Search

M dwarfs are important targets in the search for Earth-like exoplanets due to their small masses and low luminosities. Several ongoing and upcoming space missions are targeting M dwarfs for this reason, and the ESA PLATO mission is one of these. In order to fully characterise a planetary system the properties of the host star must be known. For M dwarfs we can derive effective temperature, surface gravity, metallicity, and abundances of various elements from spectroscopic observations in combination with photometric data. The Stellar Abundances and atmospheric Parameters Pipeline (SAPP) has been developed as a prototype for one of the stellar science softwares within the PLATO consortium, it is aimed at FGK stars. We have modified it to be able to analyse the M dwarf among the PLATO targets. The current version of the pipeline for M dwarfs mostly relies on spectroscopic observations. The data processing is based on the machine learning algorithm The Payne and fits a grid of model spectra to an observed spectrum to derive effective temperature and metallicity. We use spectra in the H-band, as the near-infrared region is beneficial for M dwarfs. A method based on synthetic spectra was developed for the continuum normalisation of the spectra, taking into account the pseudo-continuum formed by numerous lines of the water molecule. Photometry is used to constrain the surface gravity. We tested the modified SAPP on spectra of M dwarfs from the APOGEE survey. Our validation sample of 26 stars includes stars with interferometric observations and binaries. We found a good agreement between our values and reference values from a range of studies. The overall uncertainties in the derived effective temperature, surface gravity, and metallicity is 100 K, 0.1 dex, and 0.15 dex, respectively. We find that the modified SAPP performs well on M dwarfs and identify possible areas of future development., Comment: Accepted in A&A

This paper gives the first examples of gordian unlinks. The components of these unlinks cannot be separated while maintaining constant length and thickness. We construct infinite families of 2-component gordian unlinks and also construct $n$-component gordian unlinks for each $n \geq 2$.

TOI-2015 is a known exoplanetary system around an M4 dwarf star, consisting of a transiting sub-Neptune planet in a 3.35-day orbital period, TOI-2015b, accompanied by a non-transiting companion, TOI-2015c. High-precision RV measurements were taken with the MAROON-X spectrograph, and high-precision photometric data were collected several networks. We re-characterize the target star by combining optical spectr, Bayesian Model Averaging (BMA) and Spectral Energy Distribution (SED) analysis. The TOI-2015 host star is a K=10.3mag M4-type dwarf with a sub-solar metallicity of [Fe/H]=-0.31+/-0.16, and a Teff=3200K. Our photodynamical analysis of the system strongly favors the 5:3 mean motion resonance and in this scenario the planet b has an orbital period of 3.34days, a mass of Mp=9.02+/-0.34Me, a radius of Rp=3.309+/-0.012Re, resulting in a density of rhop= 1.40+/-0.06g/cm3, indicative of a Neptune like composition. Its transits exhibit large (>1hr) timing variations indicative of an outer perturber in the system. We performed a global analysis of the high-resolution RV measurements, the photometric data, and the TTVs, and inferred that TOI-2015 hosts a second planet, TOI-2015c, in a non-transiting configuration. TOI-2015c has an orbital period of Pc=5.583days and a mass of Mp=8.91+0.38-0.40Me. The dynamical configuration of TOI-2015b and TOI-2015c can be used to constrain the system's planetary formation and migration history. Based on the mass-radius composition models, TOI-2015b is a water-rich or rocky planet with a hydrogen-helium envelope. Moreover, TOI-2015b has a high transmission spectroscopic metric (TSM=149), making it a favorable target for future transmission spectroscopic observations with JWST to constrain the atmospheric composition of the planet. Such observations would also help to break the degeneracies in theoretical models of the planet's interior structure., Comment: The paper has been accepted for publication in Astronomy and Astrophysics

The wide adoption of platformized work has generated remarkable advancements in the labor patterns and mobility of modern society. Underpinning such progress, gig workers are exposed to unprecedented challenges and accountabilities: lack of data transparency, social and physical isolation, as well as insufficient infrastructural safeguards. Gig2Gether presents a space designed for workers to engage in an initial experience of voluntarily contributing anecdotal and statistical data to affect policy and build solidarity across platforms by exchanging unifying and diverse experiences. Our 7-day field study with 16 active workers from three distinct platforms and work domains showed existing affordances of data-sharing: facilitating mutual support across platforms, as well as enabling financial reflection and planning. Additionally, workers envisioned future use cases of data-sharing for collectivism (e.g., collaborative examinations of algorithmic speculations) and informing policy (e.g., around safety and pay), which motivated (latent) worker desiderata of additional capabilities and data metrics. Based on these findings, we discuss remaining challenges to address and how data-sharing tools can complement existing structures to maximize worker empowerment and policy impact.

