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Building more powerful quantum computers requires manufacturing processes with tight tolerances. To improve the tolerances on Josephson junctions, techniques to fine tune their properties after fabrication have been developed. Understanding how tuning techniques may physically modify the tunnel barrier of a Josephson junction is important and will enable these techniques to be optimised. We develop a model of junction tuning based on depinning theory to interpret a phase diagram of tuning rate. We extract the dependence on temperature, time varying voltages and oscillation frequency. Using depinning theory we are able to show both why time varying annealing potentials result in controlled junction tuning and how such protocols can be optimised. We examine how tuning changes the electrical breakdown of barriers and discrepancies between modeled and measured higher energy levels of transmon qubits., Comment: 5 pages 3 figures

This paper describes a method for parametric radial profile modelling of radio interferometric visibility data. Image-based parametric modelling is common in the field of circumstellar debris disks, and high resolution ALMA observations make this method computationally expensive because many high resolution images must be generated and Fourier transformed. Most circumstellar disks are axisymmetric, so here a method that avoids generating images and instead models radial profiles is outlined. The two main elements are i) $u,v$ space visibility averaging, and ii) using the Discrete Hankel Transform to convert arbitrary parametric radial surface brightness profiles to visibilities. Vertical scale height can be included, but is fixed with radius; in principle this is a limitation but in practise radially-dependent vertical structure information is beyond even ALMA's capability for all but a few debris disks. Combined, these ingredients yield a method that is one to two orders of magnitude faster than image based methods and can be run on a laptop, is sufficient for most ALMA observations of debris disks, and can be used with gradient-based fitting methods such as Hamiltonian Monte-Carlo. A small software package is provided, which is dubbed vis-r., Comment: accepted to RASTI

We establish a formula for structure constants of the quantum mirror to a log Calabi Yau surface $(Y,D)$ in terms of descendent logarithmic Gromov--Witten invariants of $(Y,D)$. Our result generalises the weak Frobenius structure conjecture for surfaces to the $q$-refined setting, and is proved by relating these invariants to counts of quantum broken lines in the associated quantum scattering diagram., Comment: 20 pages, 2 figures

We explore positivity properties of the semigroup generated by the negative of the Dirichlet-to-Neumann operator with real potential $\lambda$, defined on a subset of the vertices of a quantum graph. We show that for rationally independent edge lengths and suitable graph topologies, this semigroup will alternate between being positive, eventually positive without being positive (that is, positive only for sufficiently large times), and not even eventually positive, as $\lambda \to \infty$. For other graph topologies, the semigroup will alternate between being positive and not eventually positive. The topological conditions are related to a reduced graph which is a schematic map of the connections between the vertices on which the Dirichlet-to-Neumann operator acts.

We present the discovery of the variable optical counterpart to PSR J2055+1545, a redback millisecond pulsar, and the first radial velocity curve of its companion star. The multi-band optical light curves of this system show a $0.4$$-$$0.6 \ \mathrm{mag}$ amplitude modulation with a single peak per orbit and variable colours, suggesting that the companion is mildly irradiated by the pulsar wind. We find that the flux maximum is asymmetric and occurs at orbital phase $\simeq0.4$, anticipating the superior conjunction of the companion (where the optical emission of irradiated redback companions is typically brightest). We ascribe this asymmetry, well fit with a hot spot in our light curve modelling, to irradiation from the intrabinary shock between pulsar and companion winds. The optical spectra obtained with the \textit{Gran Telescopio Canarias} reveal a G-dwarf companion star with temperatures of $5749 \pm 34 \ \mathrm{K}$ and $6106 \pm 35 \ \mathrm{K}$ at its inferior and superior orbital conjunctions, respectively, and a radial velocity semi-amplitude of $385 \pm 3 \ \mathrm{km}\ \mathrm{s}^{-1}$. Our best-fit model yields a neutron star mass of $1.7^{+0.4}_{-0.1} \ \mathrm{M_{sun}}$ and a companion mass of $0.29^{+0.07}_{-0.01} \ \mathrm{M_{sun}}$. Based on the close similarity between the optical light curve of PSR~J2055$+$1545 and those observed from PSR J1023+0038 and PSR J1227-4853 during their rotation-powered states, we suggest this system may develop an accretion disc in the future and manifest as a transitional millisecond pulsar., Comment: 15 pages, 9 figures, 3 tables. This paper has been accepted for publication in ApJ, and currently in press

Josephson junctions manufactured to tight tolerances are necessary components for superconducting quantum computing. Developing precise manufacturing techniques for Josephson junctions requires an understanding of their make-up and robust feedback metrics against which to optimise. Here we consider complementary techniques assessing what conclusions they allow us to draw about the barriers in junctions. Monte-Carlo simulations of barriers show that standard deviations of 15-20 % of the total barrier thickness are compatible with our experimental data. Electrical breakdown allows us to probe the weakest points in barriers. Narrowing the distribution of this breakdown provides a promising feedback mechanism for barrier optimisation. Grouping junctions by breakdown voltage allows us to identify sub-ensembles of junctions with different median resistance, highlighting the importance of weak spots in junction parameters such as resistance. Transmission electron microscopy can be used to find average barrier thickness, although we highlight challenges forming robust conclusions on the distribution of thicknesses in a barrier from these experiments., Comment: 8 main pages, 5 main figures, 1 table, appended SI

