Search

Context. The supernova remnant (SNR) W44 and its surroundings are a prime target for studying the acceleration of cosmic rays (CRs). Several previous studies established an extended gamma-ray emission that is set apart from the radio shell of W44. This emission is thought to originate from escaped high-energy CRs that interact with a surrounding dense molecular cloud complex. Aims. We present a detailed analysis of Fermi-LAT data with an emphasis on the spatial and spectral properties of W44 and its surroundings. We also report the results of the observations performed with the MAGIC telescopes of the northwestern region of W44. Finally, we present an interpretation model to explain the gamma-ray emission of the SNR and its surroundings. Methods. We first performed a detailed spatial analysis of 12 years of Fermi-LAT data at energies above 1 GeV, in order to exploit the better angular resolution, while we set a threshold of 100MeV for the spectral analysis. We performed a likelihood analysis of 174 hours of MAGIC data above 130 GeV using the spatial information obtained with Fermi-LAT. Results. The combined spectra of Fermi-LAT and MAGIC, extending from 100MeV to several TeV, were used to derive constraints on the escape of CRs. Using a time-dependent model to describe the particle acceleration and escape from the SNR, we show that the maximum energy of the accelerated particles has to be ' 40 GeV. However, our gamma-ray data suggest that a small number of lower-energy particles also needs to escape. We propose a novel model, the broken-shock scenario, to account for this effect and explain the gamma-ray emission.

Mrk 421 was in its most active state around early 2010, which led to the highest TeV gamma-ray flux ever recorded from any active galactic nuclei. We aim to characterize the multiwavelength behavior during this exceptional year for Mrk 421, and evaluate whether it is consistent with the picture derived with data from other less exceptional years. We investigated the period from November 5, 2009, (MJD 55140) until July 3, 2010, (MJD 55380) with extensive coverage from very-high-energy (VHE; E$\,>\,$100$\,$GeV) gamma rays to radio with MAGIC, VERITAS, Fermi-LAT, RXTE, Swift, GASP-WEBT, VLBA, and a variety of additional optical and radio telescopes. We investigated the variability and correlation behavior among different energy bands in great detail. We find the strongest variability in X-rays and VHE gamma rays, and PSDs compatible with power-law functions. We observe strong correlations between X-rays and VHE gamma rays. We also report a marginally significant positive correlation between high-energy (HE; E$\,>\,$100$\,$MeV) gamma rays and the ultraviolet band. We detected marginally significant correlations between the HE and VHE gamma rays, and between HE gamma rays and the X-ray, that disappear when the large flare in February 2010 is excluded from the correlation study. The activity of Mrk 421 also yielded the first ejection of features in the VLBA images of the jet of Mrk 421. Yet the large uncertainties in the ejection times of these radio features prevent us from firmly associating them to the specific flares recorded during the campaign. We also show that the collected multi-instrument data are consistent with a scenario where the emission is dominated by two regions, a compact and extended zone, which could be considered as a simplified implementation of an energy-stratified jet as suggested by recent IXPE observations., Comment: Accepted for publication in Astronomy & Astrophysics. Corresponding authors: Felix Schmuckermaier, David Paneque, Axel Arbet Engels

Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of General Relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO--Virgo--KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering the single-harmonic and the dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the asymmetry in the neutron star mass distribution. For the single-harmonic emission model, 29 targets have the upper limit on the amplitude below the theoretical spin-down limit. The lowest upper limit on the amplitude is $6.4\!\times\!10^{-27}$ for the young energetic pulsar J0537-6910, while the lowest constraint on the ellipticity is $8.8\!\times\!10^{-9}$ for the bright nearby millisecond pulsar J0437-4715. Additionally, for a subset of 16 targets we performed a narrowband search that is more robust regarding the emission model, with no evidence of a signal. We also found no evidence of non-standard polarizations as predicted by the Brans-Dicke theory., Comment: main paper: 12 pages, 6 figures, 4 tables

The BL Lacertae object VER J0521+211 underwent a notable flaring episode in February 2020. A short-term monitoring campaign, led by the MAGIC (Major Atmospheric Gamma Imaging Cherenkov) collaboration, covering a wide energy range from radio to very-high-energy (VHE, 100 GeV < E < 100 TeV) gamma rays was organised to study its evolution. These observations resulted in a consistent detection of the source over six consecutive nights in the VHE gamma-ray domain. Combining these nightly observations with an extensive set of multiwavelength data made modelling of the blazar's spectral energy distribution (SED) possible during the flare. This modelling was performed with a focus on two plausible emission mechanisms: i) a leptonic two-zone synchrotron-self-Compton scenario, and ii) a lepto-hadronic one-zone scenario. Both models effectively replicated the observed SED from radio to the VHE gamma-ray band. Furthermore, by introducing a set of evolving parameters, both models were successful in reproducing the evolution of the fluxes measured in different bands throughout the observing campaign. Notably, the lepto-hadronic model predicts enhanced photon and neutrino fluxes at ultra-high energies (E > 100 TeV). While the photon component, generated via decay of neutral pions, is not directly observable as it is subject to intense pair production (and therefore extinction) through interactions with the cosmic microwave background photons, neutrino detectors (e.g. IceCube) can probe the predicted neutrino component. Finally, the analysis of the gamma-ray spectra, as observed by MAGIC and the Fermi-LAT telescopes, yielded a conservative 95\% confidence upper limit of z \leq 0.244 for the redshift of this blazar., Comment: Accepted for publication in A&A

Integral field units (IFU) have extended our knowledge of galactic properties to kpc (or, sometimes, even smaller) patches of galaxies. These scales are where the physics driving galaxy evolution (feedback, chemical enrichment, etc.) take place. Quantifying the spatially-resolved properties of galaxies, both observationally and theoretically, is therefore critical to our understanding of galaxy evolution. To this end, we investigate spatially-resolved scaling relations within central galaxies ($M_\star>10^{9.0}$) at $z=0$ in IllustrisTNG. We examine both the resolved star-forming main sequence (rSFMS) and the resolved mass-metallicity relation (rMZR) using $1~{\rm kpc}\times1~{\rm kpc}$ maps of galaxies. We find that the rSFMS in IllustrisTNG is well-described by a power-law, but has some dependence on the host galaxy's mass. Conversely, the rMZR for IllustrisTNG can be described by a single power-law at low stellar mass surface density that flattens at high surface densities and is independent of host galaxy mass. We find quantitative agreement in both the rSFMS and rMZR with recent IFU observational campaigns. Furthermore, we argue that the rSFMS is an indirect result of the Schmidt-Kennicutt (SK) law and local gas fraction relation, which are both independent of host galaxy properties. Finally, we expand upon a localized leaky-box model to study the evolution of idealized spaxels and find that it provides a good description of these resolved relations. The degree of agreement, however, between idealized spaxels and simulated spaxels depends on the `net' outflow rate for the spaxel, and the observed scaling relations indicate a preference for a low net outflow rate., Comment: 18 pages, 15 figures; Submitted to ApJ; Comments Welcome