Thermal light dark matter (LDM) with particle masses in the 1 MeV - 1 GeV range could successfully explain the observed dark matter abundance as a relic from the primordial Universe. In this picture, a new feeble interaction acts as a "portal" between the Standard Model and LDM particles, allowing for the exploration of this paradigm at accelerator experiments. In the last years, the "missing energy" experiment NA64e at CERN SPS (Super Proton Synchrotron) has set world-leading constraints in the vector-mediated LDM parameter space, by exploiting a 100 GeV electron beam impinging on an electromagnetic calorimeter, acting as an active target. In this paper, we report a detailed description of the analysis of a preliminary measurement with a 70 GeV positron beam at NA64e, performed during summer 2023 with an accumulated statistic of 1.6 x 10^10 positrons on target. This data set was analyzed with the primary aim of evaluating the performance of the NA64e detector with a lower energy positron beam, towards the realization of the post-LS3 program. The analysis results, other than additionally probing unexplored regions in the LDM parameter space, provide valuable information towards the future NA64e positron campaign.

In this work, we address the challenge of approximating unknown system dynamics and costs by representing them as a bilinear system using Koopman-based Inverse Optimal Control (IOC). Using optimal trajectories, we construct a bilinear control system in transformed state variables through a modified Extended Dynamic Mode Decomposition with control (EDMDc) that maintains exact dynamical equivalence with the original nonlinear system. We derive Pontryagin's Maximum Principle (PMP) optimality conditions for this system, which closely resemble those of the inverse Linear Quadratic Regulator (LQR) problem due to the consistent control input and state independence from the control. This similarity allows us to apply modified inverse LQR theory, offering a more tractable and robust alternative to nonlinear Inverse Optimal Control methods, especially when dealing with unknown dynamics. Our approach also benefits from the extensive analytical properties of bilinear control systems, providing a solid foundation for further analysis and application. We demonstrate the effectiveness of the proposed method through theoretical analysis, simulation studies and a robotic experiment, highlighting its potential for broader applications in the approximation and design of control systems., Comment: This work has been submitted to the IEEE for possible publication

In the world of open-source software (OSS), the number of known vulnerabilities has tremendously increased. The GitHub Advisory Database contains advisories for security risks in GitHub-hosted OSS projects. As of 09/25/2023, there are 197,609 unreviewed GitHub security advisories. Of those unreviewed, at least 63,852 are publicly documented vulnerabilities, potentially leaving many OSS projects vulnerable. Recently, bug bounty platforms have emerged to focus solely on providing bounties to help secure OSS. In this paper, we conduct an empirical study on 3,798 reviewed GitHub security advisories and 4,033 disclosed OSS bug bounty reports, a perspective that is currently understudied, because they contain comprehensive information about security incidents, e.g., the nature of vulnerabilities, their impact, and how they were resolved. We are the first to determine the explicit process describing how OSS vulnerabilities propagate from security advisories and bug bounty reports, which are the main intermediaries between vulnerability reporters, OSS maintainers, and dependent projects, to vulnerable OSS projects and entries in global vulnerability databases and possibly back. This process uncovers how missing or delayed CVE assignments for OSS vulnerabilities result in projects, both in and out of OSS, not being notified of necessary security updates promptly and corresponding bottlenecks. Based on our findings, we provide suggestions, actionable items, and future research directions to help improve the security posture of OSS projects.

For an arbitrary hypersurface singularity, we construct a family of semigroups associated with algebraically closed fields that arise as an infinite union of rings of series. These semigroups extend the value semigroup of a plane curve studied by Abhyankar and Moh. The algebraically closed fields under consideration possess a natural valuation that induces a corresponding value semigroup. We establish the necessary conditions under which these semigroups are independent of the choice of the root. Moreover, the extensions proposed by P. Gonz\'alez and Kiyek-Micus, where Gonz\'alez specifically addresses the case of quasi-ordinary singularities, and the extension introduced by Abbas-Assi, can be understood as particular instances within our constructed family.

GaN has emerged to be a major semiconductor akin to silicon due to its revolutionary impacts in solid state lighting, critically enabled by p-type doping, and high-performance radio-frequency and power electronics. Suffering from inefficient hole doping and low hole mobility, quantum oscillations in p-type GaN have not been observed, hindering fundamental studies of valence bands and hole transport in GaN. Here, we present the first observation of quantum oscillations of holes in GaN. Shubnikov-de Haas (SdH) oscillations in hole resistivity are observed in a quantum-confined two-dimensional hole gas at a GaN/AlN interface, where polarization-induced doping overcomes thermal freeze-out, and a sharp and clean interface boosts the hole mobility enough to unmask the quantum oscillations. These holes degenerately occupy the light and heavy hole bands of GaN and have record-high mobilities of ~1900 cm2/Vs and ~400 cm2/Vs at 3K, respectively. We use magnetic fields up to 72 T to resolve SdH oscillations of holes from both valence bands to extract their respective sheet densities, quantum scattering times, and the effective masses of light holes (0.5-0.7 m0) and heavy holes (1.9 m0). SdH oscillations of heavy and light holes in GaN constitute a direct metrology of valence bands and open new venues for quantum engineering in this technologically important semiconductor. Like strained silicon transistors, strain-engineering of the valence bands of GaN is predicted to dramatically improve hole mobilities by reducing the hole effective mass, a proposal that can now be explored experimentally, particularly in a fully fabricated transistor, using quantum oscillations. Furthermore, the findings of this work suggest a blueprint to create 2D hole gases and observe quantum oscillations of holes in related wide bandgap semiconductors such as SiC and ZnO in which such techniques are not yet possible.

