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In this work we carry out an analysis of star-formation and nuclear activity in the different stages during a galaxy merger identified in isolated systems (isolated galaxies, isolated pairs, and isolated triplets) using integral field spectroscopy from the SDSS-IV/MaNGA project. We classify galaxies into close pairs, pre-mergers, mergers, and post-mergers (including galaxies with post-starburst spectroscopic features), for a total sample of 137 galaxies. We constrained their star formation history from spectrophotometric SED fitting with CIGALE, and used spatially resolved WHAN diagrams, with other MaNGA data products to explore if there is any connection of their physical properties with their merging stage. In general, galaxies show characteristic properties intrinsically related to each stage of the merger process. Galaxies in the merger and post-merger stages present higher star formation activity (measured by their integrated sSFR). In the merger stage, the fraction of strong AGN spaxels is comparable to the fraction of spaxels with pure star-formation emission, with no difference between AGN activity in close pairs and strongly interacting galaxies with the same stellar mass. Our results support the scenario where galaxy interactions trigger star-formation and nuclear activity on galaxies. Nonetheless, AGN has a minor role in quenching galaxies following a merger, as AGN feedback might not have had sufficient time to inhibit star formation. In addition, we found that the quenching process in post-mergers galaxies with post-starburst emission is happening outside-in, being an observational proof of the effect of interactions on the quenching process. The transforming processes after a recent major galaxy interaction may happen slowly on isolated environments, where the system evolves in a common dark matter halo without any perturbation of external galaxies., Comment: Accepted for publication in A&A, 30 pages, 24 figures, and 6 tables

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20\% increase in the efficiency of sub-1\,cm vertex reconstruction across all neutrino flavours., Comment: 32 pages, 18 figures

Quantum language models are the alternative to classical language models, which borrow concepts and methods from quantum machine learning and computational linguistics. While several quantum natural language processing (QNLP) methods and frameworks exist for text classification and generation, there is a lack of systematic study to compare the performance across various ans\"atze, in terms of their hyperparameters and classical and quantum methods to implement them. Here, we evaluate the performance of quantum natural language processing models based on these ans\"atze at different levels in text classification tasks. We perform a comparative study and optimize the QNLP models by fine-tuning several critical hyperparameters. Our results demonstrate how the balance between simplification and expressivity affects model performance. This study provides extensive data to improve our understanding of QNLP models and opens the possibility of developing better QNLP algorithms., Comment: 10 pages, 6 figures

In this article, we present a Latent Diffusion Model (LDM) for the generation of brain Magnetic Resonance Imaging (MRI), conditioning its generation based on pathology (Healthy, Glioblastoma, Sclerosis, Dementia) and acquisition modality (T1w, T1ce, T2w, Flair, PD). To evaluate the quality of the generated images, the Fr\'echet Inception Distance (FID) and Multi-Scale Structural Similarity Index (MS-SSIM) metrics were employed. The results indicate that the model generates images with a distribution similar to real ones, maintaining a balance between visual fidelity and diversity. Additionally, the model demonstrates extrapolation capability, enabling the generation of configurations that were not present in the training data. The results validate the potential of the model to increase in the number of samples in clinical datasets, balancing underrepresented classes, and evaluating AI models in medicine, contributing to the development of diagnostic tools in radiology without compromising patient privacy.

HERMES Pathfinder is an in-orbit demonstration consisting of a constellation of six 3U cubesats hosting simple but innovative X-ray/gamma-ray detectors for the monitoring of cosmic high-energy transients. HERMES-PF, funded by ASI and by the EC Horizon 2020 grant, is scheduled for launch in Q1 2025. An identical X-ray/gamma-ray detector is hosted by the Australian 6U cubesat SpIRIT, launched on December 1st 2023. The main objective of HERMES-PF/SpIRIT is to demonstrate that high energy cosmic transients can be detected efficiently by miniatured hardware and localized using triangulation techniques. The HERMES-PF X-ray/gamma-ray detector is made by 60 GAGG:Ce scintillator crystals and 12 2x5 silicon drift detector (SDD) mosaics, used to detect both the cosmic X-rays directly and the optical photons produced by gamma-ray interactions with the scintillator crystals. This design provides a unique broad band spectral coverage from a few keV to a few MeV. Furthermore, the use of fast GAGG:Ce crystals and small SDD cells allows us to reach an exquisite time resolution better than a microsecond. We present a progress report on the missions focusing the discussion on the scientific innovation of the project and on the main lessons learned during the project development including: the importance and the challenges of using distributed architectures to achieve ambitious scientific objectives; the importance of developing critical technologies under science agreements for the realization of high-performing but low-cost payloads; best use of COTS technologies in scientific missions. We finally discuss the prospects of applying these concepts for the creation of an all-sky, all-time monitor to search for the high-energy counterparts of gravitational wave events that Advanced LIGO/Virgo/Kagra will find at the end of this decade and the Einstein Telescope during the 2030s., Comment: proceedings of the 75th International Astronautical Congress (IAC), Milan, Italy, 14-18 October 2024

We obtain a partial answer to the $3$-space problem for isomorphic polyhedrality: every twisted sum of $C(\alpha)$, $\alpha<\omega_1$ with a separable isomorphically polyhedral space with the BAP, is isomorphically polyhedral. We obtain other related results of independent interest; for instance, that every twisted sum of $c_0(\kappa)$ and a Banach space having a boundary with property $(*)$ has a boundary with property $(*)$.

