pipeline. Real transients can be well selected by our pipeline when sufficiently bright (S/N $\gtrsim15$). This pipeline is intended to serve as a tool for the broader research community. Although this pipeline is designed for DECam, our method can be easily applied to other instruments and future LSST observations., Comment: 37 pages, 25 figures, 5 tables; revised and accepted for publication in AJ

We present LAISS (Lightcurve Anomaly Identification and Similarity Search), an automated pipeline to detect anomalous astrophysical transients in real-time data streams. We deploy our anomaly detection model on the nightly ZTF Alert Stream via the ANTARES broker, identifying a manageable $\sim$1-5 candidates per night for expert vetting and coordinating follow-up observations. Our method leverages statistical light-curve and contextual host-galaxy features within a random forest classifier, tagging transients of rare classes (spectroscopic anomalies), of uncommon host-galaxy environments (contextual anomalies), and of peculiar or interaction-powered phenomena (behavioral anomalies). Moreover, we demonstrate the power of a low-latency ($\sim$ms) approximate similarity search method to find transient analogs with similar light-curve evolution and host-galaxy environments. We use analogs for data-driven discovery, characterization, (re-)classification, and imputation in retrospective and real-time searches. To date we have identified $\sim$50 previously known and previously missed rare transients from real-time and retrospective searches, including but not limited to: SLSNe, TDEs, SNe IIn, SNe IIb, SNe Ia-CSM, SNe Ia-91bg-like, SNe Ib, SNe Ic, SNe Ic-BL, and M31 novae. Lastly, we report the discovery of 325 total transients, all observed between 2018-2021 and absent from public catalogs ($\sim$1% of all ZTF Astronomical Transient reports to the Transient Name Server through 2021). These methods enable a systematic approach to finding the "needle in the haystack" in large-volume data streams. Because of its integration with the ANTARES broker, LAISS is built to detect exciting transients in Rubin data., Comment: 44 pages (68 pages with Appendix), 15 figures, accepted to ApJ

About 40 transneptunian binaries (TNBs) have fully determined orbits with about 10 others being solved except for breaking the mirror ambiguity. Despite decades of study almost all TNBs have only ever been analyzed with a model that assumes perfect Keplerian motion (e.g., two point masses). In reality, all TNB systems are non-Keplerian due to non-spherical shapes, possible presence of undetected system components, and/or solar perturbations. In this work, we focus on identifying candidates for detectable non-Keplerian motion based on sample of 45 well-characterized binaries. We use MultiMoon, a non-Keplerian Bayesian inference tool, to analyze published relative astrometry allowing for non-spherical shapes of each TNB system's primary. We first reproduce the results of previous Keplerian fitting efforts with MultiMoon, which serves as a comparison for the non-Keplerian fits and confirms that these fits are not biased by the assumption of a Keplerian orbit. We unambiguously detect non-Keplerian motion in 8 TNB systems across a range of primary radii, mutual orbit separations, and system masses. As a proof of concept for non-Keplerian fitting, we perform detailed fits for (66652) Borasisi-Pabu, possibly revealing a $J_2 \approx 0.44$, implying Borasisi (and/or Pabu) may be a contact binary or an unresolved compact binary. However, full confirmation of this result will require new observations. This work begins the next generation of TNB analyses that go beyond the point mass assumption to provide unique and valuable information on the physical properties of TNBs with implications for their formation and evolution., Comment: Accepted to AJ