The high energy footprint of 5G base stations, particularly the radio units (RUs), poses a significant environmental and economic challenge. We introduce Kairos, a novel approach to maximize the energy-saving potential of O-RAN's Advanced Sleep Modes (ASMs). Unlike state-of-the-art solutions, which often rely on complex ASM selection algorithms unsuitable for time-constrained base stations and fail to guarantee stringent QoS demands, Kairos offers a simple yet effective joint ASM selection and radio scheduling policy capable of real-time operation. This policy is then optimized using a data-driven algorithm within an xApp, which enables several key innovations: (i) a dimensionality-invariant encoder to handle variable input sizes (e.g., time-varying network slices), (ii) distributional critics to accurately model QoS metrics and ensure constraint satisfaction, and (iii) a single-actor-multiple-critic architecture to effectively manage multiple constraints. Through experimental analysis on a commercial RU and trace-driven simulations, we demonstrate Kairos's potential to achieve energy reductions ranging between 15% and 72% while meeting QoS requirements, offering a practical solution for cost- and energy-efficient 5G networks.

The HAWC Observatory collected 6 years of extensive data, providing an ideal platform for long-term monitoring of blazars in the Very High Energy (VHE) band, without bias towards specific flux states. HAWC continuously monitors blazar activity at TeV energies, focusing on sources with a redshift of {z \lt 0.3}, based on the Third Fermi-LAT Catalog of High-Energy sources. We specifically focused our analysis on Mrk 421 and Mrk 501, as they are the brightest blazars observed by the HAWC Observatory. With a dataset of 2143 days, this work significantly extends the monitoring previously published, which was based on 511 days of observation. By utilizing HAWC data for the VHE {\gamma}-ray emission in the 300 GeV to 100 TeV energy range, in conjunction with Swift-XRT data for the 0.3 to 10 keV X-ray emission, we aim to explore potential correlations between these two bands. For Mrk 501, we found evidence of a long-term correlation. Additionally, we identified a period in the light curve where the flux was very low for more than two years. On the other hand, our analysis of Mrk 421 measured a strong linear correlation for quasi-simultaneous observations collected by HAWC and Swift-XRT. This result is consistent with a linear dependence and a multiple-zone synchrotron self-Compton model to explain the X-ray and the {\gamma}-ray emission. Finally, as suggested by previous findings, we confirm a harder-when-brighter behavior in the spectral evolution of the flux properties for Mrk 421. These findings contribute to the understanding of blazar emissions and their underlying mechanisms.

Context. Supernova remnants are one potential source class considered a PeVatron (i.e. capable of accelerating cosmic rays above PeV energies). The shock fronts produced after the explosion of the supernova are ideal regions for particle acceleration. IC 443 is a supernova remnant that has been studied extensively at different wavelengths. We study this region using very-high-energy gamma-ray data. Aims. We explore the region of IC 443 using 2966 days of gamma-ray data from the HAWC observatory. We study the emission of this supernova remnant and search for signatures that would show acceleration of (hadronic) cosmic rays at the PeV range. Methods. We use the maximum likelihood estimation and a likelihood ratio test to perform a multi-source fitting search. We find the best-fit morphology and spectrum of the IC 443 region above $\sim$300 GeV that best describes the HAWC data. Results. We observe a point source located at ($\alpha$=94.42$^{\circ}$, $\delta$=22.35$^{\circ}$) that we associate with IC 443. The measured spectrum is a simple power law with an index of -3.14$\pm$0.18, which is consistent with previous TeV observations. We also find a new extended component in the region whose emission is described by a simple power law with an index of -2.49$\pm$0.08 and which we call HAWC J0615+2213. Conclusions. Although we cannot confirm that IC 443 is a hadronic PeVatron, we do not find any sign that the spectrum has a cut off at tens of TeV energies, with the spectrum extending to $\sim$30 TeV. Furthermore, we find a new extended source in the region. While we show evidence that this new source might be a new TeV halo, we defer a detailed analysis of this new source to another publication.

