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We present a theory for the relaxation time of the octupole order parameter in nanoscale chiral antiferromagnets (AFMs) coupled to thermal baths and spin injection sources. Using stochastic spin dynamics simulations, we demonstrate that the octupole moment relaxes through two distinct mechanisms$-$escape over a barrier and precessional dephasing$-$as the barrier for octupole fluctuations is lowered relative to the thermal energy. Notably, the octupole moment relaxes orders of magnitude faster than the typical dipolar order parameters, reaching picosecond timescales. By combining Langer's theory with an effective low-energy description of octupole dynamics in chiral AFMs, we derive analytical expressions for the relaxation times. We find that relaxation in chiral AFMs parallels dipole relaxation in XY magnets, with exchange fields serving the role of the dipole fields. Further, by drawing on the analogy between order parameter dynamics in XY magnets under spin injection and current-biased Josephson junctions, we propose a new scheme for electrically tuning the octupole relaxation times. Our work offers fundamental insights for the development of next-generation spintronic devices that harness octupole order parameters for information encoding, especially in octupole-based probabilistic computing.

It is believed that an isolated quantum many-body system far away from equilibrium should try to attain equilibrium via a mechanism whereby any given subsystem acts as an open quantum system that is coupled to an environment which is the complementary part of the full system and undergoing a complicated equilibration process such that all the subsystems in the long-time limit attain equilibrium states compatible with the global equilibrium state. This picture begs the question whether the dynamics of any given subsystem is Markovian (monotonic loss of information and memory) or non-Markovian. In this work, by numerically probing the dynamical behaviour of the distance between \textit{temporally-separated} subsystem states, we reveal the telltale signatures and other associated features of quantum (non-)Markovianity of the dynamics of small subsystems of an isolated quantum spin system in one dimension (the Ising spin chain) brought far from equilibrium by quantum quenches. Additionally, remarkably systematic behaviour is seen in the dynamics of the eigenvalues of the reduced density matrices of the subsystems. These features strongly depend on the direction of quenching in the parameter space, with paramagnetic-to-ferromagnetic quenches offering considerably stronger signatures of subsystem non-Markovianity, for which we offer heuristic arguments., Comment: 7 pages, 3 figures

To investigate spectra of kilonovae in the NLTE phase (t >=1week), we perform atomic calculations for dielectronic (DR) and radiative (RR) recombination rates for the light r-process elements: Se (Z = 34), Rb (Z = 37), Sr (Z = 38), Y (Z = 39), and Zr (Z = 40) using the HULLAC code. For the different elements, our results for the total rate coefficients for recombining from the ionization states of II to I, III to II, and IV to III vary between 10^{-13}-10^{-9} cm^3/s, 10^{-12}-10^{-10} cm^3/s, and 10^{-13}-10^{-10} cm^3/s, respectively, at a temperature of T = 10,000 K. We also provide fits to the ground state photoionization cross sections of the various ions, finding larger and more slowly declining values with energy in comparison to the hydrogenic approximation. Using this new atomic data, we study the impact on kilonova model spectra at phases of t = 10 days and t = 25 days using the spectral synthesis code SUMO. Compared to models using the previous treatment of recombination as a constant rate, the new models show significant changes in ionization and temperature, and correspondingly, in emergent spectra. With the new rates, we find that Zr (Z = 40) plays a yet more dominant role in kilonova spectra for light r-process compositions. Further, we show that previously predicted mid-infrared (e.g. [Se III] 4.55 \mum) and optical (e.g. [Rb I] 7802, 7949 A) lines disappear in the new model. Instead a strong [Se I] line is seen to be emerging at \lambda=5.03 \mum. These results demonstrate the importance of considering the detailed microphysics for modelling and interpreting the late-time kilonova spectra., Comment: Submitted to ApJ

