Search

We present the results of a search for gravitational-wave transients associated with core-collapse supernova SN 2023ixf, which was observed in the galaxy Messier 101 via optical emission on 2023 May 19th, during the LIGO-Virgo-KAGRA 15th Engineering Run. We define a five-day on-source window during which an accompanying gravitational-wave signal may have occurred. No gravitational waves have been identified in data when at least two gravitational-wave observatories were operating, which covered $\sim 14\%$ of this five-day window. We report the search detection efficiency for various possible gravitational-wave emission models. Considering the distance to M101 (6.7 Mpc), we derive constraints on the gravitational-wave emission mechanism of core-collapse supernovae across a broad frequency spectrum, ranging from 50 Hz to 2 kHz where we assume the GW emission occurred when coincident data are available in the on-source window. Considering an ellipsoid model for a rotating proto-neutron star, our search is sensitive to gravitational-wave energy $1 \times 10^{-5} M_{\odot} c^2$ and luminosity $4 \times 10^{-5} M_{\odot} c^2/\text{s}$ for a source emitting at 50 Hz. These constraints are around an order of magnitude more stringent than those obtained so far with gravitational-wave data. The constraint on the ellipticity of the proto-neutron star that is formed is as low as $1.04$, at frequencies above $1200$ Hz, surpassing results from SN 2019ejj., Comment: Main paper: 6 pages, 4 figures and 1 table. Total with appendices: 20 pages, 4 figures, and 1 table

The magnetar SGR 1935+2154 is the only known Galactic source of fast radio bursts (FRBs). FRBs from SGR 1935+2154 were first detected by CHIME/FRB and STARE2 in 2020 April, after the conclusion of the LIGO, Virgo, and KAGRA Collaborations' O3 observing run. Here we analyze four periods of gravitational wave (GW) data from the GEO600 detector coincident with four periods of FRB activity detected by CHIME/FRB, as well as X-ray glitches and X-ray bursts detected by NICER and NuSTAR close to the time of one of the FRBs. We do not detect any significant GW emission from any of the events. Instead, using a short-duration GW search (for bursts $\leq$ 1 s) we derive 50\% (90\%) upper limits of $10^{48}$ ($10^{49}$) erg for GWs at 300 Hz and $10^{49}$ ($10^{50}$) erg at 2 kHz, and constrain the GW-to-radio energy ratio to $\leq 10^{14} - 10^{16}$. We also derive upper limits from a long-duration search for bursts with durations between 1 and 10 s. These represent the strictest upper limits on concurrent GW emission from FRBs., Comment: 15 pages of text including references, 4 figures, 5 tables

Su-Schrieffer-Heeger (SSH)-like electron-phonon (e-ph) interactions can drive the formation of light (bi)polarons and several novel states of matter. It is, therefore, prudent to develop experimental protocols for identifying such couplings in real materials and quantifying their strength. Here, we investigate how resonant inelastic x-ray scattering (RIXS) probes e-ph interactions in the one-dimensional half-filled Hubbard-SSH model with onsite phonons. Using the density matrix renormalization group method, we compute the full RIXS response and find that the lattice excitations generated during the scattering process inevitably couple to the system's charge and magnetic sectors, resulting in combined multi-particle excitations that cannot be easily disentangled from one another. While this aspect complicates the interpretation of RIXS experiments, we outline how it can be leveraged to identify and quantify SSH-like interactions in quantum materials.

An emerging application of resonant inelastic x-ray scattering (RIXS) is the study of lattice excitations and electron-phonon ($e$-ph) interactions in quantum materials. Despite the growing importance of this area of research, the community lacks a complete understanding of how the RIXS process excites the lattice and how these excitations encode information about the $e$-ph interactions. Here, we present a detailed study of the RIXS spectra of the Hubbard-Holstein model defined on extended one-dimensional lattices. Using the density matrix renormalization group (DMRG) method, we compute the RIXS response while treating the electron mobility, many-body interactions, and core-hole interactions on an equal footing. The predicted spectra exhibit notable differences from those obtained using the commonly adopted Lang-Firsov models, with important implications for analyzing past and future experiments. Our results provide a deeper understanding of how RIXS probes $e$-ph interactions and set the stage for a more realistic analysis of future experiments.

Understanding and enhancing student engagement through digital platforms is critical in higher education. This study introduces a methodology for quantifying engagement across an entire module using virtual learning environment (VLE) activity log data. Using study session frequency, immediacy, and diversity, we create a cumulative engagement metric and model it against weekly VLE interactions with resources to identify critical periods and resources predictive of student engagement. In a case study of a computing module at University College London's Department of Statistical Science, we further examine how delivery methods (online, hybrid, in-person) impact student behaviour. Across nine regression models, we validate the consistency of the random forest model and highlight the interpretive strengths of generalised additive models for analysing engagement patterns. Results show weekly VLE clicks as reliable engagement predictors, with early weeks and the first assessment period being key. However, the impact of delivery methods on engagement is inconclusive due to inconsistencies across models. These findings support early intervention strategies to assist students at risk of disengagement. This work contributes to learning analytics research by proposing a refined VLE-based engagement metric and advancing data-driven teaching strategies in higher education., Comment: 20 pages, 6 figures

Detecting a pulsar associated with a supernova remnant (SNR) and/or pulsar wind nebula (PWN) is crucial for unraveling its formation history and pulsar wind dynamics, yet the association with a radio pulsar is observed only in a small fraction of known SNRs and PWNe. In this paper, we report the discovery of a young pulsar J1631$-$4722, associated with the Galactic SNR G336.7$+$0.5 using Murriyang, CSIRO's Parkes radio telescope. It is also potentially associated with a PWN revealed by the Rapid ASKAP (Australian Square Kilometre Array Pathfinder) Continuum Survey (RACS). This 118 ms pulsar has a high dispersion measure of 873 $\mathrm{pc\,cm^{-3}}$ and a rotation measure of $-$1004 $\mathrm{rad\,m^{-2}}$. Because of such a high DM, at frequencies below 2 GHz, the pulse profile is significantly scattered, making it effectively undetectable in previous pulsar surveys at $\sim$1.4 GHz. Follow-up observations yield a period derivative of $\dot{P} = 3.6 \times 10^{-15}$, implying a characteristic age, $\tau_{c} = 33\,$kyr, and spin-down luminosity, $\dot{E} = 1.3\times10^{36}\,$erg$\,s^{-1}$. PSR$\,$J1631$-$4722, with its high spin-down luminosity and potential link to a PWN, stands out as a promising source of the high-energy $\gamma$-ray emission observed in the region.

