High Energy Astrophysical Phenomena
Spectropolarimetric Evolution Reveals Dual-Axis Ejecta in the Atypical Magnetar-Powered SN 2012au
Sabrina DeSoto, JenniferL.Hoffman, G. Grant Williams et al. (+7 more)
We present six epochs of optical spectropolarimetric observations of the unique and slow-evolving Type Ib
supernova (SN) 2012au, between 0 and 295 days post R-band maximum. The polarization levels seen throughout our observations are on average 0.87% +/- 0.05% higher than those of any Type Ib SN~yet studied, suggesting either that it is the most asymmetric of the sample, or if all SNe Ib have similar asymmetry, that it is viewed at a more optimum angle. Significant continuum polarization indicates that the photosphere exhibited a global departure from spherical
symmetry at the level of 10%-40% at the earliest times (days 0–40), which decreased to 0%-20% by days 57–90. During the early photospheric phase, the ejecta maintained a near-constant orientation of 12{\deg}-20{\deg} on the sky, as shown by the dominant axis in the Stokes q-u plane. Polarization signatures in the Fe II {\lambda}{\lambda}{\lambda}4924, 5018, 5169 lines shared this axis. Meanwhile, high levels of polarization associated with the He I lines traced distinct q-u loops with a dramatic rotation away from the dominant axis, indicating that the early-time ejecta were also characterized by hot, fast, helium-rich material concentrated near the poles. At day 295, during the transition to the nebular phase, a new, highly elongated structure became prominent in the ejecta, with an axis orthogonal to the dominant axis that defined the photospheric phase. This dual-axis geometry may link SN 2012au's high luminosity and asymmetric structure to a magnetar powering mechanism.
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All authors Sabrina DeSoto, JenniferL.Hoffman, G. Grant Williams, Christopher Bilinski, Douglas C. Leonard, Peter A. Milne, Christopher Pickens, Manisha Shrestha, Nathan Smith, Paul S.Smith
Instrumentation and Methods for Astrophysics · Cross-listed from physics.flu-dyn
Mitigating numerical dissipation in simulations of subsonic turbulent flows
James Watt, Christoph Federrath, Claudius Birke et al. (+1 more)
Magnetohydrodynamic (MHD) simulations of subsonic (Mach number~$<1$)
turbulence are crucial to our understanding of several processes including oceanic and atmospheric flows, the amplification of
magnetic fields in the early universe,
accretion discs, and stratified flows in
stars. In this work, we demonstrate that conventional numerical schemes are excessively dissipative in this low-Mach regime. We demonstrate that a new numerical scheme (termed `USM-BK' and implemented in the FLASH MHD code) reduces the dissipation of kinetic and
magnetic energy, constrains the divergence of
magnetic field to zero close to machine precision, and resolves smaller-scale structure than other, more conventional schemes, and hence, is the most accurate for simulations of low-Mach turbulent flows among the schemes compared in this work. We first compare several numerical schemes/solvers, including Split-Roe, Split-Bouchut, USM-Roe, USM-HLLC, USM-HLLD, and the new USM-BK, on a simple
vortex problem. We then compare the schemes/solvers in simulations of the turbulent dynamo and show that the choice of scheme affects the growth rate, saturation level, and viscous and resistive dissipation scale of the dynamo. We also measure the numerical kinematic Reynolds number (Re) and
magnetic Reynolds number (Rm) of our otherwise ideal MHD flows, and show that the new USM-BK scheme provides the highest Re and comparable Rm amongst all the schemes compared.
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All authors James Watt, Christoph Federrath, Claudius Birke, Christian Klingenberg
High Energy Astrophysical Phenomena
Simulating the Diffuse Neutrino Emission from the Milky Way with GALPROP
P. D. Marinos, T. A. Porter, G. P. Rowell et al. (+2 more)
We use the GALPROP
cosmic ray (CR) propagation framework to model the diffuse
neutrino and gamma-ray emissions from the
Galaxy. A collection of realistic bounding models are developed and predictions of the resulting
neutrino and gamma-ray signals are compared to the IceCube and LHAASO data up to PeV energies. We find that all the GALPROP models are consistent with the
neutrino data within uncertainties. They are also consistent with expectations of
neutrino emissions derived from LHAASO data when accounting for possible gamma-ray point source contamination. The new models present state-of-the-art predictions for the VHE
neutrino emissions from the
Galaxy that may be used for future
neutrino searches.