A robust and efficient traffic monitoring system is essential for smart cities and Intelligent Transportation Systems (ITS), using sensors and cameras to track vehicle movements, optimize traffic flow, reduce congestion, enhance road safety, and enable real-time adaptive traffic control. Traffic monitoring models must comprehensively understand dynamic urban conditions and provide an intuitive user interface for effective management. This research leverages the LLaVA visual grounding multimodal large language model (LLM) for traffic monitoring tasks on the real-time Quanser Interactive Lab simulation platform, covering scenarios like intersections, congestion, and collisions. Cameras placed at multiple urban locations collect real-time images from the simulation, which are fed into the LLaVA model with queries for analysis. An instance segmentation model integrated into the cameras highlights key elements such as vehicles and pedestrians, enhancing training and throughput. The system achieves 84.3% accuracy in recognizing vehicle locations and 76.4% in determining steering direction, outperforming traditional models., Comment: 6 pages, 7 figures, submitted to 30th IEEE International Symposium on Computers and Communications (ISCC) 2025

The face remains relatively unexplored as a target region for haptic feedback, despite providing a considerable surface area consisting of highly sensitive skin. There are promising applications for facial haptic feedback, especially in cases of severe upper limb loss or spinal cord injury, where the face is typically less impacted than other body parts. Moreover, the neural representation of the face is adjacent to that of the hand, and phantom maps have been discovered between the fingertips and the cheeks. However, there is a dearth of compact devices for facial haptic feedback, and vibrotactile stimulation, a common modality of haptic feedback, has not been characterized for localization acuity on the face. We performed a localization experiment on the cheek, with an arrangement of off-the-shelf coin vibration motors. The study follows the methods of prior work studying other skin regions, in which participants attempt to identify the sites of discrete vibrotactile stimuli. We intend for our results to inform the future development of systems using vibrotactile feedback to convey information via the face., Comment: 5 pages, 5 figures

The Herschel open-time key program Disc Emission via a Bias-free Reconnaissance in the Infrared and Sub-millimeter (DEBRIS) is an unbiased survey of the nearest ~100 stars for each stellar type A-M observed with a uniform photometric sensitivity to search for cold debris disks around them. The analysis of the Photoconductor Array Camera and Spectrometer (PACS) photometric observations of the 94 DEBRIS M dwarfs of this program is presented in this paper, following upon two companion papers on the DEBRIS A-star and FGK-star subsamples. In the M-dwarf subsample, two debris disks have been detected, around the M3V dwarf GJ581 and the M4V dwarf FomalhautC (LP876-10). This result gives a disk detection rate of 2.1^{+2.7}_{-0.7}% at the 68% confidence level, significantly less than measured for earlier stellar types in the DEBRIS program. However, we show that the survey of the DEBRIS M-dwarf subsample is about ten times shallower than the surveys of the DEBRIS FGK subsamples when studied in the physical parameter space of the disk's fractional dust luminosity versus blackbody radius. Furthermore, had the DEBRIS K-star subsample been observed at the same shallower depth in this parameter space, its measured disk detection rate would have been statistically consistent with the one found for the M-dwarf subsample. Hence, the incidence of debris disks does not appear to drop from the K subsample to the M subsample of the DEBRIS program, when considering disks in the same region of physical parameter space. An alternative explanation is that the only two bright disks discovered in the M-dwarf subsample would not, in fact, be statistically representative of the whole population., Comment: 12 pages, long Table 3 included, accepted for publication in Astronomy & Astrophysics

We present synthetic optical light curves of the hierarchical HD98800 quadruple system over a decade-long period when the circumbinary disc encircling the system's B binary is expected to eclipse the light from the A binary. We produce and compare light curves of this transit event using hydrodynamical models with different values of the disc's gas mass, dust mass, and $\alpha$-viscosity to determine the observable effect of each parameter. These comparisons provide insight that could aid in the analysis of observational data from the system when the real transit occurs and provide recommendations for how such observations should be made. We find that a higher dust mass or higher value of $\alpha$ correspond to a longer transit, with the gas mass having a more minor effect on the overall shape and duration of the transit. A higher $\alpha$ has an observable effect on the viscous spreading at the outer edge of the disc, though is countered through truncation by the outer binary. It is also shown that long-term interactions between the outer binary and disc can excite spiral arms in the disc, which introduce observable asymmetries to the light curve. Our models suggest that the transit should have begun at the time of writing, but no dimming has yet been observed. It is likely that the disc has a smaller radial extent than our models, due to a lower viscosity than can be simulated with SPH. The transit is expected to last 8-11 years, ending in late 2034 at the latest., Comment: 12 pages, 13 figures