Machine Learning (ML) models have become a very powerful tool to extract information from large datasets and use it to make accurate predictions and automated decisions. However, ML models can be vulnerable to external attacks, causing them to underperform or deviate from their expected tasks. One way to attack ML models is by injecting malicious data to mislead the algorithm during the training phase, which is referred to as a poisoning attack. We can prepare for such situations by designing anticipated attacks, which are later used for creating and testing defence strategies. In this paper, we propose an algorithm to generate strong poisoning attacks for a ridge regression model containing both numerical and categorical features that explicitly models and poisons categorical features. We model categorical features as SOS-1 sets and formulate the problem of designing poisoning attacks as a bilevel optimization problem that is nonconvex mixed-integer in the upper-level and unconstrained convex quadratic in the lower-level. We present the mathematical formulation of the problem, introduce a single-level reformulation based on the Karush-Kuhn-Tucker (KKT) conditions of the lower level, find bounds for the lower-level variables to accelerate solver performance, and propose a new algorithm to poison categorical features. Numerical experiments show that our method improves the mean squared error of all datasets compared to the previous benchmark in the literature.

Retrieval-Augmented Generation (RAG) has become ubiquitous when deploying Large Language Models (LLMs), as it can address typical limitations such as generating hallucinated or outdated information. However, when building real-world RAG applications, practical issues arise. First, the retrieved information is generally domain-specific. Since it is computationally expensive to fine-tune LLMs, it is more feasible to fine-tune the retriever to improve the quality of the data included in the LLM input. Second, as more applications are deployed in the same real-world system, one cannot afford to deploy separate retrievers. Moreover, these RAG applications normally retrieve different kinds of data. Our solution is to instruction fine-tune a small retriever encoder on a variety of domain-specific tasks to allow us to deploy one encoder that can serve many use cases, thereby achieving low-cost, scalability, and speed. We show how this encoder generalizes to out-of-domain settings as well as to an unseen retrieval task on real-world enterprise use cases., Comment: 9 pages, 2 figures. Submitted to NAACL 2025 Industry Track

CeRh2As2 is rare among superconductors, in that magnetic field tunes it between two distinct superconducting phases. Combined with a lack of local inversion symmetry and an upper critical field exceeding the Pauli paramagnetic limit, this excitingly suggests triplet multicomponent superconductivity. Preceding the superconducting onset, f-electron correlations cause long-range order, attributed both to local antiferromagnetism and itinerant (quadrupole) density-waves. Magnetic field provides a significant perturbation of the f-electron and may reveal the nature of the many-body correlations. Thus, we report comprehensive magnetization and magnetotransport studies on microstructured devices in fields of up to 73 T. Applied along the c-axis, field causes a low-temperature valence transition at {\mu}0H ~ 24 T. By contrast, in-plane fields produce a cascade of phase transitions; the field-induced in-plane conductivity anisotropy and lack of accompanying magnetic features, plus the closed-dome nature of the overall phase boundary is consistent with a hierarchy of field-induced density-wave states.

Magnetic fields are ubiquitous across different physical systems of current interest; from the early Universe, compact astrophysical objects and heavy-ion collisions to condensed matter systems. A proper treatment of the effects produced by magnetic fields during the dynamical evolution of these systems, can help to understand observables that otherwise show a puzzling behavior. Furthermore, when these fields are comparable to or stronger than \Lambda_QCD, they serve as excellent probes to help elucidate the physics of strongly interacting matter under extreme conditions of temperature and density. In this work we provide a comprehensive review of recent developments on the description of QED and QCD systems where magnetic field driven effects are important. These include the modification of meson static properties such as masses and form factors, the chiral magnetic effect, the description of anomalous transport coefficients, superconductivity in extreme magnetic fields, the properties of neutron stars, the evolution of heavy-ion collisions, as well as effects on the QCD phase diagram. We describe recent theory and phenomenological developments using effective models as well as LQCD methods. The work represents a state-of-the-art review of the field, motivated by presentations and discussions during the "Workshop on Strongly Interacting Matter in Strong Electromagnetic Fields" that took place in the European Centre for Theoretical Studies in Nuclear Physics and Related Areas (ECT*) in the city of Trento, Italy, September 25-29, 2023., Comment: 325 pages-long review of recent topics of interest in the field of magnetic field effects on QED and QCD matter. To be susbmitted to PNPP

A recently introduced model to evaluate the equivalent hydrodynamic length scale $z_0$ for turbulent flow over static rough surfaces is reformulated and extended to enable evaluation of $z_0$ for moving surface waves. The proposed Surface Wave-Aerodynamic Roughness Length model is based on maps of the surface height and its vertical speed as function of position, and Reynolds number. Pressure drag is estimated by approximating the local flow as ideal inviscid ramp flow (Ayala et al., 2024). Wave history effects are included through dependence on the local velocity difference between the air and wave speed. The model is applied to monochromatic and multiscale surfaces, and the predicted surface roughness length scales are compared to measured values and to commonly used wave parametrization methods found in the literature. The proposed model shows significantly improved agreement with data compared to other models.

Large Language Models (LLMs) are transforming the robotics domain by enabling robots to comprehend and execute natural language instructions. The cornerstone benefits of LLM include processing textual data from technical manuals, instructions, academic papers, and user queries based on the knowledge provided. However, deploying LLM-generated code in robotic systems without safety verification poses significant risks. This paper outlines a safety layer that verifies the code generated by ChatGPT before executing it to control a drone in a simulated environment. The safety layer consists of a fine-tuned GPT-4o model using Few-Shot learning, supported by knowledge graph prompting (KGP). Our approach improves the safety and compliance of robotic actions, ensuring that they adhere to the regulations of drone operations.