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All authors P. D. Marinos, T. A. Porter, G. P. Rowell, I. V. Moskalenko, G. Jóhannesson
High Energy Astrophysical Phenomena
Searching for Long-Period Radio Transients in ASKAP EMU Data with 10-Second Imaging
Yu Wing Joshua Lee, Yuanming Wang, Manisha Caleb et al. (+10 more)
Long-period
radio transients (LPTs) are a recently identified phenomenon that challenge our current understanding of compact objects and coherent
radio emission mechanisms. These objects emit
radio pulses similar to those of
pulsars, but at much longer periods – on the order of minutes to hours. With duty cycles of only a few percent, individual pulses have been observed to last between 10 and 1000 seconds. This places LPTs in a timescale gap between the two main techniques used in transient
radio searches: time-series analysis at millisecond to second timescales, and image-plane searches sensitive to variability on the scale of days. As a result, LPTs remained undetected until recently, and only a handful are currently known. To increase the sample of known LPTs, we conducted a dedicated search using 200 hours of archival data from the ASKAP Evolutionary Map of the Universe survey, covering 750 deg$^2$ of sky at the shortest possible imaging time step of 10-seconds. This represents the first large-scale search using ASKAP data at second-scale resolution. Although no LPTs were detected, we identified
flares from six
stars, at least one had never been detected in the
radio regime before. We placed a lower limit on the transient surface density of $2.21\times10^{-6}$ deg$^{-2}$ at a 10-second timescale, with a sensitivity of 16.9 mJy. Our findings evaluate the feasibility of detecting
radio transients using 10-second imaging with ASKAP and provide insights into improving detection pipelines and observation strategies for LPTs.
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All authors Yu Wing Joshua Lee, Yuanming Wang, Manisha Caleb, Tara Murphy, Tao An, Barnali Das, Dougal Dobie, Laura N. Driessen, David L. Kaplan, Emil Lenc, Joshua Pritchard, Zorawar Wadiasingh, Zhijun Xu
Cosmology and Nongalactic Astrophysics · Cross-listed from hep-ph
Searching for screened scalar forces with long-baseline atom interferometers
Hannah Banks, John Carlton, Benjamin Elder et al. (+2 more)
Screened scalars are ubiquitous in many dark-sector models. They give rise to non-trivial fifth forces whilst evading experimental constraints through density-dependent screening mechanisms. We propose equipping a 10\,m-scale long-baseline atom interferometer with an annular planar source mass inside the
vacuum chamber to search for such screened fifth forces. Two key challenges arise: distinguishing the static fifth force from backgrounds, and isolating it from the plate's Newtonian
gravity. We introduce the `$Q$-flip protocol', which alternates between interferometry sequences to induce controllable time-dependence, aiding signal extraction and de-trending of transient noise. We further develop an in situ calibration procedure to characterise the plate's Newtonian
gravity and reach shot-noise-limited sensitivity. We show that our proposal could test theoretically motivated parameter space, advancing existing bounds in chameleon and symmetron screened scalar models by $1$ to $1.5$ orders of magnitude. Our proposal is directly applicable to forthcoming experiments, such as AION-10 or VLBAI, and is readily extensible to broader theoretical models and longer baselines.
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All authors Hannah Banks, John Carlton, Benjamin Elder, Thomas Hird, Christopher McCabe
Earth and Planetary Astrophysics
Seasonal and Diurnal Variability of Atmospheric Pressure in Jezero Crater, Mars, from MEDA Measurements on the Perseverance Rover
Julio Carlos Bertua Marasca, Homer Davila Gutierrez and Josue Ismael Mosquera Hadatty
We present an analysis of atmospheric pressure variability inside Jezero Crater on Mars based on measurements from the MEDA meteorological station aboard NASA's Perseverance rover. Pressure data from Sols 182, 361, 504, and 658 reveal seasonal and diurnal fluctuations linked to
solar insolation, CO2 condensation and sublimation cycles, and local geomorphology. During Sol 504, an unexpected pressure increase was recorded despite coinciding with the onset of northern winter, suggesting the influence of perihelion and
dust-related thermal tides. Statistical parameters such as mean, standard deviation, and amplitude show that Jezero exhibits larger diurnal pressure swings than Gale Crater, mainly due to its lower latitude and topographic confinement. These results demonstrate the strong coupling between Martian atmospheric dynamics, orbital configuration, and local topography, and illustrate the value of MEDA data for characterizing short-term and seasonal variations in the Martian boundary layer.
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Solar and Stellar Astrophysics
Towards model-free stellar chemical abundances. Potential applications in the search for chemically peculiar stars in large spectroscopic surveys
Theosamuele Signor, Paula Jofré, Hernan Lira et al. (+3 more)
Chemical abundance determinations from
stellar spectra are challenged by observational noise, limitations in
stellar models, and departures from simplifying assumptions. While traditional and supervised machine learning methods have made remarkable progress in estimating atmospheric parameters and chemical compositions within existing physical models, these factors still constrain our ability to fully exploit the vast data sets provided by modern spectroscopic surveys. We aim to develop a self-supervised, disentangled representation learning framework that extracts chemically meaningful features directly from spectra, without relying on externally imposed label catalogs. We build a variational autoencoder-based representation learning model with physics-inspired structure: multiple decoders each focus on spectral regions dominated by a particular element, enforcing that each latent dimension maps to a single abundance. To evaluate the potential application of our framework, we trained and validated the model on low-resolution, low signal-to-noise synthetic spectra focusing on $\rm [Fe/H]$, $\rm [C/Fe]$, and $\rm [\alpha/Fe]$. We then demonstrate how the trained model can be used to flag
stars as chemically enhanced or depleted in these abundances based on their position within the latent distribution. Our model successfully learns a representation of spectra whose axes correlate tightly with the target abundances ($r=0.92\pm0.01$ for $\rm [Fe/H]$, $r=0.92\pm0.01$ for $\rm [C/Fe]$, $r=0.82\pm0.02$ for $\rm [\alpha/Fe]$). The disentangled representations provide a robust means to distinguish
stars based on their chemical properties, offering an efficient and scalable solution for large spectroscopic surveys.