Despite the prevalence of sleep-tracking devices, many individuals struggle to translate data into actionable improvements in sleep health. Current methods often provide data-driven suggestions but may not be feasible and adaptive to real-life constraints and individual contexts. We present HealthGuru, a novel large language model-powered chatbot to enhance sleep health through data-driven, theory-guided, and adaptive recommendations with conversational behavior change support. HealthGuru's multi-agent framework integrates wearable device data, contextual information, and a contextual multi-armed bandit model to suggest tailored sleep-enhancing activities. The system facilitates natural conversations while incorporating data-driven insights and theoretical behavior change techniques. Our eight-week in-the-wild deployment study with 16 participants compared HealthGuru to a baseline chatbot. Results show improved metrics like sleep duration and activity scores, higher quality responses, and increased user motivation for behavior change with HealthGuru. We also identify challenges and design considerations for personalization and user engagement in health chatbots., Comment: Accepted to CHI Conference on Human Factors in Computing Systems (CHI 2025)

Let $\mathbf{F}$ be a real extension of $\mathbb{Q}$, $G$ a finite group and $\mathbf{F}G$ its group algebra. Given both a group homomorphism $\sigma:G\rightarrow \{\pm1\}$ (called an orientation) and a group involution $^\ast:G \rightarrow G$ such that $gg^\ast\in N=ker(\sigma)$, an oriented group involution $\circledast$ of $\mathbf{F}G$ is defined by $\alpha=\sum_{g\in G}\alpha_{g}g \mapsto \alpha^\circledast=\sum_{g\in G}\alpha_{g}\sigma(g)g^{\ast}$. In this paper, in case the involution on $G$ is the classical one, $x\mapsto x^{-1}$, $\beta=x+x^{-1}$ is a skew-symmetric element in $\mathbf{F}G$ such that $1+\beta$ is invertible, for $x\in G$ with $\sigma(x)=-1$, we consider Cayley unitary elements built out of $\beta$. We prove that the coefficients of $(1+\beta)^{-1}$ involve an interesting sequence which is a Fibonacci-like sequence., Comment: 10 pages

We investigate the performance of Opticks, an NVIDIA OptiX API 7.5 GPU-accelerated photon propagation compared with a single-threaded Geant4 simulation. We compare the simulations using an improved model of the NEXT-CRAB-0 gaseous time projection chamber. Performance results suggest that Opticks improves simulation speeds by between $58.47\pm{0.02}$ and $181.39\pm{0.28}$ times relative to a CPU-only Geant4 simulation and these results vary between different types of GPU and CPU. A detailed comparison shows that the number of detected photons, along with their times and wavelengths, are in good agreement between Opticks and Geant4., Comment: 12 pages, 8 Figures

This paper examines the role of manner-of-motion verbs in shaping subjective temporal perception and emotional resonance. Through four complementary studies, we explore how these verbs influence the conceptualization of time, examining their use in literal and metaphorical (temporal) contexts. Our findings reveal that faster verbs (e.g., fly, zoom) evoke dynamic and engaging temporal experiences, often linked to positive emotions and greater agency. In contrast, slower verbs (e.g., crawl, drag) convey passivity, monotony, and negative emotions, reflecting tedious or constrained experiences of time. These effects are amplified in metaphorical contexts, where manner verbs encode emotional and experiential nuances that transcend their literal meanings. We also find that participants prefer manner verbs over path verbs (e.g., go, pass) in emotionally charged temporal contexts, as manner verbs capture the experiential and emotional qualities of time more effectively. These findings highlight the interplay between language, motion, and emotion in shaping temporal perception, offering insights into how linguistic framing influences subjective experiences of time.

Machine learning applications in high-stakes scenarios should always operate under human oversight. Developing an optimal combination of human and machine intelligence requires an understanding of their complementarities, particularly regarding the similarities and differences in the way they make mistakes. We perform extensive experiments in the area of face recognition and compare two automated face recognition systems against human annotators through a demographically balanced user study. Our research uncovers important ways in which machine learning errors and human errors differ from each other, and suggests potential strategies in which human-machine collaboration can improve accuracy in face recognition.

Ultraluminous X-ray sources (ULX) are extragalactic objects with X-ray luminosities above the Eddington limit for a 10 Msun black hole (BH). ULXs may host super-Eddington accreting neutron stars or stellar mass BH, although the exact proportion of the two populations is not yet known. We investigate the properties of the ULX NGC 4559 X7, which shows flux variability up to a factor of 5 on months-to-years and hours-to-days timescales. A flaring activity was also observed during the source highest flux epochs. Flares are unpredictable, with different durations and all flat-topped in flux. The latter suggests that, at the flare peaks, there is likely a common switch-off mechanism for the accretion onto the compact object. We analysed all the available XMM-Newton and Swift/XRT observations to investigate the spectral and temporal evolution of X7, looking for short and long-term variability. We look for long-term periodicities and for coherent signals through accelerated searches that included orbital corrections. We described the X7 spectra with two thermal components plus a cut-off powerlaw model. We found three well defined spectral states, where the spectral variability is mainly driven by the two harder components. In addition, a pulsed signal at 2.6-2.7s was detected in two XMM-Newton observations. The significance of these coherent signals is relatively weak but they are found in two different observations with the same parameter space for the orbital properties. If confirmed, it would imply a high spin-down of 1e-9 s/s, which could be extreme amongst the known pulsating ULXs. X7 would become a new extragalactic ULX pulsar. We discuss the spectral and temporal results of X7 in the context of super-Eddington accretion onto a stellar-mass compact object, in particular suggesting that the source might likely host a neutron star., Comment: Accepted for publication in A&A; 18 pages, 13 figures and 4 tables

If neutrinoless double beta decay is discovered, the next natural step would be understanding the lepton number violating physics responsible for it. Several alternatives exist beyond the exchange of light neutrinos. Some of these mechanisms can be distinguished by measuring phase-space observables, namely the opening angle $\cos\theta$ among the two decay electrons, and the electron energy spectra, $T_1$ and $T_2$. In this work, we study the statistical accuracy and precision in measuring these kinematic observables in a future xenon gas detector with the added capability to precisely locate the decay vertex. For realistic detector conditions (a gas pressure of 10 bar and spatial resolution of 4 mm), we find that the average $\overline{\cos\theta}$ and $\overline{T_1}$ values can be reconstructed with a precision of 0.19 and 110 keV, respectively, assuming that only 10 neutrinoless double beta decay events are detected., Comment: 19 pages, 8 figures

