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Recent experiments with quantum simulators using ultracold atoms and superconducting qubits have demonstrated the potential of controlled dissipation as a versatile tool for realizing correlated many-body states. However, determining the dynamics of dissipative quantum many-body systems remains a significant analytical and numerical challenge. In this work, we focus on a dissipative impurity problem as a testbed for new methodological developments. We introduce an efficient non-perturbative framework that combines the superposition of Gaussian states (SGS) variational ansatz with the quantum trajectory approach to simulate open systems featuring a dissipative impurity. Applying this method to a spinful impurity subject to two-body losses and embedded in a bath of noninteracting fermions, we explore the full crossover from weak to strong dissipation regimes. The non-perturbative nature of the SGS ansatz allows us to thoroughly examine this crossover, providing comprehensive insights into the system's behavior. In the strong dissipation regime, our approach reproduces the finding that localized two-body losses can induce the Kondo effect [arXiv:2406.03527], characterized by a slowdown of spin relaxation and an enhancement of charge conductance. Furthermore, we reveal an exotic "reverse conductance" phenomenon at zero potential bias -- a counter-intuitive single-body effect resulting from intermediate dissipation and finite bandwidth. Finally, we investigate the formation of ferromagnetic domains and propose an extension to realize a higher-spin Kondo model using localized dissipation., Comment: 18 pages, 7 figures

Reconstructing the physical complexity of many-body dynamical systems can be challenging. Starting from the trajectories of their constitutive units (raw data), typical approaches require selecting appropriate descriptors to convert them into time-series, which are then analyzed to extract interpretable information. However, identifying the most effective descriptor is often non-trivial. Here, we report a data-driven approach to compare the efficiency of various descriptors in extracting information from noisy trajectories and translating it into physically relevant insights. As a prototypical system with non-trivial internal complexity, we analyze molecular dynamics trajectories of an atomistic system where ice and water coexist in equilibrium near the solid/liquid transition temperature. We compare general and specific descriptors often used in aqueous systems: number of neighbors, molecular velocities, Smooth Overlap of Atomic Positions (SOAP), Local Environments and Neighbors Shuffling (LENS), Orientational Tetrahedral Order, and distance from the fifth neighbor ($d_5$). Using Onion Clustering -- an efficient unsupervised method for single-point time-series analysis -- we assess the maximum extractable information for each descriptor and rank them via a high-dimensional metric. Our results show that advanced descriptors like SOAP and LENS outperform classical ones due to higher signal-to-noise ratios. Nonetheless, even simple descriptors can rival or exceed advanced ones after local signal denoising. For example, $d_5$, initially among the weakest, becomes the most effective at resolving the system's non-local dynamical complexity after denoising. This work highlights the critical role of noise in information extraction from molecular trajectories and offers a data-driven approach to identify optimal descriptors for systems with characteristic internal complexity., Comment: 19 pages, 5 figures + 3 in supporting information (at the bottom of the manuscript)

Quantization-aware training (QAT) schemes have been shown to achieve near-full precision accuracy. They accomplish this by training a quantized model for multiple epochs. This is computationally expensive, mainly because of the full precision backward pass. On the other hand, post-training quantization (PTQ) schemes do not involve training and are therefore computationally cheap, but they usually result in a significant accuracy drop. We address these challenges by proposing EfQAT, which generalizes both schemes by optimizing only a subset of the parameters of a quantized model. EfQAT starts by applying a PTQ scheme to a pre-trained model and only updates the most critical network parameters while freezing the rest, accelerating the backward pass. We demonstrate the effectiveness of EfQAT on various CNNs and Transformer-based models using different GPUs. Specifically, we show that EfQAT is significantly more accurate than PTQ with little extra compute. Furthermore, EfQAT can accelerate the QAT backward pass between 1.44-1.64x while retaining most accuracy., Comment: 12 pages, 5 figures

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.

Context: The emergence of Large Language Models (LLMs) has significantly transformed Software Engineering (SE) by providing innovative methods for analyzing software repositories. Objectives: Our objective is to establish a practical framework for future SE researchers needing to enhance the data collection and dataset while conducting software repository mining studies using LLMs. Method: This experience report shares insights from two previous repository mining studies, focusing on the methodologies used for creating, refining, and validating prompts that enhance the output of LLMs, particularly in the context of data collection in empirical studies. Results: Our research packages a framework, coined Prompt Refinement and Insights for Mining Empirical Software repositories (PRIMES), consisting of a checklist that can improve LLM usage performance, enhance output quality, and minimize errors through iterative processes and comparisons among different LLMs. We also emphasize the significance of reproducibility by implementing mechanisms for tracking model results. Conclusion: Our findings indicate that standardizing prompt engineering and using PRIMES can enhance the reliability and reproducibility of studies utilizing LLMs. Ultimately, this work calls for further research to address challenges like hallucinations, model biases, and cost-effectiveness in integrating LLMs into workflows.

We introduce Edify Image, a family of diffusion models capable of generating photorealistic image content with pixel-perfect accuracy. Edify Image utilizes cascaded pixel-space diffusion models trained using a novel Laplacian diffusion process, in which image signals at different frequency bands are attenuated at varying rates. Edify Image supports a wide range of applications, including text-to-image synthesis, 4K upsampling, ControlNets, 360 HDR panorama generation, and finetuning for image customization.