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All authors Theosamuele Signor, Paula Jofré, Hernan Lira, Sara Vitali, Luis Martí, Nayat Sánchez-Pi
Earth and Planetary Astrophysics
PEPSI Investigation, Retrieval, and Atlas of Numerous Giant Atmospheres (PIRANGA). IV. High-Resolution Phased-Resolved Spectroscopy of The Ultra Hot Jupiter KELT-20 b
Victoria Bonidie, Marshall C. Johnson, Ji Wang et al. (+7 more)
We present five
datasets of high-resolution optical emission spectra of the ultra-hot Jupiter KELT-20 b with the PEPSI spectrograph. Using a
Bayesian retrieval framework, we constrain its dayside pressure-temperature profile and abundances of Fe, Ni, and Ca, providing the first measurements for Ni and Ca for KELT-20 b in emission. We retrieve the pre- and post-eclipse
datasets separately (corresponding to the evening and morning sides, respectively), and compare the constraints on their thermal structures and chemical abundances. We constrain lower abundances in the pre-eclipse
datasets compared to the post-eclipse
datasets. We interpret these results with an
equilibrium chemistry model which suggests ~10-30x supersolar refractory abundances. Due to the well-known degeneracy between absolute abundances and continuum opacities, the abundance ratios are more precise probes of the planetary abundances. Therefore we measure the abundance ratios [Ni/Fe] and [Ca/Fe] across these
datasets and find they agree within 1-sigma. We constrain [Ni/Fe] to be consistent with
solar within 2-sigma, and [Ca/Fe] to be 0.001-0.01x
solar, not accounting for ionization. We compare these abundance ratios with literature results for KELT-20 b in transmission, and find they agree within 2-sigma, suggesting that even though the abundances vary significantly as a function of phase, the abundance ratios of these species remain relatively constant. We find a ~100 K difference in temperature at the top of the thermal inversion, suggesting a hotter evening side than morning side and underscoring the importance of considering 3D effects when studying ultra-hot Jupiters.
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All authors Victoria Bonidie, Marshall C. Johnson, Ji Wang, Sydney Petz, Jake Kamen, Calder Lenhart, Alison Duck, Carles Badenes, Klaus Strassmeier, Ilya Ilyin
Astrophysics of Galaxies
Type Ia supernova feedback effects on globular clusters of different masses
E. Lacchin, M. Donati, F. Calura et al. (+3 more)
Through 3D hydrodynamical simulations, we explore the impact of Type Ia
supernova (SN) explosions on the
star formation history and chemical properties of second-generation (SG)
stars in young globular clusters with masses of 10^5-10^6 Msun. We assume that the SG is formed out of the asymptotic
giant branch (AGB) ejecta of first-generation
stars plus pristine interstellar medium gas which is modelled as a uniform gas moving at a constant velocity towards the cluster. We tested two values for the infalling gas density of 10^(-24) and 10^(23) g/cm^3. Type Ia SNe start to explode together with the release of gas from the most massive AGB
stars. Three simulated models are analyzed. In the low-mass and low-density scenario, we find that SNe Ia quench
star formation which however restarts when the gas cools down again in between two explosions. SG
stars are dominated by a He-rich population (Y>0.33), which is poorly diluted by pristine gas. In the high-mass models,
star formation is mildly affected, while the He composition is significantly altered as exploding SNe prevent the
accretion of pristine gas and therefore extremely helium-rich
stars form. In the high-density model, such weak gas
accretion leads to a maximum enhancement in helium mass fraction much larger than the observed one and not correlating with the initial cluster mass as found in models without Type Ia SNe. As for the iron content, small spreads have been found in all models, but the SG is less homogeneous than the FG, at variance with current observations.