In this White Paper, we present recommendations for the scientific community and funding agencies to foster the infrastructure for a collaborative multi-messenger and time-domain astronomy (MMA/TDA) ecosystem. MMA/TDA is poised for breakthrough discoveries in the coming decade. In much the same way that expanding beyond the optical bandpass revealed entirely new and unexpected discoveries, cosmic messengers beyond light (i.e., gravitational waves, neutrinos, and cosmic rays) open entirely new windows to answer some of the most fundamental questions in (astro)physics: heavy element synthesis, equation of state of dense matter, particle acceleration, etc. This field was prioritized as a frontier scientific pursuit in the 2020 Decadal Survey on Astronomy and Astrophysics via its "New Windows on the Dynamic Universe" theme. MMA/TDA science presents technical challenges distinct from those experienced in other disciplines. Successful observations require coordination across myriad boundaries -- different cosmic messengers, ground vs. space, international borders, etc. -- all for sources that may not be well localized, and whose brightness may be changing rapidly with time. Add that all of this work is undertaken by real human beings, with distinct backgrounds, experiences, cultures, and expectations, that often conflict. To address these challenges and help MMA/TDA realize its full scientific potential in the coming decade (and beyond), the second in a series of community workshops sponsored by the U.S. National Science Foundation (NSF) and NASA titled "Windows on the Universe: Establishing the Infrastructure for a Collaborative Multi-Messenger Ecosystem" was held on October 16-18, 2023 in Tucson, AZ. Here we present the primary recommendations from this workshop focused on three key topics -- hardware, software, and people and policy. [abridged], Comment: Workshop white paper

Cardiovascular magnetic resonance imaging is emerging as a crucial tool to examine cardiac morphology and function. Essential to this endeavour are anatomical 3D surface and volumetric meshes derived from CMR images, which facilitate computational anatomy studies, biomarker discovery, and in-silico simulations. However, conventional surface mesh generation methods, such as active shape models and multi-atlas segmentation, are highly time-consuming and require complex processing pipelines to generate simulation-ready 3D meshes. In response, we introduce HybridVNet, a novel architecture for direct image-to-mesh extraction seamlessly integrating standard convolutional neural networks with graph convolutions, which we prove can efficiently handle surface and volumetric meshes by encoding them as graph structures. To further enhance accuracy, we propose a multiview HybridVNet architecture which processes both long axis and short axis CMR, showing that it can increase the performance of cardiac MR mesh generation. Our model combines traditional convolutional networks with variational graph generative models, deep supervision and mesh-specific regularisation. Experiments on a comprehensive dataset from the UK Biobank confirm the potential of HybridVNet to significantly advance cardiac imaging and computational cardiology by efficiently generating high-fidelity and simulation ready meshes from CMR images.

Light echoes give us a unique perspective on the nature of supernovae and non-terminal stellar explosions. Spectroscopy of light echoes can reveal details on the kinematics of the ejecta, probe asymmetry, and reveal details on its interaction with circumstellar matter, thus expanding our understanding of these transient events. However, the spectral features arise from a complex interplay between the source photons, the reflecting dust geometry, and the instrumental setup and observing conditions. In this work we present an improved method for modeling these effects in light echo spectra, one that relaxes the simplifying assumption of a light curve weighted sum, and instead estimates the true relative contribution of each phase. We discuss our logic, the gains we obtain over light echo analysis method(s) used in the past, and prospects for further improvements. Lastly, we show how the new method improves our analysis of echoes from Tycho's supernova (SN 1572) as an example.

We follow our first paper with an analysis of the ensemble of the extensive pre-explosion ground- and space-based infrared observations of the red supergiant (RSG) progenitor candidate for the nearby core-collapse supernova SN 2023ixf in Messier 101, together with optical data prior to explosion obtained with the Hubble Space Telescope (HST). We have confirmed the association of the progenitor candidate with the SN, as well as constrained the metallicity at the SN site, based on SN observations with instruments at Gemini-North. The internal host extinction to the SN has also been confirmed from a high-resolution Keck spectrum. We fit the observed spectral energy distribution (SED) for the star, accounting for its intrinsic variability, with dust radiative-transfer modeling, which assume a silicate-rich dust shell ahead of the underlying stellar photosphere. The star is heavily dust-obscured, likely the dustiest progenitor candidate yet encountered. We found median estimates of the star's effective temperature and luminosity of 2770 K and 9.0e4 L_Sun, with 68% credible intervals of 2340--3150 K and (7.5--10.9)e4 L_sun. The candidate may have a Galactic RSG analog, IRC -10414, with a strikingly similar SED and luminosity. Via comparison with single-star evolutionary models we have constrained the initial mass of the progenitor candidate from 12 M_sun to as high as 14 M_sun. We have had available to us an extraordinary view of the SN 2023ixf progenitor candidate, which should be further followed up in future years with HST and the James Webb Space Telescope., Comment: 40 pages, substantive modifications relative to the previous, although the overall conclusions remain the same; to appear in AAS Journals