The Ultimate Fighting Championship (UFC) has grown from a niche combat sport promotion into a globally recognized competitive enterprise. This study applies complex network analysis to explore the structural evolution of UFC matchmaking and its impact on competitive dynamics, fighter prominence, and audience engagement. By constructing directed and undirected networks where fighters represent nodes and bouts define edges, we examine key metrics such as degree distribution, clustering, betweenness centrality, and eigenvector centrality. Our findings reveal how the UFC's matchmaking strategies transitioned from tightly clustered, repetitive matchups in its early years to a more decentralized and strategically curated fight network. We identify distinct structural properties between winners and losers, showing that successful fighters maintain centrality while frequently losing fighters exhibit surprising degrees of sustained connectivity. Correlations with Pay-Per-View sales and Google search trends suggest that network dispersion and novelty in matchups drive greater audience interest, while excessive clustering and density reduce engagement. Furthermore, comparisons with official rankings (Pound-for-Pound, champions, and top-15 fighters) demonstrate that traditional success metrics only partially align with network-based prominence, highlighting the complex interplay between structural connectivity, commercial appeal, and competitive success. This research contributes to the understanding of sports as complex adaptive systems and provides insights into how strategic matchmaking shapes both competitive integrity and economic viability in professional mixed martial arts., Comment: 27 pages, 21 figures, 1 table

In this paper, we introduce a new category of simplicial effects that extends the categories of effect algebras and their multi-object counterpart, effect algebroids. Our approach is based on relaxing the associativity condition satisfied by effect algebras and, more generally, partial monoids. Within this framework, simplicial effects and weakly associative partial groups arise as two extreme cases in the category of weak partial monoids. Our motivation is to capture simplicial structures from the theory of simplicial distributions and measurements that behave like effects., Comment: 45 pages, 4 figures

By addressing a long-standing open problem, listed in a highly regarded collection of open questions in the field and described as a "worthwhile research project", this note extends Markov's theorem (Markoff, Math. Ann., 27:177-182, 1886) on the variation of zeros of orthogonal polynomials on the real line to the setting of multiple orthogonal polynomials on Angelesco sets. The analysis reveals that the only distinction from the classical 1886 result lies in establishing sufficient conditions for a given $\mathcal{Z}$-matrix--which, in the Markov case, is the identity matrix--to be an $\mathcal{M}$-matrix. In contrast to most existing studies, which often present highly technical proofs for specific results, this note seeks to provide a simple proof of a general result without imposing restrictions on the weight functions (such as their potential "classical" nature), the number of intervals, or the structure of the partition.

Several detection strategies for wave-like dark matter make use of gradients in the dark matter field, e.g. searches for spin-dependent derivative interactions in CASPEr-wind or experiments looking for oscillating forces. These gradients are usually suppressed by the local dark matter velocity $\sim 10^{-3}$. In this note we investigate how these gradients are modified in the presence of additional quadratic interactions of the dark matter field with ordinary matter. In this case the dark matter density and field are modified in the vicinity of Earth, affecting the detection sensitivity due to the change in the local field value at the Earth's surface but also due to the gradient of the field profile itself. We also use this opportunity to present results on the expected field profiles in presence of a non-vanishing relative velocity of the dark matter with respect to Earth. We also comment how this ameliorates the divergences that appear for certain attractive coupling values., Comment: 28 pages, 8 figures

Ab initio downfolding describes the electronic structure of materials within a low-energy subspace, often around the Fermi level. Typically starting from mean-field calculations, this framework allows for the calculation of one- and two-electron interactions, and the parametrization of a many-body Hamiltonian representing the active space of interest. The subsequent solution of such Hamiltonians can provide insights into the physics of strongly-correlated materials. While phonons can substantially screen electron-electron interactions, electron-phonon coupling has been commonly ignored within ab initio downfolding, and when considered this is done only for short-range interactions. Here we propose a theory of ab initio downfolding that accounts for all mechanisms of electron-phonon coupling on equal footing, regardless of the range of the interactions. Our practical computational implementation is readily compatible with current downfolding approaches. We apply our approach to polar materials MgO and GeTe, and we reveal the importance of both short-range and long-range electron-phonon coupling in determining the magnitude of electron-electron interactions. Our results show that in the static limit, phonons reduce the on-site repulsion between electrons by 40% for MgO, and by 79% for GeTe. Our framework also predicts that overall attractive nearest-neighbor interactions arise between electrons in GeTe, consistent with superconductivity in this material.

Small-scale magnetic flux emergence in the quiet Sun is crucial for maintaining solar magnetic activity. On the smallest scales studied so far, namely within individual granules, two mechanisms have been identified: emergence in tiny magnetic loops and emergence in the form of magnetic flux sheets covering the granule. While there are abundant observations of tiny magnetic loops within granules, the evidence for the emergence of granule-covering magnetic sheets is much more limited. This work aims to statistically analyze magnetic flux sheets, quantify their frequency on the solar surface and their potential contribution to the solar magnetic budget in the photosphere, and investigate the plasma dynamics and granular-scale phenomena associated with their emergence. Using spectro-polarimetric datasets from the solar optical telescope aboard the Hinode satellite and the ground-based Swedish Solar telescope, we developed a two-step method to identify magnetic flux sheet emergence events, detecting magnetic flux patches based on the calculation of the transverse and longitudinal magnetic flux density and associating them with their host granules based on velocity field analysis. We identified 42 events of magnetic flux sheet emergence and characterized their magnetic properties and the associated plasma dynamics of their host granules. Our results align with numerical simulations, indicating a similar occurrence rate. We investigated the relationship between magnetic flux emergence and granular phenomena, finding that flux sheets often emerge in association with standard nascent granules, as well as exploding granules, or granules with granular lanes. In particular, we highlight the potential role of recycled magnetic flux from downflow regions in facilitating flux sheet emergence., Comment: Accepted for publication A&A