The $\beta$-delayed neutron emission in the $^{85, 86}$As $\beta$-decays has been measured at the Ion Guide Isotope Separator On Line facility of the Accelerator Laboratory of the University of Jyv\"askyl\"a. The complete $\beta$-decays have been studied with a complex setup that consists of a plastic scintillator for $\beta$-particles, MONSTER -- the MOdular Neutron time-of-flight SpectromeTER -- for neutrons, and a high-purity germanium and four LaBr$_3$ crystals for $\gamma$-rays. The $\beta$-delayed neutron energy distributions have been determined by unfolding the time-of-flight spectra with an innovative methodology based on the iterative Bayesian unfolding method and accurate Monte Carlo simulations. The results obtained for $^{85}$As are in excellent agreement with the existing evaluated data, validating the proposed methodology. In the case of $^{86}$As, a stronger neutron intensity at higher energies than previously predicted is discovered., Comment: 10 pages, 11 figures, to be submitted to Physical Review C

We present ultraviolet (UV) spectroscopic observations covering three distinct accretion states of the low-mass X-ray binary (LMXB) MAXI J1820+070: the luminous hard state, a hard-intermediate state and the soft state. Our observations were obtained during the 2018 eruption of MAXI J1820+070 with the Hubble Space Telescope (HST) and AstroSat observatory. The extinction towards the source turns out to be low - $\rm E_{B-V} = 0.2 \pm 0.05$ - making it one of the best UV accretion laboratories among LMXBs. Remarkably, we observe only moderate differences between all three states, with all spectra displaying similar continuum shapes and emission lines. Moreover, the continua are not well-described by physically plausible irradiated disc models. All of this challenges the standard reprocessing picture for UV emission from erupting LMXBs. The UV emission lines are double-peaked, with high-ionization lines displaying higher peak-to-peak velocities. None of the lines display obvious outflow signatures, even though blue-shifted absorption features have been seen in optical and near-infrared lines during the hard state. The emission line ratios are consistent with normal abundances, suggesting that the donor mass at birth was low enough to avoid CNO processing ($\rm M_{2,i} \lesssim 1.0 - 1.5 {\mathrm M_{\odot}}$). Finally, we study the evolution of UV variability in our time-resolved HST observations (hard and hard-intermediate states). All UV power spectra can be modelled with a broken power-law, superposed on which we tentatively detect the $\simeq 18$s quasi-periodic oscillation (QPO) that has been seen in other spectral bands., Comment: 19 pages, 14 figures, submitted to MNRAS

We provide improved upper and lower bounds for the Min-Sum-Radii (MSR) and Min-Sum-Diameters (MSD) clustering problems with a bounded number of clusters $k$. In particular, we propose an exact MSD algorithm with running-time $n^{O(k)}$. We also provide $(1+\epsilon)$ approximation algorithms for both MSR and MSD with running-times of $O(kn) +(1/\epsilon)^{O(dk)}$ in metrics spaces of doubling dimension $d$. Our algorithms extend to $k$-center, improving upon previous results, and to $\alpha$-MSR, where radii are raised to the $\alpha$ power for $\alpha>1$. For $\alpha$-MSD we prove an exponential time ETH-based lower bound for $\alpha>\log 3$. All algorithms can also be modified to handle outliers. Moreover, we can extend the results to variants that observe \emph{fairness} constraints, as well as to the general framework of \emph{mergeable} clustering, which includes many other popular clustering variants. We complement these upper bounds with ETH-based lower bounds for these problems, in particular proving that $n^{O(k)}$ time is tight for MSR and $\alpha$-MSR even in doubling spaces, and that $2^{o(k)}$ bounds are impossible for MSD.