AI technologies are moving rapidly from research to production. With the popularity of Foundation Models (FMs) that generate text, images, and video, AI-based systems are increasing their complexity. Compared to traditional AI-based software, systems employing FMs, or GenAI-based systems, are more difficult to design due to their scale and versatility. This makes it necessary to document best practices, known as design patterns in software engineering, that can be used across GenAI applications. Our first contribution is to formalize two techniques, Task Decomposition and Retrieval-Augmented Generation (RAG), as design patterns for GenAI-based systems. We discuss their trade-offs in terms of software quality attributes and comment on alternative approaches. We recommend to AI practitioners to consider these techniques not only from a scientific perspective but also from the standpoint of desired engineering properties such as flexibility, maintainability, safety, and security. As a second contribution, we describe our industry experience applying Task Decomposition and RAG to build a complex real-world GenAI application for enterprise users: Workflow Generation. The task of generating workflows entails generating a specific plan using data from the system environment, taking as input a user requirement. As these two patterns affect the entire AI development cycle, we explain how they impacted the dataset creation, model training, model evaluation, and deployment phases., Comment: Under review; 12 pages, 8 figures

The pseudogap state of high-$T_{\rm c}$ cuprates, known for its partial gapping of the Fermi surface above the superconducting transition temperature $T_{\rm c}$, is believed to hold the key to understanding the origin of Planckian relaxation and quantum criticality. However, the nature of the Fermi surface in the pseudogap state has remained a fundamental open question. Here, we report the observation of the Yamaji effect above $T_{\rm c}$ in the single layer cuprate HgBa$_2$CuO$_{4+\delta}$. This observation is direct evidence of closed Fermi surface pockets in the normal state of the pseudogap phase. The small size of the pockets determined from the Yamaji effect (occupying approximately $1.3\%$ of the Brillouin zone area) is all the more surprising given the absence of evidence for long-range broken translational symmetry that can reconstruct the Fermi-surface., Comment: 26 pages including supplements

In aims to uncover insights into medical decision-making embedded within observational data from clinical settings, we present a novel application of Inverse Reinforcement Learning (IRL) that identifies suboptimal clinician actions based on the actions of their peers. This approach centers two stages of IRL with an intermediate step to prune trajectories displaying behavior that deviates significantly from the consensus. This enables us to effectively identify clinical priorities and values from ICU data containing both optimal and suboptimal clinician decisions. We observe that the benefits of removing suboptimal actions vary by disease and differentially impact certain demographic groups., Comment: 13 pages, 4 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

We introduce an $(\infty,1)$-category ${\sf Bord}_1^{\sf fr}(\mathbb{R}^n)$, the morphisms in which are framed tangles in $\mathbb{R}^n\times \mathbb{D}^1$. We prove that ${\sf Bord}_1^{\sf fr}(\mathbb{R}^n)$ has the universal mapping out property of the 1-dimensional Tangle Hypothesis of Baez--Dolan and Hopkins--Lurie: it is the rigid $\mathcal{E}_n$-monoidal $(\infty,1)$-category freely generated by a single object. Applying this theorem to a dualizable object of a braided monoidal $(\infty,1)$-category gives link invariants, generalizing the Reshetikhin--Turaev invariants., Comment: 103 pages, 12 figures

Optical detection of magnetic resonance using quantum spin sensors (QSS) provides a spatially local and sensitive technique to probe spin dynamics in magnets. However, its utility as a probe of antiferromagnetic resonance (AFMR), wherein the characteristic resonant frequencies substantially exceed the QSS probing frequency, remains an open question. Here, using the nitrogen-vacancy center in diamond as a QSS, we report the first experimental demonstration of optically detected AFMR in layered van der Waals antiferromagnets up to frequencies of 24 GHz, significantly higher than the sensor's spin resonance frequency of 2.87 GHz. To achieve this, we leverage the enhancement of the QSS spin relaxation rate due to low-frequency magnetic field fluctuations that arise from collective late-time dynamics of finite-wavevector magnons excited by the driven uniform AFMR mode. Using optically detected AFMR, we first characterize the temperature and magnetic field dependence on the AFMR modes, which shed light on the intrinsic exchange fields and magnetic anisotropies. Second, we exploit the highly localized sensitivity of the QSS to demonstrate efficient magnon transport over tens of micrometers. Finally, we find that optical detection efficiency in fact increases with increasing frequency, enabling broadband detection of magnetization dynamics. Our work showcases the dual capabilities of QSS as detectors of both high frequency magnetization dynamics and magnon transport, paving the way for understanding and controlling magnetism in Neel states in antiferromagnets.

