Search

Indirect dark matter detection methods are used to observe the products of dark matter annihilations or decays originating from astrophysical objects where large amounts of dark matter are thought to accumulate. With neutrino telescopes, an excess of neutrinos is searched for in nearby dark matter reservoirs, such as the Sun and the Galactic Centre, which could potentially produce a sizeable flux of Standard Model particles. The KM3NeT infrastructure, currently under construction, comprises the ARCA and ORCA undersea \v{C}erenkov neutrino detectors located at two different sites in the Mediterranean Sea, offshore of Italy and France, respectively. The two detector configurations are optimised for the detection of neutrinos of different energies, enabling the search for dark matter particles with masses ranging from a few GeV/c$^2$ to hundreds of TeV/c$^2$. In this work, searches for dark matter annihilations in the Galactic Centre and the Sun with data samples taken with the first configurations of both detectors are presented. No significant excess over the expected background was found in either of the two analyses. Limits on the velocity-averaged self-annihilation cross section of dark matter particles are computed for five different primary annihilation channels in the Galactic Centre. For the Sun, limits on the spin-dependent and spin-independent scattering cross sections of dark matter with nucleons are given for three annihilation channels.

Stability selection is a widely adopted resampling-based framework for high-dimensional structure estimation and variable selection. However, the concept of 'stability' is often narrowly addressed, primarily through examining selection frequencies, or 'stability paths'. This paper seeks to broaden the use of an established stability estimator to evaluate the overall stability of the stability selection framework, moving beyond single-variable analysis. We suggest that the stability estimator offers two advantages: it can serve as a reference to reflect the robustness of the outcomes obtained and help identify an optimal regularization value to improve stability. By determining this value, we aim to calibrate key stability selection parameters, namely, the decision threshold and the expected number of falsely selected variables, within established theoretical bounds. Furthermore, we explore a novel selection criterion based on this regularization value. With the asymptotic distribution of the stability estimator previously established, convergence to true stability is ensured, allowing us to observe stability trends over successive sub-samples. This approach sheds light on the required number of sub-samples addressing a notable gap in prior studies. The 'stabplot' package is developed to facilitate the use of the plots featured in this manuscript, supporting their integration into further statistical analysis and research workflows.

We show that the monodromoy group of Nikulin-type orbifolds is maximal and classify finite order symplectic automorphisms up to deformation in terms of their action on the second integral cohomology group.

It is essential to examine the physical or chemical properties of molecular gas in starburst galaxies to reveal the underlying mechanisms characterizing starbursts. We used non-negative matrix factorization (NMF) to extract individual molecular or physical components involved in the star formation process in NGC\,253. We used images of 148 transitions from 44 different species of the ALMA large program ALCHEMI. Additionally, we included the continuum images at ALMA Bands 3 and 7 from the same dataset. For the five NMF components (NF1--5), we obtained that their distributions correspond to various basic phenomena related to star formation: i) low-density gas extended through the galactic central molecular zone (NF2), ii) shocks (NF3), iii) starburst regions (NF4), and iv) young star-forming regions (NF5). The other component (NF1) is related to excitation; three components obtained by NMF (NF3, 1, and 5) show a strong dependence upon the upper state energies of transitions, and represent low-, intermediate-, and high-excitation, respectively. We also compared our results using principal component analysis (PCA) previously applied to the same dataset. Molecular components extracted from NMF are similar to the ones obtained from PCA. However, NMF is better at extracting components associated with a single physical component, while a single component in PCA usually contains information on multiple physical components. This is especially true for features with weak intensities like emission from outflows. Our results suggest that NMF can be one of promising methods interpreting molecular line survey data, especially in the upcoming era of wide-band receivers., Comment: 22 pages, 19 figures, 2 tables. accepted for Publication of the Astronomical Society of Japan. Author's original version

The rapid evolution of software libraries presents a significant challenge for code generation models, which must adapt to frequent version updates while maintaining compatibility with previous versions. Existing code completion benchmarks often overlook this dynamic aspect, and the one that does consider it relies on static code prediction tasks without execution-based evaluation, offering a limited perspective on a model's practical usability. To address this gap, we introduce \textbf{\GitChameleon{}}, a novel, manually curated dataset comprising 116 Python code completion problems, each conditioned on specific library versions and accompanied by executable unit tests. \GitChameleon{} is designed to rigorously assess the ability of modern large language models (LLMs) to generate version-specific code that is not only syntactically correct but also functionally accurate upon execution. Our comprehensive evaluations reveal that state-of-the-art LLMs struggle with this task; for instance, \textbf{GPT-4o} achieves a pass@10 of only 39.9\% (43.7\% when provided with error feedback), highlighting the complexity of the problem and the limitations of current models. By providing an execution-based benchmark that emphasizes the dynamic nature of code libraries, \GitChameleon{} serves as a critical tool to advance the development of more adaptable and reliable code generation models. For facilitation for further exploration of version-conditioned code generation, we make our code repository publicly accessible at \url{https://github.com/NizarIslah/GitChameleon}.

The KM3NeT Collaboration has tackled a common challenge faced by the astroparticle physics community, namely adapting the experiment-specific simulation software to work with the CORSIKA air shower simulation output. The proposed solution is an extension of the open-source code gSeaGen, allowing for the transport of muons generated by CORSIKA to a detector of any size at an arbitrary depth. The gSeaGen code was not only extended in terms of functionalities but also underwent a thorough redesign of the muon propagation routine, resulting in a more accurate and efficient simulation. This paper presents the capabilities of the new gSeaGen code as well as prospects for further developments., Comment: 27 pages, 13 figures

The PICOSEC-Micromegas (PICOSEC-MM) detector is a novel gaseous detector designed for precise timing resolution in experimental measurements. It eliminates time jitter from charged particles in ionization gaps by using extreme UV Cherenkov light emitted in a crystal, detected by a Micromegas photodetector with an appropriate photocathode. The first single-channel prototype tested in 150 GeV/c muon beams achieved a timing resolution below 25 ps, a significant improvement compared to standard Micropattern Gaseous Detectors (MPGDs). This work explores the specifications for applying these detectors in monitored neutrino beams for the ENUBET Project. Key aspects include exploring resistive technologies, resilient photocathodes, and scalable electronics. New 7-pad resistive detectors are designed to handle the particle flux. In this paper, two potential scenarios are briefly considered: tagging electromagnetic showers with a timing resolution below 30 ps in an electromagnetic calorimeter as well as individual particles (mainly muons) with about 20 ps respectively.