We introduce a new replicable boosting algorithm which significantly improves the sample complexity compared to previous algorithms. The algorithm works by doing two layers of majority voting, using an improved version of the replicable boosting algorithm introduced by Impagliazzo et al. [2022] in the bottom layer., Comment: 13 pages

Carbon stars (with atmospheric C/O$>1$) range widely in temperature and luminosity, from low mass dwarfs to asymptotic giant branch stars (AGB). The main sequence dwarf carbon (dC) stars have inherited carbon-rich material from an AGB companion, which has since transitioned to a white dwarf. The dC stars are far more common than C giants, but no reliable estimates of dC space density have been published to date. We present results from an all-sky survey for carbon stars using the low-resolution XP spectra from Gaia DR3. We developed and measured a set of spectral indices contrasting C$_{\rm 2}$ and CN molecular band strengths in carbon stars against common absorption features found in normal (C/O$<1$) stars such as CaI, TiO and Balmer lines. We combined these indices with the XP spectral coefficients as input to supervised machine-learning algorithms trained on a vetted sample of known C stars from LAMOST. We describe the selection of the carbon candidate sample, and provide a catalog of 43,574 candidates dominated by cool C giants in the Magellanic Clouds and at low galactic latitude in the Milky Way. We report the confirmation of candidate C stars using intermediate ($R\sim 1800$) resolution optical spectroscopy from the Fred Lawrence Whipple Observatory, and provide estimates of sample purity and completeness. From a carefully-vetted sample of over 600 dCs, we measure their local space density to be $\rho_0\,=\,1.96^{+0.14}_{-0.12}\times10^{-6}\,\text{pc}^{-3}$ (about one dC in every local disk volume of radius 50\,pc), with a relatively large disk scale height of $H_z\,=\,856^{+49}_{-43}\,$pc., Comment: Accepted to ApJ, 25 pages, 9 figures, 10 tables

In the pursuit of identifying rare two-particle events within the GADGET II Time Projection Chamber (TPC), this paper presents a comprehensive approach for leveraging Convolutional Neural Networks (CNNs) and various data processing methods. To address the inherent complexities of 3D TPC track reconstructions, the data is expressed in 2D projections and 1D quantities. This approach capitalizes on the diverse data modalities of the TPC, allowing for the efficient representation of the distinct features of the 3D events, with no loss in topology uniqueness. Additionally, it leverages the computational efficiency of 2D CNNs and benefits from the extensive availability of pre-trained models. Given the scarcity of real training data for the rare events of interest, simulated events are used to train the models to detect real events. To account for potential distribution shifts when predominantly depending on simulations, significant perturbations are embedded within the simulations. This produces a broad parameter space that works to account for potential physics parameter and detector response variations and uncertainties. These parameter-varied simulations are used to train sensitive 2D CNN object detectors. When combined with 1D histogram peak detection algorithms, this multi-modal detection framework is highly adept at identifying rare, two-particle events in data taken during experiment 21072 at the Facility for Rare Isotope Beams (FRIB), demonstrating a 100% recall for events of interest. We present the methods and outcomes of our investigation and discuss the potential future applications of these techniques.

The Hong-Ou-Mandel (HOM) effect is a quintessential process in various quantum information technologies and quantum optics applications. In this work, we investigate multi-photon interference, developing a model for the simultaneous characterization of polarization and spectro-temporal mode mismatch on the coincidence probabilities including the effects of realistic imperfections of devices used in HOM experiments. We also study the coincidence probability for coherent states as a function of source intensity, as well as spectro-temporal and polarization mismatch of the incident beams. We apply our model to the case of multi-photon interference from independent sources and analyze the consequences of mode mismatch in various instances that occur in quantum networking including entanglement swapping, quantum key distribution, quantum sensing, quantum optical classification, and photonic quantum computing.

White dwarf-main sequence (WDMS) binary systems are essential probes for understanding binary stellar evolution and play a pivotal role in constraining theoretical models of various transient phenomena. In this study, we construct a catalog of WDMS binaries using Gaia DR3's low-resolution BP/RP (XP) spectra. Our approach integrates a model-independent neural network for spectral modelling with Gaussian Process Classification to accurately identify WDMS binaries among over 10 million stars within 1 kpc. This study identify approximately 30,000 WDMS binary candidates, including ~1,700 high-confidence systems confirmed through spectral fitting. Our technique is shown to be effective at detecting systems where the main-sequence star dominates the spectrum - cases that have historically challenged conventional methods. Validation using GALEX photometry reinforces the reliability of our classifications: 70\% of candidates with an absolute magnitude $M_{G} > 7$ exhibit UV excess, a characteristic signature of white dwarf companions. Our all-sky catalog of WDMS binaries expands the available dataset for studying binary evolution and white dwarf physics and sheds light on the formation of WDMS., Comment: 30 pages, 12 figures, Submitted to ApJS

White dwarfs are often found in close binaries with stellar or even substellar companions. It is generally thought that these compact binaries form via common envelope evolution, triggered by the progenitor of the white dwarf expanding after it evolved off the main-sequence and engulfing its companion. To date, a handful of white dwarfs in compact binaries with substellar companions have been found, typically with masses greater than around 50 M$_\mathrm{Jup}$. Here we report the discovery of two eclipsing white dwarf plus brown dwarf binaries containing very low mass brown dwarfs. ZTF J1828+2308 consists of a hot ($15900\pm75$ K) $0.610\pm0.004$ M$_{\odot}$ white dwarf in a 2.7 hour binary with a $0.0186\pm0.0008$ M$_{\odot}$ ($19.5\pm0.8$ M$_\mathrm{Jup}$) brown dwarf. ZTF J1230$-$2655 contains a cool ($10000\pm110$ K) $0.65\pm0.02$ M$_{\odot}$ white dwarf in a 5.7 hour binary with a companion that has a mass of less than 0.0211 M$_{\odot}$ (22.1 M$_\mathrm{Jup}$). While the brown dwarf in ZTF J1828+2308 has a radius consistent with its mass and age, ZTF J1230$-$2655 contains a roughly 20 per cent overinflated brown dwarf for its age. We are only able to reconstruct the common envelope phase for either system if it occurred after the first thermal pulse, when the white dwarf progenitor had already lost a significant fraction of its original mass. This is true even for very high common envelope ejection efficiencies ($\alpha_\mathrm{CE}\sim 1$), unless both systems have extremely low metallicities. It may be that the lowest mass companions can only survive a common envelope phase if it occurs at this very late stage., Comment: 15 pages, 13 figures. Accepted for publication in MNRAS

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai., Comment: 25 pages, 6 figures