We consider a d-dimensional symmetric inclusion process (SIP), where particles are allowed to jump arbitrarily far apart. We establish both the hydrodynamic limit and non-equilibrium fluctuations for the empirical measure of particles. With the help of self-duality and Mosco convergence of Dirichlet forms, we extend structural parallels between exclusion and inclusion dynamics from the short-range scenario to the long-range setting. The hydrodynamic equation for the symmetric inclusion process turns out to be of non-local type. At the level of fluctuations from the hydrodynamic limit, we demonstrate that the density fluctuation field converges to a time-dependent generalized Ornstein-Uhlenbeck process whose characteristics are again non-local., Comment: 33 pages

Very-high-energy (0.1-100 TeV) gamma-ray emission was observed in HAWC data from the lobes of the microquasar SS 433, making them the first set of astrophysical jets that were resolved at TeV energies. In this work, we update the analysis of SS 433 using 2,565 days of data from the High Altitude Water Cherenkov (HAWC) observatory. Our analysis reports the detection of a point-like source in the east lobe at a significance of $6.6\,\sigma$ and in the west lobe at a significance of $8.2\,\sigma$. For each jet lobe, we localize the gamma-ray emission and identify a best-fit position. The locations are close to the X-ray emission sites "e1" and "w1" for the east and west lobes, respectively. We analyze the spectral energy distributions and find that the energy spectra of the lobes are consistent with a simple power-law $\text{d}N/\text{d}E\propto E^{\alpha}$ with $\alpha = -2.44^{+0.13+0.04}_{-0.12-0.04}$ and $\alpha = -2.35^{+0.12+0.03}_{-0.11-0.03}$ for the east and west lobes, respectively. The maximum energy of photons from the east and west lobes reaches 56 TeV and 123 TeV, respectively. We compare our observations to various models and conclude that the very-high-energy gamma-ray emission can be produced by a population of electrons that were efficiently accelerated.

Large language models (LLMs) have achieved a degree of success in generating coherent and contextually relevant text, yet they remain prone to a significant challenge known as hallucination: producing information that is not substantiated by the input or external knowledge. Previous efforts to mitigate hallucinations have focused on techniques such as fine-tuning models on high-quality datasets, incorporating fact-checking mechanisms, and developing adversarial training methods. While these approaches have shown some promise, they often address the issue at the level of individual model outputs, leaving unexplored the effects of inter-model interactions on hallucination. This study investigates the phenomenon of hallucination in LLMs through a novel experimental framework where multiple instances of GPT-4o-Mini models engage in a debate-like interaction prompted with questions from the TruthfulQA dataset. One model is deliberately instructed to generate plausible but false answers while the other models are asked to respond truthfully. The experiment is designed to assess whether the introduction of misinformation by one model can challenge the truthful majority to better justify their reasoning, improving performance on the TruthfulQA benchmark. The findings suggest that inter-model interactions can offer valuable insights into improving the accuracy and robustness of LLM outputs, complementing existing mitigation strategies.

Microquasars are laboratories for the study of jets of relativistic particles produced by accretion onto a spinning black hole. Microquasars are near enough to allow detailed imaging of spatial features across the multiwavelength spectrum. The recent extension of the spatial morphology of a microquasar, SS 433, to TeV gamma rays \cite{abeysekara2018very} localizes the acceleration of electrons at shocks in the jet far from the black hole \cite{hess2024ss433}. Here we report TeV gamma-ray emission from another microquasar, V4641~Sgr, which reveals particle acceleration at similar distances from the black hole as SS~433. Additionally, the gamma-ray spectrum of V4641 is among the hardest TeV spectra observed from any known gamma-ray source and is detected up to 200 TeV. Gamma rays are produced by particles, either electrons or hadrons, of higher energies. Because electrons lose energy more quickly the higher their energy, such a spectrum either very strongly constrains the electron production mechanism or points to the acceleration of high-energy hadrons. This observation suggests that large-scale jets from microquasars could be more common than previously expected and that microquasars could be a significant source of Galactic cosmic rays. high energy gamma-rays also provide unique constraints on the acceleration mechanisms of extra-Galactic cosmic rays postulated to be produced by the supermassive black holes and relativistic jets of quasars. The distance to quasars limits imaging studies due to insufficient angular resolution of gamma-rays and due to attenuation of the highest energy gamma-rays by the extragalactic background light.