HI-rich absorbers seen within quasar spectra contain the bulk of neutral gas in the Universe. However, the spatial extent of these reservoirs are not extensively studied due to the pencil beam nature of quasar sightlines. Using two giant gravitational arc fields (at redshifts 1.17 and 2.06) as 2D background sources with known strong MgII absorption observed with the MUSE integral field spectrograph (IFS), we investigated whether spatially mapped MgII absorption can predict the presence of strong HI systems, and determine both the physical extent and HI mass of the two absorbing systems. We created a simple model of an ensemble of gas clouds in order to simultaneously predict the HI column density and gas covering fraction of HI-rich absorbers based on observations of the MgII rest-frame equivalent width in IFS spaxels. We first test the model on the field with HI observations already available from the literature, finding that we can recover HI column densities consistent with the previous estimates (although with large uncertainties). We then use our framework to simultaneously predict the gas covering fraction, HI column density and total HI mass ($M_{\rm{HI}}$) for both fields. We find that both of the observed strong systems have a covering fraction of $\approx70$% and are likely damped Lyman $\alpha$ systems (DLAs) with $M_{\rm{HI}}>10^9\ M_{\odot}$. Our model shows that the typical MgII metrics used in the literature to identify the presence of DLAs are sensitive to the gas covering fraction. However, these MgII metrics are still sensitive to strong HI, and can be still applied to absorbers towards gravitational arcs or other spatially extended background sources. Based on our results, we speculate that the two strong absorbers are likely representative of a neutral inner circumgalactic medium and are a significant reservoir of fuel for star formation within the host galaxies., Comment: 15 pages, 6 Figures, 3 appendices. Accepted for publication on Astronomy & Astrophysics

Shocked POst-starburst Galaxies (SPOGs) exhibit both emission lines suggestive of shock-heated gas and post-starburst-like stellar absorption, resulting in a unique subset for galaxy evolution studies. We have observed 77 galaxies that fulfilled the SPOGs criteria selection using the DeVeny Spectrograph on the Lowell Discovery Telescope. Our long-slit minor axis spectra detect H$\alpha$ and [O III] in some SPOGs out to 6 kpc above the galactic plane. We find extraplanar ionized gas in 31 targets of our sample overall. Using their internal and external kinematics, we argue that 22 galaxies host outflows with ionized gas masses ranging from $10^2 M_{\odot}$ to $10^5 M_{\odot}$. The rest are likely extended diffuse ionized gas. A positive correlation exists between AGN luminosity and the extraplanar gas extent, velocity dispersion, and mass$\unicode{x2013}\unicode{x2013}$suggesting that the AGN may indeed drive the outflows detected in AGN hosts. The low masses of the extraplanar gas suggest that these outflows are not depleting each galaxy's gas reserves. The outflows, therefore, are not likely a significant quenching mechanism in these SPOGs., Comment: 27 pages, 11 figures, ApJ accepted

We have conducted a GPU accelerated reprocessing of $\sim 87\%$ of the archival data from the High Time Resolution Universe South Low Latitude (HTRU-S LowLat) pulsar survey by implementing a pulsar search pipeline that was previously used to reprocess the Parkes Multibeam pulsar survey (PMPS). We coherently searched the full 72-min observations of the survey with an acceleration search range up to $|50|\, \rm m\,s^{-2}$, which is most sensitive to binary pulsars experiencing nearly constant acceleration during 72 minutes of their orbital period. Here we report the discovery of 71 pulsars, including 6 millisecond pulsars (MSPs) of which five are in binary systems, and seven pulsars with very high dispersion measures (DM $>800 \, \rm pc \, cm^{-3}$). These pulsar discoveries largely arose by folding candidates to a much lower spectral signal-to-noise ratio than previous surveys, and exploiting the coherence of folding over the incoherent summing of the Fourier components to discover new pulsars as well as candidate classification techniques. We show that these pulsars could be fainter and on average more distant as compared to both the previously reported 100 HTRU-S LowLat pulsars and background pulsar population in the survey region. We have assessed the effectiveness of our search method and the overall pulsar yield of the survey. We show that through this reprocessing we have achieved the expected survey goals including the predicted number of pulsars in the survey region and discuss the major causes as to why these pulsars were missed in previous processings of the survey., Comment: 18 Pages, 12 figures, 9 tables. Accepted for publication in MNRAS

Context: The clusters Abell 3017 and Abell 3016 are located within a large-scale filament. A prominent X-ray bridge has been detected connecting the two clusters and a potential galaxy group between them. Aims: The aim of this work is to investigate the existence of a radio bridge in the filament between Abell 3017 and Abell 3016, to explore other diffuse radio structures within this system, and to investigate the origins of these diffuse radio emission. Methods: We analyzed MeerKAT L-band data to study the morphology and spectra of the diffuse radio structures in Abell 3016-Abell 3017. X-ray imaging and spectral analysis were carried out with archival Chandra and XMM-Newton data. Additionally, correlations between radio ($I_R$) and X-ray surface brightness ($I_X$) were generated to explore the connections between thermal and non-thermal components in the diffuse radio emission. Results: We detected a faint radio bridge with an average surface brightness of $\sim 0.1~\mu\rm Jy~arcsec^{-2}$ at 1280 MHz using MeerKAT. It connects Abell 3017 with a potential galaxy group and extends towards Abell 3016, aligning with the X-ray bridge. A high X-ray temperature of $7.09 \pm 0.54$ keV detected in the bridge region suggests an interaction between Abell 3017 and the group. In Abell 3017, we identified two distinct components of diffuse radio emission: a radio mini-halo and an outer radio halo with a northern extension (N-extension hereafter). The radio surface brightness profile of Abell 3017 shows a steep inner component consistent with other mini-halos, and a faint outer component likely linked to an infalling subcluster. The $I_{\rm R}-I_{\rm X}$ diagram indicates superlinear and sublinear correlations for the mini-halo and N-extension, respectively., Comment: 18 pages, 14 figures, 4 tables; submitted to A&A; abstract shortened due to arXiv character limit; comments are welcome