In this work we study the circumstellar material (CSM) around massive stars, and the mass-loss rates depositing this CSM, using a large sample of radio observations of 325 core-collapse supernovae (CCSNe; only $\sim 22 \%$ of them being detected). This sample comprises both archival data and our new observations of 99 CCSNe conducted with the AMI-LA radio array in a systematic approach devised to constrain the mass-loss at different stages of stellar evolution. In the SN-CSM interaction model, observing the peak of the radio emission of a SN provides the CSM density at a given radius (and therefore mass-loss rate that deposited this CSM). On the other hand, limits on the radio emission, and/or on the peak of the radio emission provide a region in the CSM phase space that can be ruled out. Our analysis shows discrepancy between the values of mass-loss rates derived from radio-detected and radio-non-detected SNe. Furthermore, we rule out mass-loss rates in the range of $2 \times 10^{-6} - 10^{-4} \, \rm M_{\odot} \, yr^{-1}$ for different epochs during the last 1000 years before the explosion (assuming wind velocity of $10 \, \rm km \, s^{-1}$) for the progenitors of $\sim 80\%$ of the type II SNe in our sample. In addition, we rule out the ranges of mass-loss rates suggested for red supergiants for $\sim 50 \%$ of the progenitors of type II SNe in our sample. We emphasize here that these results take a step forward in constraining mass-loss in winds from a statistical point of view., Comment: 22 pages, 9 figures, accepted for publication in the Astrophysical Journal

We present a numerically efficient and accurate implementation of the Passaglia-Hu effective fluid approximation for ultralight axions (ULAs) within the Boltzmann code CAMB. This method is specifically designed to evolve the axion field accurately across cosmological timescales, mitigating the challenges associated with its rapid oscillations. Our implementation is based on the latest version of CAMB, ensuring compatibility with other cosmological codes., e.g. for calculating cosmological parameter constraints. Compared to exact solutions of the Klein-Gordon equation, our method achieves sub-percent accuracy in the CMB power spectrum across a broad range of axion masses, from $10^{-28}\,\mathrm{eV}$ to $10^{-24}\,\mathrm{eV}$. We perform Markov Chain Monte Carlo (MCMC) analyses incorporating our implementation, and find improved constraints on the axion mass and abundance compared to previous, simpler fluid-based approximations. For example, using \Planck\ PR4 and DESI BAO data, we find $2\sigma$ upper limits on the axion fraction $f_{\rm ax} < 0.0082$ and physical density $\Omega_{\rm ax}h^2 < 0.0010$ for $m=10^{-28}$ eV. The code is publicly available at \url{https://github.com/adammoss/AxiCAMB}., Comment: 12 pages, 7 figures

Changing-look quasars exhibit dramatic variability in broad emission-line fluxes on short timescales. This behavior is challenging to many models of the quasar broad line region, due in large part to the short transition times between high and low states. In order to constrain the cause of the dramatic variability, we obtained contemporaneous Hubble Space Telescope UV and Hobby Eberly Telescope optical spectra of three changing-look quasars caught in their low state. We use these spectra, along with archival spectra taken during both the high and low states, to investigate potential scenarios for the change in state. Our data strongly disfavor a variable dust obscuration scenario for these three CLQs, and instead suggest that the observed transformation reflects a change in the intrinsic luminosity of the central engine. We also find that the low-state spectral energy distributions of all three quasars are reminiscent of those of low-luminosity active galactic nuclei, which suggests that the transition may result from a change in accretion flow structure caused by a reduced Eddington ratio., Comment: 20 pages, 10 figures. Accepted to ApJ January 22, 2025

In this paper, we report the temperature-field phase diagram as well as present a comprehensive study of the electronic structure and three-dimensional fermiology of the triangular-lattice magnet EuAg$_4$Sb$_2$, utilizing quantum oscillation measurements, angle-resolved photoemission spectroscopy and first-principles calculations. The complex magnetic phase diagram of EuAg$_4$Sb$_2$ highlights many transitions through nontrivial AFM states. Shubnikov-de Haas and de Haas-van Alphen oscillations were observed in the polarized ferromagnetic state of EuAg$_4$Sb$_2$, revealing three pairs of distinct spin-split frequency branches with small effective masses. A comparison of the angle-dependent oscillation data with first-principles calculations in the ferromagnetic state and angle-resolved photoemission spectra shows good agreement, identifying tubular hole pockets and hourglass-shaped hole pockets at the Brillouin zone center, as well as diamond-shaped electron pockets at the zone boundary. As the temperature increases, the frequency branches of the tiny hourglass pockets evolve into a more cylindrical shape, while the larger pockets remain unchanged. This highlights that variations in exchange splitting, driven by changes in the magnetic moment, primarily impact the small Fermi pockets without significantly altering the overall band structure. This is consistent with first-principles calculations, which show minimal changes near the Fermi level across ferromagnetic and simple antiferromagnetic states or under varying on-site Coulomb repulsion., Comment: 10 pages, 5 figures

We give an exact count of the number of trivalent graphs whose faces all have 3 or 6 sides, or equivalently, the number of polyhedra with triangular and hexagonal faces and three faces around each vertex. The count is given in terms of the prime factorization of the number of vertices. We also enumerate graphs of this type with mirror symmetry, with 3-fold rotational symmetry, and with both types of symmetry., Comment: 20 pages, 4 figures, 1 table

We present the strongest limits to date on the mixing angle, $\theta$, with which a new scalar particle, $S$, mixes with the Higgs field in the mass range $100$ $MeV

A 2.1-year periodic oscillation of the gamma-ray flux from the blazar PG 1553+113 has previously been tentatively identified in almost 7 year of data from the Fermi Large Area Telescope. After 15 years of Fermi sky-survey observations, doubling the total time range, we report >7 cycle gamma-ray modulation with an estimated significance of 4 sigma against stochastic red noise. Independent determinations of oscillation period and phase in the earlier and the new data are in close agreement (chance probability <0.01). Pulse timing over the full light curve is also consistent with a coherent periodicity. Multiwavelength new data from Swift X-Ray Telescope, Burst Alert Telescope, and UVOT, and from KAIT, Catalina Sky Survey, All-Sky Automated Survey for Supernovae, and Owens Valley Radio Observatory ground-based observatories as well as archival Rossi X-Ray Timing Explorer satellite-All Sky Monitor data, published optical data of Tuorla, and optical historical Harvard plates data are included in our work. Optical and radio light curves show clear correlations with the gamma-ray modulation, possibly with a nonconstant time lag for the radio flux. We interpret the gamma-ray periodicity as possibly arising from a pulsational accretion flow in a sub-parsec binary supermassive black hole system of elevated mass ratio, with orbital modulation of the supplied material and energy in the jet. Other astrophysical scenarios introduced include instabilities, disk and jet precession, rotation or nutation, and perturbations by massive stars or intermediate-mass black holes in polar orbit., Comment: 23 pages, 14 figures, 20 plots, 1 table, accepted and published by The Astrophysical Journal. Article produced by the Fermi Large Area Telescope (LAT) Collaboration