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All authors E. Lacchin, M. Donati, F. Calura, C. Nipoti, A. Lupi, A. Yaghoobi
Solar and Stellar Astrophysics
Simulated Operational Testing of the Prototype Implementation of the SOFIE Model: The 2025 Space Weather Prediction Testbed Exercise
Weihao Liu, Lulu Zhao, Igor V. Sokolov et al. (+29 more)
The CLEAR Space Weather Center of Excellence's
solar energetic particle (SEP) model,
SOlar wind with FIeld lines and Energetic particles (SOFIE), was run and evaluated on-site during the Space Weather Prediction Testbed (SWPT) exercise at the National Oceanic and Atmospheric Administration's Space Weather Prediction Center (NOAA/SWPC) in May 2025. As a physics-based SEP model, SOFIE simulates the acceleration and transport of energetic particles by the coronal mass ejection (CME)-driven shock in the
solar corona and inner heliosphere, and has been validated against historical events. However, questions remain regarding whether a physics-based model, traditionally considered computationally expensive, could meet operational needs. The SWPT exercise offered a valuable opportunity to evaluate SOFIE under simulated operational conditions. On-site interactive feedback from SWPC forecasters, Space Radiation Analysis Group (SRAG) console operators, Community Coordinated Modeling Center (CCMC) personnel, and Moon-to-Mars Space Weather Analysis Office (M2M SWAO) analysts led to significant strategic improvements in the model configuration. The simulation grid was optimized by combining a coarser background grid with higher-resolution regions along the CME path and toward Earth, reducing computational cost without compromising accuracy. In this work, we present the simulated operational performance of SOFIE and its capability to predict SEP fluxes significantly faster than real time. During the SWPT exercise, SOFIE completed a 4-day SEP simulation within 5 hours using 1,000 central processing unit cores, although the earliest SEP forecast was obtained a few hours after CME onset. This marks a milestone in demonstrating SOFIE's operational usefulness and robustness to support future human space exploration.
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All authors Weihao Liu, Lulu Zhao, Igor V. Sokolov, Kathryn Whitman, Tamas I. Gombosi, Nishtha Sachdeva, Eric T. Adamson, Hazel M. Bain, Claudio Corti, M. Leila Mays, Michelangelo Romano, Carina R. Alden, Madeleine M. Anastopulos, Mary E. Aronne, Janet E. Barzilla, Wesley T. Cook, Shawn D. Dahl, Hannah Hermann, Anthony J. Iampietro, A. Steve Johnson, Elizabeth A. Juelfs, Melissa R. Kane, Jonathan D. Lash, Kimberly Moreland, Briana K. Muhlestein, Teresa Nieves-Chinchilla, Edward Semones, James F. Spann, Earl M. Spencer, Luke A. Stegeman, Christopher J. Stubenrauch, Kenneth L. Tegnell
Cosmology and Nongalactic Astrophysics
Towards a Machine Learning Solution for Hubble Tension: Physics-Informed Neural Network (PINN) Analysis of Tsallis Holographic Dark Energy in Presence of Neutrinos
Muhammad Yarahmadi and Amin Salehi
We present a Physics-Informed Neural Network (PINN) framework for reconstructing the
redshift-dependent Hubble parameter \(H(z)\) within the Tsallis
Holographic Dark Energy (THDE) model extended by massive
neutrinos. In this approach, the modified Friedmann equation is incorporated into the neural network loss function, enabling training on
Cosmic Chronometers data up to \(z \leq 2\). The framework allows for the simultaneous estimation of the Hubble constant \(H_0\), the
neutrino density parameter \(\Omega_\nu\), and the Tsallis non-extensivity index \(\delta\). Uncertainty quantification is performed through dropout simulations, resulting in statistically consistent \(1\sigma\) confidence bands. Our results show that the THDE+$\nu$ model, reconstructed via PINN, alleviates the statistical Hubble tension from the canonical \(\sim 5\sigma\) level down to a range of \(0.5\sigma \leq T \leq 2.2\sigma\), depending on the
redshift sampling. Additionally, we constrain the total
neutrino mass to \(\Sigma m_\nu < 0.11\,\text{eV}\). A detailed comparison with the traditional Markov Chain Monte Carlo (MCMC) analysis demonstrates the consistency of both methods, while highlighting the competitiveness of the PINN-based THDE framework as a robust, data-driven approach for non-parametric cosmological inference within generalized thermodynamics.
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Instrumentation and Methods for Astrophysics
Analyzing Exoplanet Transits Observed with the WFC3/UVIS G280 Grism
Munazza K. Alam, Frederick Dauphin and Amanda Pagul
Here we describe a Jupyter notebook demonstrating methods for the reduction and analysis of
exoplanet transit observations taken with the WFC3/UVIS G280 grism. Released on Space
Telescope's hst_notebooks GitHub repository, this notebook presents an example workflow for processing time-series observations taken with the G280 grism - from the calibrated flat-fielded spectra to transit light curves ready for fitting. The specific routines presented in the notebook are explained here, and are meant to highlight data reduction steps that users will typically apply to extract transit light curves. The steps include background subtraction, spatial and temporal
cosmic ray correction, spectral trace fitting, spectral extraction, and light curve generation. The end products of the routines in the Jupyter notebook are the raw broadband and spectroscopic light curves, which can be ingested into publicly available light curve fitting tools to extract planetary transmission spectra.