Hot sub-luminous stars represent a population of stripped and evolved red giants located at the Extreme Horizontal Branch (EHB). Since they exhibit a wide range of variability due to pulsations or binary interactions, unveiling their intrinsic and extrinsic variability is crucial for understanding the physical processes responsible for their formation. In the Hertzsprung-Russell diagram, they overlap with interacting binaries such as Cataclysmic Variables (CVs). By leveraging cutting-edge clustering algorithm tools, we investigate the variability of 1,576 hot subdwarf variable candidates using comprehensive data from Gaia DR3 multi-epoch photometry and Transiting Exoplanet Survey Satellite (TESS) observations. We present a novel approach that utilises the t-distributed stochastic neighbor embedding (t-SNE) and the Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction algorithms to facilitate the identification and classification of different populations of variable hot subdwarfs and Cataclysmic Variables in a large dataset. In addition to the Gaia time-series statistics table, we adopt extra statistical features that enhance the performance of the algorithms. The clustering results lead to the identification of 85 new hot subdwarf variables based on Gaia and TESS lightcurves and 108 new variables based on Gaia lightcurves alone, including reflection-effect systems, HW Vir, ellipsoidal variables, and high-amplitude pulsating variables. A significant number of known Cataclysmic Variables (140) distinctively cluster in the 2-D feature space among an additional 152 objects that we consider new Cataclysmic Variable candidates. This study paves the way for more efficient and comprehensive analyses of stellar variability from both ground and space-based observations, as well as the application of machine learning classifications of variable candidates in large surveys., Comment: Resubmitted to Astronomy & Astrophyiscs, after having taken into account the positive minor referee comments; 11 pages, 9 figures, 1 table, 1 appendix (3 additional figures, 10 additional tables)

Purpose: To explore best-practice approaches for generating synthetic chest X-ray images and augmenting medical imaging datasets to optimize the performance of deep learning models in downstream tasks like classification and segmentation. Materials and Methods: We utilized a latent diffusion model to condition the generation of synthetic chest X-rays on text prompts and/or segmentation masks. We explored methods like using a proxy model and using radiologist feedback to improve the quality of synthetic data. These synthetic images were then generated from relevant disease information or geometrically transformed segmentation masks and added to ground truth training set images from the CheXpert, CANDID-PTX, SIIM, and RSNA Pneumonia datasets to measure improvements in classification and segmentation model performance on the test sets. F1 and Dice scores were used to evaluate classification and segmentation respectively. One-tailed t-tests with Bonferroni correction assessed the statistical significance of performance improvements with synthetic data. Results: Across all experiments, the synthetic data we generated resulted in a maximum mean classification F1 score improvement of 0.150453 (CI: 0.099108-0.201798; P=0.0031) compared to using only real data. For segmentation, the maximum Dice score improvement was 0.14575 (CI: 0.108267-0.183233; P=0.0064). Conclusion: Best practices for generating synthetic chest X-ray images for downstream tasks include conditioning on single-disease labels or geometrically transformed segmentation masks, as well as potentially using proxy modeling for fine-tuning such generations.

We demonstrate the impact of a generic zero-free region and zero-density estimate on the error term in the prime number theorem. Consequently, we are able to improve upon previous work of Pintz and provide an essentially optimal error term for some choices of the zero-free region. As an example, we show that if there are no zeros $\rho=\beta+it$ of $\zeta(s)$ for $$\beta>1-\frac{1}{c(\log t)^{2/3}(\log\log t)^{1/3}},$$ then $$\frac{|\psi(x)-x|}{x}\ll\exp(-\omega(x))\frac{(\log x)^9}{(\log\log x)^3},$$ where $\psi(x)$ is the Chebyshev prime-counting function, and $$\omega(x)=\left(\frac{5^6}{2^2\cdot 3^4\cdot c^3}\right)^{1/5}\frac{(\log x)^{3/5}}{(\log\log x)^{1/5}}.$$ This improves upon the best known error term for the prime number theorem, previously given by $$\frac{|\psi(x)-x|}{x}\ll_{\varepsilon}\exp(-(1-\varepsilon)\omega(x))$$ for any $\varepsilon>0$., Comment: 8 pages

Parameter inference is essential when interpreting observational data using mathematical models. Standard inference methods for differential equation models typically rely on obtaining repeated numerical solutions of the differential equation(s). Recent results have explored how numerical truncation error can have major, detrimental, and sometimes hidden impacts on likelihood-based inference by introducing false local maxima into the log-likelihood function. We present a straightforward approach for inference that eliminates the need for solving the underlying differential equations, thereby completely avoiding the impact of truncation error. Open-access Jupyter notebooks, available on GitHub, allow others to implement this method for a broad class of widely-used models to interpret biological data., Comment: 11 pages, 2 figures

Adiabatic quantum-flux-parametron (AQFP) logic is a proven energy-efficient superconductor technology for various applications. To address the scalability challenges, we investigated AQFP shift registers with the AQFP footprint area reduced by 25% with respect to prior work and with more than 2x denser overall designs obtained by eliminating the previously used free space between the AQFPs. We also investigated AQFP cells with different designs of flux trapping moats in the superconducting ground plane as well as compact AQFP cells that took advantage of the smaller feature sizes available in the new fabrication process, SFQ5ee+, at MIT Lincoln Laboratory. This new process features nine planarized Nb layers with a 0.25 $\mu$m minimum linewidth. The fabricated circuits were tested in a liquid He probe and in a closed-cycle cryocooler using a controlled cooling rate through the superconducting critical temperature. Using multiple thermal cycles, we investigated flux trapping in the dense AQFP shift registers as well as in the registers using the old (sparse) AQFP designs at two levels of the residual magnetic field, about 0.53 $\mu$T and about 1.2 $\mu$T. The sparse designs demonstrated 95% to almost 100% probability of operation after the cooldown and very wide operation margins, although the flux trapping probability was increasing with circuit complexities. The margins were similarly wide in the newer dense designs, but flux trapping probability that rendered the registers nonoperational was significantly, by an order of magnitude, higher in the denser circuits and was also very sensitive to the moats' shape and location. Our findings indicate that AQFP circuits are amendable to increasing the scale of integration and further densification, but a careful moat design and optimization are required to reduce flux trapping effects in the dense AQFP circuits., Comment: 5 pages, 10 figures, 2 tables, 18 references. Presented at Applied Superconductivity Conference, ASC2024, 1-6 September 2024, Salt Lake City, UT, USA