X-ray emission from wind-driven bow shocks is both difficult to measure and predict, but may give important insights into the energy budget of the hot phase of the ISM by quantifying mixing at the interface between hot and warm gas phases. We investigate the effect of magnetic fields and numerical resolution on predicted X-ray emission and other observable properties of bow shocks, to study convergence properties and assess robustness of predicted observables from simulations. A suite of 2D and 3D HD and MHD simulations of bow shocks were run and analysed to generate synthetic emission maps and lightcurves in X-ray and infrared emission. Resolving the Kelvin-Helmholtz (KH) instability at the wind-ISM contact discontinuity is crucial for obtaining converged results and for predicting X-ray emission and the properties of the hot shocked wind. When sufficient spatial resolution is used, we measure time variation of X-ray emission of at least an order of magnitude on a timescale comparable to the advection timescale of the wake downstream from the bow shock. Good correspondence is found between 2D and 3D simulations with comparable resolution, and 3D simulations can achieve the required resolution with reasonable computing resources. Development of the KH instability is inhibited for shear flows parallel to the ISM magnetic field, compared with what is seen in the perpendicular direction, resulting in synthetic IR emission maps of bow shocks that are smooth when seen from one perspective but show strong distortions from another. Measuring the X-ray morphology and luminosity in bow shocks may be useful for constraining mixing and energy-transfer rates between hot and warm gas phases of the ISM. Dynamical instabilities at the wind-ISM interface are a crucial ingredient in determining the properties of the hot-gas phase in stellar bow-shocks, in particular to capture its time dependence., Comment: submitted to A&A, comments welcome

Many renewable energy resources are integrated into power systems via grid-following (GFL) inverters which rely on a phase-locked loop (PLL) for grid synchronization. During severe grid faults, GFL inverters are vulnerable to transient instability, often leading to disconnection from the grid. This paper aims to elucidate the interaction mechanisms and define the stability boundaries of systems of two inverters, including GFL, grid-forming (GFM), or grid-supporting (GSP) inverters. First, the generalized large-signal expression for the two-inverter system under various inverter combinations is derived, revealing that no energy function exists for systems containing GFL inverters. This implies that the traditional direct method cannot be applied to such systems. To overcome these challenges, a manifold method is employed to precisely determine the domain of attraction (DOA) of the system, and the transient stability margin is assessed by a new metric termed the critical clearing radius (CCR). A case study of the two-inverter system under various inverter combinations is conducted to explore large-signal interactions across different scenarios. Manifold analysis and simulation results reveal that GSP inverters using PLL for grid synchronization exhibit behavior similar to GFM inverters when the droop coefficients in the terminal voltage control loop (TVC) are sufficiently large. Compared to GFL inverters, GSP inverters incorporating a TVC significantly enhances the transient stability of other inverters. In the STATCOM case, the optimal placement of the STATCOM, realized by GSP or GFM inverters, is identified to be at the midpoint of a transmission line. All findings in this paper are validated through electromagnetic transient (EMT) simulations

Quantum system calibration is limited by the ability to characterize a quantum state under unknown device errors. We develop an accurate calibration protocol that is blind to the precise preparation of a specific quantum state. It extracts device errors from simple tomographic data only, and does not require bespoke experiments for a priori specified error mechanisms. Using a trapped-ion quantum computer, we experimentally demonstrate the accuracy of the method by recovering intentional miscalibrations. We then use blind calibration to estimate the native calibration parameters of the experimental system. The recovered calibrations are close to directly measured values and perform similarly in predicting state properties.

Some microscopic dynamics are also macroscopically irreversible, dissipating energy and producing entropy. For many-particle systems interacting with deterministic thermostats, the rate of thermodynamic entropy dissipated to the environment is the average rate at which phase space contracts. Here, we use this identity and the properties of a classical density matrix to derive upper and lower bounds on the entropy flow rate with the spectral properties of the local stability matrix. These bounds are an extension of more fundamental bounds on the Lyapunov exponents and phase space contraction rate of continuous-time dynamical systems. They are maximal and minimal rates of entropy production, heat transfer, and transport coefficients set by the underlying dynamics of the system and deterministic thermostat. Because these limits on the macroscopic dissipation derive from the density matrix and the local stability matrix, they are numerically computable from the molecular dynamics. As an illustration, we show that these bounds are on the electrical conductivity for a system of charged particles subject to an electric field., Comment: Published in J. Phys. A: Math. Theor., unnecessary autolinking in the abstract removed

In previous papers it has been shown that the coefficients of terms in the large-$N$ expansion of a certain integrated four-point correlator of superconformal primary operators in $\mathcal{N}=4$ supersymmetric Yang-Mills theory are rational sums of real-analytic Eisenstein series and "generalised Eisenstein series''. The latter are novel modular functions first encountered in the context of graviton amplitudes in type IIB superstring theory. Similar modular functions, known as two-loop modular graph functions, are also encountered in the low-energy expansion of the integrand of genus-one closed superstring amplitudes. In this paper we further develop the mathematical structure of such generalised Eisenstein series emphasising, in particular, the occurrence of $L$-values of holomorphic cusp forms in their Fourier mode decomposition. We show that both the coefficients in the large-$N$ expansion of the integrated correlator and two-loop modular graph functions admit a unifying description in terms of four-dimensional lattice sums generated by theta lifts of local Maass functions, which generalise the structure of real-analytic Eisenstein series. Through the theta lift representation, we demonstrate that elements belonging to these two families of non-holomorphic modular functions can be expressed as rational linear combinations of generalised Eisenstein series for which all the $L$-values of holomorphic cusp forms precisely cancel., Comment: 41 pages + appendices, 1 figure

We present multi-wavelength analysis of ZTF23abelseb (AT 2023sva), an optically discovered fast-fading ($\Delta m_r = 2.2$ mag in $\Delta t = 0.74 $ days), luminous ($M_r \sim -30.0$ mag) and red ($g-r = 0.50$ mag) transient at $z = 2.28$ with accompanying luminous radio emission. AT 2023sva does not possess a $\gamma$-ray burst (GRB) counterpart to an isotropic equivalent energy limit of $E_{\rm{\gamma, \, iso}} < 1.6 \times 10^{52}$ erg, determined through searching $\gamma$-ray satellite archives between the last non-detection and first detection, making it the sixth example of an optically-discovered afterglow with a redshift measurement and no detected GRB counterpart. We analyze AT 2023sva's optical, radio, and X-ray observations to characterize the source. From radio analyses, we find the clear presence of strong interstellar scintillation (ISS) 72 days after the initial explosion, allowing us to place constraints on the source's angular size and bulk Lorentz factor. When comparing the source sizes derived from ISS of orphan events to those of the classical GRB population, we find orphan events have statistically smaller source sizes. We also utilize Bayesian techniques to model the multi-wavelength afterglow. Within this framework, we find evidence that AT 2023sva possesses a shallow power-law structured jet viewed slightly off-axis ($\theta_{\rm{v}} = 0.07 \pm 0.02$) just outside of the jet's core opening angle ($\theta_{\rm{c}} = 0.06 \pm 0.02$). We determine this is likely the reason for the lack of a detected GRB counterpart, but also investigate other scenarios. AT 2023sva's evidence for possessing a structured jet stresses the importance of broadening orphan afterglow search strategies to a diverse range of GRB jet angular energy profiles, to maximize the return of future optical surveys., Comment: 22 pages, 14 Figures, Submitted to MNRAS