Rare events, due to their infrequent occurrences, do not have much data, and hence deep learning techniques fail in estimating the distribution for such data. Open-vocabulary models represent an innovative approach to image classification. Unlike traditional models, these models classify images into any set of categories specified with natural language prompts during inference. These prompts usually comprise manually crafted templates (e.g., 'a photo of a {}') that are filled in with the names of each category. This paper introduces a simple yet effective method for generating highly accurate and contextually descriptive prompts containing discriminative characteristics. Rare event detection, especially in medicine, is more challenging due to low inter-class and high intra-class variability. To address these, we propose a novel approach that uses domain-specific expert knowledge on rare events to generate customized and contextually relevant prompts, which are then used by large language models for image classification. Our zero-shot, privacy-preserving method enhances rare event classification without additional training, outperforming state-of-the-art techniques., Comment: Accepted in IEEE ISBI, 2025

Asymptotic behavior of generic Tomonaga-Luttinger liquid in the vicinity of phase-separated regions is known to produce an instability where well-known relativistic Conformal Field Theory (CFT) techniques fail. In this letter, we introduce an analytic paradigm which solves this important issue. We show that there is an emergent Carrollian symmetry when phase separation is reached and techniques of Carroll CFT, as opposed to its relativistic relative, is central to the understanding of the physics. We work with the analogous spinless fermionic system in this region and capture the transition across this phase separation. Our numerical results corroborate the density-density correlations intrinsically computed using Carroll CFT., Comment: 8+\epsilon pages including supplementary material. Comments are welcome!

Satellite and CubeSat-based quantum key distribution (QKD) presents a promising solution for secure long-distance communication by transmitting quantum keys through free space, with CubeSats offering a compact, cost-effective, and scalable platform for deployment. This study investigates the performance of statistical techniques used to compute the finite-block and single-pass secret key lengths (SKL) for weak coherent pulse (WCP)-based efficient BB84 and standard decoy-state BB84 protocols in CubeSat-based systems. An asymptotic key rate analysis is also conducted for both protocols, providing deeper insights into their theoretical performance within the CubeSat context. The channel transmittance is modeled using an elliptical beam approximation, and the key rate performance is evaluated under varying weather conditions for the downlink scenario. The results demonstrate that the efficient BB84 protocol consistently outperforms the standard version across different atmospheric conditions. Furthermore, the probability distribution of key rates (PDR) for both implementations is analyzed, offering a comprehensive evaluation of their practical effectiveness in CubeSat-based QKD applications.

Photonic crystal fibres (PCFs) are optical fibres that guide light using a modulated dielectric medium. They provide an exceptionally versatile platform for various applications, thanks to the flexibility with which light-guiding can be customised by modifying the fibre geometry. Here, we realise a PCF with guided modes produced by photonic bandstructure topology rather than conventional mode-trapping mechanisms. The design, which is compatible with the stack-and-draw fabrication process, consists of a cross-sectional photonic topological crystalline insulator with a disclination. A bulk-defect correspondence produces degenerate topological modes, lying below the cladding light line. We use various theoretical methods to confirm their topological origins, including a spectral localiser that makes minimal assumptions about the bandstructure. Our experiments on the fabricated topological fibre show it transmitting visible to near-infrared light with low losses of 10--20 dB/km, which do not increase much when the fibre is bent. A comparable solid-core PCF of conventional design exhibits substantially higher bending losses. Optical fibres based on topological modes thus hold promise for improved performance and novel functionalities.

Hydrogen production via the Hydrogen Evolution Reaction (HER) is critical for sustainable energy solutions, yet the reliance on expensive platinum (Pt) catalysts limits scalability. Zirconium-doped (\ce{Zr}-doped) MXenes, such as \ce{Ti3C2} and \ce{Ti3CN}, emerge as transformative alternatives, combining abundance, tunable electronic properties, and high catalytic potential. Using first-principles density functional theory (DFT), we show that \ce{Zr} doping at 3\% and 7\% significantly enhances HER activity by reducing the work function to the optimal range of 3.5-4.5~eV and achieving near-zero Gibbs free energy (\dgh) values of 0.18-0.16~eV, conditions ideal for efficient hydrogen adsorption and desorption. Bader charge analysis reveals substantial charge redistribution with enhanced electron accumulation at \ce{Zr} and \ce{N} sites, further driving catalytic performance. This synergy between optimized electronic structure and catalytic properties establishes \ce{Zr}-doped MXenes as cost-effective, high-performance alternatives to noble metals for HER. By combining exceptional catalytic efficiency with scalability, our work positions \ce{Zr}-doped MXenes as a breakthrough for green hydrogen production, offering a robust pathway toward renewable energy technologies and advancing the design of next-generation non-precious metal catalysts.