Using the electrostatic analogy, we derive an exact formula for the limiting Yang-Lee zero distribution in the random allocation model of general weights. This exhibits a real-space condensation phase transition, which is induced by a pressure change. The exact solution allows one to read off the scaling of the density of zeros at the critical point and the angle at which locus of zeros hits the critical point. Since the order of the phase transition and critical exponents can be tuned with a single parameter for several families of weights, the model provides a useful testing ground for verifying various relations between the distribution of zeros and the critical behavior, as well as for exploring the behavior of physical quantities in the mesoscopic regime, i.e., systems of large but finite size. The main result is that asymptotically the Yang-Lee zeros are images of a conformal mapping, given by the generating function for the weights, of uniformly distributed complex phases.

PSR B1259-63 is a gamma-ray binary system with a 48 ms radio pulsar orbiting around an O9.5Ve star, LS 2883, in a highly eccentric ~3.4 yr long orbit. Close to the periastron the system is detected from radio up to the TeV energies due to the interaction of LS 2883 and pulsar's outflows. The observations of last 4 periastra passages taken in 2010-2021 demonstrate periastron to periastron variability at all wavelength, probably linked to the state of the decretion disk. In this paper we present the results of our optical, radio and X-ray observational campaigns on PSR B1259-63 performed in 2024 accompanied with the analysis of the publicly available GeV FERMI/LAT data. We show that this periastron passage was characterised by the early flaring of X-rays before the periastron passage and GeV emission after the periastron passage, which can be explained by a larger size of the decretion disk as supported by the optical observations. The structure of the GeV flare is also in agreement with the disruption of the large dense disk. The possible X-ray/radio correlation was observed only during the post-periastron rise of X-ray and radio emission., Comment: accepted to MNRAS

Can we understand and predict the evolutionary pathways by which bacteria acquire multi-drug resistance (MDR)? These questions have substantial potential impact in basic biology and in applied approaches to address the global health challenge of antimicrobial resistance (AMR). Here, we review how a class of machine learning approaches called evolutionary accumulation modelling (EvAM) may help reveal these dynamics using genetic and/or phenotypic AMR datasets, without requiring longitudinal sampling. These approaches are well-established in cancer progression and evolutionary biology, but currently less used in AMR research. We discuss how EvAM can learn the evolutionary pathways by which drug resistances and AMR features are acquired as pathogens evolve, predict next evolutionary steps, identify influences between AMR features, and explore differences in MDR evolution between regions, demographics, and more. We demonstrate a case study on MDR evolution in Mycobacterium tuberculosis and discuss the strengths and weaknesses of these approaches, providing links to some approaches for implementation.

After over three decades of unsuccessful attempts, we report the first detection of molecular gas emission in Malin 1, the largest spiral galaxy observed to date, and one of the most iconic giant low surface brightness galaxies. Using ALMA, we detect significant $^{12}$CO(J=1-0) emission in the galaxy's central region and tentatively identify CO emission across three regions on the disc. These observations allow for a better estimate of the H$_2$ mass and molecular gas mass surface density, both of which are remarkably low given the galaxy's scale. By integrating data on its HI mass, we derive a very low molecular-to-atomic gas mass ratio. Overall, our results highlight the minimal presence of molecular gas in Malin 1, contrasting sharply with its extensive, homogeneous atomic gas reservoir. For the first time, we position Malin 1 on the Kennicutt-Schmidt (K-S) diagram, where it falls below the main sequence for normal spirals, consistent with previous upper limits but now with more accurate figures. These findings are crucial for constraining our understanding of star formation processes in environments characterized by extremely low molecular gas densities and for refining models of galaxy formation, thereby improving predictions concerning the formation, evolution, and distribution of these giant, elusive galaxies., Comment: Accepted for publication in The Astrophysical Journal Letters. Published

The deployment of large-scale models, such as large language models (LLMs) and sophisticated image generation systems, incurs substantial costs due to their computational demands. To mitigate these costs and address challenges related to scalability and data security, there is a growing shift towards decentralized systems for deploying such models. In these decentralized environments, efficient inference acceleration becomes crucial to manage computational resources effectively and enhance system responsiveness. In this work, we address the challenge of selecting optimal acceleration methods in decentralized systems by introducing a meta-learning-based framework. This framework automates the selection process by learning from historical performance data of various acceleration techniques across different tasks. Unlike traditional methods that rely on random selection or expert intuition, our approach systematically identifies the best acceleration strategies based on the specific characteristics of each task. We demonstrate that our meta-learning framework not only streamlines the decision-making process but also consistently outperforms conventional methods in terms of efficiency and performance. Our results highlight the potential of meta-learning to revolutionize inference acceleration in decentralized AI systems, offering a path towards more democratic and economically feasible artificial intelligence solutions.