Superconductivity in doped SrTiO$_3$ was discovered in 1964, the first superconducting transition observed in a doped semiconductor. However, the mechanism behind electron pairing in SrTiO$_3$ remains a subject of debate. By developing a theoretical framework to incorporate dynamical lattice screening in the electronic Coulomb interactions of semiconductors and insulators, we demonstrate analytically that long-range electron-phonon interactions described by a generalized multi-phonon Fr\"ohlich mechanism result in phonon-mediated electron-electron attraction in SrTiO$_3$. Moreover, by combining our theory with first-principles calculations, we reveal an additional attractive interaction between electrons in SrTiO$_3$ due to the deformation potential mechanism, arising from the mixed ionic-covalent character of the Ti-O bond. Our results may have implications for the emergence of phonon-mediated electron attraction and superconductivity in a broader range of materials.

The work of Emergency Management (EM) agencies requires timely collection of relevant data to inform decision-making for operations and public communication before, during, and after a disaster. However, the limited human resources available to deploy for field data collection is a persistent problem for EM agencies. Thus, many of these agencies have started leveraging social media as a supplemental data source and a new venue to engage with the public. While prior research has analyzed the potential benefits and attitudes of practitioners and the public when leveraging social media during disasters, a gap exists in the critical analysis of the actual practices and uses of social media among EM agencies, across both geographical regions and phases of the EM lifecycle - typically mitigation, preparedness, response, and recovery. In this paper, we conduct a mixed-method analysis to update and fill this gap on how EM practitioners in the U.S. and Europe use social media, building on a survey study of about 150 professionals and a follow-up interview study with 11 participants. The results indicate that using social media is no longer a non-traditional practice in operational and informational processes for the decision-making of EM agencies working at both the local level (e.g., county or town) and non-local level (e.g., state/province, federal/national) for emergency management. Especially, the practitioners affiliated with agencies working at the local level have a very high perceived value of social media for situational awareness (e.g., analyzing disaster extent and impact) and public communication (e.g., disseminating timely information and correcting errors in crisis coverage). We conclude with the policy, technological, and socio-technical needs to design future social media analytics systems to support the work of EM agencies in such communication including the applications of AI., Comment: To appear at CSCW 2025 (PACMHCI - Proceedings of the ACM on Human Computer Interaction)

We introduce conditions on cones of normal toric varieties under which the polyhedron defining the normalized Nash blowup does not depend on the characteristic of the base field. As a consequence, we deduce several results on the resolution of singularities properties of normalized Nash blowups. In particular, we recover all known results of the families that can be resolved via normalized Nash blowups in positive characteristic. We also provide new families of toric varieties whose normalized Nash blowup is non-singular in arbitrary characteristic., Comment: 23 pages, 3 figures

We present measurements and simulations of the polarization purity of leaky lens-antenna coupled microwave Kinetic Inductance Detectors (KIDs) at 1.5 THz. We find the integrated cross-polarization level to be at -21.5 dB for 1 f\#$\lambda$ spatial sampling. The measurements agree well with the theoretical description which is based on a combination of in-transmission simulation of the antenna feed, and an in-reception analysis of the antenna-KID system. Combined with the measured noise equivalent power of 5--7$\times$10$^{-20}$ W/$\sqrt{\mathrm{Hz}}$, these detectors are excellent candidates for large scale and high performance imaging polarimetric instruments., Comment: This work has been submitted to IEEE Transactions of THz Science and Technology for possible publication

It has been recently shown that cosmological models with scale-dependent primordial non-Gaussianities (sPNG) could provide a possible path to solve current cosmic tensions. Moreover, it has been pointed out that some of these models might mimic the effects of Warm Dark Matter (WDM) for several observables at low redshift. Here, we confirm the qualitative similarity of the matter power spectrum for sPNG and WDM models, but also point out differences in the halo mass function and void size function. We then jointly simulate WDM and sPNG together. Such simulations allow us to demonstrate that the joint impact of WDM and sPNG is close to the linear superposition of their respective effects at low redshift, at the percent level. We finally propose a model with mixed hot and cold dark matter together with sPNG, that reproduces the $\Lambda$CDM power spectrum at redshifts $z \leq 3$ but is still distinct in terms of halo statistics., Comment: 13 pages, 7 figures, comments welcome :)

The polynomial affine model of gravity was proposed as an alternative to metric and metric-affine gravitational models. What at the beginning was thought as a source of unpredictability, the presence of many terms in the action, turned out to be a milestone, since it contains all possible combinations of the fields compatible with the covariance under diffeomorphisms. Here, we present a review of the advances in the analysis of the model after ten years of its proposal, and sketch the guideline of our future perspectives., Comment: revtex4-2. Main: 22 pag., Appendix: 2 pag. Biblography: 4 pag

Machine Learning (ML) algorithms are vital for supporting clinical decision-making in biomedical informatics. However, their predictive performance can vary across demographic groups, often due to the underrepresentation of historically marginalized populations in training datasets. The investigation reveals widespread sex- and age-related inequities in chronic disease datasets and their derived ML models. Thus, a novel analytical framework is introduced, combining systematic arbitrariness with traditional metrics like accuracy and data complexity. The analysis of data from over 25,000 individuals with chronic diseases revealed mild sex-related disparities, favoring predictive accuracy for males, and significant age-related differences, with better accuracy for younger patients. Notably, older patients showed inconsistent predictive accuracy across seven datasets, linked to higher data complexity and lower model performance. This highlights that representativeness in training data alone does not guarantee equitable outcomes, and model arbitrariness must be addressed before deploying models in clinical settings., Comment: This paper will be presented in American Medical Informatics Association (AMIA) Informatics Summit Conference 2025 (Pittsburgh, PA). 10 pages, 2 figures, 5 tables