Muon colliders offer a compelling opportunity to explore the TeV scale and conduct precision tests of the Standard Model, all within a relatively compact geographical footprint. This paper introduces a new detector concept, MAIA (Muon Accelerator Instrumented Apparatus), optimized for $\sqrt{s}=10$ TeV $\mu\mu$ collisions. The detector features an all-silicon tracker immersed in a 5T solenoid field. High-granularity silicon-tungsten and iron-scintillator calorimeters surrounding the solenoid capture high-energy electronic and hadronic showers, respectively, and support particle-flow reconstruction. The outermost subsystem comprises an air-gap muon spectrometer, which enables standalone track reconstruction for high-momentum muons. The performance of the MAIA detector is evaluated in terms of differential particle reconstruction efficiencies and resolutions. Beam-induced background (BIB) simulations generated in FLUKA are overlaid with single particle gun samples to assess detector reconstruction capabilities under realistic experimental conditions. Even with BIB, reconstruction efficiencies exceed 95% for energetic tracks, photons, and neutrons in the central region of the detector. This paper outlines promising avenues of future work, including forward region optimization and opportunities for enhanced flavor/boosted object tagging, and addresses the technological assumptions needed to achieve the desired detector performance., Comment: 41 pages, 24 figures

We present absolute L-shell photoionisation cross sections for the S+, S2+, S3+ions. The cross sections were obtained using the monochromatised photon beam delivered by the SOLEIL synchrotron source coupled with an ion beam extracted from an electron cyclotron resonance source (ECRIS) in the merged dual-beam configuration. The cross sections for single, double and triple ionisation were measured and combined to generate total photoionisation cross sections. For each of the S+, S2+, S3+ ions, the photon energy regions corresponding to the excitation and ionisation of a 2p or a 2s electron (175-230 eV) were investigated. The experimental results are interpreted with the help of multiconfigurational Dirac-Fock (MCDF) and Breit-Pauli R-Matrix (BPRM) or Dirac R-Matrix (DARC) theoretical calculations. The former generates photoabsorption cross sections from eigenenergies and eigenfunctions obtained by solving variationally the multiconfiguration Dirac Hamiltonian while the latter calculate cross sections for photon scattering by atoms. The cross sectional spectra feature rich resonance structures with narrow natural widths (typically less than 100 meV) due to 2p to nd excitations below and up to the 2p thresholds. This behaviour is consistent with the large number of inner-shell states based on correlation and spin-orbit mixed configurations having three open subshells. Strong and wide (typically 1 eV) Rydberg series of resonances due to 2s to np excitations dominate above the 2p threshold., Comment: Submitted for publication in Journal of Physics B: Atomic, Molecular and Optical Physics

This paper provides an overview of the nonequilibrium fluctuational forces and torques acting on a body either in motion or at rest relative to another body or the thermal vacuum blackbody radiation. For a moving body, a retarding force emerges, called quantum or Casimir friction, which in vacuum was first predicted by Einstein and Hopf in 1907. Moreover, if a stationary body is not in thermal equilibrium with the blackbody vacuum, a self-propulsive force or torque can appear, resulting in a potentially observable linear or angular terminal velocity, even after thermalization., Comment: 8 pages, 9 figures. arXiv admin note: text overlap with arXiv:2411.14274

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

Dwarf novae are a crucial astrophysical laboratory for probing the nature of accretion, binary mass transfer, and binary evolution -- yet their diverse observational characteristics continue to challenge our theoretical understanding. We here present the discovery of, and subsequent observing campaign on GOTO065054+593624 (hereafter GOTO0650), a dwarf nova of the WZ Sge type, discovered in real-time by citizen scientists via the Kilonova Seekers citizen science project. An extensive dataset charts the photometric and spectroscopic evolution of this object, covering the first two months of its 2024 superoutburst. GOTO0650 shows a complete absence of visible emission lines during the high state, strong H and barely-detected He~II emission, and high-amplitude echo outbursts with a rapidly decreasing timescale that together do not neatly fit in with our current view of cataclysmic variables. The comprehensive dataset presented here not only underscores the uniqueness of this dwarf nova and marks it as a candidate period bouncer, but also highlights the important contribution that citizen scientists can make to the study of Galactic transients., Comment: 14 pages, 14 figures. Submitted to A&A

Planetesimal belts are ubiquitous around nearby stars, and their spatial properties hold crucial information for planetesimal and planet formation models. We present resolved dust observations of 74 planetary systems as part of the REsolved ALMA and SMA Observations of Nearby Stars (REASONS) survey and archival reanalysis. We uniformly modelled interferometric visibilities for the entire sample to obtain the basic spatial properties of each belt, and combined these with constraints from multi-wavelength photometry. We report key findings from a first exploration of this legacy dataset: (1) Belt dust masses are depleted over time in a radially dependent way, with dust being depleted faster in smaller belts, as predicted by collisional evolution. (2) Most belts are broad discs rather than narrow rings, with much broader fractional widths than rings in protoplanetary discs. We link broad belts to either unresolved substructure or broad planetesimal discs produced if protoplanetary rings migrate. (3) The vertical aspect ratios (h = H/R) of 24 belts indicate orbital inclinations of 1-20 degrees, implying relative particle velocities of 0.1-4 km/s, and no clear evolution of heights with system age. This could be explained by early stirring within the belt by large bodies (with sizes of at least 140 km to the size of the Moon), by inheritance of inclinations from the protoplanetary disc stage, or by a diversity in evolutionary pathways and gravitational stirring mechanisms. We release the REASONS legacy multidimensional sample of millimetre-resolved belts to the community as a valuable tool for follow-up multi-wavelength observations and population modelling studies., Comment: Published in A&A, 693, A151. 27 pages, 15 figures, 3 tables