Stellar streams retain a memory of their gravitational interactions with small-scale perturbations. While perturbative models for streams have been formulated in action-angle coordinates, a direct transformation to these coordinates is only available for static and typically axisymmetric models for the galaxy. The real Milky Way potential is in a state of disequilibrium, complicating the application of perturbative methods around an equilibrium system. Here, we utilize a combination of differentiable simulations and Hamiltonian perturbation theory to model the leading-order effect of dark matter subhalos on stream observables. To obtain a perturbative description of streams, we develop a direct and efficient forward mode differentiation of Hamilton's equations of motion. Our model operates in observable coordinates, allowing us to treat the effects of arbitrary subhalo potentials on streams perturbatively, while simultaneously capturing non-linear effects due to other substructures like the infalling LMC or the rotating bar. The model predicts the velocity dispersion of streams as a function of subhalo statistics, allowing us to constrain the low-mass range of subhalos down to $\sim 10^5~M_\odot$. We forecast the velocity dispersion of the GD-1 stream, and find that observations are in agreement with a CDM subhalo population, with a slight preference for more dense subhalos. The method provides a new approach to characterize streams in the presence of substructure, with significantly more modeling flexibility compared to previous works., Comment: 31 pages (+5 appendix), 17 figures (+4 appendix). Submitted to ApJ. Comments welcome. Code release will accompany publication

Understanding quantum materials -- solids in which quantum-mechanical interactions among constituent electrons yield a great variety of novel emergent phenomena -- is a forefront challenge in modern condensed matter physics. This goal has driven the invention and refinement of several experimental methods, which can spectroscopically determine the elementary excitations and correlation functions that determine material properties. This Perspectives article focuses on the future experimental and theoretical trends of resonant inelastic x-ray scattering (RIXS), which is a remarkably versatile and rapidly growing technique for probing different charge, lattice, spin, and orbital excitations in quantum materials. We provide a forward-looking introduction to RIXS and outline how this technique is poised to deepen our insight into the nature of quantum materials and their emergent electronic phenomena., Comment: Review of RIXS to appear in Physical Review X as a Perspective

PSR J0737$-$3039A/B is unique among double neutron star systems. Its near-perfect edge-on orbit causes the fast spinning pulsar A to be eclipsed by the magnetic field of the slow spinning pulsar B. Using high-sensitivity MeerKAT radio observations combined with updated constraints on the system geometry, we studied the impact of these eclipses on the incident polarization properties of pulsar A. Averaging light curves together after correcting for the rotation of pulsar B revealed enormous amounts of circular polarization and rapid changes in the linear polarization position angle, which occur at phases where emission from pulsar A is partially transmitted through the magnetosphere of pulsar B. These behaviours confirm that the eclipse mechanism is the result of synchrotron absorption in a relativistic pair-plasma confined to the closed-field region of pulsar B's truncated dipolar magnetic field. We demonstrate that changes in circular polarization handedness throughout the eclipses are directly tied to the average line of sight magnetic field direction of pulsar B, from which we unambiguously determine the complete magnetic and viewing geometry of the pulsar., Comment: 8 pages, 6 figures. Accepted for publication in MNRAS

Understanding the exact fault location in the post-event analysis is the key to improving the accuracy of outage management. Unfortunately, the fault location is not generally well documented during the restoration process, creating a big challenge for post-event analysis. By utilizing various data source systems, including outage management system (OMS) data, asset geospatial information system (GIS) data, and vehicle location data, this paper creates a novel method to pinpoint the outage location accurately to create additional insights for distribution operations and performance teams during the post-event analysis.

A Gelfand-Tsetlin function is a real-valued function $\phi:C \to \mathbb{R}$ defined on a finite subset $C$ of the lattice $\mathbb{Z}^2$ with the property that $\phi(x) \leq \phi(y)$ for every edge $\langle x,y \rangle$ directed north or east between two elements of $C$. We study the statistical physics properties of random Gelfand-Tsetlin functions from the perspective of random surfaces, showing in particular that the surface tension of Gelfand-Tsetlin functions at gradient $u = (u_1,u_2) \in \mathbb{R}_{>0}^2$ is given by \begin{align*} \sigma(u_1,u_2) = - \log (u_1 + u_2 ) - \log \sin (\pi u_1/(u_1+u_2)) -1 + \log \pi. \end{align*} A Gelfand-Tsetlin pattern is a Gelfand-Tsetlin function defined on the triangle $T_n = \{(x_1,x_2) \in \mathbb{Z}^2 : 1 \leq x_2 \leq x_1 \leq n \}$. We show that after rescaling, a sequence of random Gelfand-Tsetlin patterns with fixed diagonal heights approximating a probability measure $\mu$ satisfies a large deviation principle with speed $n^2$ and rate functional of the form \begin{align*} \mathcal{E}[\psi] := \int_{\blacktriangle} \sigma(\nabla \psi)\, \mathrm{d}s \,\mathrm{d}t - \chi[\mu] \end{align*} where $\chi[\mu]$ is Voiculescu's free entropy. We show that the Euler-Lagrange equations satisfied by the minimiser of the rate functional agree with those governing the free compression operation in free probability, thereby resolving a recent conjecture of Shlyakhtenko and Tao., Comment: 56 pages

The Horn inequalities characterise the possible spectra of triples of $n$-by-$n$ Hermitian matrices $A+B=C$. We study integral inequalities that arise as limits of Horn inequalities as $n \to \infty$. These inequalities are parametrised by the points of an infinite-dimensional convex body, the asymptotic Horn system $\mathscr{H}$, which can be regarded as a topological closure of the countable set of Horn inequalities for all finite $n$. We prove three main results. The first shows that arbitrary points of $\mathscr{H}$ can be well approximated by specific sets of finite-dimensional Horn inequalities. The second is a quantitative result on the redundancy of the Horn inequalities in an infinite-dimensional setting. Concretely, the Horn inequalities for finite $n$ are indexed by certain sets $T^n_r$ with $1 \le r \le n-1$; we show that if $(n_k)_{k \ge 1}$ and $(r_k)_{k \ge 1}$ are any sequences such that $(r_k / n_k)_{k \ge 1}$ is a dense subset of $(0,1)$, then the Horn inequalities indexed by the sets $T^{n_k}_{r_k}$ are sufficient to imply all of the others. Our third main result shows that $\mathscr{H}$ has a remarkable self-characterisation property. Namely, membership in $\mathscr{H}$ is determined by the very inequalities corresponding to the points of $\mathscr{H}$ itself. To illuminate this phenomenon, we sketch a general theory of sets that characterise themselves in the sense that they parametrise their own membership criteria, and we consider the question of what further information would be needed in order for this self-characterisation property to determine the Horn inequalities uniquely., Comment: 35 pages, 2 figures. This version: strengthened Theorem 2.3, added several remarks and corollaries

Haptic devices have shown to be valuable in supplementing surgical training, especially when providing haptic feedback based on user performance metrics such as wrench applied by the user on the tool. However, current 6-axis force/torque sensors are prohibitively expensive. This paper presents the design and calibration of a low-cost, six-axis force/torque sensor specially designed for laparoscopic haptic training applications. The proposed design uses Hall-effect sensors to measure the change in the position of magnets embedded in a silicone layer that results from an applied wrench to the device. Preliminary experimental validation demonstrates that these sensors can achieve an accuracy of 0.45 N and 0.014 Nm, and a theoretical XY range of +/-50N, Z range of +/-20N, and torque range of +/-0.2Nm. This study indicates that the proposed low-cost 6-axis force/torque sensor can accurately measure user force and provide useful feedback during laparoscopic training on a haptic device.