Microlensing surveys of stars in the Large Magellanic Cloud constrain the fraction of the Milky Way halo in Primordial Black Holes (PBHs) with mass $10^{-9} \lesssim M/M_{\odot} \lesssim 10^{4}$. Various studies have reached different conclusions on the uncertainties in these constraints due to uncertainties in the Dark Matter (DM) distribution. We therefore revisit the dependence of the microlensing differential event rate, and hence exclusion limits, on the DM density and velocity distributions. The constraints on the abundance of low- and high-mass PBHs depend, respectively, on the long- and short-duration tails of the differential event rate distribution. Long-duration events are due to PBHs moving close to the line of sight and their rate (and hence the constraints on low-mass PBHs) has a fairly weak ($\sim 10\%$) dependence on the DM density and velocity distributions. Short-duration events are due to PBHs close to the observer and their rate (and hence the constraints on moderate- and high-mass PBHs) depends much more strongly on the DM velocity distribution. An accurate calculation of the local DM velocity distribution is therefore crucial for accurately calculating PBH stellar microlensing constraints., Comment: 14 pages, 6 figures

Modern precision medicine aims to utilize real-world data to provide the best treatment for an individual patient. An individualized treatment rule (ITR) maps each patient's characteristics to a recommended treatment scheme that maximizes the expected outcome of the patient. A challenge precision medicine faces is population heterogeneity, as studies on treatment effects are often conducted on source populations that differ from the populations of interest in terms of the distribution of patient characteristics. Our research goal is to explore a transfer learning algorithm that aims to address the population heterogeneity problem and obtain targeted, optimal, and interpretable ITRs. The algorithm incorporates a calibrated augmented inverse probability weighting (CAIPW) estimator for the average treatment effect (ATE) and employs value function maximization for the target population using Genetic Algorithm (GA) to produce our desired ITR. To demonstrate its practical utility, we apply this transfer learning algorithm to two large medical databases, Electronic Intensive Care Unit Collaborative Research Database (eICU-CRD) and Medical Information Mart for Intensive Care III (MIMIC-III). We first identify the important covariates, treatment options, and outcomes of interest based on the two databases, and then estimate the optimal linear ITRs for patients with sepsis. Our research introduces and applies new techniques for data fusion to obtain data-driven ITRs that cater to patients' individual medical needs in a population of interest. By emphasizing generalizability and personalized decision-making, this methodology extends its potential application beyond medicine to fields such as marketing, technology, social sciences, and education., Comment: 23 pages, 4 figures

Background: The MAJORANA DEMONSTRATOR , a modular array of isotopically enriched high-purity germanium (HPGe) detectors, was constructed to demonstrate backgrounds low enough to justify building a tonne-scale experiment to search for the neutrinoless double-beta decay ($\beta\beta(0\nu)$) of $^{76}\mathrm{Ge}$. Purpose: This paper presents a description of the instrument, its commissioning, and operations. It covers the electroforming, underground infrastructure, enrichment, detector fabrication, low-background and construction techniques, electronics, data acquisition, databases, and data processing of the MAJORANA DEMONSTRATOR. Method: The MAJORANA DEMONSTRATOR operated inside an ultra-low radioactivity passive shield at the 4850-foot~level of the Sanford Underground Research Facility (SURF) from 2015-2021. Results and Conclusions: The MAJORANA DEMONSTRATOR achieved the best energy resolution and second-best background level of any $\beta\beta(0\nu)$ search. This enabled it to achieve an ultimate half-life limit on $\beta\beta(0\nu)$ in $^{76}\mathrm{Ge}$ of $8.3\times 10^{25}$~yr (90\% C.L.) and perform a rich set of searches for other physics beyond the Standard Model., Comment: 72 pages

The advancement of machine learning and the availability of large-scale reaction datasets have accelerated the development of data-driven models for computer-aided synthesis planning (CASP) in the past decade. Here, we detail the newest version of ASKCOS, an open source software suite for synthesis planning that makes available several research advances in a freely available, practical tool. Four one-step retrosynthesis models form the basis of both interactive planning and automatic planning modes. Retrosynthetic planning is complemented by other modules for feasibility assessment and pathway evaluation, including reaction condition recommendation, reaction outcome prediction, and auxiliary capabilities such as solubility prediction and quantum mechanical descriptor prediction. ASKCOS has assisted hundreds of medicinal, synthetic, and process chemists in their day-to-day tasks, complementing expert decision making. It is our belief that CASP tools like ASKCOS are an important part of modern chemistry research, and that they offer ever-increasing utility and accessibility.

Debris disks, which consist of dust, planetesimals, planets, and gas, offer a unique window into the mineralogical composition of their parent bodies, especially during the critical phase of terrestrial planet formation spanning 10 to a few hundred million years. Observations from the $\textit{Spitzer}$ Space Telescope have unveiled thousands of debris disks, yet systematic studies remain scarce, let alone those with unsupervised clustering techniques. This study introduces $\texttt{CLUES}$ (CLustering UnsupErvised with Sequencer), a novel, non-parametric, fully-interpretable machine-learning spectral analysis tool designed to analyze and classify the spectral data of debris disks. $\texttt{CLUES}$ combines multiple unsupervised clustering methods with multi-scale distance measures to discern new groupings and trends, offering insights into compositional diversity and geophysical processes within these disks. Our analysis allows us to explore a vast parameter space in debris disk mineralogy and also offers broader applications in fields such as protoplanetary disks and solar system objects. This paper details the methodology, implementation, and initial results of $\texttt{CLUES}$, setting the stage for more detailed follow-up studies focusing on debris disk mineralogy and demographics., Comment: 23 pages, 16 figures, Accepted to ApJS, $\texttt{CLUES}$ software available on GitHub