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Earth and Planetary Astrophysics
Planetary architectures under the influence of a stellar binary
Milenne Ávila-Bravo, Carolina Charalambous and Claudia Aguilera-Gómez
Context. The presence of a
stellar companion can strongly influence the architecture and long-term stability of planetary systems. Motivated by the discovery of
exoplanets exhibiting extremely high eccentricities (e >= 0.8) in systems with a binary companion, we investigate how planetary orbits around one
star (S-type configuration) evolve under the gravitational perturbations of the companion. Aims. We aim to assess the role of a
stellar companion in shaping the orbital
evolution of S-type
planets and to explore whether dynamical interactions in such environments can account for the formation of highly eccentric
planets. Methods. We performed a suite of N-body simulations, modeling systems initially composed of three Jupiter-mass
planets on nearly circular, coplanar orbits around the primary
star. We systematically varied the semi-major axis, eccentricity, and inclination of the
stellar companion, to characterize the conditions under which extreme eccentricities can be excited. Results. Our results show that dynamical processes such as
planet-
planet scattering and secular mechanisms–including the von Zeipel-Kozai-Lidov effect induced by the binary–often act together to produce abrupt and significant changes in planetary orbital
evolution, with the outcome strongly dependent on the binary separation. The binary's eccentricity primarily dictates the number of surviving
planets, while its inclination not only governs the final eccentricities of those survivors but also drives their orbits to align with the binary plane. Our simulations successfully reproduce the high eccentricities and compact orbits observed in four observed systems, showing close agreement between the modeled configurations and the actual systems.
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Earth and Planetary Astrophysics
glitterin: Towards Replacing the Role of Lorenz-Mie Theory in Astronomy Using Neural Networks Trained on Light Scattering of Irregularly Shaped Grains
Zhe-Yu Daniel Lin, Alycia J. Weinberger, Evgenij Zubko et al. (+2 more)
Light scattering by
dust particles is often modeled assuming the
dust is spherical for numerical simplicity and speed. However, real
dust particles have highly irregular morphologies that significantly affect their scattering properties. We have developed glitterin, a neural network trained to predict light scattering from irregularly shaped
dust grains, offering a computationally efficient alternative to Lorenz-Mie theory. We computed scattering properties using the Discrete Dipole Approximation code ADDA for irregularly shaped particles across size parameters x from 0.1 to 65, covering a range in complex refractive index m that includes astrosilicates, pyroxene, enstatite, water-ice, etc. The neural network operates at millisecond timescales while maintaining superior accuracy compared to linear interpolation. Irregular grains exhibit x-dependent deviations from spherical predictions. At small x, cross-sections approach volume-equivalent spheres for low m. At large x, irregular grains show enhanced cross-sections due to greater
geometric extension. Increasing m also enhances the absorption cross-section relative to the volume-equivalent spheres. This differential x and m dependence creates mid-IR solid-state features distinct from predictions from spherical grains. Validation against laboratory measurements of forsterite and hematite demonstrates that our neural network captures both qualitative and quantitative behaviors more accurately than spherical models. Millimeter-wavelength applications reveal that spherical grains produce opposite polarization signatures compared to irregular grains, potentially relaxing stringent ~100um grain size constraints in protoplanetary disks. glitterin is publicly available and alleviates the computational barriers to incorporating emission and scattering of realistic grain morphologies.
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All authors Zhe-Yu Daniel Lin, Alycia J. Weinberger, Evgenij Zubko, Jessica A. Arnold, Gorden Videen
Cosmology and Nongalactic Astrophysics
Measuring the Dark Matter Self-Interaction Cross-Section with Deep Compact Clustering for Robust Machine Learning Inference
Ethan Tregidga, David Harvey, Luca Biggio et al. (+1 more)
We have developed a machine learning
algorithm capable of detecting “out-of-domain data” for trustworthy cosmological inference. By using data from two separate suites of cosmological simulations, we show that our
algorithm is able to determine whether “observed” data is consistent with its training domain, returning confidence estimates as well as accurate parameter estimations. We apply our
algorithm to two-dimensional images of
galaxy clusters from the BAHAMAS-SIDM and DARKSKIES simulations with the aim to measure the self-interaction cross-section of dark matter. Through deep compact clustering we construct an informative latent space where
galaxy clusters are mapped to the latent space forming “latent-clusters” for each simulation, with the location of the latent-cluster corresponding to the macroscopic parameters, such as the cross-section, $\sigma_{\rm DM}/m$. We then pass through mock observations, where the location of the observed latent-cluster informs us of which properties are shared with the training data. If the observed latent-cluster shares no similarities with latent-clusters from the known simulations, we can conclude that our simulations do not represent the observations and discard any parameter estimations, thus providing us with a method to measure machine learning confidence. This method serves as a blueprint for transparent and robust inference that is in demand in scientific machine learning.