Stability selection is a versatile framework for structure estimation and variable selection in high-dimensional setting, primarily grounded in frequentist principles. In this paper, we propose an enhanced methodology that integrates Bayesian analysis to refine the inference of inclusion probabilities within the stability selection framework. Traditional approaches rely on selection frequencies for decision-making, often disregarding domain-specific knowledge and failing to account for the inherent uncertainty in the variable selection process. Our methodology uses prior information to derive posterior distributions of inclusion probabilities, thereby improving both inference and decision-making. We present a two-step process for engaging with domain experts, enabling statisticians to elucidate prior distributions informed by expert knowledge while allowing experts to control the weight of their input on the final results. Using posterior distributions, we offer Bayesian credible intervals to quantify uncertainty in the variable selection process. In addition, we highlight how selection frequencies can be uninformative or even misleading when covariates are correlated with each other, and demonstrate how domain expertise can alleviate such issues. Our approach preserves the versatility of stability selection and is suitable for a broad range of structure estimation challenges.

Antiterminators are essential components of bacterial transcriptional regulation, allowing the control of gene expression in response to fluctuating environmental conditions. RNA-binding antiterminators are particularly important regulatory proteins that play a significant role in preventing transcription termination by binding to specific RNA sequences. These RNA-binding antiterminators have been extensively studied for their roles in regulating various metabolic pathways. However, their role in modulating the physiology of pathogens requires further investigations. This review focuses on these RNA-binding proteins in both Gram-positive and Gram-negative bacteria, particularly on their structures, mechanism of action, and target genes. Additionally, the involvement of the antitermination mechanisms in bacterial pathogenicity will be discussed. This knowledge is crucial for understanding the regulatory mechanisms that govern bacterial pathogenicity, opening up exciting prospects for future research, and potentially new alternative strategies to fight against infectious diseases., Comment: arXiv admin comment: This version has been removed by arXiv administrators as the submitter did not have the rights to agree to the license at the time of submission

The growing use of naturalistic stimuli, such as feature films, brings research on emotions closer to ecologically valid settings within brain scanners, such as functional magnetic resonance imaging (fMRI). Music is another cultural artifact known to evoke emotions, and film soundtracks are often designed to enhance the emotional impact of the narrative. However, the neural basis of shared emotional perception during movie-watching, and its relationship to the soundtrack, remains unclear. In this study, participants watched Forrest Gump in a 3T fMRI scanner. The reported shared arousal and valence (positive and negative) was correlated with the spectrogram and tempo information extracted from the soundtrack. For neuroimaging, four regions of interest (ROIs) related to audiovisual input and narrative content were examined: the superior temporal sulcus (STS), amygdala, inferior frontal gyrus, and precuneus. Results: Strong correlations between spectral and tempo, and emotional features (Bonferroni corr). BOLD responses associated with shared positive and negative valence and high-arousal moments were compared to film events with low emotional agreement. Significant activations were found in the STS and precuneus (pFWE < 0.05 peak level). No significant responses were observed in the amygdala or inferior frontal gyrus, but whole-brain analysis (pFWE < 0.05 cluster extent) revealed frontal activity linked to negative valence, alongside expected occipito-temporal lobe responses to the audiovisual stimuli. The STS and precuneus were particularly active during shared emotional perception of valenced and high-arousal events, with the precuneus encoding valence from auditory information. Naturalistic stimuli show promise as diagnostic and therapeutic tools for emotion regulation deficits although challenges may arise when crafting an experimental control.

This paper introduces Slipstream, a Byzantine Fault Tolerance (BFT) protocol where nodes concurrently propose blocks to be added to a Directed Acyclic Graph (DAG) and aim to agree on block ordering. Slipstream offers two types of block orderings: an optimistic ordering, which is live and secure in a sleepy model under up to 50% Byzantine nodes, and a final ordering, which is a prefix of the optimistic ordering and ensures safety and liveness in an eventual lock-step synchronous model under up to 33% Byzantine nodes. Additionally, Slipstream integrates a payment system that allows for fast UTXO transaction confirmation independently of block ordering. Transactions are confirmed in three rounds during synchrony, and unconfirmed double spends are resolved in a novel way using the DAG structure., Comment: 43 pages, 3 tables, 5 figures

This article delves into the concept of quantum contextuality, specifically focusing on proofs of the Kochen-Specker theorem obtained by assigning Pauli observables to hypergraph vertices satisfying a given commutation relation. The abstract structure composed of this hypergraph and the graph of anticommutations is named a hypergram. Its labelings with Pauli observables generalize the well-known magic sets. A first result is that all these quantum labelings satisfying the conditions of a given hypergram inherently possess the same degree of contextuality. Then we provide a necessary and sufficient algebraic condition for the existence of such quantum labelings and an efficient algorithm to find one of them. We finally attach to each assignable hypergram an abstract notion of contextuality degree. By presenting the study of observable-based Kochen-Specker proofs from the perspective of graphs and matrices, this abstraction opens the way to new methods to search for original contextual configurations., Comment: 18 pages, 3 figures, 1 table

AlScN is a new wide bandgap, high-k, ferroelectric material for RF, memory, and power applications. Successful integration of high quality AlScN with GaN in epitaxial layer stacks depends strongly on the ability to control lattice parameters and surface or interface through growth. This study investigates the molecular beam epitaxy growth and transport properties of AlScN/GaN multilayer heterostructures. Single layer Al$_{1-x}$Sc$_x$N/GaN heterostructures exhibited lattice-matched composition within $x$ = 0.09 -- 0.11 using substrate (thermocouple) growth temperatures between 330 $ ^\circ$C and 630 $ ^\circ$C. By targeting the lattice-matched Sc composition, pseudomorphic AlScN/GaN multilayer structures with ten and twenty periods were achieved, exhibiting excellent structural and interface properties as confirmed by X-ray diffraction (XRD) and scanning transmission electron microscopy (STEM). These multilayer heterostructures exhibited substantial polarization-induced net mobile charge densities of up to 8.24 $\times$ 10$^{14}$/cm$^2$ for twenty channels. The sheet density scales with the number of AlScN/GaN periods. By identifying lattice-matched growth condition and using it to generate multiple conductive channels, this work enhances our understanding of the AlScN/GaN material platform.

We experimentally study the formation of surface patterns in grafted hydrogel films of nanometer-to-micrometer thicknesses during imbibition-driven swelling followed by evaporation-driven shrinking. Creases are known to form at the hydrogel surface during swelling; the wavelength of the creasing pattern is proportional to the initial thickness of the hydrogel film with a logarithmic correction that depends on microscopic properties of the hydrogel. We find that, although the characteristic wavelength of the pattern is determined during swelling, the surface morphology can be significantly influenced by evaporation-induced shrinking. We observe that the elastocapillary length based on swollen mechanical properties gives a threshold thickness for a surface pattern formation, and consequently an important change in morphology.