Generating high output powers while achieving narrow line single mode lasing are often mutual exclusive properties of commercial laser diodes. For this reason, efficient and scalable amplification of narrow line laser light is still a major driving point in modern laser system designs. Commonly, injection locking of high-power semiconductor laser diodes are used for this purpose. However, for many laser diodes it is very challenging to achieve stable operation of the injection locked state due to a complex interplay of non-linearities and thermal effects. Different approaches of active or passive stabilization usually require a large overhead of optical and electrical equipment and are not generally applicable. In our work we present a passive stabilization scheme, that is generally applicable, technically easy to implement and extremely cost-effective. It is based on the externally synchronized automatic acquisition of the optimal injection state. Central to our simple but powerful scheme is the management of thermalization effects during lock acquisition. By periodical relocking, spectrally pure amplified light is maintained in a quasi-CW manner over long timescales. We characterize the performance of our method for laser diodes amplifying 671 nm light and demonstrate the general applicability by confirming the method to work also for laser diodes at 401 nm, 461 nm and 689 nm. Our scheme enables the scaled operation of injection locks, even in cascaded setups, for the distributed amplification of single frequency laser light.

We investigate the role of constraints in the computational complexity of min-max optimization. The work of Daskalakis, Skoulakis, and Zampetakis [2021] was the first to study min-max optimization through the lens of computational complexity, showing that min-max problems with nonconvex-nonconcave objectives are PPAD-hard. However, their proof hinges on the presence of joint constraints between the maximizing and minimizing players. The main goal of this paper is to understand the role of these constraints in min-max optimization. The first contribution of this paper is a fundamentally new proof of their main result, which improves it in multiple directions: it holds for degree 2 polynomials, it is essentially tight in the parameters, and it is much simpler than previous approaches, clearly highlighting the role of constraints in the hardness of the problem. Second, we show that with general constraints (i.e., the min player and max player have different constraints), even convex-concave min-max optimization becomes PPAD-hard. Along the way, we also provide PPAD-membership of a general problem related to quasi-variational inequalities, which has applications beyond our problem.

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, submitted to Computer Physics Communications

In response to the growing demand for more efficient and compact refrigeration and energy conversion devices, electrocaloric poly(vinylidene fluoride-trifluoroethylene-chlorofluoroethylene) is among the most promising active substances. However, despite its high electrocaloric response, the maximum efficiency achievable over a cooling cycle is hampered by losses. To overcome this major limitation, losses have been reduced by using an electrothermal poling treatment as well as by controlling the surface roughness. The upper bound of the efficiency computed over a thermodynamic cycle mimicking the working conditions of an actual cooling device is increased from 1% to 10% of the Carnot efficiency. This represents a major improvement in enhancing ferroelectric materials for advanced energy applications.

The Parameterized Post-Newtonian (PPN) formalism offers an agnostic framework for evaluating theories of gravity that extend beyond General Relativity. Departures from General Relativity are represented by a set of dimensionless parameters that, at the first order in the expansion, reduce to $\beta$ and $\gamma$, which describe deviations in spatial curvature and non-linear superposition effects of gravity, respectively. We exploit future observations of stars at the Galactic Center, orbiting the supermassive black hole Sagittarius A*, to forecast the ability to constrain the first-order PPN parameters $\gamma$ and $\beta$. We have generated a mock catalog of astrometric and spectroscopic data for S2, based on the Schwarzschild metric, simulating observations over multiple orbital periods with the GRAVITY and SINFONI instruments. Our analysis includes the effects of relativistic orbital precession and line-of-sight (LOS) velocity gravitational redshift. Since future data for S2 can provide constraints only on a linear combination of the PPN parameters $\beta$ and $\gamma$ we also analyzed the impact of future observations of the gravitational lensing for stars that pass closer in the sky to Sgr A*, like the known star S62, which can potentially provide tight constraints on the parameter $\gamma$, that alone regulates the amplitude of the astrometric deviations due to lensing. When combining lensing observations for S62, and the precise orbital tracking of S2, one obtains independent constraints on both $\gamma$ (with a potential precision as good as $\sim 1\%$) and $\beta$ (with a corresponding precision of $\sim 2\%$), providing a precision test of General Relativity and its extensions., Comment: 9 pages, 7 figures, 1 table. Comments are welcome

This exploratory pilot study investigated the potential of combining a domain-specific model, BERN2, with large language models (LLMs) to enhance automated disease phenotyping from research survey data. Motivated by the need for efficient and accurate methods to harmonize the growing volume of survey data with standardized disease ontologies, we employed BERN2, a biomedical named entity recognition and normalization model, to extract disease information from the ORIGINS birth cohort survey data. After rigorously evaluating BERN2's performance against a manually curated ground truth dataset, we integrated various LLMs using prompt engineering, Retrieval-Augmented Generation (RAG), and Instructional Fine-Tuning (IFT) to refine the model's outputs. BERN2 demonstrated high performance in extracting and normalizing disease mentions, and the integration of LLMs, particularly with Few Shot Inference and RAG orchestration, further improved accuracy. This approach, especially when incorporating structured examples, logical reasoning prompts, and detailed context, offers a promising avenue for developing tools to enable efficient cohort profiling and data harmonization across large, heterogeneous research datasets.