Observational evidence points to a red supergiant (RSG) progenitor for SN 2023ixf. The progenitor candidate has been detected in archival images at wavelengths (>0.6 micron) where RSGs typically emit profusely. This object is distinctly variable in the infrared (IR). We characterize the variability using pre-explosion mid-IR (3.6 and 4.5 micron) Spitzer and ground-based near-IR (JHKs) archival data jointly covering 19 yr. The IR light curves exhibit significant variability with RMS amplitudes in the range of 0.2-0.4 mag, increasing with decreasing wavelength. From a robust period analysis of the more densely sampled Spitzer data, we measure a period of 1091+/-71 days. We demonstrate using Gaussian Process modeling that this periodicity is also present in the near-IR light curves, thus indicating a common physical origin, which is likely pulsational instability. We use a period-luminosity relation for RSGs to derive a value of M_K=-11.58+/-0.31 mag. Assuming a late M spectral type, this corresponds to log(L/L_sun)=5.27+/-0.12 at T_eff=3200 K and to log(L/L_sun)=5.37+/-0.12 at T_eff=3500 K. This gives an independent estimate of the progenitor's luminosity, unaffected by uncertainties in extinction and distance. Assuming the progenitor candidate underwent enhanced dust-driven mass-loss during the time of these archival observations, and using an empirical period-luminosity-based mass-loss prescription, we obtain a mass-loss rate of around (2-4)x10^-4 M_sun/yr. Comparing the above luminosity with stellar evolution models, we infer an initial mass for the progenitor candidate of 20+/-4 M_sun, making this one of the most massive progenitors for a Type II SN detected to-date., Comment: 20 pages, 2 tables, accepted to ApJ

Hot DA white dwarfs have fully radiative pure hydrogen atmospheres that are the least complicated to model. Pulsationally stable, they are fully characterized by their effective temperature Teff, and surface gravity log g, which can be deduced from their optical spectra and used in model atmospheres to predict their spectral energy distribution (SED). Based on this, three bright DAWDs have defined the spectrophotometric flux scale of the CALSPEC system of HST. In this paper we add 32 new fainter (16.5 < V < 19.5) DAWDs spread over the whole sky and within the dynamic range of large telescopes. Using ground based spectra and panchromatic photometry with HST/WFC3, a new hierarchical analysis process demonstrates consistency between model and observed fluxes above the terrestrial atmosphere to < 0.004 mag rms from 2700 {\AA} to 7750 {\AA} and to 0.008 mag rms at 1.6{\mu}m for the total set of 35 DAWDs. These DAWDs are thus established as spectrophotometric standards with unprecedented accuracy from the near ultraviolet to the near-infrared, suitable for both ground and space based observatories. They are embedded in existing surveys like SDSS, PanSTARRS and GAIA, and will be naturally included in the LSST survey by Rubin Observatory. With additional data and analysis to extend the validity of their SEDs further into the IR, these spectrophotometric standard stars could be used for JWST, as well as for the Roman and Euclid observatories., Comment: Accepted for publication in Astrophysical Journal. Corrected error in Table 10 and associated Fig 7 in which RP and BP values for the 3 CALSPEC standards had been transposed