A comprehensive characterization of internal climate variability and irreducible uncertainty through initial-condition large ensembles of Earth system models across different spatiotemporal scales remains a significant challenge in climate science. In this study, we find significant differences in the spatial connectivity structures of temperature networks across ensemble members, with variations in long-range connections providing a distinguishing feature across the outcomes of initial conditions. Based on this, we introduce a novel quantifier, the 'Connectivity Ratio' (R), to encapsulate the spatial connectivity structure of each ensemble member by investigating the influence of internal climate variability on the global connectivity patterns in air temperatures. R allows us to characterize the variability of spatial dependence structure across the initial condition ensemble members as well as multiple models. Furthermore, we examine changes in spatial connectivity between near-term and long-term projections using R, which shows a potential shift in climate predictability under anthropogenic influence on a spatial scale., Comment: 30 pages, 7 figures

Dynamic max-min fair allocation (DMMF) is a simple and popular mechanism for the repeated allocation of a shared resource among competing agents: in each round, each agent can choose to request or not for the resource, which is then allocated to the requesting agent with the least number of allocations received till then. Recent work has shown that under DMMF, a simple threshold-based request policy enjoys surprisingly strong robustness properties, wherein each agent can realize a significant fraction of her optimal utility irrespective of how other agents' behave. While this goes some way in mitigating the possibility of a 'tragedy of the commons' outcome, the robust policies require that an agent defend against arbitrary (possibly adversarial) behavior by other agents. This however may be far from optimal compared to real world settings, where other agents are selfish optimizers rather than adversaries. Therefore, robust guarantees give no insight on how agents behave in an equilibrium, and whether outcomes are improved under one. Our work aims to bridge this gap by studying the existence and properties of equilibria under DMMF. To this end, we first show that despite the strong robustness guarantees of the threshold based strategies, no Nash equilibrium exists when agents participate in DMMF, each using some fixed threshold-based policy. On the positive side, however, we show that for the symmetric case, a simple data-driven request policy guarantees that no agent benefits from deviating to a different fixed threshold policy. In our proposed policy agents aim to match the historical allocation rate with a vanishing drift towards the rate optimizing overall welfare for all users. Furthermore, the resulting equilibrium outcome can be significantly better compared to what follows from the robustness guarantees., Comment: 45 pages, 2 Figures, Sigmetrics 2025

Tidally induced spin-up of stripped helium stars in short-period (<\,1\,d) binaries with black holes has been presented as one of the possible mechanisms to reproduce the high-spin tail of the black hole spin distribution derived from gravitational wave (GW) merger observations. At such short periods, a fraction of the strong stellar wind from the stripped helium stars may be accreted by the black holes, and its gravitational potential energy may be released as observable radiation in the X-ray regime. We estimate the X-ray luminosity and its observability from black holes in orbit with stripped helium stars, which evolve into binary black hole or black hole+neutron star binaries that merge within Hubble time. We post-process recent advancements for estimating X-ray luminosities (via wind accretion onto stellar mass black holes) into two rapid population synthesis codes, BSE and StarTrack. We derive lower limits on the X-ray luminosity distribution from populations of stripped helium+black hole binaries at four metallicities (0.01, 0.1, 0.5, 1 $Z_{\odot}$) and two mass transfer stability criteria. We find that a large fraction (0.1-0.5) of stripped-helium stars that get spun up by tides also transfer enough wind matter onto the black hole to produce X-ray luminosities above $10^{35}$\,erg\,s$^{-1}$, up to $\sim10^{39}$\,erg\,s$^{-1}$. Such binaries should be observable as X-ray bright systems at 0.1\,$Z_{\odot}$, 0.5\,$Z_{\odot}$ and $Z_{\odot}$, representative of Sextans A, the Large Magellanic Cloud (LMC) and the Solar neighbourhood, respectively. The formation efficiency of these systems increases with decreasing metallicity. However, accounting for the local star formation rates, our population synthesis predicts $\sim$2 and $\sim$1 such observable binaries in the Milky Way and LMC, respectively, that will produce a binary compact object merger within a Hubble time. (Abridged), Comment: submitted to A&A, comments welcome