Fuzzy Dark Matter (FDM) is among the most suitable candidates to replace WIMPs and to resolve the puzzling mystery of dark matter. A galactic dark matter halo made of these ultralight bosonic particles leads to the formation of a solitonic core surrounded by quantum interference patterns that, on average, reproduce a Navarro-Frenk-White-like mass density profile in the outskirts of the halo. The structure of such a core is determined once the boson mass and the total mass of the halo are set. We investigated the capability of future astrometric Theia-like missions to detect the properties of such a halo within the FDM model, namely the boson mass and the core radius. To this aim, we built mock catalogs containing three-dimensional positions and velocities of stars within a target dwarf galaxy. We exploited these catalogs using a Markov Chain Monte Carlo algorithm and found that measuring the proper motion of at least 2000 stars within the target galaxy, with uncertainty $\sigma_v \leq 3$ km/s on the velocity components, will constrain the boson mass and the core radius with 3\% accuracy. Furthermore, the transition between the solitonic core and the outermost NFW-like density profile could be detected with an uncertainty of 7\%. Such results would not only help to confirm the existence of FDM, but they would also be useful for alleviating the current tension between galactic and cosmological estimations of the boson mass, or demonstrating the need for multiple particles with a broad mass spectrum as naturally arise String Axiverse., Comment: 11 pages, 3 Figures, 4 Tables

Stacking van der Waals magnets holds promise for creating new hybrid materials with properties that do not exist in bulk materials. Here we investigate orthogonally twisted stacks of the van der Waals antiferromagnet CrSBr, aiming to exploit an extreme misalignment of magnetic anisotropy across the twisted interface.Using nitrogen-vacancy centre microscopy, we construct vector maps of the magnetisation, and track their evolution under an external field, in a range of twisted compensated and uncompensated configurations differing by the number of layers. We show that twisted stacking consistently modifies the local magnetic switching behaviour of constituent flakes, and that these modifications are spatially non-uniform. In the case of compensated component flakes (even number of layers), we demonstrate that the combination of dipolar coupling and stacking-induced strain can reduce the switching field by over an order of magnitude. Conversely, in uncompensated component flakes (odd number of layers), we observe indications of a non-zero interlayer exchange interaction between twisted flakes during magnetization reversal, which can persistently modify magnetic order. This work highlights the importance of spatial imaging in investigating stacking-induced magnetic effects, particularly in the case of twistronics where spatial variation is expected and can be conflated with structural imperfections., Comment: 6 main text pages, 4 figures plus 8 supplementary information pages, 9 figures

We compute and apply the minimum spanning tree (MST) of the binary millisecond pulsar population, and discuss aspects of the known phenomenology of these systems in this context. We find that the MST effectively separates different classes of spider pulsars, eclipsing radio pulsars in tight binary systems either with a companion with a mass in the range of approximately 0.1-0.8 solar masses (redbacks) or with a companion of less than or approximately 0.06 solar masses (black widows), into distinct branches. The MST also separates black widows located in globular clusters from those found in the field and groups other pulsar classes of interest, including transitional millisecond pulsars. Using the MST and a defined ranking for similarity, we identify possible candidates likely to belong to these pulsar classes. In particular, based on this approach, we propose the black widows' classification of J1300+1240, J1630+3550, J1317-0157, J1221-0633, J1627+3219, J1737-0314A, and J1701-3006F, discuss that of J1908+2105, and analyze J1723-2837, J1431-4715, and J1902-5105 as possible transitional systems. We introduce an algorithm that quickly locates where new pulsars fall within the MST and use this to examine the positions of the transitional millisecond pulsar IGR J18245-2452 (PSR J1824-2452I), the transitional millisecond pulsar candidate 3FGL J1544.6-1125, and the accreting millisecond X-ray pulsar SAX J1808.4-3658. Assessing the positions of these sources in the MST assuming a range for their unknown variables (e.g., the spin period derivative of PSR J1824-2452I) we can effectively narrow down the parameter space necessary for searching and determining key pulsar parameters through targeted observations., Comment: For the millisecond pulsar tree website, see http://www.pulsartree.ice.csic.es/millisecondpulsartree

We introduce the concept of a sum-rank saturating system and outline its correspondence to a covering properties of a sum-rank metric code. We consider the problem of determining the shortest sum-rank-$\rho$-saturating systems of a fixed dimension, which is equivalent to the covering problem in the sum-rank metric. We obtain upper and lower bounds on this quantity. We also give constructions of saturating systems arising from geometrical structures.

The inhomogeneous magnetic stray field of micromagnets has been extensively used to manipulate electron spin qubits. By means of micromagnetic simulations and scanning superconducting quantum interference device microscopy, we show that the polycrystallinity of the magnet and non-uniform magnetization significantly impact the stray field and corresponding qubit properties. We find that the random orientation of the crystal axis in polycrystalline Co magnets alters the qubit frequencies by up to 0.5 GHz, compromising single qubit addressability and single gate fidelities. We map the stray field of Fe micromagnets with an applied magnetic field of up to 500 mT (mimicking conditions when operating qubits), finding field gradients above 1 mT/nm. The measured gradients and the lower magnetocrystalline anisotropy of Fe demonstrate the advantage of using Fe instead of Co for magnets in spin qubit devices. These properties of Fe also enabled us to design a 2D arrangement of nanomagnets for driving spin qubits distributed on a 2D lattice.