We present VLT/MUSE integral-field spectroscopy ($R\approx 1\,800$) of four giant gravitational arcs exhibiting strong C IV absorption at 8 intervening redshifts, $z_{abs}\approx 2.0$--$2.5$. We detect C IV absorption in a total of 222 adjacent and seeing-uncorrelated sightlines, whose spectra sample beams of ("de-lensed") linear size $\approx 1$ kpc. Our data show that (1) absorption velocities cluster at all probed transverse scales, $\Delta r_\perp\approx0$--$15$ kpc, depending on system; (2) the (transverse) velocity dispersion never exceeds the mean (line-of-sight) absorption spread; and (3) the (transverse) velocity autocorrelation function does not resolve kinematic patterns at the above spatial scales, but its velocity projection, $\xi^{arc}(\Delta v)$, exhibits a similar shape to the known two-point correlation function toward quasars, $\xi^{QSO}(\Delta v)$. An empirical kinematic model suggests that these results are a natural consequence of wide-beam observations of an unresolved clumpy medium. Our model recovers both the underlying velocity dispersion of the clumps ($70$--$170$ \kms) and the mean number of clumps per unit area ($2$--$13$ kpc$^{-2}$). The latter constrains the projected mean inter-clump distance to within $\approx0.3$--$0.8$ kpc, which we argue is a measure of clump size for near-unity covering fraction. The model is also able to predict $\xi^{arc}(\Delta v)$ from $\xi^{QSO}(\Delta v)$, suggesting that the strong systems that shape the former and the line-of-sight velocity components that define the latter trace the same kinematic population. Consequently, the clumps must possess an internal density structure that generates both weak and strong components. We discuss how our interpretation is consistent with previous observations using background galaxies and multiple quasars., Comment: Accepted for publication in A&A

The infall of the LMC into the Milky Way (MW) has dynamical implications throughout the MW's dark matter halo. We study the impact of this merger on the statistical properties of populations of simulated stellar streams. Specifically, we investigate the radial and on-sky angular dependence of stream perturbations caused by the direct effect of stream--LMC interactions and/or the response of the MW dark matter halo. We use a time-evolving MW--LMC simulation described by basis function expansions to simulate streams. We quantify the degree of perturbation using a set of stream property statistics including the misalignment of proper motions with the stream track. In the outer halo, direct stream--LMC interactions produce a statistically significant effect, boosting the fraction of misaligned proper motions by ~25% relative to the model with no LMC. Moreover, there is on-sky angular dependence of stream perturbations: the highest fractions of perturbed streams coincide with the same on-sky quadrant as the present-day LMC location. In the inner halo, the MW halo dipole response primarily drives stream perturbations, but it remains uncertain whether this is a detectable signature distinct from the LMC's influence. For the fiducial MW--LMC model, we find agreement between the predicted fraction of streams with significantly misaligned proper motions, $\bar{\vartheta}>10^{\circ}$, and Dark Energy Survey data. Finally, we predict this fraction for the Rubin Observatory Legacy Survey of Space and Time (LSST) footprint. Using LSST data will improve our constraints on dark matter models and LMC properties as it is sensitive to both., Comment: ApJ accepted. 24 pages, 9 figures, 2 Tables

Monitoring the Future (MTF) is designed to give such attention to substance use among the nation's youth and adults. It is an investigator-initiated study that originated with, and is conducted by, a team of research professors at the University of Michigan's Institute for Social Research. Since its onset in 1975, MTF has been funded continuously by the National Institute on Drug Abuse--one of the National Institutes of Health--under a series of peer reviewed, competitive research grants. This 2023 survey is the 49th consecutive national survey of 12th grade students and the 33rd national survey of 8th and 10th grade students (who were added to the study in 1991). MTF contains ongoing national surveys of both adolescents and adults in the United States. It provides the nation with a vital window into the important but often hidden problem behaviors of use of illegal drugs, alcohol, tobacco, and psychotherapeutic drugs used without a doctor's orders. Two of the major topics included in the present monograph are: (1) the prevalence and frequency of use of a great many substances, both licit and illicit, among U.S. secondary school students in 8th, 10th, and 12th grades; and (2) historical trends in use by students in those grades. Distinctions are made among important demographic subgroups in these populations based on gender, college plans, region of the country, population density, parent education, and race/ethnicity. MTF has demonstrated that key attitudes and beliefs about drug use are important determinants of usage trends, in particular the amount of risk to the user perceived to be associated with the various drugs and disapproval of using them; thus, those measures also are tracked over time, as are students' perceptions of certain relevant aspects of the social environment--in particular, perceived availability of each drug, peer norms about their use, and use by friends. Data on grade of first use, noncontinuation of use, trends in use in lower grades (based on retrospective reports), and intensity of use are also reported. [For "Monitoring the Future National Survey Results on Drug Use, 1975-2022: Secondary School Students," see ED627366.]