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All authors Ethan Tregidga, David Harvey, Luca Biggio, Felix Vecchi
High Energy Astrophysical Phenomena · Cross-listed from gr-qc
Finite Populations & Finite Time: The Non-Gaussianity of a Gravitational Wave Background
William G. Lamb, Jeremy M. Wachter, Andrea Mitridate et al. (+5 more)
Strong evidence for an isotropic, Gaussian gravitational wave background (GWB) has been found by multiple
pulsar timing arrays (PTAs). The GWB is expected to be sourced by a finite population of supermassive black hole binaries (SMBHBs) emitting in the PTA sensitivity band, and astrophysical inference of PTA data sets suggests a GWB signal that is at the higher end of GWB spectral amplitude estimates. However, current inference analyses make simplifying assumptions, such as modeling the GWB as Gaussian, assuming that all SMBHBs only emit at frequencies that are integer multiples of the total observing time, and ignoring the interference between the signals of different SMBHBs. In this paper, we build analytical and numerical models of an astrophysical GWB from circular, inspiralling binaries inclined relative to the line-of-sight of the observer, without the above approximations, and compare the statistical properties of its induced PTA signal to those of a signal produced by a Gaussian GWB. We show that finite population and windowing effects introduce non-Gaussianities in the PTA signal, which are currently unmodeled in PTA analyses.
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All authors William G. Lamb, Jeremy M. Wachter, Andrea Mitridate, Shashwat C. Sardesai, Bence Bécsy, Emily L. Hagen, Stephen R. Taylor, Luke Zoltan Kelley
Instrumentation and Methods for Astrophysics · Cross-listed from gr-qc
Photon counting readout for detection and inference of gravitational waves from neutron star merger remnants
Ethan Payne, Lee McCuller and Katerina Chatziioannou
Gravitational waves emitted after
neutron star binary coalescences and the information they carry about dense matter are a high-priority target for next-generation detectors. Even though such detectors are expected to observe millions of signals, detectable postmerger emission will remain rare. In this work, we explore postmerger detectability and inference through an alternative detector readout scheme for data dominated by
quantum-noise, which is the case above $1$\,kHz:
photon-counting. In such a readout, signals and noise become quantized into discrete distributions corresponding to the detection of single
photons measured in a chosen basis of modes. Through simulated data, we demonstrate that
photon counting can be efficient even for weak signals. We find ${\sim}1$ in 100 signals with a postmerger signal-to-noise ratio of 0.2 can result in a single
photon and thus be detected. Furthermore, after $2\times10^4$ signals – equivalent to $10^{-2}$ to $1.5$ years of observation –
photon counting results in a twofold improvement in the measurement of the radius of a $1.6\,M_\odot$
neutron star. Constraints can be further tightened if the detector classical noise is reduced.
Photon counting offers a promising alternative to traditional homodyne readout techniques for extracting information from low signal-to-noise ratio postmerger signals.
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Instrumentation and Methods for Astrophysics
Analysis of the TAIGA-HiSCORE Data Using the Latent Space of Autoencoders
Yu.Yu. Dubenskaya, S.P. Polyakov, A.P. Kryukov et al. (+6 more)
The aim of extensive air shower (EAS) analysis is to reconstruct the physical parameters of the primary particle that initiated the shower. The TAIGA experiment is a hybrid detector system that combines several imaging atmospheric Cherenkov
telescopes (IACTs) and an array of non-imaging Cherenkov detectors (TAIGA-HiSCORE) for EAS detection. Because the signals recorded by different detector types differ in physical nature, the direct merging of data is unfeasible, which complicates
multimodal analysis. Currently, to analyze data from the IACTs and TAIGA-HiSCORE, a set of auxiliary parameters specific to each detector type is calculated from the recorded signals. These parameters are chosen empirically, so there is no certainty that they retain all important information and are the best suited for the respective problems. We propose to use autoencoders (AE) for the analysis of TAIGA experimental data and replace the conventionally used auxiliary parameters with the parameters of the AE latent space. The advantage of the AE latent space parameters is that they preserve essential physics from experimental data without prior assumptions. This approach also holds potential for enabling seamless integration of heterogeneous IACT and HiSCORE data through a joint latent space. To reconstruct the parameters of the primary particle of the EAS from the latent space of the AE, a separate artificial neural network is used. In this paper, the proposed approach is used to reconstruct the energy of the EAS primary particles based on Monte Carlo simulation data for TAIGA-HiSCORE. The dependence of the energy determination accuracy on the dimensionality of the latent space is analyzed, and these results are also compared with the results obtained by the conventional technique. It is shown that when using the AE latent space, the energy of the primary particle is reconstructed with satisfactory accuracy.