As machine learning (ML) and artificial intelligence (AI) technologies become increasingly prevalent in society, concerns about their environmental sustainability have grown. Developing and deploying ML-enabled systems, especially during training and inference, are resource-intensive, raising sustainability issues. Green AI has emerged as a response, advocating for reducing the computational demands of AI while maintaining accuracy. While recent research has identified various green tactics for developing sustainable ML-enabled systems, there is a gap in understanding the extent to which these tactics are adopted in real-world projects and whether additional, undocumented practices exist. This paper addresses these gaps by presenting a mining software repository study that evaluates the adoption of green tactics in 168 open-source ML projects on GitHub. In doing so, we introduce a novel mining mechanism based on large language models to identify and analyze green tactics within software repositories. Our results provide insights into the adoption of green tactics found in the literature and expand previous catalogs by providing 12 new tactics, with code examples to support wider implementation. This study contributes to the development of more sustainable ML systems by identifying adopted green tactics that offer substantial environmental benefits with minimal implementation effort. It provides practical insights for developers to green their systems and offers a path for future research to automate the integration of these tactics.

For an algebraic torus defined over a local (or global) field $F$, a celebrated result of R.P. Langlands establishes a natural homomorphism from the group of continuous cohomology classes of the Weil group, valued in the dual torus, onto the space of complex characters of the rational points of the torus (or automorphic characters in the global case). We slightly extend this result by showing that, if we topologize the relevant spaces of continuous homomorphisms and continuous cochains with the compact-open topology, then Langlands's homomorphism is continuous and open. Moreover, we demonstrate that, in both the local and global settings, the subset of unramified characters corresponds to the identity component of the relevant space of characters when viewed in this topological framework. Finally, we compare the group of unramified characters and the Galois (co)invariants of the dual torus., Comment: 27 pages, in this new version, we corrected some inaccuracies in the manuscript, added a few more references and corrected some typos

We have probed the capability of third-generation Gravitational Waves (GW) interferometers, such as the Einstein Telescope and Cosmic Explorer, to constrain a cosmological model with an interacting dark sector. We focused on GW events with a detected electromagnetic counterpart being the $\gamma$ or X emission of Gamma-Ray Burst, and a Kilonova emission. We assume the first one to be detected by the THESEUS satellite, while the second one to be detected by the Vera Rubin Observatory. We probed three different interaction kernels and found that the posterior estimation of the cosmological parameters is biased due to the existing degeneracies between the dark and matter sectors. We also found that introducing an external prior on the matter density parameter breaks the degeneracy, removes the bias results, and improves the accuracy on the dark sector parameters., Comment: 16 pages, 6 Table, and 3 Figures. Accepted for publication in Physical Review D

Holomorphic functions are fundamental in operator theory and their Cauchy formula is a crucial tool for defining functions of operators. The Fueter-Sce extension theorem (often called Fueter-Sce mapping theorem) provides a two-step procedure for extending holomorphic functions to hyperholomorphic functions. In the first step, slice hyperholomorphic functions are obtained, and their associated Cauchy formula establishes the $S$-functional calculus for noncommuting operators on the $S$-spectrum. The second step produces axially monogenic functions, which lead to the development of the monogenic functional calculus. In this review paper we discuss the second operator in the Fueter-Sce mapping theorem that takes slice hyperholomorphic to axially monogenic functions. This operator admits several factorizations which generate various function spaces and their corresponding functional calculi, thereby forming the so-called fine structures of spectral theories on the $S$-spectrum., Comment: To appear in the Special Volume of ICHAA 2024. arXiv admin note: substantial text overlap with arXiv:2303.00253

Classical finance models are based on the premise that investors act rationally and utilize all available information when making portfolio decisions. However, these models often fail to capture the anomalies observed in intertemporal choices and decision-making under uncertainty, particularly when accounting for individual differences in preferences and consumption patterns. Such limitations hinder traditional finance theory's ability to address key questions like: How do personal preferences shape investment choices? What drives investor behaviour? And how do individuals select their portfolios? One prominent contribution is Pompian's model of four Behavioral Investor Types (BITs), which links behavioural finance studies with Keirsey's temperament theory, highlighting the role of personality in financial decision-making. Yet, traditional parametric models struggle to capture how these distinct temperaments influence intertemporal decisions, such as how individuals evaluate trade-offs between present and future outcomes. To address this gap, the present study employs Functional Data Analysis (FDA) to specifically investigate temporal discounting behaviours revealing nuanced patterns in how different temperaments perceive and manage uncertainty over time. Our findings show heterogeneity within each temperament, suggesting that investor profiles are far more diverse than previously thought. This refined classification provides deeper insights into the role of temperament in shaping intertemporal financial decisions, offering practical implications for financial advisors to better tailor strategies to individual risk preferences and decision-making styles.

We study a cylindrical plasmonic waveguide consisting of a magnetic Weyl semimetal embedded in a dielectric medium. We determine the dispersion relation of the surface plasmon polaritons and show how it depends on the plasma frequency, the radius of the semimetal and the separation between the nodes. We show that the band structure, which modifies the electrodynamics in the medium, manifests itself through a pronounced asymmetry in the dispersion curves and a giant splitting in the group velocity, with the orbital angular momentum as a control parameter for the direction of propagation.