Neutrinos described as an open quantum system may interact with the environment which introduces stochastic perturbations to their quantum phase. This mechanism leads to a loss of coherence along the propagation of the neutrino $-$ a phenomenon commonly referred to as decoherence $-$ and ultimately, to a modification of the oscillation probabilities. Fluctuations in space-time, as envisaged by various theories of quantum gravity, are a potential candidate for a decoherence-inducing environment. Consequently, the search for decoherence provides a rare opportunity to investigate quantum gravitational effects which are usually beyond the reach of current experiments. In this work, quantum decoherence effects are searched for in neutrino data collected by the KM3NeT/ORCA detector from January 2020 to November 2021. The analysis focuses on atmospheric neutrinos within the energy range of a few GeV to $100\,\mathrm{GeV}$. Adopting the open quantum system framework, decoherence is described in a phenomenological manner with the strength of the effect given by the parameters $\Gamma_{21}$ and $\Gamma_{31}$. Following previous studies, a dependence of the type $\Gamma_{ij} \propto (E/E_0)^n$ on the neutrino energy is assumed and the cases $n = -2,-1$ are explored. No significant deviation with respect to the standard oscillation hypothesis is observed. Therefore, $90\,\%$ CL upper limits are estimated as $\Gamma_{21} < 4.6\cdot 10^{-21}\,$GeV and $\Gamma_{31} < 8.4\cdot 10^{-21}\,$GeV for $n = -2$, and $\Gamma_{21} < 1.9\cdot 10^{-22}\,$GeV and $\Gamma_{31} < 2.7\cdot 10^{-22}\,$GeV for $n = -1$, respectively., Comment: 17 pages, 5 figures

Model merging, such as model souping, is the practice of combining different models with the same architecture together without further training. In this work, we present a model merging methodology that addresses the difficulty of fine-tuning Large Language Models (LLMs) for target tasks in non-English languages, where task-specific data is often unavailable. We focus on mathematical reasoning and without in-language math data, facilitate cross-lingual transfer by composing language and math capabilities. Starting from the same pretrained model, we fine-tune separate "experts" on math instruction data in English and on generic instruction data in the target language. We then replace the top and bottom transformer layers of the math expert directly with layers from the language expert, which consequently enhances math performance in the target language. The resulting merged models outperform the individual experts and other merging methods on the math benchmark, MGSM, by 10% across four major languages where math instruction data is scarce. In addition, this layer swapping is simple, inexpensive, and intuitive, as it is based on an interpretative analysis of the most important parameter changes during the fine-tuning of each expert. The ability to successfully re-compose LLMs for cross-lingual transfer in this manner opens up future possibilities to combine model expertise, create modular solutions, and transfer reasoning capabilities across languages all post hoc., Comment: 11 main pages, 23 pages total, 9 figures, 5 tables

We report evidence for superconductivity with onset temperatures up to 11 K in thin films of the infinite-layer nickelate parent compound NdNiO$_2$. A combination of oxide molecular-beam epitaxy and atomic hydrogen reduction yields samples with high crystallinity and low residual resistivities, a substantial fraction of which exhibit superconducting transitions. We survey a large series of samples with a variety of techniques, including electrical transport, scanning transmission electron microscopy, x-ray absorption spectroscopy, and resonant inelastic x-ray scattering, to investigate the possible origins of superconductivity. We propose that superconductivity could be intrinsic to the undoped infinite-layer nickelates but suppressed by disorder due to its nodal order parameter, a finding which would necessitate a reconsideration of the nickelate phase diagram. Another possible hypothesis is that the parent materials can be hole doped from randomly dispersed apical oxygen atoms, which would suggest an alternative pathway for achieving superconductivity., Comment: Main: 10 pages, 6 figures. Supplementary: 9 pages, 10 figures

Detections of fast X-ray transients (FXTs) have been accrued over the last few decades. However, their origin has remained mysterious. There is now rapid progress thanks to timely discoveries and localisations with the Einstein Probe mission. Early results indicate that FXTs may frequently, but not always, be associated with gamma-ray bursts (GRBs). Here, we report on the multi-wavelength counterpart of FXT EP240414a, which has no reported gamma-ray counterpart. The transient is located 25.7~kpc in projection from a massive galaxy at $z=0.40$. We perform comprehensive photometric and spectroscopic follow-up. The optical light curve shows at least three distinct emission episodes with timescales of $\sim 1, 4$ and 15 days and peak absolute magnitudes of $M_R \sim -20$, $-21$, and $-19.5$, respectively. The optical spectrum at early times is extremely blue, inconsistent with afterglow emission. It may arise from the interaction of both jet and supernova shock waves with the stellar envelope and a dense circumstellar medium, as has been suggested for some Fast Blue Optical Transients (LFBOTs). At late times, the spectrum evolves to a broad-lined~Type~Ic supernova, similar to those seen in collapsar long-GRBs. This implies that the progenitor of EP240414a is a massive star creating a jet-forming supernova inside a dense envelope, resulting in an X-ray outburst with a luminosity of $\sim 10^{48}$ erg s$^{-1}$, and the complex observed optical/IR light curves. If correct, this argues for a causal link between the progenitors of long-GRBs, FXTs and LFBOTs., Comment: 36 pages, 13 figures, submitted to ApJ

We propose the use of latent space generative world models to address the covariate shift problem in autonomous driving. A world model is a neural network capable of predicting an agent's next state given past states and actions. By leveraging a world model during training, the driving policy effectively mitigates covariate shift without requiring an excessive amount of training data. During end-to-end training, our policy learns how to recover from errors by aligning with states observed in human demonstrations, so that at runtime it can recover from perturbations outside the training distribution. Additionally, we introduce a novel transformer-based perception encoder that employs multi-view cross-attention and a learned scene query. We present qualitative and quantitative results, demonstrating significant improvements upon prior state of the art in closed-loop testing in the CARLA simulator, as well as showing the ability to handle perturbations in both CARLA and NVIDIA's DRIVE Sim., Comment: 7 pages, 6 figures, for ICRA 2025 conference, for associated video file, see https://youtu.be/fO7RZ57gVxk

We use a neural network model and ALMA observations of HCN and HNC to constrain the physical conditions, most notably the cosmic-ray ionization rate (CRIR, zeta), in the Central Molecular Zone (CMZ) of the starburst galaxy NGC 253. Using output from the chemical code UCLCHEM, we train a neural network model to emulate UCLCHEM and derive HCN and HNC molecular abundances from a given set of physical conditions. We combine the neural network with radiative transfer modeling to generate modeled integrated intensities, which we compare to measurements of HCN and HNC from the ALMA Large Program ALCHEMI. Using a Bayesian nested sampling framework, we constrain the CRIR, molecular gas volume and column densities, kinetic temperature, and beam-filling factor across NGC 253's CMZ. The neural network model successfully recovers UCLCHEM molecular abundances with about 3 percent error and, when used with our Bayesian inference algorithm, increases the parameter inference speed tenfold. We create images of these physical parameters across NGC 253's CMZ at 50 pc resolution and find that the CRIR, in addition to the other gas parameters, is spatially variable with zeta a few times 10^{14} s^{-1} at greater than 100 pc from the nucleus, increasing to zeta greater than 10^{-13} s^{-1} at its center. These inferred CRIRs are consistent within 1 dex with theoretical predictions based on non-thermal emission. Additionally, the high CRIRs estimated in NGC 253's CMZ can be explained by the large number of cosmic-ray-producing sources as well as a potential suppression of cosmic-ray diffusion near their injection sites.