In this article, we highlight physics improvements in the NuWro Monte Carlo event generator. The upcoming version of NuWro will incorporate the integration of the argon spectral function for quasi-elastic scattering, along with the MINER$\nu$A parametrization of the axial form factor. Additionally, the new release will feature the implementation of the Valencia 2020 model for meson exchange current. The previously used simplistic delta resonance model for single-pion production will be replaced by a more accurate Ghent hybrid model in the upcoming version of NuWro. We also discuss the recent advancements made by the Wroclaw Neutrino Group in applying machine-learning techniques to achieve model-independent reconstruction of lepton-nucleus interactions, Comment: 4 pages, 3 figures. This is a conference proceeding. The text may overlap from [1]https://doi.org/10.48550/arXiv.2312.13369 [2] https://doi.org/10.48550/arXiv.2411.11523 [3]https://doi.org/10.48550/arXiv.2405.05212 [4] https://doi.org/10.48550/arXiv.2312.17298 [5] https://doi.org/10.48550/arXiv.2408.09936

In recent years, materials with topological flat bands have attracted significant attention due to their association with extraordinary transport properties and strongly correlated electrons. This includes phenomena such as high-temperature superconductivity, magnetism, Wigner crystallization, and Mott-insulating behavior. Among these systems, two-dimensional (2D) materials are particularly compelling as they can host electronic states with unique band structures, such as dispersionless states alongside linearly dispersive Dirac cones. In this work, we use tight-binding models to comprehensively investigate a class of 2D lattices that generically support flat bands, and focus on the effects of strain on their electronic and topological properties. The studied lattices are constructed within a unifying graph-theoretic framework, whereupon split-graph and line-graph operations on bipartite square and hexagonal lattices are employed to generate new structures. In the absence of strain, the introduction of spin-orbit coupling (SOC) induces a bulk excitation gap, which transforms flat bands into quasi-flat bands with topologically nontrivial characteristics. By tuning system parameters and external strain, we observe the emergence of directional flat bands, and tilted and semi-Dirac cones. Remarkably, all lattices studied show phase transitions among trivial insulating, semimetallic, and topological phases. Our results highlight the potential of strain engineering as a versatile tool for manipulating electronic and topological phases in a wide variety of 2D materials., Comment: Keywords: Flat bands, strongly correlated electrons, topological phase transitions, graph theory, 2D materials

Quasi-one-dimensional (1D) materials can manifest exotic electronic properties in manners that are distinct from the bulk phase or other low-dimensional systems. Helical symmetries in such materials -- e.g., nanotubes with intrinsic or applied twist -- can simultaneously lead to strong electronic correlation and anomalous transport behavior. However, these materials remain underexplored, in part due to computational challenges. Using specialized symmetry-adapted first-principles calculations, we show that mono-layer $P_2C_3$ -- identified in a previous letter to possess ``double Kagome bands'' -- exhibits a number of striking properties when rolled up into phosphorous carbide nanotubes ($P_2C_3$NTs). Both armchair and zigzag $P_2C_3$NTs are stable at room temperature and display a degenerate combination of Dirac points and electronic flat bands at the Fermi level. Notably, these flat bands are highly resilient to elastic deformations. Large strains can transform the nanotube structure from honeycomb-kagome to ``brick-wall'', and trigger multiple quantum phase transitions. Edge states in $P_2C_3$NTs, spin-degeneracy lifting induced by vacancies and dopants, and strain-tunable magnetism are also discussed., Comment: Keywords: chiral nanomaterial, flat bands, strong correlation, quantum phase transition