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

Almost all accreting black hole and neutron star X-ray binary systems (XRBs) exhibit prominent brightness variations on a few characteristic time-scales and their harmonics. These quasi-periodic oscillations (QPOs) are thought to be associated with the precession of a warped accretion disc, but the physical mechanism that generates the precessing warp remains uncertain. Relativistic frame dragging (Lense-Thirring precession) is one promising candidate, but a misaligned magnetic field is an alternative, especially for neutron star XRBs. Here, we report the discovery of 5 accreting white dwarf systems (AWDs) that display strong optical QPOs with characteristic frequencies and harmonic structures that suggest they are the counterpart of the QPOs seen in XRBs. Since AWDs are firmly in the classical (non-relativistic) regime, Lense-Thirring precession cannot account for these QPOs. By contrast, a weak magnetic field associated with the white dwarf can drive disc warping and precession in these systems, similar to what has been proposed for neutron star XRBs. Our observations confirm that magnetically driven warping is a viable mechanism for generating QPOs in disc-accreting astrophysical systems, certainly in AWDs and possibly also in (neutron star) XRBs. Additionally, they establish a new way to estimate magnetic field strengths, even in relatively weak-field systems where other methods are not available., Comment: 16 pages, 9 figures, accepted for publication in MNRAS

We present our findings from the first long X-ray observation of the hard X-ray source Swift J0826.2-7033 with XMM-Newton, which has shown characteristics of magnetic accretion. The system appears to have a long orbital period (~7.8 h) accompanied by short timescale variabilities, which we tentatively interpret as the spin and beat periods of an intermediate polar. These short- and long-timescale modulations are energy-independent, suggesting that photoelectric absorption does not play any role in producing the variabilities. If our suspected spin and beat periods are true, then Swift J0826.2-7033 accretes via disc-overflow with an equal fraction of accretion taking place via disc and stream. The XMM-Newton and Swift-BAT spectral analysis reveals that the post-shock region in Swift J0826.2-7033 has a multi-temperature structure with a maximum temperature of ~43 keV, which is absorbed by a material with an average equivalent hydrogen column density of ~1.6$\times$10$^{22}$ cm$^{-2}$ that partially covers ~27% of the X-ray source. The suprasolar abundances, with hints of an evolved donor, collectively make Swift J0826.2-7033 an interesting target, which likely underwent a thermal timescale mass transfer phase., Comment: 10 pages, 7 figures. Accepted for publication in A&A

CXOU J110926.4-650224 is a candidate transitional millisecond pulsar (tMSP) with X-ray and radio emission properties reminiscent of those observed in confirmed tMSPs in their X-ray 'subluminous' disc state. We present the results of observing campaigns that, for the first time, characterise the optical and near-infrared variability of this source and establish a connection with the mode-switching phenomenon observed in X-rays. The optical emission exhibited flickering activity, frequent dipping episodes where it appeared redder, and a multi-peaked flare where it was bluer. The variability pattern was strongly correlated with that of the X-ray emission. Each dip matched an X-ray low-mode episode, indicating that a significant portion of the optical emission originates from nearly the same region as the X-ray emission. The near-infrared emission also displayed remarkable variability, including a dip of 20 min in length during which it nearly vanished. Time-resolved optical spectroscopic observations reveal significant changes in the properties of emission lines from the disc and help infer the spectral type of the companion star to be between K0 and K5. We compare the properties of CXOU J110926.4-650224 with those of other tMSPs in the X-ray subluminous disc state and discuss our findings within the context of a recently proposed scenario that explains the phenomenology exhibited by the prototypical tMSP PSR J1023+0038., Comment: 12 pages, 7 figures, 2 tables. Accepted for publication on Astronomy & Astrophysics

Auto-associative neural networks (e.g., the Hopfield model implementing the standard Hebbian prescription) serve as a foundational framework for pattern recognition and associative memory in statistical mechanics. However, their hetero-associative counterparts, though less explored, exhibit even richer computational capabilities. In this work, we examine a straightforward extension of Kosko's Bidirectional Associative Memory (BAM), introducing a Three-directional Associative Memory (TAM), that is a tripartite neural network equipped with generalized Hebbian weights. Through both analytical approaches (using replica-symmetric statistical mechanics) and computational methods (via Monte Carlo simulations), we derive phase diagrams within the space of control parameters, revealing a region where the network can successfully perform pattern recognition as well as other tasks tasks. In particular, it can achieve pattern disentanglement, namely, when presented with a mixture of patterns, the network can recover the original patterns. Furthermore, the system is capable of retrieving Markovian sequences of patterns and performing generalized frequency modulation.

We present the first X-ray observation of the energetic millisecond pulsar binary PSR J1431-4715, performed with XMM-Newton and complemented with fast optical multi-band photometry acquired with the ULTRACAM instrument at ESO-NTT. It is found as a faint X-ray source without a significant orbital modulation. This contrasts with the majority of systems that instead display substantial X- ray orbital variability. The X-ray spectrum is dominated by non-thermal emission and, due to the lack of orbital modulation, does not favour an origin in an intrabinary shock between the pulsar and companion star wind. While thermal emission from the neutron star polar cap cannot be excluded in the soft X-rays, the dominance of synchrotron emission favours an origin in the pulsar magnetosphere that we describe at both X-ray and gamma-ray energies with a synchro-curvature model. The optical multi-colour light curve folded at the 10.8h orbital period is double-humped, dominated by ellipsoidal effects, but also affected by irradiation. The ULTRACAM light curves are fit with several models encompassing direct heating and a cold spot, or heat redistribution after irradiation either through convection or convection plus diffusion. Despite the inability to constrain the best irradiation models, the fits provide consistent system parameters, giving an orbital inclination of 59$\pm$6deg and a distance of 3.1$\pm$0.3 kpc. The companion is found to be an F-type star, underfilling its Roche lobe ( f_RL = 73$\pm$4%), with a mass of 0.20$\pm$0.04 M_sun, confirming the redback status, although hotter than the majority of redbacks. The stellar dayside and nightside temperatures of 7500K and 7400K, respectively, indicate a weak irradiation effect on the companion, likely due to its high intrinsic luminosity. Although the pulsar mass cannot be precisely derived, a heavy (1.8-2.2 M_sun) neutron star is favoured, Comment: 16 pages, 11 figures, Accepted for publication in A&A