There is now substantial evidence for traveling waves and other structured spatiotemporal recurrent neural dynamics in cortical structures; but these observations have typically been difficult to reconcile with notions of topographically organized selectivity and feedforward receptive fields. We introduce a new 'spacetime' perspective on neural computation in which structured selectivity and dynamics are not contradictory but instead are complimentary. We show that spatiotemporal dynamics may be a mechanism by which natural neural systems encode approximate visual, temporal, and abstract symmetries of the world as conserved quantities, thereby enabling improved generalization and long-term working memory.

Retrieval-Augmented Generation (RAG) has emerged as a common paradigm to use Large Language Models (LLMs) alongside private and up-to-date knowledge bases. In this work, we address the challenges of using LLM-as-a-Judge when evaluating grounded answers generated by RAG systems. To assess the calibration and discrimination capabilities of judge models, we identify 7 generator failure modes and introduce GroUSE (Grounded QA Unitary Scoring of Evaluators), a meta-evaluation benchmark of 144 unit tests. This benchmark reveals that existing automated RAG evaluation frameworks often overlook important failure modes, even when using GPT-4 as a judge. To improve on the current design of automated RAG evaluation frameworks, we propose a novel pipeline and find that while closed models perform well on GroUSE, state-of-the-art open-source judges do not generalize to our proposed criteria, despite strong correlation with GPT-4's judgement. Our findings suggest that correlation with GPT-4 is an incomplete proxy for the practical performance of judge models and should be supplemented with evaluations on unit tests for precise failure mode detection. We further show that finetuning Llama-3 on GPT-4's reasoning traces significantly boosts its evaluation capabilities, improving upon both correlation with GPT-4's evaluations and calibration on reference situations.

Schwarzschild dynamical models are now regularly employed in large surveys of galaxies in the local and distant Universe to derive information on galaxies' intrinsic properties such as their orbital structure and their (dark matter and stellar) mass distribution. Comparing the internal orbital structures and mass distributions of galaxies in the distant Universe with simulations is key to understanding what physical processes are responsible for shaping galaxy properties. However it is first crucial to understand whether observationally derived properties are directly comparable with intrinsic ones in simulations. To assess this, we build Schwarzschild dynamical models for MUSE-like IFS cubes (constructed to be like those obtained by the MAGPI survey) of 75 galaxies at z ~ 0.3 from the Eagle simulations. We compare the true particle-derived properties with the galaxies' model-derived properties. In general, we find that the models can recover the true galaxy properties qualitatively well, with the exception of the enclosed dark matter, where we find a median offset of 48%, which is due to the assumed NFW profile not being able to reproduce the dark matter distribution in the inner region of the galaxies. We then compare our model-derived properties with Schwarzschild models-derived properties of observed MAGPI galaxies and find good agreement between MAGPI and Eagle: the majority of our galaxies (57%) have non-oblate shapes within 1 effective radius. More triaxial galaxies show higher fractions of hot orbits in their inner regions and tend to be more radially anisotropic., Comment: 22 pages. Accepted for publication in MNRAS

Early prediction of seizures and timely interventions are vital for improving patients' quality of life. While seizure prediction has been shown in software-based implementations, to enable timely warnings of upcoming seizures, prediction must be done on an edge device to reduce latency. Ideally, such devices must also be low-power and track long-term drifts to minimize maintenance from the user. This work presents SPIRIT: Stochastic-gradient-descent-based Predictor with Integrated Retraining and In situ accuracy Tuning. SPIRIT is a complete system-on-a-chip (SoC) integrating an unsupervised online-learning seizure prediction classifier with eight 14.4 uW, 0.057 mm2, 90.5 dB dynamic range, Zoom Analog Frontends. SPIRIT achieves, on average, 97.5%/96.2% sensitivity/specificity respectively, predicting seizures an average of 8.4 minutes before they occur. Through its online learning algorithm, prediction accuracy improves by up to 15%, and prediction times extend by up to 7x, without any external intervention. Its classifier consumes 17.2 uW and occupies 0.14 mm2, the lowest reported for a prediction classifier by >134x in power and >5x in area. SPIRIT is also at least 5.6x more energy efficient than the state-of-the-art., Comment: Lacking critical data to prove an end-to-end verification of the system

The Zwicky Transient Facility SN Ia Data Release 2 (ZTF SN Ia DR2) contains more than 3,000 Type Ia supernovae (SNe Ia), providing the largest homogeneous low-redshift sample of SNe Ia. Having at least one spectrum per event, this data collection is ideal for large-scale statistical studies of the photometric, spectroscopic and host-galaxy properties of SNe Ia, particularly of the more rare "peculiar" subclasses. In this paper, we first present the method we developed to spectroscopically classify the SNe in the sample, and the techniques we used to model their multi-band light curves and explore their photometric properties. We then show a method to distinguish between the "peculiar" subtypes and the normal SNe Ia. We also explore the properties of their host galaxies and estimate their relative rates, focusing on the "peculiar" subtypes and their connection to the cosmologically useful SNe Ia. Finally, we discuss the implications of our study with respect to the progenitor systems of the "peculiar" SN Ia events., Comment: 19 pages, 13 figures, submitted to Astronomy and Astrophysics