Metal halide perovskite solar cells (MHPSCs) hold great promise related to their high efficiency and low fabrication costs, but their long-term stability under environmental conditions remains a major challenge. In this study, we demonstrate an effective protection strategy to enhance the stability of MHPSCs through the incorporation of a double passivation layer based on an adamantane-based plasma polymer (ADA) at both the electron transport layer (ETL)/perovskite and perovskite/hole transport layer (HTL) interfaces. Our results show that the implemented ADA deposition technique is compatible with delicate substrates such as perovskites thin films, as their optical, morphological and optoelectronic properties are unaltered upon ADA deposition. At the same time, it provides effective protection to the perovskite material in high humidity environments. The ADA-double passivation not only reduces the formation of mobile ionic defects that cause additional recombination, but also significantly reduces humidity-induced degradation and mitigates the photocatalytic degradation caused by TiO2 under UV exposure. Stability tests performed under 100% relative humidity and continuous AM 1.5G illumination (ISOS-L-1) show that ADA dual passivated devices retained 80% of their initial efficiency after 4000 minutes, while reference samples dropped to 30%. The enhanced performance of ADA-passivated cells is attributed to protective nature of the plasma polymer layer resulting in a preservation of photocurrent and the prevention of new recombination routes. This dual passivation strategy offers a promising route to improve the environmental stability of PSCs and extend their operational lifetime.

This article proposes a framework for estimating temperature fields in food-freezing applications that significantly reduces computational load while ensuring accurate temperature monitoring, representing a promising technological tool for optimizing and controlling food engineering processes. The strategy is based on (i) a mathematical model of a convection-dominated problem coupling thermal convection and turbulence and (ii) a least-squares approach for solving the inverse data assimilation problem, regularized by projecting the governing dynamics onto a reduced-order model (ROM). The unsteady freezing process considers an idealized salmon slice in a freezer cabinet, modeled with temperature-dependent thermophysical properties. The forward problem is approximated using a third-order WENO finite volume solver, including an optimized second-order backward scheme for time discretization. We employ our data assimilation framework to reconstruct the temperature field from a limited number of sensor data and to estimate temperature distributions within frozen food. Sensor placement is optimized using a new greedy algorithm, relying on maximizing the observability of the reduced-order dynamics for a fixed set of sensors. The proposed approach allows efficient extrapolation from external sensor measurements to the internal temperature of the food, which is crucial for maintaining food quality.

Robotic telescope networks play an important role in capturing early and bright optical afterglows, providing critical insights into the energetics and emission mechanisms of GRBs. In this study, we analyze GRB 230204B, an exceptionally energetic and multi-pulsed long GRB, detected by the Fermi GBM and MAXI detectors, with an isotropic equivalent gamma-ray energy exceeding 10$^{54}$ erg. Time-resolved spectral analysis reveals a transition in the prompt emission from hard (sub-photospheric dominated) spectra during early pulses to softer (synchrotron radiation dominated) spectra in later pulses, indicative of a hybrid jet composition. We report the discovery and characterization of the optical afterglow using the MASTER and BOOTES robotic telescope networks, alongside long-term radio observations extending to 335 days post-burst with the ATCA. At ~1.3 ks post-burst, the optical luminosity was exceptionally high, surpassing even other bright GRBs, such as GRB 221009A (the ``BOAT"). Multi-wavelength modeling, incorporating data from MASTER, BOOTES, DOT, Swift/XRT, and radio observations, was conducted using an external ISM forward-shock top-hat jet model with afterglowpy. The results reveal a narrow and highly collimated jet with a circumburst density of n$_{0}$ ~ 28.12 cm$^{-3}$, kinetic energy E$_{K}$ ~ 4.18 x 10$^{55}$ erg, and a relatively low value of $\epsilon_{B}$ = 2.14 x 10$^{-6}$, indicating shock-compression of the magnetic field in the surrounding interstellar medium. We constrained a low radiative efficiency of ~ 4.3 %. This study highlights the indispensable contribution of robotic networks to early afterglow observations and advances our understanding of GRB 230204B unique characteristics and underlying jet physics., Comment: 27 pages, 12 figures, 8 tables, submitted

In this research work, we present our open-source Geant4-based Monte-Carlo simulation application, called RadField3D, for generating threedimensional radiation field datasets for dosimetry. Accompanying, we introduce a fast, machine-interpretable data format with a Python API for easy integration into neural network research, that we call RadFiled3D. Both developments are intended to be used to research alternative radiation simulation methods using deep learning.

We study ultrafilters from the perspective of the algebra in the \v{C}ech-Stone compactification of the natural numbers, and idempotent elements therein. The first two results that we prove establish that, if $p$ is a Q-point (resp. a selective ultrafilter) and $\mathscr F^p$ (resp. $\mathscr G^p$) is the smallest family containing $p$ and closed under iterated sums (resp. closed under Blass--Frol\'{\i}k sums and Rudin--Keisler images), then $\mathscr F^p$ (resp. $\mathscr G^p$) contains no idempotent elements. The second of these results about a selective ultrafilter has the following interesting consequence: assuming a conjecture of Blass, in models of the form $\mathbf{L}(\mathbb R)[p]$ where $\mathbf{L}(\mathbb R)$ is a Solovay model (of $\mathsf{ZF}$ without choice) and $p$ is a selective ultrafilter, there are no idempotent elements. In particular, the theory $\mathsf{ZF}$ plus the existence of a nonprincipal ultrafilter on $\omega$ does not imply the existence of idempotent ultrafilters, which answers a question of DiNasso and Tachtsis (Proc. Amer. Math. Soc. 146, 397-411). Following the line of obtaining independence results in $\mathsf{ZF}$, we finish the paper by proving that $\mathsf{ZF}$ plus "every additive filter can be extended to an idempotent ultrafilter" does not imply the Ultrafilter Theorem over $\mathbb R$, answering another question of DiNasso and Tachtsis from the same paper., Comment: 27 pages