Pyramidal cells that emit spikes when the animal is at specific locations of the environment are known as "place cells": these neurons are thought to provide an internal representation of space via "cognitive maps". Here, we consider the Battaglia-Treves neural network model for cognitive map storage and reconstruction, instantiated with McCulloch & Pitts binary neurons. To quantify the information processing capabilities of these networks, we exploit spin-glass techniques based on Guerra's interpolation: in the low-storage regime (i.e., when the number of stored maps scales sub-linearly with the network size and the order parameters self-average around their means) we obtain an exact phase diagram in the noise vs inhibition strength plane (in agreement with previous findings) by adapting the Hamilton-Jacobi PDE-approach. Conversely, in the high-storage regime, we find that -- for mild inhibition and not too high noise -- memorization and retrieval of an extensive number of spatial maps is indeed possible, since the maximal storage capacity is shown to be strictly positive. These results, holding under the replica-symmetry assumption, are obtained by adapting the standard interpolation based on stochastic stability and are further corroborated by Monte Carlo simulations (and replica-trick outcomes for the sake of completeness). Finally, by relying upon an interpretation in terms of hidden units, in the last part of the work, we adapt the Battaglia-Treves model to cope with more general frameworks, such as bats flying in long tunnels.

Photon Number Resolving Detectors (PNRDs) are devices capable of measuring the number of photons present in an incident optical beam, enabling light sources to be measured and characterized at the quantum level. In this paper, we explore the performance and design considerations of a linearly multiplexed photon number-resolving single-photon detector array, integrated on a single mode waveguide. Our investigation focus on defining and analyzing the fidelity of such an array under various conditions and proposing practical designs for its implementation. Through theoretical analysis and numerical simulations, we show how propagation losses and dark counts may have a strong impact on the performance of the system and highlight the importance of mitigating these effects in practical implementations.

Two-dimensional materials are extraordinarily sensitive to external stimuli, making them ideal for studying fundamental properties and for engineering devices with new functionalities. One such stimulus, strain, affects the magnetic properties of the layered magnetic semiconductor CrSBr to such a degree that it can induce a reversible antiferromagnetic-to-ferromagnetic phase transition. Given the pervasiveness of non-uniform strain in exfoliated two-dimensional magnets, it is crucial to understand its impact on their magnetic behavior. Using scanning SQUID-on-lever microscopy, we directly image the effects of spatially inhomogeneous strain on the magnetization of layered CrSBr as it is polarized by a field applied along its easy axis. The evolution of this magnetization and the formation of domains is reproduced by a micromagnetic model, which incorporates the spatially varying strain and the corresponding changes in the local interlayer exchange stiffness. The observed sensitivity to small strain gradients along with similar images of a nominally unstrained CrSBr sample suggest that unintentional strain inhomogeneity influences the magnetic behavior of exfoliated samples and must be considered in the design of future devices., Comment: 15 pages, 4 figures, 1 supplementary section

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

For a Weyl semimetal (WSM) in a magnetic field, a semiclassical description of the Fermi-arc surface state dynamics is usually employed for explaining various unconventional magnetotransport phenomena, e.g., Weyl orbits, the three-dimensional Quantum Hall Effect, and the high transmission through twisted WSM interfaces. For a half-space geometry, we determine the low-energy quantum eigenstates for a four-band model of a WSM in a magnetic field perpendicular to the surface. The eigenstates correspond to in- and out-going chiral Landau level (LL) states, propagating (anti-)parallel to the field direction near different Weyl nodes, which are coupled by evanescent surface-state contributions generated by all other LLs. These replace the Fermi arc in a magnetic field. Computing the phase shift accumulated between in- and out-going chiral LL states, we compare our quantum-mechanical results to semiclassical predictions. We find quantitative agreement between both approaches., Comment: 17 pages, 10 figures

The vast majority of materials science knowledge exists in unstructured natural language, yet structured data is crucial for innovative and systematic materials design. Traditionally, the field has relied on manual curation and partial automation for data extraction for specific use cases. The advent of large language models (LLMs) represents a significant shift, potentially enabling efficient extraction of structured, actionable data from unstructured text by non-experts. While applying LLMs to materials science data extraction presents unique challenges, domain knowledge offers opportunities to guide and validate LLM outputs. This review provides a comprehensive overview of LLM-based structured data extraction in materials science, synthesizing current knowledge and outlining future directions. We address the lack of standardized guidelines and present frameworks for leveraging the synergy between LLMs and materials science expertise. This work serves as a foundational resource for researchers aiming to harness LLMs for data-driven materials research. The insights presented here could significantly enhance how researchers across disciplines access and utilize scientific information, potentially accelerating the development of novel materials for critical societal needs.