Eclipsing binaries are crucial for understanding stellar physics, allowing detailed studies of stellar masses, radii, and orbital dynamics. Recent space missions like the Transiting Exoplanet Survey Satellite (TESS) have significantly expanded the catalogue of observed eclipsing binaries with uninterrupted time series photometry, providing an opportunity for large-scale ensemble studies. This study aims to analyse the statistical properties of circularisation in a large sample of intermediate-to-high mass eclipsing binaries observed by TESS. We explore the dependence of orbital circularisation on stellar properties and orbital parameters to improve our understanding of the physical processes affecting these systems. We further aim to assess the role of stellar pulsations in circularisation. We compiled a catalogue of O- to F-type stars to search for eclipsing binary signals in the TESS data. Using automated classification and data analysis methodologies, we arrive at a well-characterised sample of 14,573 eclipsing binaries. We investigate the statistical characteristics of the sample as a function of temperature, orbital period, and scaled orbital separation. The orbital circularisation was measured with statistical methods to obtain three distinct measurements of the critical period and separation in four temperature ranges. Pulsations were identified in the g- and p-mode regimes and a reduced fraction of eccentric systems was found among them. Our analysis confirmed and expanded upon previous findings that additional dissipation is needed as compared to the predictions of turbulent viscosity and non-resonant radiative damping. We speculate that pulsations may play a role in the circularisation of close binaries. Our study highlights the need for dissipative mechanisms that can produce a wide range of critical periods from a range of initial conditions., Comment: 15 pages, 10 figures, 4 appendices (15 pages, 26 figures). Accepted for publication in A&A

The problem of determining when entanglement is present in a quantum system is one of the most active areas of research in quantum physics. Depending on the setting at hand, different notions of entanglement (or lack thereof) become relevant. Examples include separability (of bosons, fermions, and distinguishable particles), Schmidt number, biseparability, entanglement depth, and bond dimension. In this work, we propose and study a unified notion of separability, which we call X-arability, that captures a wide range of applications including these. For a subset (more specifically, an algebraic variety) of pure states X, we say that a mixed quantum state is X-arable if it lies in the convex hull of X. We develop unified tools and provable guarantees for X-arability, which already give new results for the standard separability problem. Our results include: -- An X-tensions hierarchy of semidefinite programs for X-arability (generalizing the symmetric extensions hierarchy for separability), and a new de Finetti theorem for fermionic separability. -- A hierarchy of eigencomputations for optimizing a Hermitian operator over X, with applications to X-tanglement witnesses and polynomial optimization. -- A hierarchy of linear systems for the X-tangled subspace problem, with improved polynomial time guarantees even for the standard entangled subspace problem, in both the generic and worst case settings., Comment: 34 pages. Feedback welcome!

The degree distribution of a real world network -- the number of links per node -- often follows a power law, with some hubs having many more links than traditional graph generation methods predict. For years, preferential attachment and growth have been the proposed mechanisms that lead to these scale free networks. However, the two sides of bipartite graphs like collaboration networks are usually not scale free, and are therefore not well-explained by these processes. Here we develop a bipartite extension to the Randomly Stopped Linking Model and show that mixtures of geometric distributions lead to power laws according to a Central Limit Theorem for distributions with high variance. The two halves of the actor-movie network are not scale free and can be represented by just 5 geometric distributions, but they combine to form a scale free actor-actor unipartite projection without preferential attachment or growth. This result supports our claim that scale free networks are the natural result of many Bernoulli trials with high variance of which preferential attachment and growth are only one example., Comment: 10 pages, 7 figures

We explore the enhanced self-calibration of photometric galaxy redshift distributions, $n(z)$, through the combination of up to six two-point functions. Our $\rm 3\times2pt$ configuration is comprised of photometric shear, spectroscopic galaxy clustering, and spectroscopic-photometric galaxy-galaxy lensing (GGL). We further include spectroscopic-photometric cross-clustering; photometric GGL; and photometric auto-clustering, using the photometric shear sample as density tracer. We perform simulated likelihood forecasts of the cosmological and nuisance parameter constraints for Stage-III- and Stage-IV-like surveys. For the Stage-III-like case, we employ realistic but perturbed redshift distributions, and distinguish between "coherent" shifting in one direction, versus more internal scattering and full-shape errors. For perfectly known $n(z)$, a $\rm 6\times2pt$ analysis gains $\sim40\%$ in Figure of Merit (FoM) in the $S_8\equiv\sigma_8\sqrt{\Omega_{\rm m}/0.3}$ and $\Omega_{\rm m}$ plane relative to the $\rm 3\times2pt$ analysis. If untreated, coherent and incoherent redshift errors lead to inaccurate inferences of $S_8$ and $\Omega_{\rm m}$, respectively. Employing bin-wise scalar shifts $\delta{z}_i$ in the tomographic mean redshifts reduces cosmological parameter biases, with a $\rm 6x2pt$ analysis constraining the shift parameters with $2-4$ times the precision of a photometric $\rm 3^{ph}\times2pt$ analysis. For the Stage-IV-like survey, a $\rm 6\times2pt$ analysis doubles the FoM($\sigma_8{-}\Omega_{\rm m}$) compared to any $\rm 3\times2pt$ or $\rm 3^{ph}\times2pt$ analysis, and is only $8\%$ less constraining than if the $n(z)$ were perfectly known. A Gaussian mixture model for the $n(z)$ reduces mean-redshift errors and preserves the $n(z)$ shape. It also yields the most accurate and precise cosmological constraints for any $N\rm\times2pt$ configuration given $n(z)$ biases., Comment: 38 pages, 20 figures, to be submitted to A&A

Recent developments in natural language generation have tremendous implications for healthcare. For instance, state-of-the-art systems could automate the generation of sections in clinical reports to alleviate physician workload and streamline hospital documentation. To explore these applications, we present a shared task consisting of two subtasks: (1) Radiology Report Generation (RRG24) and (2) Discharge Summary Generation ("Discharge Me!"). RRG24 involves generating the 'Findings' and 'Impression' sections of radiology reports given chest X-rays. "Discharge Me!" involves generating the 'Brief Hospital Course' and 'Discharge Instructions' sections of discharge summaries for patients admitted through the emergency department. "Discharge Me!" submissions were subsequently reviewed by a team of clinicians. Both tasks emphasize the goal of reducing clinician burnout and repetitive workloads by generating documentation. We received 201 submissions from across 8 teams for RRG24, and 211 submissions from across 16 teams for "Discharge Me!"., Comment: ACL Proceedings. BioNLP workshop