Understanding causal relationships in the presence of complex, structured data remains a central challenge in modern statistics and science in general. While traditional causal inference methods are well-suited for scalar outcomes, many scientific applications demand tools capable of handling functional data -- outcomes observed as functions over continuous domains such as time or space. Motivated by this need, we propose DR-FoS, a novel method for estimating the Functional Average Treatment Effect (FATE) in observational studies with functional outcomes. DR-FoS exhibits double robustness properties, ensuring consistent estimation of FATE even if either the outcome or the treatment assignment model is misspecified. By leveraging recent advances in functional data analysis and causal inference, we establish the asymptotic properties of the estimator, proving its convergence to a Gaussian process. This guarantees valid inference with simultaneous confidence bands across the entire functional domain. Through extensive simulations, we show that DR-FoS achieves robust performance under a wide range of model specifications. Finally, we illustrate the utility of DR-FoS in a real-world application, analyzing functional outcomes to uncover meaningful causal insights in the SHARE (Survey of Health, Aging and Retirement in Europe) dataset., Comment: 19 pages, 2 figures

The COVID-19 pandemic caused widespread disruptions to education, with school closures affecting over one billion children. These closures, aimed at reducing virus transmission, resulted in significant learning losses, particularly in mathematics and science. Using data from TIMSS 2023, which assesses fourth and eighth-grade achievements across 71 education systems, this study analyzes the impact of school closure duration on learning outcomes. Mixed-effect models estimate deviations from pre-pandemic trends, adjusting for demographic factors. Results show a global average decline of 0.11 standard deviations (SD) in student achievement, with longer closures linked to more severe losses. The effects on low performers, girls, and linguistic minorities show effect sizes up to 0.22 SD. These findings highlight the lasting impact of school closures and emphasize the need for targeted recovery strategies and international cooperation to promote equitable educational outcomes post-pandemic.

The undergraduate curriculum in statistics and data science is undergoing changes to accommodate new methods, newly interested students, and the changing role of statistics in society. Because of this, it is more important than ever that students understand the role of study design and how to formulate meaningful scientific and statistical research questions. While the traditional Design of Experiments course is still extremely valuable for students heading to industry and research careers, a broader study design course that incorporates survey sampling, observational studies, and the basics of causal inference with randomized experiment design is particularly useful for students with a wide range of applied interests. Here, I describe such a course at a small liberal arts college, along with ways to adapt it to meet different student and instructor background and interests. The course serves as a valuable bridge to advanced statistical coursework, meets key statistical literacy and communication learning goals, and can be tailored to the desired level of computational and mathematical fluency. Through reading, discussing, and critiquing actual published research studies, students learn that statistics is a living discipline with real consequences and become better consumers and producers of scientific research and data-driven insights., Comment: 27 pages, 3 inset boxes, two appendices (18 pages total)

The field of exocomets has been built around the unmatched number of detections made in the circumstellar disc of the archetypal star Beta Pictoris. An exocomet detection in spectroscopy is identified by variable atomic absorption features in a stellar spectrum, associated with transiting gas in and trailing an exocomet coma. This paper presents the largest spectroscopic search for exocomet transits to date, which overcomes the limitations of biased samples of stars with debris discs, and instead looks through the $\approx$7500 stars in the HARPS archive for signs of exocomets in the CaII doublet (H:396.847nm and K:393.366nm). The search resulted in 155 candidate stars, which after filtering for false positives (e.g. binaries, stellar activity, etc.), were cut down to 22 stars. These 22 stars are classified into Tier1, 2, and 3 exocomet candidates, reflecting the confidence level of their exocomet detection. Our two best candidates (Tier1: Beta Pictoris, HD172555) and four lower confidence candidates (Tier2: Gl1, HIP5158, HD94771, HR1996) are discussed, yielding a detection rate of 0.03% (Tier1 only) and 0.1% (Tier1 & 2) in the HARPS sample. Both Tier1 stars are known exocomet host stars. These two young A-type stars correspond to 0.4% of all A-types in the sample, suggesting that detecting signs of exocomet transits using CaII is more likely around young A-type stars. Reanalysing a past HARPS study, we found no evidence to support the previously claimed four exocomet detections, indicating either that those detections are not robust or that we are only sensitive to the strongest signals., Comment: 23 pages, 36 figures, Accepted for publication in MNRAS

The measurement of fetal thalamus diameter (FTD) and fetal head circumference (FHC) are crucial in identifying abnormal fetal thalamus development as it may lead to certain neuropsychiatric disorders in later life. However, manual measurements from 2D-US images are laborious, prone to high inter-observer variability, and complicated by the high signal-to-noise ratio nature of the images. Deep learning-based landmark detection approaches have shown promise in measuring biometrics from US images, but the current state-of-the-art (SOTA) algorithm, BiometryNet, is inadequate for FTD and FHC measurement due to its inability to account for the fuzzy edges of these structures and the complex shape of the FTD structure. To address these inadequacies, we propose a novel Swoosh Activation Function (SAF) designed to enhance the regularization of heatmaps produced by landmark detection algorithms. Our SAF serves as a regularization term to enforce an optimum mean squared error (MSE) level between predicted heatmaps, reducing the dispersiveness of hotspots in predicted heatmaps. Our experimental results demonstrate that SAF significantly improves the measurement performances of FTD and FHC with higher intraclass correlation coefficient scores in FTD and lower mean difference scores in FHC measurement than those of the current SOTA algorithm BiometryNet. Moreover, our proposed SAF is highly generalizable and architecture-agnostic. The SAF's coefficients can be configured for different tasks, making it highly customizable. Our study demonstrates that the SAF activation function is a novel method that can improve measurement accuracy in fetal biometry landmark detection. This improvement has the potential to contribute to better fetal monitoring and improved neonatal outcomes.