The human MHC transplantation loci (HLA-A, -B, -C, -DPB1, -DQB1, -DRB1) are the most polymorphic in the human genome. It is generally accepted this polymorphism reflects a role in presenting pathogen-derived peptide to the adaptive immune system. Proposed mechanisms for the polymorphism such as negative frequency-dependent selection (NFDS) and heterozygote advantage (HA) focus on HLA alleles, not haplotypes. Here, we propose a model for the polymorphism in which infectious diseases impose independent density-dependent regulation on HLA haplotypes. More specifically, a complex pathogen environment drives extensive host polymorphism through a guild of HLA haplotypes that are specialised and show incomplete peptide recognition. Separation of haplotype guilds is maintained by limiting similarity. The outcome is a wide and stable range of haplotype densities at steady-state in which effective Fisher fitnesses are zero. Densities, and therefore frequencies, emerge theoretically as alternative measures of fitness. A catalogue of ranked frequencies is therefore one of ranked fitnesses. The model is supported by data from a range of sources including a Caucasian HLA dataset compiled by the US National Marrow Donor Program (NMDP). These provide evidence of positive selection on the top 350-2000 5-locus HLA haplotypes taken from an overall NMDP sample set of 10E5. High-fitness haplotypes drive the selection of 137 high-frequency alleles spread across the 5 HLA loci under consideration. These alleles demonstrate positive epistasis and pleiotropy in the formation of haplotypes. Allelic pleiotropy creates a network of highly inter-related HLA haplotypes that account for 97% of the census sample. We suggest this network has properties of a quasi-species and is itself under selection. We also suggest this is the origin of balancing selection in the HLA system., Comment: si45 pages, 16 figures

The quantum chromodynamics (QCD) phase diagram is key to answering open questions in physics, from states of matter in neutron stars to the early universe. However, classical simulations of QCD face significant computational barriers, such as the sign problem at finite matter densities. Quantum computing offers a promising solution to overcome these challenges. Here, we take an important step toward exploring the QCD phase diagram with quantum devices by preparing thermal states in one-dimensional non-Abelian gauge theories. We experimentally simulate the thermal states of SU(2) and SU(3) gauge theories at finite densities on a trapped-ion quantum computer using a variational method. This is achieved by introducing two features: Firstly, we add motional ancillae to the existing qubit register to efficiently prepare thermal probability distributions. Secondly, we introduce gauge-invariant measurements to enforce local gauge symmetries. This work marks the first lattice gauge theory quantum simulation of QCD at finite density and temperature for two and three colors, laying the foundation to explore QCD phenomena on quantum platforms., Comment: 20 pages, 10 figures

Non-split Real Tambara-Yamagami categories are a family of fusion categories over the real numbers that were recently introduced and classified by Plavnik, Sanford, and Sconce. We consider which of these categories admit braidings, and classify the resulting braided equivalence classes. We also prove some new results about the split real and split complex Tambara-Yamagami Categories., Comment: 42 pages. Comments welcome!

A key aspect of temporal domains is the ability to make predictions multiple time steps into the future, a process known as multi-step forecasting (MSF). At the core of this process is selecting a forecasting strategy, however, with no existing frameworks to map out the space of strategies, practitioners are left with ad-hoc methods for strategy selection. In this work, we propose Stratify, a parameterised framework that addresses multi-step forecasting, unifying existing strategies and introducing novel, improved strategies. We evaluate Stratify on 18 benchmark datasets, five function classes, and short to long forecast horizons (10, 20, 40, 80). In over 84% of 1080 experiments, novel strategies in Stratify improved performance compared to all existing ones. Importantly, we find that no single strategy consistently outperforms others in all task settings, highlighting the need for practitioners explore the Stratify space to carefully search and select forecasting strategies based on task-specific requirements. Our results are the most comprehensive benchmarking of known and novel forecasting strategies. We make code available to reproduce our results., Comment: 30 pages, 9 figures, journal

We define the Tannakian radical of a braided fusion category $\mathcal{C}$ as the intersection of its maximal Tannakian subcategories. The localization of $\mathcal{C}$ corresponding to the Tannakian radical, termed the mantle of $\mathcal{C}$, admits a canonical central extension that serves as a complete invariant of $\mathcal{C}$. The mantle has a trivial Tannakian radical, and we refer to braided fusion categories with this property as reductive. We investigate the properties and structure of reductive categories and prove several classification results., Comment: 31 pages, comments are welcome

The Majorana Demonstrator was an ultra-low-background experiment designed for neutrinoless double-beta decay ($0\nu\beta\beta$) investigation in $^{76}$Ge. Located at the Sanford Underground Research Facility in Lead, South Dakota, the Demonstrator utilized modular high-purity Ge detector arrays within shielded vacuum cryostats, operating deep underground. The arrays, with a capacity of up to 40.4 kg (27.2 kg enriched to $\sim 88\%$ in $^{76}$Ge), have accumulated the full data set, totaling 64.5 kg yr of enriched active exposure and 27.4 kg yr of exposure for natural detectors. Our updated search improves previously explored three-nucleon decay modes in Ge isotopes, setting new half-life limits of $1.27\times10^{26}$ years (90\% confidence level) for $^{76}$Ge($ppp$) $\rightarrow$ $^{73}$Cu e$^+\pi^+\pi^+$ and $^{76}$Ge($ppn$) $\rightarrow$ $^{73}$Zn e$^+\pi^+$. The half-life limit for the invisible tri-proton decay mode of $^{76}$Ge is found to be $1.4\times10^{25}$ yr. Furthermore, we have updated limits for corresponding multi-nucleon decays.

Here we present a derivation of the hierarchical equations of motion (HEOM) for an overdamped Lorentz-Drude environment containing an undamped oscillator (LDUO-HEOM). The new approach avoids the artifact of superfluous damping inherent in underdamped spectral densities. We show that the new HEOM is a useful model for intramolecular vibrations in condensed phase molecules.

This Letter presents an investigation of low-energy electron-neutrino interactions in the Fermilab Booster Neutrino Beam by the MicroBooNE experiment, motivated by the excess of electron-neutrino-like events observed by the MiniBooNE experiment. This is the first measurement to use data from all five years of operation of the MicroBooNE experiment, corresponding to an exposure of $1.11\times 10^{21}$ protons on target, a $70\%$ increase on past results. Two samples of electron neutrino interactions without visible pions are used, one with visible protons and one without any visible protons. MicroBooNE data is compared to two empirical models that modify the predicted rate of electron-neutrino interactions in different variables in the simulation to match the unfolded MiniBooNE low energy excess. In the first model, this unfolding is performed as a function of electron neutrino energy, while the second model aims to match the observed shower energy and angle distributions of the MiniBooNE excess. This measurement excludes an electron-like interpretation of the MiniBooNE excess based on these models at $> 99\%$ CL$_\mathrm{s}$ in all kinematic variables., Comment: 8 pages, 5 figures, 1 table

The increasing deployment of AI models in critical applications has exposed them to significant risks from adversarial attacks. While adversarial vulnerabilities in 2D vision models have been extensively studied, the threat landscape for 3D generative models, such as Neural Radiance Fields (NeRF), remains underexplored. This work introduces \textit{AdvIRL}, a novel framework for crafting adversarial NeRF models using Instant Neural Graphics Primitives (Instant-NGP) and Reinforcement Learning. Unlike prior methods, \textit{AdvIRL} generates adversarial noise that remains robust under diverse 3D transformations, including rotations and scaling, enabling effective black-box attacks in real-world scenarios. Our approach is validated across a wide range of scenes, from small objects (e.g., bananas) to large environments (e.g., lighthouses). Notably, targeted attacks achieved high-confidence misclassifications, such as labeling a banana as a slug and a truck as a cannon, demonstrating the practical risks posed by adversarial NeRFs. Beyond attacking, \textit{AdvIRL}-generated adversarial models can serve as adversarial training data to enhance the robustness of vision systems. The implementation of \textit{AdvIRL} is publicly available at \url{https://github.com/Tommy-Nguyen-cpu/AdvIRL/tree/MultiView-Clean}, ensuring reproducibility and facilitating future research., Comment: Accepted to The AAAI-25 Workshop on Artificial Intelligence for Cyber Security (AICS)