We present a multi-wavelength analysis of MCG+11-11-032, a nearby AGN with the unique classification of both a binary and a dual AGN candidate. With new Chandra observations we aim to resolve any dual AGN system via imaging data, and search for signs of a binary AGN via analysis of the X-ray spectrum. Analyzing the Chandra spectrum, we find no evidence of previously suggested double-peaked Fe K$\alpha$ lines; the spectrum is instead best fit by an absorbed powerlaw with a single Fe K$\alpha$ line, as well as an additional line centered at $\approx$7.5 keV. The Chandra observation reveals faint, soft, and extended X-ray emission, possibly linked to low-level nuclear outflows. Further analysis shows evidence for a compact, hard source -- MCG+11-11-032 X2 -- located 3.27'' from the primary AGN. Modeling MCG+11-11-032 X2 as a compact source, we find that it is relatively luminous ($L_{\text{2$-$10 keV}} = 1.52_{-0.48}^{+0.96}\times 10^{41}$ erg s$^{-1}$), and the location is coincident with an compact and off-nuclear source resolved in Hubble Space Telescope infrared (F105W) and ultraviolet (F621M, F547M) bands. Pairing our X-ray results with a 144 MHz radio detection at the host galaxy location, we observe X-ray and radio properties similar to those of ESO 243-49 HLX-1, suggesting that MCG+11-11-032 X2 may be a hyper-luminous X-ray source. This detection with Chandra highlights the importance of a high-resolution X-ray imager, and how previous binary AGN candidates detected with large-aperture instruments benefit from high-resolution follow-up. Future spatially resolved optical spectra, and deeper X-ray observations, can better constrain the origin of MCG+11-11-032 X2., Comment: 16 pages, 7 figures, submitted to ApJ

A promising architecture for next-generation, low energy spintronic devices uses skyrmions -- nanoscale whirlpools of magnetic moment -- as information carriers. Notably, schemes for racetrack memory have been proposed in which skyrmions and antiskyrmions, their antiparticle, serve as the logical bits 1 and 0. However, major challenges exist to designing skyrmion-antiskyrmion based computing. The presence of both particles in one material is often mutually exclusive such that few systems have been identified in which they coexist, and in these systems their appearance is stochastic rather than deterministic. Here, we create a tunable skyrmion-antiskyrmion system in FeGe films through ion-irradiation and annealing, and detail the structural properties of the films under these various conditions. Specifically, we irradiate epitaxial B20-phase FeGe films with 2.8 MeV Au$^{4+}$ ions, showing evidence that the amorphized regions preferentially host antiskyrmions at densities controlled by the irradiation fluence. In this work, we focus on a subsequent, systematic electron diffraction study with in-situ annealing, demonstrating the ability to recrystallize controllable fractions of the material at temperatures ranging from approximately 150$^{\circ}$ C to 250$^{\circ}$ C, enabling further tunability of skyrmion/antiskyrmion populations. We describe the crystallization kinetics using the Johnson-Mehl-Avrami-Kolmogorov model, finding that growth of crystalline grains is consistent with diffusion-controlled one-to-two dimensional growth with a decreasing nucleation rate. The procedures developed here can be applied towards creation of skyrmion-antiskyrmion systems for energy-efficient, high-density data storage, spin wave emission produced by skyrmion-antiskyrmion pair annihilation, and more generally testbeds for research on skyrmion-antiskyrmion liquids and crystals.

The Green River Regional Educational Cooperative (GRREC) and its partners administered the STEM-CS intervention to support the professional learning of middle and high school STEM teachers in rural southcentral Kentucky counties. The goals of the STEM-CS intervention were to improve teacher STEM-CS knowledge, practice, implementation, and effectiveness, while also improving opportunities, access, and outcomes for high-need rural students in STEM-CS fields. GRREC recruited rural, disadvantaged schools from among their member school districts to participate in the intervention funded by the Education Innovation and Research (EIR) grant. The evaluation was designed to provide the most rigorous possible study of the impact of the STEM-CS intervention given the parameters presented by program implementation. Unfortunately, the most rigorous possible study design was underpowered for detecting hypothesized effect sizes of interest. The pre-registration of the study indicated a minimal detectable effect size (MDES) of 0.50, meaning that even if STEM-CS had moderate to large effect on students' mathematics proficiency, the study was unlikely to detect these changes. Despite the poor sensitivity to even very large effect sizes, the study was conducted to meet evaluation requirements. This impact evaluation focuses on the high school portion of the intervention, using a cluster quasi-experimental design (QED), with non-random assignment to treatment at the teacher level to estimate the impact of the STEM-CS intervention in high schools on student academic proficiency in mathematics at grade 10. The six high schools participating in the STEM-CS intervention were propensity score matched with 12 rural high schools from GRREC-member school districts, with the final analytic sample of students in grade 10 in the 2021-2022 academic year consisting of 380 students in treatment high schools and 1,120 students in comparison high schools. Though school-level characteristics after propensity score matching showed inadequate baseline balance on gender and percentage of economically disadvantaged students (likely due to the purposive recruitment), final baseline equivalency on students' grade 7 academic proficiency in mathematics was satisfied, with additional student characteristics showing adequate baseline balance as well. Using a multilevel regression model with blocking to account for the propensity score matching, final results indicated that the STEM-CS intervention was not statistically significantly related to differences in grade 10 students' academic proficiency in mathematics. [This document was produced by the Center for Evaluation, Policy, & Research (CEPR).]

We present the second data release of the MeerKAT Absorption Line Survey (MALS), consisting of wideband continuum catalogues of 391 pointings observed at L~band. The full wideband catalogue covers 4344 deg$^2$ of sky, reaches a depth of 10 $\mu$Jy beam$^{-1}$, and contains 971,980 sources. With its balance between survey depth and sky coverage, MALS DR2 covers five orders of magnitude of flux density, presenting a robust view of the extragalactic radio source population down to 200 $\mu$Jy. Using this catalogue, we perform a measurement of the cosmic radio dipole, an anisotropy in the number counts of radio sources with respect to the cosmic background, analogous to the dipole found in the cosmic microwave background (CMB). For this measurement, we present the characterisation of completeness and noise properties of the catalogue, and show that a declination-dependent systematic affects the number density of faint sources. In the dipole measurement on the MALS catalogue, we recover reasonable dipole measurements once we model the declination systematic with a linear fit between the size of the major axis of the restoring beam and the amount of sources of each pointing. The final results are consistent with the CMB dipole in terms of direction and amplitude, unlike many recent measurements of the cosmic radio dipole made with other centimetre wavelength catalogues, which generally show a significantly larger amplitude. This result demonstrates the value of dipole measurements with deeper and more sparse radio surveys, as the population of faint sources probed may have had a significant impact on the measured dipole., Comment: 25 pages, 14 figures. Accepted for publication in Astronomy & Astrophysics. The MALS wideband catalogues and images are publicly available at https://mals.iucaa.in

The discovery of the superconductivity in the infinite-layer nickelates, as topotactically reduced from their respective perovskite percussors via co-annealing with CaH2, extends the understanding in superconductivity. Nevertheless, whether the incorporated 1H composition is critical to the infinite-layer superconductivity recently arouses considerable debates, while the central challenge lies in the quantification of 1H that is easily interfered by the conventional electron or orbital associated processes. Herein, we demonstrate the irrelevance between the superconductivity in the infinite-layer nickelates and their incorporated 1H composition, assisted by nuclear reaction analysis (NRA) and heavy ion energy recoil detection analysis (HIERDA) based on the nuclear interactions at MeV energy scale. These approaches completely overwhelm the conventional interferes, such as ionization, activation and chemical bonds, and achieves the 1H quantification within superconducting La0.8Sr0.2NiO2 (or Nd0.8Sr0.2NiO2). A large diversity of 1H composition far beyond the previously expected critical dome was observed, while their TC were not changed significantly. Furthermore, the superconductivity was demonstrated to be achievable for La0.8Sr0.2NiO2 reduced by Al without any hydrogen associated process, while the superconducting properties for the CaH2 reduced La0.8Sr0.2NiO2 is rather stable after long term exposure in air, despite the high volatility of 1H within oxides. All these results indicate that the 1H incorporation composition is not critical to the superconductivity of the infinite-layer nickelates.