We aim to investigate the energy-resolved pulse profile changes of the accreting X-ray pulsar V 0332+53, focusing in the cyclotron line energy range, using the full set of available NuSTAR observations. We applied a tailored pipeline to study the energy dependence of the pulse profiles and to build the pulsed fraction spectra (PFS) for the different observations. We studied the profile changes also using cross-correlation and lag spectra. We re-analysed the energy spectra to search for links between the local features observed in the PFS and spectral emission components associated with the shape of the fundamental cyclotron line. In the PFS data, with sufficiently high statistics, we observe a consistent behaviour around the cyclotron line energy. Specifically, two Gaussian-shaped features appear symmetrically on either side of the putative cyclotron line. These features exhibit minimal variation with source luminosity, and their peak positions consistently remain on the left and right of the cyclotron line energy. Associated with the cyclotron line-forming region, we interpret them as evidence for the resonant cyclotron absorption line wings, as predicted by theoretical models of how the cyclotron line profile should appear along the observer's line of sight. A phase-resolved analysis of the pulse in the energy bands surrounding these features enables us to determine both the spectral shape and the intensity of the photons responsible for these peaks in the PFS. Assuming these features correspond to a spectral component, we used their shapes as priors for the corresponding emission components, finding a statistically satisfactory description of the spectra. To explain these results, we propose that our line of sight is close to the direction of the spin axis, while the magnetic axis is likely orthogonal to it., Comment: 33 pages, 58 figures. Accepted for publication in A&A

Randomized iterative algorithms, such as the randomized Kaczmarz method, have gained considerable popularity due to their efficacy in solving matrix-vector and matrix-matrix regression problems. Our present work leverages the insights gained from studying such algorithms to develop regression methods for tensors, which are the natural setting for many application problems, e.g., image deblurring. In particular, we extend the randomized Kaczmarz method to solve a tensor system of the form $\mathbf{\mathcal{A}}\mathcal{X} = \mathcal{B}$, where $\mathcal{X}$ can be factorized as $\mathcal{X} = \mathcal{U}\mathcal{V}$, and all products are calculated using the t-product. We develop variants of the randomized factorized Kaczmarz method for matrices that approximately solve tensor systems in both the consistent and inconsistent regimes. We provide theoretical guarantees of the exponential convergence rate of our algorithms, accompanied by illustrative numerical simulations. Furthermore, we situate our method within a broader context by linking our novel approaches to earlier randomized Kaczmarz methods.

This work presents PyPSA-Spain, an open-source model of the Spanish energy system based on the European model PyPSA-Eur. It aims to leverage the benefits of single-country modelling over a multi-country approach. In particular, several databases provided by Spanish institutions are exploited to improve the estimation of solar photovoltaic (PV) and onshore wind generation hourly profiles, as well as the spatio-temporal description of the electricity demand. PyPSA-Spain attains hourly resolution for a entire year and represents the Spanish energy system using a configurable number of nodes, while selecting around 35-50 nodes is identified as a good compromise between spatial resolution and model simplicity. To accommodate cross-border interactions, a nested model approach with PyPSA-Eur was used, wherein time-dependent electricity prices from neighbouring countries were precomputed through the optimisation of the European energy system. As a case study, the optimal electricity mix for 2030 was obtained and compared with the latest update of the Spanish National Energy and Climate Plan (NECP) from September 2024., Comment: 45 pages, 35 figures, 4 appendices

Pedestrian detection is a critical task in autonomous driving, aimed at enhancing safety and reducing risks on the road. Over recent years, significant advancements have been made in improving detection performance. However, these achievements still fall short of human perception, particularly in cases involving occluded pedestrians, especially entirely invisible ones. In this work, we present the Occlusion-Rich Road Scenes with Pedestrians (OccluRoads) dataset, which features a diverse collection of road scenes with partially and fully occluded pedestrians in both real and virtual environments. All scenes are meticulously labeled and enriched with contextual information that encapsulates human perception in such scenarios. Using this dataset, we developed a pipeline to predict the presence of occluded pedestrians, leveraging Knowledge Graph (KG), Knowledge Graph Embedding (KGE), and a Bayesian inference process. Our approach achieves a F1 score of 0.91, representing an improvement of up to 42% compared to traditional machine learning models.

Software services play a crucial role in daily life, with automated actions determining access to resources and information. Trusting service providers to perform these actions fairly and accurately is essential, yet challenging for users to verify. Even with publicly available codebases, the rapid pace of development and the complexity of modern deployments hinder the understanding and evaluation of service actions, including for experts. Hence, current trust models rely heavily on the assumption that service providers follow best practices and adhere to laws and regulations, which is increasingly impractical and risky, leading to undetected flaws and data leaks. In this paper, we argue that gathering verifiable evidence during software development and operations is needed for creating a new trust model. Therefore, we present TrustOps, an approach for continuously collecting verifiable evidence in all phases of the software life cycle, relying on and combining already existing tools and trust-enhancing technologies to do so. For this, we introduce the adaptable core principles of TrustOps and provide a roadmap for future research and development., Comment: To be published in International Conference on Enterprise Design, Operations, and Computing 2024 (EDOC 2024), 15 pages, 3 figures