We construct a QCD coupling ${\mathcal{A}}(Q^2)$ in the Effective Charge (ECH) scheme of the canonical part $d(Q^2)$ of the (inelastic) polarised Bjorken Sum Rule (BSR) ${\overline \Gamma}_1^{{\rm p-n}}(Q^2)$. In the perturbative domain, the coupling ${\mathcal{A}}(Q^2)$ practically coincides with the perturbative coupling $a(Q^2)$ [$\equiv \alpha_s(Q^2)/\pi$] in the four-loop ECH renormalisation scheme. In the deep infrared (IR) regime, ${\mathcal{A}}(Q^2)$ behaves as suggested by the Holographic Light-Front QCD up to the second derivative. Furthermore, in contrast to its perturbative counterpart $a(Q^2)$, the coupling ${\mathcal{A}}(Q^2)$ is holomorphic in the entire complex $Q^2$-plane with the exception of the negative semiaxis, reflecting the holomorphic properties of the BSR observable $d(Q^2)$ [or: ${\overline \Gamma}_1^{{\rm p-n}}(Q^2)$] as dictated by the general principles of the Quantum Field Theory. It turns out that the obtained coupling, used as ECH, reproduces quite well the experimental data for ${\overline \Gamma}_1^{{\rm p-n}}(Q^2)$ in the entire $N_f=3$ regime $0 < Q^2 \lesssim 5 \ {\rm GeV}^2$., Comment: v2, 15 pages, 7 figures; additional Figs.4 and 5; version as it appears in JHEP; relations Eqs.(35)-(39) of our arXiv 2312.13134v2, and the corresponding explanations, are summarized here as Appendix B for convenience

We study the properties of a system composed of strongly interacting matter with an isospin imbalance, using as an effective description of QCD the two-flavor Linear Sigma Model with quarks. From the one-loop effective potential, including the two light quarks, pions and sigma contributions, and enforcing the restrictions imposed by chiral symmetry, we show that the development of an isospin condensate comes together with the emergence of a Goldstone mode that provides a constraint for the chiral and isospin condensates as a result of a non-trivial mixing between the charged pions and the sigma. We compute the thermodynamical quantities of interest and in particular the sound velocity squared, showing that it presents a maximum for an isospin chemical potential similar to the one reported by lattice QCD results and also with a similar height. Therefore, we attribute the origin of the peak of the sound velocity to the proper treatment of the Goldstone mode and to the non-trivial mixing of the charged pions and sigma in the isospin condensed phase., Comment: 7 pages, 2 figures

We report the first study of the $\mathcal{O}(\alpha)$ structure-dependent electromagnetic radiative corrections to unique first-forbidden nuclear beta decays. We show that the insertion of angular momentum into the nuclear matrix element by the virtual/real photon exchange opens up the decay at vanishing nuclear recoil momentum which was forbidden at tree level, leading to a dramatic change in the decay spectrum not anticipated in existing studies. We discuss its implications for precision tests on the Standard Model and searches for new physics., Comment: 9 pages, 4 figures, 1 table (including supplementary material)

SWEET-Cat (Stars With ExoplanETs Catalogue) was originally introduced in 2013, and since then, the number of confirmed exoplanets has increased significantly. A crucial step for a comprehensive understanding of these new worlds is the precise and homogeneous characterization of their host stars. We used a large number of high-resolution spectra to continue the addition of new stellar parameters for planet-host stars in SWEET-Cat following the new detection of exoplanets listed both at the Extrasolar Planets Encyclopedia and at the NASA exoplanet archive. We obtained high-resolution spectra for a significant number of these planet-host stars, either observed by our team or collected through public archives. For FGK stars, the spectroscopic stellar parameters were derived for the spectra following the same homogeneous process using ARES+MOOG as for the previous SWEET-Cat releases. The stellar properties are combined with the planet properties to study possible correlations that could shed more light into the star-planet connection studies. We increase the number of stars with homogeneous parameters by 232 ($\sim$ 25\% - from 959 to 1191). We then focus on the exoplanets with both mass and radius determined to review the mass-radius relation where we find consistent results with the ones previously reported in the literature. For the massive planets we also revisit the radius anomaly where we confirm a metallicity correlation for the radius anomaly already hinted in previous results., Comment: 8 pages, 5 figures, Accepted for A&A

This paper introduces a novel method for creating spectral time series, which can be used for generating synthetic light curves for photometric classification but also for applications like K-corrections and bolometric corrections. This approach is particularly valuable in the era of large astronomical surveys, where it can significantly enhance the analysis and understanding of an increasing number of SNe, even in the absence of extensive spectroscopic data. methods: By employing interpolations based on optimal transport theory, starting from a spectroscopic sequence, we derive weighted average spectra with high cadence. The weights incorporate an uncertainty factor for penalizing interpolations between spectra that show significant epoch differences and lead to a poor match between the synthetic and observed photometry. results: Our analysis reveals that even with phase difference of up to 40 days between pairs of spectra, optical transport can generate interpolated spectral time series that closely resemble the original ones. Synthetic photometry extracted from these spectral time series aligns well with observed photometry. The best results are achieved in the V band, with relative residuals of less than 10% for 87% and 84% of the data for type Ia and II, respectively. For the B, g, R and r bands, the relative residuals are between 65% and 87% within the previously mentioned 10% threshold for both classes. The worse results correspond to the i and I bands where, in the case, of SN~Ia the values drop to 53% and 42%, respectively. conclusions: We introduce a new method for constructing spectral time series for individual SNe starting from a sparse spectroscopic sequence, and demonstrate its capability to produce reliable light curves that can be used for photometric classification., Comment: Accepted for publication in A&A