Sodium niobate, a lead-free ferroic material, hosts delicately-balanced, competing order parameters, including ferroelectric states that can be stabilized by epitaxial strain. Here, we show that the resulting macroscopic ferroelectricity exhibits an unconventional microscopic structure using multislice electron ptychography. This technique overcomes multiple scattering artifacts limiting conventional electron microscopy, enabling both lateral spatial resolution beyond the diffraction limit and recovery of three-dimensional structural information. These imaging capabilities allow us to separate the ferroelectric interior of the sample from the relaxed surface structure and identify the soft phonon mode and related structural distortions with picometer precision. Unlike conventional ferroelectric perovskites, we find that the polar distortion in this material involves minimal distortions of the cation sublattices and is instead dominated by anion displacements. We establish limits on film thickness for interfacial octahedral rotation engineering and directly visualize an incommensurate octahedral rotation pattern, arising from the flat dispersion of the associated phonon mode., Comment: 63 pages, 5 figures, 17 supplementary figures

Handling high-dimensional datasets presents substantial computational challenges, particularly when the number of features far exceeds the number of observations and when features are highly correlated. A modern approach to mitigate these issues is feature screening. In this work, the High-dimensional Ordinary Least-squares Projection (HOLP) feature screening method is advanced by employing adaptive ridge regularization. The impact of the ridge penalty on the Ridge-HOLP method is examined and Air-HOLP is proposed, a data-adaptive advance to Ridge-HOLP where the ridge-regularization parameter is selected iteratively and optimally for better feature screening performance. The proposed method addresses the challenges of penalty selection in high dimensions by offering a computationally efficient and stable alternative to traditional methods like bootstrapping and cross-validation. Air-HOLP is evaluated using simulated data and a prostate cancer genetic dataset. The empirical results demonstrate that Air-HOLP has improved performance over a large range of simulation settings. We provide R codes implementing the Air-HOLP feature screening method and integrating it into existing feature screening methods that utilize the HOLP formula.

KM3NeT/ORCA is a water Cherenkov neutrino detector under construction and anchored at the bottom of the Mediterranean Sea. The detector is designed to study oscillations of atmospheric neutrinos and determine the neutrino mass ordering. This paper focuses on an initial configuration of ORCA, referred to as ORCA6, which comprises six out of the foreseen 115 detection units of photo-sensors. A high-purity neutrino sample was extracted, corresponding to an exposure of 433 kton-years. The sample of 5828 neutrino candidates is analysed following a binned log-likelihood method in the reconstructed energy and cosine of the zenith angle. The atmospheric oscillation parameters are measured to be $\sin^2\theta_{23}= 0.51^{+0.04}_{-0.05}$, and $ \Delta m^2_{31} = 2.18^{+0.25}_{-0.35}\times 10^{-3}~\mathrm{eV^2} \cup \{-2.25,-1.76\}\times 10^{-3}~\mathrm{eV^2}$ at 68\% CL. The inverted neutrino mass ordering hypothesis is disfavoured with a p-value of 0.25., Comment: 29 pages, 12 figures

Despite advancements, fine-tuning Large Language Models (LLMs) remains costly due to the extensive parameter count and substantial data requirements for model generalization. Accessibility to computing resources remains a barrier for the open-source community. To address this challenge, we propose the In2Core algorithm, which selects a coreset by analyzing the correlation between training and evaluation samples with a trained model. Notably, we assess the model's internal gradients to estimate this relationship, aiming to rank the contribution of each training point. To enhance efficiency, we propose an optimization to compute influence functions with a reduced number of layers while achieving similar accuracy. By applying our algorithm to instruction fine-tuning data of LLMs, we can achieve similar performance with just 50% of the training data. Meantime, using influence functions to analyze model coverage to certain testing samples could provide a reliable and interpretable signal on the training set's coverage of those test points., Comment: EMNLP 2024 - Findings

With wide-field phased array feed technology, the Australian Square Kilometre Array Pathfinder (ASKAP) is ideally suited to search for seemingly rare radio transient sources. The Commensal Real-time ASKAP Fast Transient (CRAFT) Survey Science Project has developed instrumentation to continuously search for fast radio transients (duration $\lesssim$ 1 second) with ASKAP, with a particular focus on finding and localising Fast Radio Bursts (FRBs). Of particular interest are Fast Radio Bursts (FRBs). Since 2018, the CRAFT survey has been searching for FRBs and other fast transients by incoherently adding the intensities received by individual ASKAP antennas, and then correcting for the impact of frequency dispersion on these short-duration signals in the resultant incoherent sum (ICS) in real-time. This low-latency detection enables the triggering of voltage buffers, which facilitates the localisation of the transient source and the study spectro-polarimetric properties at high time resolution. Here we report the sample of 43 FRBs discovered in this CRAFT/ICS survey to date. This includes 22 FRBs that had not previously been reported: 16 FRBs localised by ASKAP to $\lesssim$ 1 arcsec and 6 FRBs localised to approximately 10 arcmin. Of the new arcsecond-localised FRBs, we have identified and characterised host galaxies (and measured redshifts) for 11. The median of all 30 measured host redshifts from the survey to date is z = 0.23. We summarise results from the searches, in particular those contributing to our understanding of the burst progenitors and emission mechanisms, and on the use of bursts as probes of intervening media. We conclude by foreshadowing future FRB surveys with ASKAP using a coherent detection system that is currently being commissioned., Comment: 37 pages, 23 Figures, 7 Tables. Submitted for publication in PASA

Electrodes for decoding speech from electromyography (EMG) are typically placed on the face, requiring adhesives that are inconvenient and skin-irritating if used regularly. We explore a different device form factor, where dry electrodes are placed around the neck instead. 11-word, multi-speaker voiced EMG classifiers trained on data recorded with this device achieve 92.7% accuracy. Ablation studies reveal the importance of having more than two electrodes on the neck, and phonological analyses reveal similar classification confusions between neck-only and neck-and-face form factors. Finally, speech-EMG correlation experiments demonstrate a linear relationship between many EMG spectrogram frequency bins and self-supervised speech representation dimensions.