Ultra-light axion-like particles (ALPs) can be a viable solution to the dark matter problem. The scalar field associated with ALPs, coupled to the electromagnetic field, acts as an active birefringent medium, altering the polarisation properties of light through which it propagates. In particular, oscillations of the axionic field induce monochromatic variations of the plane of linearly polarised radiation of astrophysical signals. The radio emission of millisecond pulsars provides an excellent tool to search for such manifestations, given their high fractional linear polarisation and negligible fluctuations of their polarisation properties. We have searched for the evidence of ALPs in the polarimetry measurements of pulsars collected and preprocessed for the European Pulsar Timing Array (EPTA) campaign. Focusing on the twelve brightest sources in linear polarisation, we searched for an astrophysical signal from axions using both frequentist and Bayesian statistical frameworks. For the frequentist analysis, which uses Lomb-Scargle periodograms at its core, no statistically significant signal has been found. The model used for the Bayesian analysis has been adjusted to accommodate multiple deterministic systematics that may be present in the data. A statistically significant signal has been found in the dataset of multiple pulsars with common frequency between $10^{-8}$ Hz and $2\times10^{-8}$ Hz, which can most likely be explained by the residual Faraday rotation in the terrestrial ionosphere. Strong bounds on the coupling constant $g_{a\gamma}$, in the same ballpark as other searches, have been obtained in the mass range between $6\times10^{-24}$ eV and $5\times10^{-21}$ eV. We conclude by discussing problems that can limit the sensitivity of our search for ultra-light axions in the polarimetry data of pulsars, and possible ways to resolve them., Comment: 24 pages, 15 figures

The Pauli exclusion principle is fundamental to understanding electronic quantum systems. It namely constrains the expected occupancies $n_i$ of orbitals $\varphi_i$ according to $0 \leq n_i \leq 2$. In this work, we first refine the underlying one-body $N$-representability problem by taking into account simultaneously spin symmetries and a potential degree of mixedness $\boldsymbol w$ of the $N$-electron quantum state. We then derive a comprehensive solution to this problem by using basic tools from representation theory, convex analysis and discrete geometry. Specifically, we show that the set of admissible orbital one-body reduced density matrices is fully characterized by linear spectral constraints on the natural orbital occupation numbers, defining a convex polytope $\Sigma_{N,S}(\boldsymbol w) \subset [0,2]^d$. These constraints are independent of $M$ and the number $d$ of orbitals, while their dependence on $N, S$ is linear, and we can thus calculate them for arbitrary system sizes and spin quantum numbers. Our results provide a crucial missing cornerstone for ensemble density (matrix) functional theory.

Ecological forecasts are model-based statements about currently unknown ecosystem states in time or space. For a model forecast to be useful to inform decision-makers, model validation and verification determine adequateness. The measure of forecast goodness that can be translated into a limit up to which a forecast is acceptable is known as the `forecast horizon'. While verification of meteorological models follows strict criteria with established metrics and forecast horizons, assessments of ecological forecasting models still remain experiment-specific and forecast horizons are rarely reported. As such, users of ecological forecasts remain uninformed of how far into the future statements can be trusted. In this work, we synthesise existing approaches, define empirical forecast horizons in a unified framework for assessing ecological predictability and offer recipes on their computation. We distinguish upper and lower boundary estimates of predictability limits, reflecting the model's potential and actual forecast horizon, and show how a benchmark model can help determine its relative forecast horizon. The approaches are demonstrated with four case studies from population, ecosystem, and earth system research.

Magnetic bimerons are potential information carriers in spintronic devices. Bimerons, topologically equivalent to skyrmions, manifest in chiral magnetic systems with in-plane magnetization due to anisotropies or external magnetic fields. Applications demanding their current-driven motion face significant challenges, notably the bimeron Hall effect, which causes transverse movement and annihilation at nanomagnet borders. This study addresses the problem of stabilizing bimeron propagation under current-driven conditions. We demonstrate that bimerons can propagate through thin ferromagnetic strips without annihilation when the easy-axis anisotropy and the electric current are orthogonal. Our findings indicate that below a threshold value of current, the repulsion between the bimeron and the strip boundary allows for stable soliton propagation, even in bent regions. This phenomenon extends to bimeron chains, which propagate parallel to the current flow. By enabling stable long-distance propagation, our results open new avenues for developing bimeron-based racetrack memory devices, enhancing the efficiency and reliability of future spintronic applications.

We prove Kim's Assumtion A for the split classical groups in positive characteristic. Actually, we work in the slightly more general setting of groups of classical kind, which includes quasi-split classical groups and generalized spinor groups. We establish our results whenever a local Ramanujan bound holds; a bound that is known for the split classical groups in characteristic $p$, and we prove it for groups of classical kind under a local-global restriction.

Let $F$ be a locally compact non-Archimedean field, and $\bf G$ a connected quasi-split reductive group over $F$. We are interested in complex irreducible smooth generic representations $\pi$ of ${\bf G}(F)$. When $F$ has positive characteristic, we prove important properties which previously were only available for $F$ of characteristic 0. The first one is the tempered $L$-function conjecture of Shahidi, stating that when $\pi$ as above is tempered, then the $L$-functions attached to $\pi$ by the Langlands-Shahidi method have no pole for ${\rm Re}(s)>0$. We also establish the standard module conjecture of Casselman and Shahidi, saying that if $\pi$ is written as the Langlands quotient of a standard module, then it is in fact the full standard module. Finally, for a split classical group $\bf G$ we prove a useful result on the unramified unitary spectrum of ${\bf G}(F)$.