Hybrid halide perovskites (HHPs) have attracted significant attention due to their remarkable optoelectronic properties that combine the advantages of low cost-effective fabrication methods of organic-inorganic materials. Notably, low-dimensional hybrid halide perovskites including two-dimensional (2D) layers and one-dimensional (1D) chains, are recognized for their superior stability and moisture resistance, making them highly appealing for practical applications. Particularly, DMAPbI3 has attracted attention due to other interesting behaviors and properties, such as thermally induced order-disorder processes, dielectric transition, and cooperative electric ordering of DMA dipole moments. In this paper, we investigated the interplay between low-temperature SPT undergone by the low-dimensional (1D) hybrid halide perovskite-like material DMAPbI3 and its optoelectronic properties. Our approach combines synchrotron X-ray powder diffraction, Raman spectroscopy, thermo-microscopy, differential scanning calorimetry (DSC), and photoluminescence (PL) techniques. Temperature-dependent Synchrotron powder diffraction and Raman Spectroscopy reveal that the modes associated with I-Pb-I and DMA+ ion play a crucial role in the order-disorder SPT in DMAPbI3. The reversible SPT modifies its optoelectronic properties, notably affecting its thermochromic behavior and PL emission. The origin of the PL phenomenon is associated to self-trapped excitons (STEs), which are allowed due to a strong electron-phonon coupling quantified by the Huang-Rhys factor (S = 97+-1). Notably, we identify the longitudinal optical (LO) phonon mode at 84 cm-1 which plays a significant role in electron-phonon interaction. Our results show these STEs not only intensify the PL spectra at lower temperatures but also induce a shift in the color emission, transforming it from a light orange-red to an intense bright strong red., Comment: 38 pages, 8 figures

In open-source software (OSS), software vulnerabilities have significantly increased. Although researchers have investigated the perspectives of vulnerability reporters and OSS contributor security practices, understanding the perspectives of OSS maintainers on vulnerability management and platform security features is currently understudied. In this paper, we investigate the perspectives of OSS maintainers who maintain projects listed in the GitHub Advisory Database. We explore this area by conducting two studies: identifying aspects through a listing survey ($n_1=80$) and gathering insights from semi-structured interviews ($n_2=22$). Of the 37 identified aspects, we find that supply chain mistrust and lack of automation for vulnerability management are the most challenging, and barriers to adopting platform security features include a lack of awareness and the perception that they are not necessary. Surprisingly, we find that despite being previously vulnerable, some maintainers still allow public vulnerability reporting, or ignore reports altogether. Based on our findings, we discuss implications for OSS platforms and how the research community can better support OSS vulnerability management efforts.

Researchers have investigated the bug bounty ecosystem from the lens of platforms, programs, and bug hunters. Understanding the perspectives of bug bounty report reviewers, especially those who historically lack a security background and little to no funding for bug hunters, is currently understudied. In this paper, we primarily investigate the perspective of open-source software (OSS) maintainers who have used \texttt{huntr}, a bug bounty platform that pays bounties to bug hunters who find security bugs in GitHub projects and have had valid vulnerabilities patched as a result. We address this area by conducting three studies: identifying characteristics through a listing survey ($n_1=51$), their ranked importance with Likert-scale survey data ($n_2=90$), and conducting semi-structured interviews to dive deeper into real-world experiences ($n_3=17$). As a result, we categorize 40 identified characteristics into benefits, challenges, helpful features, and wanted features. We find that private disclosure and project visibility are the most important benefits, while hunters focused on money or CVEs and pressure to review are the most challenging to overcome. Surprisingly, lack of communication with bug hunters is the least challenging, and CVE creation support is the second-least helpful feature for OSS maintainers when reviewing bug bounty reports. We present recommendations to make the bug bounty review process more accommodating to open-source maintainers and identify areas for future work.

Hyperspectral imaging (HSI) is emerging as a promising novel imaging modality with various potential surgical applications. Currently available cameras, however, suffer from poor integration into the clinical workflow because they require the lights to be switched off, or the camera to be manually recalibrated as soon as lighting conditions change. Given this critical bottleneck, the contribution of this paper is threefold: (1) We demonstrate that dynamically changing lighting conditions in the operating room dramatically affect the performance of HSI applications, namely physiological parameter estimation, and surgical scene segmentation. (2) We propose a novel learning-based approach to automatically recalibrating hyperspectral images during surgery and show that it is sufficiently accurate to replace the tedious process of white reference-based recalibration. (3) Based on a total of 742 HSI cubes from a phantom, porcine models, and rats we show that our recalibration method not only outperforms previously proposed methods, but also generalizes across species, lighting conditions, and image processing tasks. Due to its simple workflow integration as well as high accuracy, speed, and generalization capabilities, our method could evolve as a central component in clinical surgical HSI., Comment: Oral at MICCAI 2024