We survey noncommutative Choquet theory and some of its applications., Comment: To appear in "Operator Theory" edited by Daniel Alpay, Fabrizio Colombo and Irene Sabadini with Springer Nature. 27 pages

In a previous paper we showed that an inhomogeneous body in vacuum will experience a spontaneous force if it is not in thermal equilibrium with its environment. This is due to the asymmetric asymptotic radiation pattern such an object emits. We demonstrated this self-propulsive force by considering an expansion in powers of the electric susceptibility: A torque arises in first order, but only if the material constituting the body is nonreciprocal. No force arises in first order. A force does occur for bodies made of ordinary (reciprocal) materials in second order. Here we extend these considerations to the torque. As one would expect, a spontaneous torque will also appear on an inhomogeneous chiral object if it is out of thermal equilibrium with its environment. Once a chiral body starts to rotate, it will experience a small quantum frictional torque, but much more important, unless a mechanism is provided to maintain the nonequilibrium state, is thermalization: The body will rapidly reach thermal equilibrium with the vacuum, and the angular acceleration will essentially become zero. For a small, or even a large, inhomogeneous chiral body, a terminal angular velocity will result, which seems to be in the realm of observability., Comment: 19 pages, 10 figures; clarifications and new Appendix A added

This technical report presents Prithvi-EO-2.0, a new geospatial foundation model that offers significant improvements over its predecessor, Prithvi-EO-1.0. Trained on 4.2M global time series samples from NASA's Harmonized Landsat and Sentinel-2 data archive at 30m resolution, the new 300M and 600M parameter models incorporate temporal and location embeddings for enhanced performance across various geospatial tasks. Through extensive benchmarking with GEO-Bench, the 600M version outperforms the previous Prithvi-EO model by 8\% across a range of tasks. It also outperforms six other geospatial foundation models when benchmarked on remote sensing tasks from different domains and resolutions (i.e. from 0.1m to 15m). The results demonstrate the versatility of the model in both classical earth observation and high-resolution applications. Early involvement of end-users and subject matter experts (SMEs) are among the key factors that contributed to the project's success. In particular, SME involvement allowed for constant feedback on model and dataset design, as well as successful customization for diverse SME-led applications in disaster response, land use and crop mapping, and ecosystem dynamics monitoring. Prithvi-EO-2.0 is available on Hugging Face and IBM terratorch, with additional resources on GitHub. The project exemplifies the Trusted Open Science approach embraced by all involved organizations.

Recently, the quality of artworks generated using Artificial Intelligence (AI) has increased significantly, resulting in growing difficulties in detecting synthetic artworks. However, limited studies have been conducted on identifying the authenticity of synthetic artworks and their source. This paper introduces AI-ArtBench, a dataset featuring 185,015 artistic images across 10 art styles. It includes 125,015 AI-generated images and 60,000 pieces of human-created artwork. This paper also outlines a method to accurately detect AI-generated images and trace them to their source model. This work proposes a novel Convolutional Neural Network model based on the ConvNeXt model called AttentionConvNeXt. AttentionConvNeXt was implemented and trained to differentiate between the source of the artwork and its style with an F1-Score of 0.869. The accuracy of attribution to the generative model reaches 0.999. To combine the scientific contributions arising from this study, a web-based application named ArtBrain was developed to enable both technical and non-technical users to interact with the model. Finally, this study presents the results of an Artistic Turing Test conducted with 50 participants. The findings reveal that humans could identify AI-generated images with an accuracy of approximately 58%, while the model itself achieved a significantly higher accuracy of around 99%.

Type Ia supernovae, critical for studying cosmic expansion, arise from thermonuclear explosions of white dwarfs, but their precise progenitor pathways remain unclear. Growing evidence supports the ``double-degenerate'' scenario, where two white dwarfs interact. The absence of other companion types capable of explaining the observed Ia rate, along with observations of hyper-velocity white dwarfs interpreted as surviving companions of such systems provide compelling evidence in favor of this scenario. Upcoming millihertz gravitational wave observatories like the Laser Interferometer Space Antenna (LISA) are expected to detect thousands of double-degenerate systems, though the most compact known candidate Ia progenitors produce only marginally detectable gravitational wave signals. Here, we report observations of ATLAS J1138-5139, a binary white dwarf system with an orbital period of 28 minutes. Our analysis reveals a 1 solar mass carbon-oxygen white dwarf accreting from a helium-core white dwarf. Given its mass, the accreting carbon-oxygen white dwarf is poised to trigger a typical-luminosity Type Ia supernova within a few million years, or to evolve into a stably mass-transferring AM CVn system. ATLAS J1138-5139 provides a rare opportunity to calibrate binary evolution models by directly comparing observed orbital parameters and mass transfer rates closer to merger than any previously identified candidate Type Ia progenitor. Its compact orbit ensures detectability by LISA, demonstrating the potential of millihertz gravitational wave observatories to reveal a population of Type Ia progenitors on a Galactic scale, paving the way for multi-messenger studies offering insights into the origins of these cosmologically significant explosions., Comment: 40 pages, 7 figures, 2 tables