Given $p\geq 2$ and a map $g : B^n(0,1)\to S_n^{++}$, where $S_n^{++}$ is the group of positively definite matrices, we study critical points of the following functional: $$ v\in W^{1,p}\left(B^n(0,1);\mathbb{R}^N \right) \mapsto \int_{B^n(0,1)} |\nabla v|^p_g\, d\mathrm{vol}_g = \int_{B^n(0,1)} \left( g^{\alpha\beta}(x) \left\langle \partial_\alpha v(x), \partial_\beta v(x) \right\rangle \right)^{\frac{p}{2}}\, \sqrt{\det g(x)}\, dx. $$ We show that if $g$ is uniformly close to a constant matrix, then $v$ is locally H\"older-continuous. If $g$ is H\"older-continuous, we show that $\nabla v$ is locally H\"older-continuous. As an application, we specialize to the case $p=n$ and we prove that any continuous solution to $|\Delta_{g,n}u|\lesssim |\nabla u|^n_g$ satisfies additional regularity properties depending on the regularity of $g$., Comment: 23 pages

In this paper we investigate new results on the theory of superoscillations using time-frequency analysis tools and techniques such as the short-time Fourier transform (STFT) and the Zak transform. We start by studying how the short-time Fourier transform acts on superoscillation sequences. We then apply the supershift property to prove that the short-time Fourier transform preserves the superoscillatory behavior by taking the limit. It turns out that these computations lead to interesting connections with various features of time-frequency analysis such as Gabor spaces, Gabor kernels, Gabor frames, 2D-complex Hermite polynomials, and polyanalytic functions. We treat different cases depending on the choice of the window function moving from the general case to more specific cases involving the Gaussian and the Hermite windows. We consider also an evolution problem with an initial datum given by superoscillation multiplied by the time-frequency shifts of a generic window function. Finally, we compute the action of STFT on the approximating sequences with a given Hermite window., Comment: to appear in Applied and Computational Harmonic Analysis

The goal of the PolarKID project is testing a new method for the measurement of polarized sources, in order to identify all the possible instrumental systematic effects that could impact the detection of CMB B-modes of polarization. It employs the KISS (KIDs Interferometer Spectrum Survey) instrument coupled to a sky simulator and to sources such as point-like black bodies (simulating planets), a dipole (extended source) and a polarizer. We use filled-arrays Lumped Element Kinetic Inductance Detectors (LEKIDs) since they have multiple advantages when observing both in a photometry and in a polarimetry configuration, Comment: 8 pages, 1 figure, Proceeding of the SPIE conference Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy XII, SPIE Astronomical Telescopes + Instrumentation 2024

The discovery of pulsations in (at least) six ultraluminous X-ray sources (ULXs) has shown that neutron stars can accrete at (highly) super-Eddington rates, challenging the standard accretion theories. M51 ULX-7, with a spin signal of $P\simeq2.8$ s, is the pulsating ULX (PULX) with the shortest known orbital period ($P_\mathrm{orb}\simeq2$ d) and has been observed multiple times by XMM-Newton, Chandra, and NuSTAR. We report on the timing and spectral analyses of three XMM-Newton observations of M51 ULX-7 performed between the end of 2021 and the beginning of 2022, together with a timing re-analysis of XMM-Newton, Chandra, and NuSTAR archival observations. We investigated the spin signal by applying accelerated search techniques and studied the power spectrum through the fast Fourier transform, looking for (a)periodic variability in the source flux. We analysed the energy spectra of the 2021-2022 observations and compared them to the older ones. We report the discovery of a recurrent, significant ($>$3$\sigma$) broad complex at mHz frequencies in the power spectra of M51 ULX-7. We did not detect the spin signal, setting a 3$\sigma$ upper limit on the pulsed fraction of $\lesssim10\%$ for the single observation. The complex is significantly detected also in five Chandra observations performed in 2012. M51 ULX-7 represents the second PULX for which we have a significant detection of mHz-QPOs at super-Eddington luminosities. These findings suggest that one should avoid using the observed QPO frequency to infer the mass of the accretor in a ULX. The absence of spin pulsations when the broad complex is detected suggests that the mechanism responsible for the aperiodic modulation also dampens the spin signal's pulsed fraction. If true, this represents an additional obstacle in the detection of new PULXs, suggesting an even larger occurrence of PULXs among ULXs., Comment: 14 pages (12 main text + Appendix), 5 figures. Accepted for publication on A&A

The tilt-to-length coupling during the LISA Pathfinder mission has been numerically and analytically modeled for particular timespans. In this work, we investigate the long-term stability of the coupling coefficients of this noise. We show that they drifted slowly (by 1\,$\mu$m/rad and 6$\times10^{-6}$ in 100 days) and strongly correlated to temperature changes within the satellite (8\,$\mu$m/rad/K and 30$\times10^{-6}$/K). Based on analytical TTL coupling models, we attribute the temperature-driven coupling changes to rotations of the test masses and small distortions in the optical setup. Particularly, we show that LISA Pathfinder's optical baseplate was bent during the cooldown experiment, which started in late 2016 and lasted several months.

A precise characterization of the magnetic properties of LISA Pathfinder free falling test-masses is of special interest for future gravitational wave observatory in space. Magnetic forces have an important impact on the instrument sensitivity in the low frequency regime below the millihertz. In this paper we report on the magnetic injection experiments performed throughout LISA Pathfinder operations. We show how these experiments allowed a high precision estimate of the instrument magnetic parameters. The remanent magnetic moment was found to have a modulus of $(0.245\pm0.081)\,\rm{nAm}^2$, the x-component of the background magnetic field within the test masses position was measured to be $(414 \pm 74)$ nT and its gradient had a value of $(-7.4\pm 2.1)\,\mu$T/m. Finally, we also measured the test mass magnetic susceptibility to be $(-3.35\pm0.15)\times$10$^{-5}$ in the low frequency regime. All results are in agreement with on-ground estimates.