Let $(G,+)$ be an Abelian group. Given $h\in \mathbb{Z}^+$, a non-empty subset $A$ of $G$ is called an $S_h$-set if all the sums of $h$ distinct elements of $A$ are different. We extend the concept of $S_h$-set to a more general context in the context of finite vectorial spaces over finite fields. More precisely, a $\emptyset \neq A\subseteq \mathbb{F}_q^r$ is called an $S_h$-linear set if all the linear combinations of $h$ elements of $A$ are different. We establish a correspondence between $q$-ary linear codes and $S_h$-linear sets. This connection allow us to find lower bounds for the maximum size of $S_h$-sets in $\mathbb{F}_q^r$., Comment: 17 pages, 2 figures

Detecting and characterizing decoherence-inducing noise sources is critical for developing scalable quantum technologies and deploying quantum sensors that operate at molecular scales. Yet, existing methods for such noise spectroscopy face fundamental difficulties, including their reliance on severe approximations and the need for extensively averaged measurements. Here, we propose an alternative approach that processes the commonly performed dynamical decoupling-based coherence measurements using a novel self-consistent optimization framework to extract the noise power spectrum that characterizes the interaction between a qubit or quantum sensor and its environment. Our approach adopts minimal assumptions and is robust to the presence of measurement errors. We introduce a protocol to quantify confidence intervals and a physically motivated heuristic to determine which new dynamical decoupling measurement can improve spectral reconstruction. We employ our method to reconstruct the noise spectrum of a nitrogen-vacancy sensor in diamond, resolving previously undetected nuclear species at the diamond surface and revealing that the previous measurements of low-frequency noise had overestimated its strength by an order of magnitude. Our method's noise spectrum reconstructions uncover previously unsuspected structure and offer unprecedented accuracy, setting the stage for precision noise spectroscopy-based quantum metrology., Comment: 16 pages, 5 figures

Predicting the exact many-body quantum dynamics of polarons in materials with strong carrier-phonon interactions presents a fundamental challenge, often necessitating one to adopt approximations that sacrifice the ability to predict the transition from nonequilibrium relaxation to thermodynamic equilibrium. Here, we exploit a recent breakthrough that generalizes the concept of memory beyond its conventional temporal meaning to also encompass space. Specifically, we leverage our discovery that the dynamics of observables in systems with local couplings satisfy Green's functions with kernels that are local in time and space. This enables us to employ the dynamics of small lattices over short times to predict the dynamics of thermodynamically large lattices over arbitrarily long timescales while circumventing the deleterious impacts of finite-size effects. We thus interrogate the \textit{exact} nonequilibrium formation and migration of polarons in one- (1D) and two-dimensional (2D) systems, revealing that their motion approaches diffusive transport only asymptotically in time and system size. We also compare transport in 1D and 2D systems to investigate the effect of dimension in polaron migration physics, illustrating how energy variations can cause localization -- a phenomenon observable via current microscopy experiments.

The molecular gas in the interstellar medium (ISM) of star-forming galaxy populations exhibits diverse physical properties. We investigate the $^{12}$CO excitation of twelve dusty, luminous star-forming galaxies at $z \sim 2-4$ by combining observations of the $^{12}$CO from $J_{\rm up} = 1$ to $J_{\rm up} = 8$. The spectral line energy distribution (SLED) has a similar shape to NGC 253, M82, and local ULIRGs, with much stronger excitation than the Milky Way inner disc. By combining with resolved dust continuum sizes from high-resolution $870$-$\mu$m ALMA observations and dust mass measurements determined from multi-wavelength SED fitting, we measure the relationship between the $^{12}$CO SLED and probable physical drivers of excitation: star-formation efficiency, the average intensity of the radiation field $\langle U\rangle$, and the star-formation rate surface density. The primary driver of high-$J_{\rm up}$ $^{12}$CO excitation in star-forming galaxies is star-formation rate surface density. We use the ratio of the CO($3-2$) and CO($6-5$) line fluxes to infer the CO excitation in each source and find that the average ratios for our sample are elevated compared to observations of low-redshift, less actively star-forming galaxies and agree well with predictions from numerical models that relate the ISM excitation to the star-formation rate surface density. The significant scatter in the line ratios of a factor $\approx 3$ within our sample likely reflects intrinsic variations in the ISM properties which may be caused by other effects on the excitation of the molecular gas, such as cosmic ray ionization rates and mechanical heating through turbulence dissipation., Comment: Accepted for publication in MNRAS; 17 pages, 7 figures

This document summarizes the prospective physics plans of the French QCD and Heavy-Ion community, including the experimental programs at the LHC Run 5 and beyond and future colliders at CERN, within the context of the French contribution to the update of the European Strategy in Particle Physics (ESPPU 2025), as discussed in the workshop on European Strategy for Particle Physics Update 2025 organised by the QCD GdR in Oct. 2024., Comment: 6.5 pages without title page and without references, no figures. Keywords: QCD, Heavy Ions, Quark Gluon Plasma, LHC, FCC

The electron-phonon interaction is one of the most fundamental mechanisms in condensed matter physics. Phonons can induce memory effects in solid-state platforms when localized electronic states interact with lattice vibrations in non-unitary dynamical maps. In this work, we demonstrate how single-mode and structured phonon environments can give rise to non-Markovian dynamics of an individual negatively charged silicon-vacancy center in diamond. Using trace distance as a quantifier via numerical simulations and theoretical calculations, we identify the physical conditions for emerging and understanding non-Markovian behavior in diverse scenarios. Most importantly, we investigate the influence of magnetic fields (longitudinal and transverse), phonon couplings, Fock states, and temperature to understand how these factors influence memory effects in this solid-state device., Comment: 14 pages, 7 figures, 1 table

We present analytical expressions for the fluxes of energy and angular momentum from a point mass on an inclined spherical orbit about a Kerr black hole. The expressions are obtained using the method of Mano, Suzuki and Takasugi to construct analytical solutions of the Teukolsky equation, and are given as post-Newtonian expansions valid through 12PN, with arbitrary values for the inclination parameter $x$ and black hole spin $a$. We characterize the structure of the PN expansions in terms of their dependence on $x$ and $a$, and we validate our results against numerical calculations.

In this paper, we investigate the transformation laws of the Wigner function under changes of reference frames. By employing the coordinate transformation of the wave functions, we derive an integral representation for the transformed Wigner function in both position and momentum representations. To illustrate our results, we include some basic examples., Comment: 9 pages, no figures