Despite more than fifty years of gamma-ray burst (GRB) observations, several questions regarding the origin of the prompt emission, particularly at high energies, remain unresolved. We present a comprehensive analysis of 35 GRBs observed by \textit{Fermi}/GBM and \textit{Fermi}/LAT over the past 15 years, focusing on the nature of high-energy (HE, E$>$100 MeV) emission during the prompt emission phase. Our study combines temporal and spectral analyses to investigate the synchrotron origin of the observed emission spanning the energy range from 10 keV to 100 GeV and explore the possible contribution of additional spectral components. Temporal modeling of \textit{Fermi}/LAT light curves for 12 GRBs in our sample reveals deviations from standard afterglow scenarios during the early phases, suggesting a significant contamination from prompt emission. We find that most GRB spectra align with synchrotron emission extending to GeV energies, with the slope $p$ of the non-thermal electron distribution clustering around $p\sim2.7$, consistently with theoretical predictions. For three GRBs, an additional power law component is required to explain the high-energy emission, but the nature and temporal evolution of this component remain unclear due to the limited quality of \textit{Fermi}/LAT data. When the power law component is needed, the synchrotron spectrum shows a sharp MeV suppression. It could be explained by the pair loading effects in the early afterglow. These findings emphasize the importance of multi-wavelength observations in unveiling the mechanisms driving early HE prompt emission in GRBs. We briefly discuss the implications of our findings for future very-high-energy (VHE, E$>$100 GeV) gamma-ray observatories, such as the Cherenkov Telescope Array, and address the detection prospects of additional non-thermal components in GRB spectra., Comment: Comments and suggestions are welcome

We present ASTRA (A} Scene-aware TRAnsformer-based model for trajectory prediction), a light-weight pedestrian trajectory forecasting model that integrates the scene context, spatial dynamics, social inter-agent interactions and temporal progressions for precise forecasting. We utilised a U-Net-based feature extractor, via its latent vector representation, to capture scene representations and a graph-aware transformer encoder for capturing social interactions. These components are integrated to learn an agent-scene aware embedding, enabling the model to learn spatial dynamics and forecast the future trajectory of pedestrians. The model is designed to produce both deterministic and stochastic outcomes, with the stochastic predictions being generated by incorporating a Conditional Variational Auto-Encoder (CVAE). ASTRA also proposes a simple yet effective weighted penalty loss function, which helps to yield predictions that outperform a wide array of state-of-the-art deterministic and generative models. ASTRA demonstrates an average improvement of 27%/10% in deterministic/stochastic settings on the ETH-UCY dataset, and 26% improvement on the PIE dataset, respectively, along with seven times fewer parameters than the existing state-of-the-art model (see Figure 1). Additionally, the model's versatility allows it to generalize across different perspectives, such as Bird's Eye View (BEV) and Ego-Vehicle View (EVV).

Charged scalars appear in many motivated extensions beyond the Standard Model. We analyze the constraints on charged scalar pair production via the Drell-Yan process at the Large Hadron Collider and interpret them in terms of weak isospin quantum numbers. Leveraging the experimental limits from existing LHC data and phenomenological recast analyses, we place bounds on the branching ratio of the charged scalar, as a function of its mass, electric charge, and isospin. This approach enables to determine limits on the branching ratios directly from experimental data, without appealing to a specific model. We provide a detailed analysis for singly and doubly charged scalars across various weak isospin scenarios, focusing on decays into leptonic and bosonic final states, and validate this approach in extended Higgs sectors such as the Higgs triplet model and Georgi-Machacek model., Comment: 16 pages, 7 captioned figures. Comments are welcome

In this article, we try to complete the regularity implications between the regularitites of the well-known tree forcing notions at the $\boldsymbol{\Delta}^1_2$ level of the projective hierarchy. The missing links in this case were the regularities corresponding to Matet and Willow tree Forcings. Some of the techniques yield more general results related to locally countable closed graphs too, which we mention as corollaries.