LISA Pathfinder was a mission designed to test key technologies required for gravitational wave detection in space. Magnetically driven forces play a key role in the instrument sensitivity in the low-frequency regime, which corresponds to the measurement band of interest for future space-borne gravitational wave observatories. Magnetic-induced forces couple to the test mass motion, introducing a contribution to the relative acceleration noise between the free falling test masses. In this Letter we present the first complete estimate of this term of the instrument performance model. Our results set the magnetic-induced acceleration noise during the February 2017 noise run of $\rm 0.25_{-0.08}^{+0.15}\,fm\,s^{-2}/\sqrt{Hz}$ at 1 mHz and $\rm 1.01_{-0.24}^{+0.73}\, fm\,s^{-2}/\sqrt{Hz}$ at 0.1 mHz. We also discuss how the non-stationarities of the interplanetary magnetic field can affect these values during extreme space weather conditions.

W2 (CXOGlb J002415.8-720436) is a cataclysmic variable (CV) in the Galactic globular cluster 47 Tucanae. Its modulation was discovered within the CATS@BAR project. The source shows all the properties of magnetic CVs, but whether it is a polar or an intermediate polar is still a matter of debate. This paper investigates the spectral and temporal properties of the source, using all archival X-ray data from Chandra and eROSITA Early Data Release, to establish whether the source falls within the category of polars or intermediate polars. We fitted Chandra archival spectra with three different models: a power law, a bremsstrahlung and an optically thin thermal plasma. We also explored the temporal properties of the source with searches for pulsations with a power spectral density analysis and a Rayleigh test ($Z_n^2$). W2 displays a mean luminosity of $\sim 10^{32}$ erg s$^{-1}$ over a 20-year span, despite lower values in a few epochs. The source is not detected in the latest observation, taken with Chandra in 2022, and we infer an X-ray luminosity $\leq 7 \times 10^{31}$ erg s$^{-1}$. The source spectral shape does not change over time and can be equally well fitted with each of the three models, with a best-fit photon index of 1.6 for the power law and best-fit temperatures of 10 keV for both the bremsstrahlung and the thermal plasma models. We confirm the previously detected period of 8649 s, ascribed to the binary orbital period, and found a cycle-to-cycle variability associated with this periodicity. No other significant pulsation is detected. Considering the source orbital period, luminosity, spectral characteristics, long-term evolution and strong cycle-to-cycle variability, we suggest that W2 is a magnetic CV of the polar type., Comment: 13 pages, 8 figures. Accepted for publication on A&A

We establish a quantum analogue of the classical metaplectic Howe duality involving the pair of Lie algebras $(\mathfrak{sp}_{2n},\mathfrak{sl}_2)$ in the case when $n=1$. Our results yield commuting representations of the pair of Drinfeld-Jimbo quantum groups $(\mathcal U_{q^2}(\mathfrak{sl}_2),\mathcal U_{q}(\mathfrak{sl}_2))$ realized in a suitable algebra of $q$-differential operators acting on the space of symplectic polynomial spinors. We obtain $q$-analogues for the symplectic Dirac operator, the Fischer decomposition, the expression for the symplectic polynomial monogenics and for the projection operators onto the monogenics. We also discuss $q$-analogues of generalized symmetries of the $q$-symplectic Dirac operator raising the homogeneous polynomial degree., Comment: 22 pages. Comments are welcome

Overflow metabolism is a ubiquitous phenomenon whereby cells in aerobic conditions excrete byproducts of glycolysis, such as lactate or acetate, into the medium in a seemingly wasteful and polluting fashion. Whilst overflow may confer microbes a fitness advantage by allowing them to overcome a finite oxidative capacity, its occurrence in higher organisms is harder to assess. Important insight was however obtained in recent experiments conducted at single-cell resolution, which revealed that accumulation of overflow products in tumor cell cultures known as the Warburg effect arises from imbalances in the dynamic and heterogeneous inter-cellular exchange network through which cells collectively regulate the microenvironment. Here we provide a quantitative characterization of this scenario by integrating metabolic network modeling with diffusion constraints, statistical physics theory and single-cell experimental flux data. On the theoretical side, we clarify how diffusion-limited exchanges shape the space of viable metabolic states of a multi-cellular system. Specifically, a phase transition from a balanced network of exchanges to an unbalanced overflow regime occurs as the mean cellular glucose and oxygen uptakes vary while single-cell metabolic phenotypes are highly heterogeneous around this transition. We then show that time-resolved data from human tumor-stroma cell co-cultures consistently map to this crossover region, supporting the idea that environmental deterioration reflects a failure of coordination among recurrently interacting cells. In summary, our findings suggest that, rather than deriving from multiple independent cell-autonomous processes, environmental control is an emergent feature of multi-cellular systems., Comment: Main(14 pages)+ supporting information(14 pages). Comments are welcome

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 illustrate a time and memory efficient application of Runge-Kutta discontinuous Galerkin (RKDG) methods for the simulation of the ultrasounds advection in moving fluids. In particular, this study addresses to the analysis of transit-time ultrasonic meters which rely on the propagation of acoustic waves to measure fluids flow rate. Accurate and efficient simulations of the physics related to the transport of ultrasounds are therefore crucial for studying and enhancing these devices. Starting from the description of the linearized Euler equations (LEE) model and presenting the general theory of explicit-time DG methods for hyperbolic systems, we then motivate the use of a spectral basis and introduce a novel high-accuracy method for the imposition of absorbing and resistive walls which analyses the incident wave direction across the boundary surface. The proposed implementation is both accurate and efficient, making it suitable for industrial applications of acoustic wave propagation.