Adversarial attacks pose significant challenges in 3D object recognition, especially in scenarios involving multi-view analysis where objects can be observed from varying angles. This paper introduces View-Invariant Adversarial Perturbations (VIAP), a novel method for crafting robust adversarial examples that remain effective across multiple viewpoints. Unlike traditional methods, VIAP enables targeted attacks capable of manipulating recognition systems to classify objects as specific, pre-determined labels, all while using a single universal perturbation. Leveraging a dataset of 1,210 images across 121 diverse rendered 3D objects, we demonstrate the effectiveness of VIAP in both targeted and untargeted settings. Our untargeted perturbations successfully generate a singular adversarial noise robust to 3D transformations, while targeted attacks achieve exceptional results, with top-1 accuracies exceeding 95% across various epsilon values. These findings highlight VIAPs potential for real-world applications, such as testing the robustness of 3D recognition systems. The proposed method sets a new benchmark for view-invariant adversarial robustness, advancing the field of adversarial machine learning for 3D object recognition., Comment: Accepted to AAAI-25 Workshop on Artificial Intelligence for Cyber Security (AICS): http://aics.site/AICS2025/index.html

The development of accurate medical image classification models is often constrained by privacy concerns and data scarcity for certain conditions, leading to small and imbalanced datasets. To address these limitations, this study explores the use of generative models, such as Denoising Diffusion Probabilistic Models (DDPM) and Progressive Growing Generative Adversarial Networks (PGGANs), for dataset augmentation. The research introduces a framework to assess the impact of synthetic images generated by DDPM and PGGANs on the performance of four models: a custom CNN, Untrained VGG16, Pretrained VGG16, and Pretrained ResNet50. Experiments were conducted using Random Sampling and Greedy K Sampling to create small, imbalanced datasets. The synthetic images were evaluated using Frechet Inception Distance (FID) and compared to original datasets through classification metrics. The results show that DDPM consistently generated more realistic images with lower FID scores and significantly outperformed PGGANs in improving classification metrics across all models and datasets. Incorporating DDPM-generated images into the original datasets increased accuracy by up to 6%, enhancing model robustness and stability, particularly in imbalanced scenarios. Random Sampling demonstrated superior stability, while Greedy K Sampling offered diversity at the cost of higher FID scores. This study highlights the efficacy of DDPM in augmenting small, imbalanced medical image datasets, improving model performance by balancing the dataset and expanding its size.

Emissive organic radicals are currently of great interest for their potential use in the next generation of highly efficient organic light emitting diode (OLED) devices and as molecular qubits. However, simulating their optoelectronic properties is challenging, largely due to spin-contamination and the multireference character of their excited states. Here we present a data-driven approach where, for the first time, the excited electronic states of organic radicals are learned directly from experimental excited state data, using a much smaller amount of data than required by typical Machine Learning. We adopt ExROPPP, a fast and spin-pure semiempirical method for calculation of excited states of radicals, as a surrogate physical model for which we learn the optimal set of parameters. We train the model on 81 previously published radicals and find that the trained model is a huge improvement over ExROPPP with literature parameters, giving RMS and mean absolute errors of 0.24 and 0.16 eV respectively with R$^2$ and SRCC of 0.86 and 0.88 respectively. We synthesise four new radicals and validate the model on their spectra, finding even lower errors and similar correlation as for the testing set. This model paves the way for high throughput discovery of next-generation radical based optoelectronics.

Distillation in lattice QCD is a smearing method that uses the lowest eigenvectors of the spatial Laplacian to construct a subspace in which the Dirac operator can be fully inverted. However, local multiquark interpolators are expensive in this framework because the cost of the contractions scales with a high power of the number of Laplacian eigenvectors. To address this, a position-space sampling method within distillation is presented that avoids this cost scaling. Our simulations show that this method works well for meson operators, but also for local tetraquark operators. In a preliminary study, we investigate the relevance of the latter for the ground state energy of the $T_{cc}(3875)^+$ tetraquark. There we find a downward shift in the lowest level when local tetraquark operators are added to a basis of bilocal scattering operators in the variational method. However, this shift is small compared to the error of the energy., Comment: 10 pages, 3 figures. Talk presented at the 41st International Symposium on Lattice Field Theory (LATTICE2024), 28 July - 3 August 2024, Liverpool, UK

The growing number of satellite constellations in low Earth orbit (LEO) enhances global communications and Earth observation, and support of space commerce is a high priority of many governments. At the same time, the proliferation of satellites in LEO has negative effects on astronomical observations and research, and the preservation of the dark and quiet sky. These satellite constellations reflect sunlight onto optical telescopes, and their radio emission impacts radio observatories, jeopardising our access to essential scientific discoveries through astronomy. The changing visual appearance of the sky also impacts our cultural heritage and environment. Both ground-based observatories and space-based telescopes in LEO are affected, and there are no places on Earth that can escape the effects of satellite constellations given their global nature. The minimally disturbed dark and radio-quiet sky is crucial for conducting fundamental research in astronomy and important public services such as planetary defence, technology development, and high-precision geolocation. Some aspects of satellite deployment and operation are regulated by States and intergovernmental organisations. While regulatory agencies in some States have started to require operators to coordinate with their national astronomy agencies over impacts, mitigation of the impact of space objects on astronomical activities is not sufficiently regulated. To address this issue, the CPS urges States and the international community to take steps to protect the dark and quiet sky as specified in this paper., Comment: This position paper was developed by the IAU Centre for the Protection of the Dark and Quiet Sky from Satellite Constellation Interference (CPS). It can also be downloaded at the CPS website at https://cps.iau.org/news/cps-urges-action-in-first-recommendations-paper/