Ferroelectric (FE)-based devices show great promise for non-volatile memory applications, yet few demonstrate reliable operation at elevated temperatures. In this work, we fabricated and characterized metal ferroelectric semiconductor capacitors integrating Aluminum Scandium Nitride onto Silicon Carbide, a prospective high temperature semiconductor for logic operations in extreme environments. The resultant Ni/Al0.68Sc0.32N/4H-SiC structure was evaluated for non-volatile memory performance from room temperature to high-temperature conditions. The 30-nm thick Al0.68Sc0.32N/SiC-based ferroelectric capacitors demonstrated ferroelectric switching at 900 C. The coercive field of the FE layer decreased linearly from -6.4/+11.9 MV cm-1 at room temperature to -3.1/+7.8 MV cm-1 at 800 C. Using positive-up negative-down measurements, we characterized the temperature dependence of remanent polarization. At 600 C, the devices achieved remarkable reliability, demonstrating endurance of ~2000 cycles and retention exceeding 100 hours with negligible polarization loss. Further reliability measurements extended to 800 C with 10,000 secs retention and > 300 endurance cycles, establish these devices as promising candidates for high-temperature memory applications.

From 2020 to 2023, Major League Baseball changed rules affecting team composition, player positioning, and game time. Understanding the effects of these rules is crucial for leagues, teams, players, and other relevant parties to assess their impact and to advocate either for further changes or undoing previous ones. Panel data and quasi-experimental methods provide useful tools for causal inference in these settings. I demonstrate this potential by analyzing the effect of the 2023 shift ban at both the league-wide and player-specific levels. Using difference-in-differences analysis, I show that the policy increased batting average on balls in play and on-base percentage for left-handed batters by a modest amount (nine points). For individual players, synthetic control analyses identify several players whose offensive performance (on-base percentage, on-base plus slugging percentage, and weighted on-base average) improved substantially (over 70 points in several cases) because of the rule change, and other players with previously high shift rates for whom it had little effect. This article both estimates the impact of this specific rule change and demonstrates how these methods for causal inference are potentially valuable for sports analytics -- at the player, team, and league levels -- more broadly., Comment: 25 pages main text, 12 pages appendices, 8 figures (4 main, 4 appendix), 3 tables

Recent methodological research in causal inference has focused on effects of stochastic interventions, which assign treatment randomly, often according to subject-specific covariates. In this work, we demonstrate that the usual notion of stochastic interventions have a surprising property: when there is unmeasured confounding, bounds on their effects do not collapse when the policy approaches the observational regime. As an alternative, we propose to study generalized policies, treatment rules that can depend on covariates, the natural value of treatment, and auxiliary randomness. We show that certain generalized policy formulations can resolve the "non-collapsing" bound issue: bounds narrow to a point when the target treatment distribution approaches that in the observed data. Moreover, drawing connections to the theory of optimal transport, we characterize generalized policies that minimize worst-case bound width in various sensitivity analysis models, as well as corresponding sharp bounds on their causal effects. These optimal policies are new, and can have a more parsimonious interpretation compared to their usual stochastic policy analogues. Finally, we develop flexible, efficient, and robust estimators for the sharp nonparametric bounds that emerge from the framework., Comment: 37 pages, 1 figure

This article summarizes our recent efforts to understand spontaneous quantum vacuum forces and torques, which require that a stationary object be out of thermal equilibrium with the blackbody background radiation. We proceed by a systematic expansion in powers of the electric susceptibility. In first order, no spontaneous force can arise, although a torque can appear, but only if the body is composed of nonreciprocal material. In second order, both forces and torques can appear, with ordinary materials, but only if the body is inhomogeneous. In higher orders, this last requirement may be removed. We give a number of examples of bodies displaying second-order spontaneous forces and torques, some of which might be amenable to observation., Comment: 11 pages, 12 figures. Paper submitted for Proceedings of the 5th Symposium on the Casimir Effect, Prian, Slovenia, September 2024

We report the discovery of three ultracompact binary white dwarf systems hosting accretion disks, with orbital periods of 7.95, 8.68, and 13.15 minutes. This significantly augments the population of mass-transferring binaries at the shortest periods, and provides the first evidence that accretors in ultracompacts can be dense enough to host accretion disks even below 10 minutes (where previously only direct-impact accretors were known). In the two shortest-period systems, we measured changes in the orbital periods driven by the combined effect of gravitational wave emission and mass transfer; we find $\dot{P}$ is negative in one case, and positive in the other. This is only the second system measured with a positive $\dot{P}$, and it the most compact binary known that has survived a period minimum. Using these systems as examples, we show how the measurement of $\dot{P}$ is a powerful tool in constraining the physical properties of binaries, e.g. the mass and mass-radius relation of the donor stars. We find that the chirp masses of ultracompact binaries at these periods seem to cluster around $\mathcal{M}_c \sim 0.3 M_\odot$, perhaps suggesting a common origin for these systems or a selection bias in electromagnetic discoveries. Our new systems are among the highest-amplitude known gravitational wave sources in the millihertz regime, providing exquisite opportunity for multi-messenger study with future space-based observatories such as \textit{LISA} and TianQin; we discuss how such systems provide fascinating laboratories to study the unique regime where the accretion process is mediated by gravitational waves., Comment: Accepted for publication in ApJ