Calls for engagement with the public in Artificial Intelligence (AI) research, development, and governance are increasing, leading to the use of surveys to capture people's values, perceptions, and experiences related to AI. In this paper, we critically examine the state of human participant surveys associated with these topics. Through both a reflexive analysis of a survey pilot spanning six countries and a systematic literature review of 44 papers featuring public surveys related to AI, we explore prominent perspectives and methodological nuances associated with surveys to date. We find that public surveys on AI topics are vulnerable to specific Western knowledge, values, and assumptions in their design, including in their positioning of ethical concepts and societal values, lack sufficient critical discourse surrounding deployment strategies, and demonstrate inconsistent forms of transparency in their reporting. Based on our findings, we distill provocations and heuristic questions for our community, to recognize the limitations of surveys for meeting the goals of engagement, and to cultivate shared principles to design, deploy, and interpret surveys cautiously and responsibly., Comment: To appear in 7th AAAI Conference on AI, Ethics, and Society (AIES)

Doping impurity atoms is a strategy commonly used to tune the functionality of materials including catalysts, semiconductors, and quantum emitters. The location of dopants and their interaction with surrounding atoms could significantly modulate the transport, optical, or magnetic properties of materials. However, directly imaging individual impurity atoms inside materials remains a generally unaddressed need. Here, we demonstrate how single atoms can be detected and located in three dimensions via multislice electron ptychography.Interstitial atoms in a complex garnet oxide heterostructure are resolved with a depth resolution better than 2.7 nm, together with a deep-sub-{\AA}ngstrom lateral resolution. Single-scan atomic-layer depth resolution should be possible using strongly divergent electron probe illumination. Our results provide a new approach to detecting individual atomic defects and open doors to characterize the local environments and spatial distributions that underlie a broad range of systems such as single-atom catalysts, nitrogen-vacancy centers, and other atomic-scale quantum sensors., Comment: 28 pages, 5 figures, 10 supplementary figures

The supersingular locus of the $\mathrm{GU}(1,n-1)$ Shimura variety at a ramified prime $p$ is stratified by Coxeter varieties attached to finite symplectic groups. In this paper, we compute the $\ell$-adic cohomology of the Zariski closure of any such stratum. These are known as closed Bruhat-Tits strata. We prove that the cohomology groups of odd degree vanish, and those of even degree are explicitely determined as representations of the symplectic group with a Frobenius action. Each closed Bruhat-Tits stratum is linearly stratified by Coxeter varieties attached to smaller symplectic groups. Thanks to results of Lusztig who computed the cohomology of Coxeter varieties for classical groups, we make use of the spectral sequence associated to this stratification and describe explicitely all the terms at infinity. We point out that the closed Bruhat-Tits strata have isolated singularities when the dimension is greater than 1. Our analysis requires discussing the smoothness of the blow-up at the singular points, as well as comparing the ordinary $\ell$-adic cohomology with intersection cohomology. A by-product of our computations is that these two cohomologies actually coincide, so that surprisingly the presence of singularities does not interfere with the cohomology., Comment: 26 pages. arXiv admin note: text overlap with arXiv:2212.09922

The PICOSEC Micromegas detector is a precise-timing gaseous detector based on a Cherenkov radiator coupled with a semi-transparent photocathode and a Micromegas amplifying structure, targeting a time resolution of tens of picoseconds for minimum ionising particles. Initial single-pad prototypes have demonstrated a time resolution below 25 ps, prompting ongoing developments to adapt the concept for applications. The achieved performance is being transferred to robust multi-channel detector modules suitable for large-area detection systems requiring excellent timing precision. To enhance the robustness and stability of the PICOSEC Micromegas detector, research on robust carbon-based photocathodes, including Diamond-Like Carbon (DLC) and Boron Carbide (B4C), is pursued. Results from prototypes equipped with DLC and B4C photocathodes exhibited a time resolution of approximately 32 ps and 34.5 ps, respectively. Efforts dedicated to improve detector robustness and stability enhance the feasibility of the PICOSEC Micromegas concept for large experiments, ensuring sustained performance while maintaining excellent timing precision.

More than 3000 spectroscopically confirmed Type Ia supernovae (SNe Ia) are presented in the Zwicky Transient Facility SN Ia Data Release 2 (ZTF DR2). In this paper, we detail the spectral properties of 482 SNe Ia near maximum light, up to a redshift limit of $z$ $\leq$ 0.06. We measure the velocities and pseudo-equivalent widths (pEW) of key spectral features (Si II $\lambda$5972 and Si II $\lambda$6355) and investigate the relation between the properties of the spectral features and the photometric properties from the SALT2 light-curve parameters as a function of spectroscopic sub-class. We discuss the non-negligible impact of host galaxy contamination on SN Ia spectral classifications, as well as investigate the accuracy of spectral template matching of the ZTF DR2 sample. We define a new subclass of underluminous SNe Ia (`04gs-like') that lie spectroscopically between normal SNe Ia and transitional 86G-like SNe Ia (stronger Si II $\lambda$5972 than normal SNe Ia but significantly weaker Ti II features than `86G-like' SNe). We model these `04gs-like' SN Ia spectra using the radiative-transfer spectral synthesis code tardis and show that cooler temperatures alone are unable to explain their spectra; some changes in elemental abundances are also required. However, the broad continuity in spectral properties seen from bright (`91T-like') to faint normal SN Ia, including the transitional and 91bg-like SNe Ia, suggests that variations within a single explosion model may be able to explain their behaviour.

We extend the lattice-theoretic approach of Brandhorst--Cattaneo to classify algebraically trivial actions on the known IHS manifolds, up to deformation and birational conjugacy. In particular, we classify even order algebraically trivial non symplectic automorphisms, with or without trivial discriminant action. In the case of nontrivial discriminant actions, we show that such automorphisms exist only for finitely many known deformation types and orders., Comment: 41 pages, 7 tables. Comments welcome!