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All authors Yu.Yu. Dubenskaya, S.P. Polyakov, A.P. Kryukov, A.P. Demichev, E.O. Gres, E.B. Postnikov, A.Yu. Razumov, P.A. Volchugov, D.P. Zhurov
Cosmology and Nongalactic Astrophysics
The origin of scatter in the X-ray luminosity - halo mass relation of galaxy clusters
Joey Braspenning, Joop Schaye, Annalisa Pillepich et al. (+1 more)
Galaxy groups and clusters are excellent probes of large-scale structure and are shaped by some of the most energetic physical processes in the Universe. They follow a tight scaling relation of X-ray luminosity with
halo mass. However, predicting the dependence of the scatter in this relation on mass and
redshift is challenging, due to the statistical requirement of large simulation volumes. Using the large volume cosmological hydrodynamical simulations for
galaxy cluster physics FLAMINGO and TNG300+TNG-Cluster, we fit this relation and its scatter, focusing on $M_{\rm 500c}>10^{13}~\mathrm{M_\odot}$ and $z \leq 2$. We find qualitatively similar, but quantitatively different results for the two models. For the first time, we study ways to reduce the scatter using properties beyond X-ray luminosity, namely six ICM, six
galaxy, and eleven dark matter
halo properties. For both FLAMINGO and TNG300+TNG-Cluster, the gas fraction and thermal Sunyaev-Zel'dovich (SZ) signal correlate strongest with X-ray scatter, reducing it by over 50% when accounting for their partial correlations.
Galaxy and
halo properties correlate weakly with X-ray scatter, typically reducing it by 10-20%. Our results are qualitatively robust across different FLAMINGO feedback variations, though the correlations weaken for stronger feedback and with increasing
redshift. Differences between FLAMINGO and TNG300+TNG-Cluster are only apparent at the high-mass end - where e.g. the
galaxy stellar age correlates strongly for FLAMINGO, but not for TNG300+TNG-Cluster - confirming robustness across physics implementations. We provide fitting formulas for the scatter and its corrections, for direct application to cosmological analyses and observational data.
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All authors Joey Braspenning, Joop Schaye, Annalisa Pillepich, Dylan Nelson
Astrophysics of Galaxies
Fractional Dynamics in Galactic Nuclei: Non-Local Transport, Transient Phenomena and the Nullification of the Schwarzschild Barrier
Pau Amaro Seoane
We investigate the application of fractional calculus to model
stellar dynamics, focusing on Resonant Relaxation (RR) near a supermassive black hole (SMBH). Standard theories use the local Fokker-Planck (FP) equation, restricted to Gaussian processes under the Central Limit
Theorem (CLT). We argue this is inadequate for RR. We demonstrate that gravitational interactions inherently produce infinite variance in
stochastic torques, violating the CLT. Consequently, RR is governed by the Generalized Central Limit
Theorem (GCLT) and constitutes a superdiffusive Lévy flight. We apply the space-fractional Fokker-Planck equation (FFPE), utilizing non-local operators, to explore resolutions to observational discrepancies. In transient regimes, the FFPE predicts immediate, linear flux ($\Gamma(t) \propto t$), consistent with high
Tidal Disruption Event (TDE) rates in post-starburst
galaxies, whereas local FP models predict significant exponential delay. Furthermore, we demonstrate analytically that non-local integral operators permit “barrier jumping,” bypassing bottlenecks like the Schwarzschild Barrier (SB), which local models interpret as severely suppressing Extreme Mass-Ratio Inspiral (EMRI) rates. We present proof-of-concept $N$-body simulations that confirm non-local RR transport, although the resolution must be improved to rule out enhanced Two-Body Relaxation in the small-N setup. The fractional framework offers a compelling alternative description for non-local transport, potentially resolving TDE and EMRI rate questions.
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Astrophysics of Galaxies
statmorph-lsst: Quantifying and correcting morphological biases in galaxy surveys
Elizaveta Sazonova, Cameron R. Morgan, Michael Balogh et al. (+16 more)
Quantitative morphology provides a key probe of
galaxy evolution across
cosmic time and environments. However, these metrics can be biased by changes in imaging quality - resolution and depth - either across the survey area or the sample. To prepare for the upcoming Rubin LSST data, we investigate this bias for all metrics measured by statmorph and single-component Sérsic fitting with Galfit. We find that geometrical measurements (ellipticity, axis ratio, Petrosian radius, and effective radius) are robust within 10% at most depths and resolutions. Light concentration measurements ($C$, Gini, $M_{20}$) systematically decrease with resolution, leading low-mass or high-
redshift bulge-dominated sources to appear indistinguishable from disks. Sérsic index $n$, while unbiased, suffers from a 20-40% uncertainty due to degeneracies in the Sérsic fit. Disturbance measurements ($A$, $A_S$, $D$) depend on signal-to-noise and are thus affected by noise and surface-brightness dimming. We quantify this dependence for each parameter, offer empirical correction functions, and show that the
evolution in $C$ observed in JWST
galaxies can be explained purely by observational biases. We propose two new measurements - isophotal asymmetry $A_X$ and substructure $St$ - that aim to resolve some of these biases. Finally, we provide a Python package statmorph-lsst implementing these changes and a full
dataset that enables tests of custom functions (see text for links).