The lack of both nesting and a van Hove singularity at half filling, together with the presence of Dirac cones makes the honeycomb lattice a special laboratory to explore strongly correlated phenomena. For instance, at zero temperature the repulsive [attractive] Hubbard model only undergoes a transition to an antiferromagnetic [$s$-wave superconducting degenerate with charge density wave (SC-CDW)] for sufficiently strong on-site coupling, $U/t\gtrsim 3.85$ [$U/t\lesssim -3.85$]; in between these, the system is a semi-metal, by virtue of the Dirac cones. The addition of an additional interaction, $V>0$ or $V<0$, between fermions in nearest neighbor orbitals should break the SC-CDW degeneracy giving rise to a phase diagram quite distinct from the one for the square lattice. Here we perform determinant quantum Monte Carlo simulations to investigate the whole phase diagram, covering the four combinations of signs of $U$ and $V$; the use of complex Hubbard-Stratonovich fields renders the region $|V|\leq |U|/3$ free from the `minus sign problem'. We calculate structure factors associated with different orderings, which, together with the double occupancy and the average sign allows us to map out the whole phase diagram. We have found that the SM phase forms a zone from which ordered phases are excluded, preventing the stabilization of a $d$-wave SC phase, i.e., only $s$-wave pairing is allowed.

The emerging in-context learning (ICL) ability of large language models (LLMs) has prompted their use for predictive tasks in various domains with different types of data facilitated by serialization methods. However, with increasing applications in high-stakes domains, it has been shown that LLMs can inherit social bias and discrimination from their pre-training data. In this work, we investigate this inherent bias in LLMs during in-context learning with tabular data. We focus on an optimal demonstration selection approach that utilizes latent concept variables for resource-efficient task adaptation. We design data augmentation strategies that reduce correlation between predictive outcomes and sensitive variables helping to promote fairness during latent concept learning. We utilize the learned concept and select demonstrations from a training dataset to obtain fair predictions during inference while maintaining model utility. The latent concept variable is learned using a smaller internal LLM and the selected demonstrations can be used for inference with larger external LLMs. We empirically verify that the fair latent variable approach improves fairness results on tabular datasets compared to multiple heuristic demonstration selection methods., Comment: 12 pages

Understanding treatment effect heterogeneity is vital for scientific and policy research. However, identifying and evaluating heterogeneous treatment effects pose significant challenges due to the typically unknown subgroup structure. Recently, a novel approach, causal k-means clustering, has emerged to assess heterogeneity of treatment effect by applying the k-means algorithm to unknown counterfactual regression functions. In this paper, we expand upon this framework by integrating hierarchical and density-based clustering algorithms. We propose plug-in estimators that are simple and readily implementable using off-the-shelf algorithms. Unlike k-means clustering, which requires the margin condition, our proposed estimators do not rely on strong structural assumptions on the outcome process. We go on to study their rate of convergence, and show that under the minimal regularity conditions, the additional cost of causal clustering is essentially the estimation error of the outcome regression functions. Our findings significantly extend the capabilities of the causal clustering framework, thereby contributing to the progression of methodologies for identifying homogeneous subgroups in treatment response, consequently facilitating more nuanced and targeted interventions. The proposed methods also open up new avenues for clustering with generic pseudo-outcomes. We explore finite sample properties via simulation, and illustrate the proposed methods in voting and employment projection datasets., Comment: 38th Conference on Neural Information Processing Systems (NeurIPS 2024)

Copper(I) iodide, CuI, is the leading $p$-type non-toxic and earth-abundant semiconducting material for transparent electronics and thermoelectric generators. Defects play a crucial role in determining the carrier concentration, scattering process, and therefore thermoelectric performance of a material. A result of defect engineering, the power factor of thin film CuI was increased from $332\pm32$ {\mu}Wm$^{-1}$K$^{-2}$ to $578\pm58$ {\mu}Wm$^{-1}$K$^{-2}$ after implantation with noble gas ions (Ne, Ar, Xe). The increased power factor is due to a decoupling of the Seebeck coefficient and electrical conductivity identified through a changing scattering mechanism. Ion implantation causes the abundant production of Frenkel pairs, which were found to suppress compensating donors in CuI, and which scenario was also supported by density functional theory calculations. The compensating donor suppression led to a significantly improved Hall carrier concentration, increasing from $6.5\times10^{19}\pm0.1\times10^{19}$ cm$^{-3}$ to $11.5\times10^{19}\pm0.4\times10^{19}$ cm$^{-3}$. This work provides an important step forward in the development of CuI as a transparent conducting material for electronics and thermoelectric generators by introducing beneficial point defects with ion implantation., Comment: 7 pages, 4 figures, 57 references. The following article has been accepted by Applied Physics Letters. After it is published, it will be found at https://doi.org/10.1063/5.0233754