Small solar system bodies have widely dispersed orbital poles, posing challenges to dynamical models of solar system origin and evolution. To characterize the orbit pole distribution of dynamical groups of small bodies it helps to have a functional form for a model of the distribution function. Previous studies have used the small-inclination approximation and adopted variations of the normal distribution to model orbital inclination dispersions. Because the orbital pole is a directional variable, its distribution can be more appropriately modeled with directional statistics. We describe the von Mises-Fisher (vMF) distribution on the surface of the unit sphere for application to small bodies' orbital poles. We apply it to the orbit pole distribution of the observed Plutinos. We find a mean pole located at inclination of 3.57 degrees and a longitude of ascending node of 124.38 degrees (in the J2000 reference frame), with a 99.7 per cent confidence cone of half-angle 1.68 degrees. We also estimate a debiased mean pole located 4.6 degrees away, at an inclination of 2.26 degrees and a longitude of ascending node of 292.69 degrees, of similar-size confidence cone. The vMF concentration parameter of Plutino inclinations (relative to either mean pole estimate) is 31.6. This resembles a Rayleigh distribution function with a width parameter of 10.2 degrees. Unlike previous models, the vMF model naturally accommodates all physical inclinations (and no others), whereas Rayleigh or Gaussian models must be truncated to the physical inclination range 0-180 degrees. Further work is needed to produce a theory for the mean pole of the Plutinos against which to compare the observational results., Comment: 10 pages, 7 figures. Accepted for Monthly Notices of the Royal Astronomical Society (MNRAS) in April 2023

Mean plane measurements of the Kuiper Belt from observational data are of interest for their potential to test dynamical models of the solar system. Recent measurements have yielded inconsistent results. Here we report a measurement of the Kuiper Belt's mean plane with a sample size more than twice as large as in previous measurements. The sample of interest is the non-resonant Kuiper belt objects, which we identify by using machine learning on the observed Kuiper Belt population whose orbits are well-determined. We estimate the measurement error with a Monte Carlo procedure. We find that the overall mean plane of the non-resonant Kuiper Belt (semimajor axis range 35-150 au) and also that of the classical Kuiper Belt (semimajor axis range 42-48 au) are both close to (within about 0.7 degrees) but distinguishable from the invariable plane of the solar system to greater than 99.7% confidence. When binning the sample into smaller semimajor axis bins, we find the measured mean plane mostly consistent with both the invariable plane and the theoretically expected Laplace surface forced by the known planets. Statistically significant discrepancies are found only in the semimajor axis ranges 40.3-42 au and 45-50 au; these ranges are in proximity to a secular resonance and Neptune's 2:1 mean motion resonance where the theory for the Laplace surface is likely to be inaccurate. These results do not support a previously reported anomalous warp at semimajor axes above 50 au., Comment: 15 pages, 4 figures. Accepted for The Astronomical Journal

We report early-time ultraviolet (UV) and optical spectroscopy of the young, nearby Type II supernova (SN) 2022wsp obtained by the Hubble Space Telescope (HST)/STIS at about 10 and 20 days after the explosion. The SN 2022wsp UV spectra are compared to those of other well-observed Type II/IIP SNe, including the recently studied Type IIP SN 2021yja. Both SNe exhibit rapid cooling and similar evolution during early phases, indicating a common behavior among SNe II. Radiative-transfer modeling of the spectra of SN 2022wsp with the TARDIS code indicates a steep radial density profile in the outer layer of the ejecta, a supersolar metallicity, and a relatively high total extinction of E(B-V) = 0.35 mag. The early-time evolution of the photospheric velocity and temperature derived from the modeling agree with the behavior observed from other previously studied cases. The strong suppression of hydrogen Balmer lines in the spectra suggests interaction with a pre-existing circumstellar environment could be occurring at early times. In the SN 2022wsp spectra, the absorption component of the Mg II P Cygni profile displays a double-trough feature on day +10 that disappears by day +20. The shape is well reproduced by the model without fine-tuning the parameters, suggesting that the secondary blueward dip is a metal transition that originates in the SN ejecta., Comment: Submitted to ApJ Letters on 4/11/2023