Given a graph $G$ and a family of graphs $\cal F$, an $\cal F$-isolating set, as introduced by Caro and Hansberg, is any set $S\subset V(G)$ such that $G - N[S]$ contains no member of $\cal F$ as a subgraph. In this paper, we introduce a game in which two players with opposite goals are together building an $\cal F$-isolating set in $G$. Following the domination games, Dominator (Staller) wants that the resulting $\cal F$-isolating set obtained at the end of the game, is as small (as big) as possible, which leads to the graph invariant called the game $\cal F$-isolation number, denoted $\iota_{\rm g}(G,\cal F)$. We prove that the Continuation Principle holds in the $\cal F$-isolation game, and that the difference between the game $\cal F$-isolation numbers when either Dominator or Staller starts the game is at most $1$. Considering two arbitrary families of graphs $\cal F$ and $\cal F'$, we find relations between them that ensure $\iota_{\rm g}(G,{\cal{F}}') \leq \iota_{\rm g}(G,{\cal{F}})$ for any graph $G$. A special focus is given on the isolation game, which takes place when ${\cal F}=\{K_2\}$. We prove that $\iota_{\rm g}(G,\{K_2\})\le |V(G)|/2$ for any graph $G$, and conjecture that $\lceil 3|V(G)|/7\rceil$ is the actual (sharp) upper bound. We prove that the isolation game on a forest when Dominator has the first move never lasts longer than the one in which Staller starts the game. Finally, we prove good lower and upper bounds on the game isolation numbers of paths $P_n$, which lead to the exact values $\iota_{\rm g}(P_n,\{K_2\})=\left\lfloor\frac{2n+2}{5}\right\rfloor$ when $n \equiv i \pmod 5$ and $i \in \{1,2,3\}$., Comment: 15 pages, 1 figure, 18 references

Take a self-similar fragmentation process with dislocation measure $\nu$ and index of self-similarity $\alpha > 0$. Let $e^{-m_t}$ denote the size of the largest fragment in the system at time $t\geq 0$. We prove fine results for the asymptotics of the stochastic process $(m_t)_{t \geq 0}$ for a broad class of dislocation measures satisfying $$\nu(1-s_1 > \delta ) = \delta^{-\theta} \ell(1/\delta),$$ for some $\theta \in (0,1)$ and $\ell:(0,\infty) \to (0,\infty)$ slowly varying at infinity. Under this regularity condition, we find that if for $t \geq 0$ we have the almost-sure convergence $\lim_{t \to \infty} (m_t - g(t)) = 0$, where $$ g(t) :=\left( \log t - (1-\theta) \log \log t +f(t) \right)/\alpha$$ and $f(t) = o(\log \log t)$ can be given explicitly in terms of $\alpha,\theta$ and $\ell(\cdot)$. We prove a similar result in the finite activity case, which corresponds roughly speaking to the setting $\theta = 0$. Our results sharpen significantly the best prior result on general self-similar fragmentation processes, due to Bertoin, which states that $m_t = (1+o(1)) \log (t)/\alpha$., Comment: are welcome!

Abdominal computed tomography (CT) scans are frequently performed in clinical settings. Opportunistic CT involves repurposing routine CT images to extract diagnostic information and is an emerging tool for detecting underdiagnosed conditions such as sarcopenia, hepatic steatosis, and ascites. This study utilizes deep learning methods to promote accurate diagnosis and clinical documentation. We analyze 2,674 inpatient CT scans to identify discrepancies between imaging phenotypes (characteristics derived from opportunistic CT scans) and their corresponding documentation in radiology reports and ICD coding. Through our analysis, we find that only 0.5%, 3.2%, and 30.7% of scans diagnosed with sarcopenia, hepatic steatosis, and ascites (respectively) through either opportunistic imaging or radiology reports were ICD-coded. Our findings demonstrate opportunistic CT's potential to enhance diagnostic precision and accuracy of risk adjustment models, offering advancements in precision medicine.

We study the implications of relaxing the requirement for ultralight axions to account for all dark matter in the Universe by examining mixed dark matter (MDM) cosmologies with axion fractions $f \leq 0.3$ within the fuzzy dark matter (FDM) window $10^{-25}$ eV $\lesssim m \lesssim 10^{-23}$ eV. Our simulations, using a new MDM gravity solver implemented in AxiREPO, capture wave dynamics across various scales with high accuracy down to redshifts $z\approx 1$. We identify halos with Rockstar using the CDM component and find good agreement of inferred halo mass functions (HMFs) and concentration-mass relations with theoretical models across redshifts $z=1-10$. This justifies our halo finder approach a posteriori as well as the assumptions underlying the MDM halo model AxionHMcode. Using the inferred axion halo mass - cold halo mass relation $M_{\text{a}}(M_{\text{c}})$ and calibrating a generalised smoothing parameter $\alpha$ to our MDM simulations, we present a new version of AxionHMcode. The code exhibits excellent agreement with simulations on scales $k< 20 \ h$ cMpc$^{-1}$ at redshifts $z=1-3.5$ for $f\leq 0.1$ around the fiducial axion mass $m = 10^{-24.5}$ eV $ = 3.16\times 10^{-25}$ eV, with maximum deviations remaining below 10%. For axion fractions $f\leq 0.3$, the model maintains accuracy with deviations under 20% at redshifts $z\approx 1$ and scales $k< 10 \ h$ cMpc$^{-1}$, though deviations can reach up to 30% for higher redshifts when $f=0.3$. Reducing the run-time for a single evaluation of AxionHMcode to below $1$ minute, these results highlight the potential of AxionHMcode to provide a robust framework for parameter sampling across MDM cosmologies in Bayesian constraint and forecast analyses., Comment: 20 pages, 10 figures, 5 Tables, comments welcome

We argue that two prominent theories of ion heating in low-$\beta$ collisionless plasmas -- stochastic and quasi-linear heating -- represent similar physical processes in turbulence with different normalized cross helicities. To capture both, we propose a simple phenomenology based on the power in scales at which critically balanced fluctuations reach their smallest parallel scale. Simulations of test ions interacting with turbulence confirm our scalings across a wide range of different ion and turbulence properties, including with a steep ion-kinetic transition range as relevant to the solar wind., Comment: 12 pages, 4 figures. Submitted to Physical Review Letters; includes supplemental material (6 figures)