The molecular Kennicutt-Schmidt (mK-S) Law has been key for understanding star formation (SF) in galaxies across all redshifts. However, recent sub-kpc observations of nearby galaxies reveal deviations from the nearly unity slope (N) obtained with disk-averaged measurements. We study SF and molecular gas (MG) distribution in the early-stage luminous infrared galaxy merger Arp240 (NGC5257-8). Using VLA radio continuum (RC) and ALMA CO(2-1) observations with a uniform grid analysis, we estimate SF rates and MG surface densities ($\Sigma_{\mathrm{SFR}}$ and $\Sigma_{\mathrm{H_2}}$, respectively). In Arp 240, N is sub-linear at 0.52 $\pm$ 0.17. For NGC 5257 and NGC 5258, N is 0.52 $\pm$ 0.16 and 0.75 $\pm$ 0.15, respectively. We identify two SF regimes: high surface brightness (HSB) regions in RC with N $\sim$1, and low surface brightness (LSB) regions with shallow N (ranging 0.15 $\pm$ 0.09 to 0.48 $\pm$ 0.04). Median CO(2-1) linewidth and MG turbulent pressure (P$_{\mathrm{turb}}$) are 25 km s$^{-1}$ and 9 $\times$10$^{5}$ K cm$^{-3}$. No significant correlation was found between $\Sigma_{\mathrm{SFR}}$ and CO(2-1) linewidth. However, $\Sigma_{\mathrm{SFR}}$ correlates with P$_{\mathrm{turb}}$, particularly in HSB regions ($\rho >$0.60). In contrast, SF efficiency moderately anti-correlates with P$_{\mathrm{turb}}$ in LSB regions but shows no correlation in HSB regions. Additionally, we identify regions where peaks in SF and MG are decoupled, yielding a shallow N ($\leq$ 0.28 $\pm$ 0.18). Overall, the range of N reflects distinct physical properties and distribution of both the SF and MG, which can be masked by disk-averaged measurements.

We report on a search for millicharged particles (mCPs) produced in cosmic ray proton atmospheric interactions using data collected during the first science run of the LUX-ZEPLIN experiment. The mCPs produced by two processes -- meson decay and proton bremsstrahlung -- are considered in this study. This search utilized a novel signature unique to liquid xenon (LXe) time projection chambers (TPCs), allowing sensitivity to mCPs with masses ranging from 10 to 1000 MeV/c$^2$ and fractional charges between 0.001 and 0.02 of the electron charge e. With an exposure of 60 live days and a 5.5 tonne fiducial mass, we observed no significant excess over background. This represents the first experimental search for atmospheric mCPs and the first search for mCPs using an underground LXe experiment.

We consider weakly non-linear gravitational perturbations of a near-extremal Kerr black hole governed by the second order vacuum Einstein equation. Using the GHZ formalism [Green et al., Class. Quant. Grav. 7(7):075001, 2020], these are parameterized by a Hertz potential. We make an ansatz for the Hertz potential as a series of zero-damped quasinormal modes with time-dependent amplitudes, and derive a non-linear dynamical system for them. We find that our dynamical system has a time-independent solution within the near horizon scaling limit. This equilibrium solution is supported on axisymmetric modes, with amplitudes scaling as $c_\ell \sim C^{\rm low} 2^{-\ell/2} \ell^{-\frac{7}{2}}$ for large polar angular momentum mode number $\ell$, where $C^{\rm low}$ is a cumulative amplitude of the low $\ell$ modes. We interpret our result as evidence that the dynamical evolution will approach, for a parametrically long time as extremality is approached, a distribution of mode amplitudes dyadically exponentially suppressed in $\ell$, hence as the endpoint of an inverse cascade. It is reminiscent of weather-like phenomena in certain models of atmospheric dynamics of rotating bodies. During the timescale considered, the decay of the QNMs themselves plays no role given their parametrically long half-life. Hence, our result is due entirely to weakly non-linear effects., Comment: 51 pages, 1 figure, RevTex4-2

The predictions of inflation are usually defined in terms of equal time in-in correlation functions in an accelerating cosmological background. These same observables exist for quantum field theory in other spacetimes, including flat space. In this paper, we will explore how the Wilsonian renormalization group (RG) and effective field theory (EFT) apply to these observables in both flat and de Sitter space. Specifically, we show that matching the short- and long-distance calculations requires additional terms localized at the time of the measurement that are not captured by the effective action of the EFT. These additional terms only correct the local and semi-local terms in the EFT correlators. In flat space, we give an explicit demonstration by matching in-in correlators of light scalars interacting with a heavy field with the EFT result. We then show how these additional terms arise generically via exact RG. We also compare these explicit results in flat space with the corresponding theory in de Sitter and show that the local terms typically redshift away. Our results are closely related to momentum space entanglement that arises from tracing over short-wavelength modes., Comment: 45 pages

Stellar-mass black holes descend from high-mass stars, most of which had stellar binary companions. However, the number of those binary systems that survive the binary evolution and black hole formation is uncertain by multiple orders of magnitude. The survival rate is particularly uncertain for massive stars with low-mass companions, which are thought to be the progenitors of most black hole X-ray binaries. We present a search for close black hole companions (separations less than 20 solar radii) to AFGK-type stars in TESS, i.e. the non-accreting counterparts to and progenitors of low-mass X-ray binaries. Such black holes can be detected by the tidally induced ellipsoidal deformation of the visible star, and the ensuing photometric light-curve variations. From an initial sample of 4.7 million TESS stars, we have selected 457 candidates for such variations. However, spectroscopic followup of 251 of them shows that none are consistent with a close black hole companion. On the basis of this non-detection, we determine (2 $\sigma$ confidence) that fewer than one in $10^5$ Solar-type stars in the Solar neighbourhood host a short-period black hole companion. This upper limit is in tension with a number of ``optimistic'' population models in the literature that predict short-period black hole companions around one in $10^{4-5}$ stars. Our limits are still consistent with other models that predict only a few in $10^{7-8}$., Comment: 14 pages, 12 figures. Submitted to A&A. Comments welcome. Long forms of Tables 3 and 4 are included as FITS files in the Arxiv zip folder

Solvation free energy is an important design parameter in reaction kinetics and separation processes, making it a critical property to predict during process development. In previous research, directed message passing neural networks (D-MPNN) have successfully been used to predict solvation free energies and enthalpies in organic solvents. However, solvent mixtures provide greater flexibility for optimizing solvent interactions than monosolvents. This work aims to extend our previous models to mixtures. To handle mixtures in a permutation invariant manner we propose a pooling function; MolPool. With this pooling function, the machine learning models can learn and predict properties for an arbitrary number of molecules. The novel SolProp-mix software that applies MolPool to D-MPNN was compared to state-of-the-art architectures for predicting mixture properties and validated with our new database of COSMOtherm calculations; BinarySolv-QM. To improve predictions towards experimental accuracy, the network was then fine-tuned on experimental data in monosolvents. To demonstrate the benefit of this transfer learning methodology, experimental datasets of solvation free energies in binary (BinarySolv-Exp) and ternary (TernarySolv-Exp) solvent mixtures were compiled from data on vapor-liquid equilibria and activity coefficients. The neural network performed better than COSMOtherm calculations with an MAE of 0.25 kcal/mol and an RMSE of 0.37 kcal/mol for non-aqueous mixed solvents. Additionally, the ability to capture trends for a varying mixture composition was validated successfully. Our model's ability to accurately predict mixture properties from the combination of in silico data and pure component experimental data is promising given the scarcity of experimental data for mixtures in many fields.