We present the database of potential targets for the Large Interferometer For Exoplanets (LIFE), a space-based mid-infrared nulling interferometer mission proposed for the Voyage 2050 science program of the European Space Agency (ESA). The database features stars, their planets and disks, main astrophysical parameters, and ancillary observations. It allows users to create target lists based on various criteria to predict, for instance, exoplanet detection yields for the LIFE mission. As such, it enables mission design trade-offs, provides context for the analysis of data obtained by LIFE, and flags critical missing data. Work on the database is in progress, but given its relevance to LIFE and other space missions, including the Habitable Worlds Observatory (HWO), we present its main features here. A preliminary version of the LIFE database is publicly available on the German Astrophysical Virtual Observatory (GAVO)., Comment: RNAAS published, 3 pages, 1 figure

Cloud formation and magnetic effects are both expected to significantly impact the structures and observable properties of hot Jupiter atmospheres. For some hot Jupiters, thermal ionization and condensation can coexist in a single atmosphere, and both processes are important. We present a grid of general circulation models across a wide range of irradiation temperatures with and without incorporating the effects of magnetism and cloud formation to investigate how these processes work in tandem. We find that clouds are present in the atmosphere at all modeled irradiation temperatures, while magnetic effects are negligible for planets with irradiation temperatures cooler than 2000 K. At and above this threshold, clouds and magnetic fields shape atmospheres together, with mutual feedback. Models that include magnetism, through their influence on the temperature structure, produce more longitudinally symmetric dayside cloud coverage and more equatorially concentrated clouds on the nightside and morning terminator. To indicate how these processes would affect observables, we generate bolometric thermal and reflected phase curves from these models. The combination of clouds and magnetic effects increases thermal phase curve amplitudes and decreases peak offsets more than either process does individually., Comment: 19 pages, 8 figures, submitted to ApJ

Despite its many advantages, the sensible application of the Hybrid Monte Carlo (HMC) method is often hindered by the presence of large - or even infinite - potential barriers. These potential barriers partition the configuration space into distinct sectors, which leads to ergodicity violations and biased measurements of observables. In this work, we address this problem by augmenting the HMC method with a multiplicative Metropolis-Hastings update in a so-called "radial direction" of the fields, which enables jumps over the aforementioned potential barriers at comparably low computational cost. The effectiveness of this approach is demonstrated for the Hubbard model, formulated in a non-compact space by means of a continuous Hubbard-Stratonovich transformation. Our numerical results show that the radial updates successfully resolve the ergodicity violation, while simultaneously reducing autocorrelations., Comment: 10 pages, 5 figures, contribution to the 41st International Symposium on Lattice Field Theory (Lattice 2024), July 28th - August 3rd, 2024, Liverpool, UK

Operationalizing AI ethics and safety principles and frameworks is essential to realizing the potential benefits and mitigating potential harms caused by AI systems. To that end, actors across industry, academia, and regulatory bodies have created formal taxonomies of harm to support operationalization efforts. These include novel holistic methods that go beyond exclusive reliance on technical benchmarking. However, our paper argues that such taxonomies must also be transferred into local categories to be readily implemented in sector-specific AI safety operationalization efforts, and especially in underresourced or high-risk sectors. This is because many sectors are constituted by discourses, norms, and values that "refract" or even directly conflict with those operating in society more broadly. Drawing from emerging anthropological theories of human rights, we propose that the process of "vernacularization"--a participatory, decolonial practice distinct from doctrinary "translation" (the dominant mode of AI safety operationalization)--can help bridge this gap. To demonstrate this point, we consider the education sector, and identify precisely how vernacularizing a leading holistic taxonomy of harm leads to a clearer view of how harms AI systems may cause are substantially intensified when deployed in educational spaces. We conclude by discussing the generalizability of vernacularization as a useful AI safety methodology., Comment: Accepted to the Proceedings of the Conference on AI Ethics and Society (AIES), 2024

Many applications of causal inference require using treatment effects estimated on a study population to make decisions in a separate target population. We consider the challenging setting where there are covariates that are observed in the target population that were not seen in the original study. Our goal is to estimate the tightest possible bounds on heterogeneous treatment effects conditioned on such newly observed covariates. We introduce a novel partial identification strategy based on ideas from ecological inference; the main idea is that estimates of conditional treatment effects for the full covariate set must marginalize correctly when restricted to only the covariates observed in both populations. Furthermore, we introduce a bias-corrected estimator for these bounds and prove that it enjoys fast convergence rates and statistical guarantees (e.g., asymptotic normality). Experimental results on both real and synthetic data demonstrate that our framework can produce bounds that are much tighter than would otherwise be possible.

The Plateau's problem seeks to determine a surface of minimal area which spans a given boundary. It is widely studied for its varied mathematical formulations, applications and relevance to physical models such as soap films. We revisit the problem and study a soap film model in the spirit of capillarity formulations in two dimensions. Our approach introduces a nonlocal geometric potential in the variational length minimization scheme. This incorporates effects of thickness of soap films and provides insight into addressing the so-called collapsing phenomenon and other observable physical phenomena and properties.