We introduce and describe a new heuristic method for finding an upper bound on the degree of contextuality and the corresponding unsatisfied part of a quantum contextual configuration with three-element contexts (i.e., lines) located in a multi-qubit symplectic polar space of order two. While the previously used method based on a SAT solver was limited to three qubits, this new method is much faster and more versatile, enabling us to also handle four- to six-qubit cases. The four-qubit unsatisfied configurations we found are quite remarkable. That of an elliptic quadric features 315 lines and has in its core three copies of the split Cayley hexagon of order two having a Heawood-graph-underpinned geometry in common. That of a hyperbolic quadric also has 315 lines but, as a point-line incidence structure, is isomorphic to the dual $\mathcal{DW}(5,2)$ of $\mathcal{W}(5,2)$. Finally, an unsatisfied configuration with 1575 lines associated with all the lines/contexts of the four-qubit space contains a distinguished $\mathcal{DW}(5,2)$ centered on a point-plane incidence graph of PG$(3,2)$. The corresponding configurations found in the five-qubit space exhibit a considerably higher degree of complexity, except for a hyperbolic quadric, whose 6975 unsatisfied contexts are compactified around the point-hyperplane incidence graph of PG$(4,2)$. The most remarkable unsatisfied patterns discovered in the six-qubit space are a couple of disjoint split Cayley hexagons (for the full space) and a subgeometry underpinned by the complete bipartite graph $K_{7,7}$ (for a hyperbolic quadric)., Comment: 35 pages, 14 figures

Localisation of fast radio bursts (FRBs) to arcsecond and sub-arcsecond precision maximizes their potential as cosmological probes. To that end, FRB detection instruments are deploying triggered complex-voltage capture systems to localize FRBs, identify their host galaxy and measure a redshift. Here, we report the discovery and localisation of two FRBs (20220717A and 20220905A) that were captured by the transient buffer system deployed by the MeerTRAP instrument at the MeerKAT telescope in South Africa. We were able to localize the FRBs to a precision of $\sim$1 arc-second that allowed us to unambiguously identify the host galaxy for FRB 20220717A (posterior probability$\sim$0.97). FRB 20220905A lies in a crowded region of the sky with a tentative identification of a host galaxy but the faintness and the difficulty in obtaining an optical spectrum preclude a conclusive association. The bursts show low linear polarization fractions (10--17$\%$) that conform to the large diversity in the polarization fraction observed in apparently non-repeating FRBs akin to single pulses from neutron stars. We also show that the host galaxy of FRB 20220717A contributes roughly 15$\%$ of the total dispersion measure (DM), indicating that it is located in a plasma-rich part of the host galaxy which can explain the large rotation measure. The scattering in FRB 20220717A can be mostly attributed to the host galaxy and the intervening medium and is consistent with what is seen in the wider FRB population., Comment: 13 pages, 8 figures, 1 Appendix, revised version after addressing the reviewer's comments

High-significance evidences of the existence of a high-energy diffuse flux of cosmic neutrinos have emerged in the last decade from several observations by the IceCube Collaboration. The ANTARES neutrino telescope took data for 15 years in the Mediterranean Sea, from 2007 to 2022, and collected a high-purity all-flavour neutrino sample. The search for a diffuse cosmic neutrino signal using this dataset is presented in this article. This final analysis did not provide a statistically significant observation of the cosmic diffuse flux. However, this is converted into limits on the properties of the cosmic neutrino spectrum. In particular, given the sensitivity of the ANTARES neutrino telescope between 1 and 50 TeV, constraints on single-power-law hypotheses are derived for the cosmic diffuse flux below 20 TeV, especially for power-law fits of the IceCube data with spectral index softer than 2.8.

We describe the planned near-term and potential longer-term upgrades of the Belle II detector at the SuperKEKB electron-positron collider operating at the KEK laboratory in Tsukuba, Japan. These upgrades will allow increasingly sensitive searches for possible new physics beyond the Standard Model in flavor, tau, electroweak and dark sector physics that are both complementary to and competitive with the LHC and other experiments., Comment: Editor: F. Forti 170 pages

We present the findings of a study based on a new inelastic electron-scattering experiment on the ${}^{12}\mathrm{C}$ nucleus focusing on the kinematic region of $Q^2=0.8\,\mathrm{GeV}^2/{c}^2$. The measured cross section is sensitive to the transverse response function and provides a stringent test of theoretical models, as well as of the theoretical assumptions made in Monte-Carlo event-generator codes developed for the interpretation of neutrino-nucleus experiments, such as DUNE and HyperK. We find that modern generators such as GENIE and GiBUU reproduce our new experimental data within 10$\%$.

Hot Jupiters generally do not have nearby planet companions, as they may have cleared out other planets during their inward migration from more distant orbits. This gives evidence that hot Jupiters more often migrate inward via high-eccentricity migration due to dynamical interactions between planets rather than more dynamically cool migration mechanisms through the protoplanetary disk. Here we further refine the unique system of WASP-132 by characterizing the mass of the recently validated 1.0-day period super-Earth WASP-132c (TOI-822.02) interior to the 7.1-day period hot Jupiter WASP-132b. Additionally, we announce the discovery of a giant planet at a 5-year period (2.7 AU). We also detect a long-term trend in the radial velocity data indicative of another outer companion. Using over nine years of CORALIE RVs and over two months of highly-sampled HARPS RVs, we determine the masses of the planets from smallest to largest orbital period to be M$_{\rm{c}}$ = $6.26^{+1.84}_{-1.83}$ $M_{\oplus}$, M$_{\rm{b}}$ = $0.428^{+0.015}_{-0.015}$ $M_{\rm{Jup}}$, and M$_{\rm{d}}\sin{i}$ = $5.16^{+0.52}_{-0.52}$ $M_{\rm{Jup}}$, respectively. Using TESS and CHEOPS photometry data we measure the radii of the two inner transiting planets to be $1.841^{+0.094}_{-0.093}$ $R_{\oplus}$ and $0.901^{+0.038}_{-0.038}$ $R_{\rm{Jup}}$. WASP-132 is a unique multi-planetary system in that both an inner rocky planet and an outer giant planet are in a system with a hot Jupiter. This suggests it migrated via a more rare dynamically cool mechanism and helps to further our understanding of how hot Jupiter systems may form and evolve., Comment: 19 Pages, 15 figures, in review process with Astronomy & Astrophysics

Low-Rank Adaptation (LoRA) methods have gained popularity in efficient parameter fine-tuning of models containing hundreds of billions of parameters. In this work, instead, we demonstrate the application of LoRA methods to train small-vision models in Federated Learning (FL) from scratch. We first propose an aggregation-agnostic method to integrate LoRA within FL, named FLoCoRA, showing that the method is capable of reducing communication costs by 4.8 times, while having less than 1% accuracy degradation, for a CIFAR-10 classification task with a ResNet-8. Next, we show that the same method can be extended with an affine quantization scheme, dividing the communication cost by 18.6 times, while comparing it with the standard method, with still less than 1% of accuracy loss, tested with on a ResNet-18 model. Our formulation represents a strong baseline for message size reduction, even when compared to conventional model compression works, while also reducing the training memory requirements due to the low-rank adaptation.