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All authors Elizaveta Sazonova, Cameron R. Morgan, Michael Balogh, Matías Blaña, Carlos G. Bornancini, Aidan P. Cotter, Darko Donevski, Alister W. Graham, Hector M. Hernandez Toledo, Benne W. Holwerda, Jeyhan S. Kartaltepe, Garreth Martin, William J. Pearson, Rossella Ragusa, Vicente Rodriguez-Gomez, Michael J. Rutkowski, Jose Antonio Vázquez-Mata, Rogier A. Windhorst, Jacob Yuzovitskiy
Astrophysics of Galaxies
Chandra and HST Observations of Radio-Selected (Wandering) Massive Black Hole Candidates in Dwarf Galaxies
Megan R. Sturm, Amy E. Reines, Anne M. Lohfink et al. (+6 more)
We present Chandra X-ray Observatory and Hubble Space
Telescope (HST) follow-up observations of 12
dwarf galaxies from Reines et al. (2020) that are potential hosts of
radio-selected active
galactic nuclei (AGNs), eight of which are non-
nuclear and possible “wandering" black holes (BHs). Our multi-wavelength analysis indicates a heterogeneous sample with five
radio sources detected at both X-ray and optical wavelengths within positional uncertainties and non-detections for the remaining objects. Of the
radio objects detected in the X-ray/optical, three have multi-wavelength evidence for hosting
nuclear massive BHs and one object is consistent with an extreme compact starburst. Only one of the off-
nuclear radio sources has a significant optical counterpart and we present Palomar spectroscopy that identifies this object as a background AGN. We cannot definitively determine if the seven remaining off-
nuclear radio sources are wandering massive BHs in the target
dwarf galaxies or background AGNs, although the three sources with the largest offsets have compact
radio cores detected with the Very Large Baseline Array and are consistent with expectations for background AGNs (Sargent et al 2022). Our HST sensitivity limits also allow for wandering massive BHs in the target
dwarf galaxies that are hosted by
stellar clusters with masses $\lesssim 10^6 M_\odot$.
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All authors Megan R. Sturm, Amy E. Reines, Anne M. Lohfink, Akos Bogdan, Ralph Kraft, Daniel Stern, Thomas Connor, Jeremy Darling, Mallory Molina
Astrophysics of Galaxies
The SEEDZ Simulations: Methodology and First Results on Massive Black Hole Seeding and Early Galaxy Growth
Lewis R. Prole, John A. Regan, Daxal Mehta et al. (+13 more)
Here we introduce the SEEDZ simulations, a suite of cosmological hydrodynamic simulations exploring the formation and growth of the first massive black holes in the Universe. SEEDZ includes models for Population III
star formation,
supernovae explosions and the resulting formation of light seed black holes, metal enrichment and subsequent Population II
star formation, heavy seed black hole formation, Eddington and super-Eddington
accretion schemes as well as black hole feedback. In this paper, we cover the overall methodologies employed and present our current results at $z=15$. Our main result so far is that black holes initially grow faster than their host
galaxy, and hence over-massive black holes are a feature of the high-
redshift Universe. The fundamental black hole-
galaxy relationships we observe at $z = 0$ (especially the M$_{\rm BH}$ - M$_*$ relationship) likely only emerge in more mature
galaxies. At high-
redshift, that relationship has not yet been established. We find that even at these high
redshifts, MBHs can grow from their initial heavy seed mass of $\sim$10$^4$ M$_\odot$ up to 10$^6$ M$_\odot$. At the high end of our MBH masses, our simulated
galaxy M$_{\rm BH}$ - M$_*$ relations match the observed high
redshift trends i.e. over-massive BHs with M$_{\rm BH}$/M$_{\rm star} \sim 10^{-2}$. This initial set of simulations will continue to run down to $z=10$, where we will perform a comprehensive comparison of simulated MBH number densities and M$_{\rm BH}$ - M$_*$ relations with JWST observations. Further simulations with higher resolution will then follow.
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All authors Lewis R. Prole, John A. Regan, Daxal Mehta, Rudiger Pakmor, Sophie Koudmani, Martin A. Bourne, Simon C.O. Glover, John H. Wise, Ralf S. Klessen, Michael Tremmel, Debora Sijacki, Ricarda S. Beckmann, Martin G. Haehnelt, John Brennan, Pelle van de Bor, Paul C. Clark
Cosmology and Nongalactic Astrophysics
Dark Photons in the Radio Sky: II. Resonant Conversions in the Intergalactic Medium
Ethan Baker and Hongwan Liu
This is the second in a pair of papers
forecasting the sensitivity of the Square Kilometre Array (SKA) to dark
photons, a highly motivated, simple extension of the Standard Model. Through a kinetic mixing term, visible
photons from the
cosmic microwave background can resonantly convert into dark
photons, generating new temperature anisotropies in the sky. In this work, we detail the entire analysis pipeline that we use to compute SKA's sensitivity, focusing on resonant conversions that occur in the intergalactic medium. We also discuss the sensitivity of 21-cm experiments to dark
photons. Our results show that both SKA in combination with
galaxy surveys and 21-cm experiments could discover dark
photons with masses between $5\times 10^{-15}$ and $5\times 10^{-12}$ eV, and kinetic mixing parameter $\epsilon$ as low as $10^{-8}$.
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