In this paper, using the concept of ideal, we study the idea of rough ideal convergence of sequences which is an extension of the notion of rough convergence of sequences in a partial metric space. We define the set of rough $\mathcal{I}$-limit points and the set of rough $\mathcal{I}$-cluster points and then we prove some relevant results associated with these sets., Comment: 10 pages

This study investigates the internal mechanisms of BERT, a transformer-based large language model, with a focus on its ability to cluster narrative content and authorial style across its layers. Using a dataset of narratives developed via GPT-4, featuring diverse semantic content and stylistic variations, we analyze BERT's layerwise activations to uncover patterns of localized neural processing. Through dimensionality reduction techniques such as Principal Component Analysis (PCA) and Multidimensional Scaling (MDS), we reveal that BERT exhibits strong clustering based on narrative content in its later layers, with progressively compact and distinct clusters. While strong stylistic clustering might occur when narratives are rephrased into different text types (e.g., fables, sci-fi, kids' stories), minimal clustering is observed for authorial style specific to individual writers. These findings highlight BERT's prioritization of semantic content over stylistic features, offering insights into its representational capabilities and processing hierarchy. This study contributes to understanding how transformer models like BERT encode linguistic information, paving the way for future interdisciplinary research in artificial intelligence and cognitive neuroscience., Comment: arXiv admin note: text overlap with arXiv:2408.03062, arXiv:2408.04270, arXiv:2307.01577

We study strong existence and pathwise uniqueness for a class of infinite-dimensional singular stochastic differential equations (SDE), with state space as the cone $\{x \in \mathbb{R}^{\mathbb{N}}: -\infty < x_1 \leq x_2 \leq \cdots\}$, referred to as an infinite system of competing Brownian particles. A `mass' parameter $p \in [0,1]$ governs the splitting proportions of the singular collision local time between adjacent state coordinates. Solutions in the case $p=1/2$ correspond to the well-studied rank-based diffusions, while the general case arises from scaling limits of interacting particle systems on the lattice with asymmetric interactions and the study of the KPZ equation. Under conditions on the initial configuration, the drift vector, and the growth of the local time terms, we establish pathwise uniqueness and strong existence of solutions to the SDE. A key observation is the connection between pathwise uniqueness and the finiteness of `chains of collisions' between adjacent particles influencing a tagged particle in the system. Ingredients in the proofs include classical comparison and monotonicity arguments for reflected Brownian motions, techniques from Brownian last-passage percolation, large deviation bounds for random matrix eigenvalues, and concentration estimates for extrema of Gaussian processes., Comment: 50 pages

Developing a dark matter detector with wide mass tunability is an immensely desirable property, yet it is challenging due to maintaining strong sensitivity. Resonant cavities for dark matter detection have traditionally employed mechanical tuning, moving parts around to change electromagnetic boundary conditions. However, these cavities have proven challenging to operate in sub-Kelvin cryogenic environments due to differential thermal contraction, low heat capacities, and low thermal conductivities. Instead, we develop an electronically tunable cavity architecture by coupling a superconducting 3D microwave cavity with a DC flux tunable SQUID. With a flux delivery system engineered to maintain high coherence in the cavity, we perform a hidden-photon dark matter search below the quantum-limited threshold. A microwave photon counting technique is employed through repeated quantum non-demolition measurements using a transmon qubit. With this device, we perform a hidden-photon search with a dark count rate of around 64 counts/s and constrain the kinetic mixing angle to ${\varepsilon}< 4\times 10^{-13}$ in a tunable band from 5.672 GHz to 5.694 GHz. By coupling multimode tunable cavities to the transmon, wider hidden-photon searching ranges are possible.

Detecting and interpreting operator actions, engagement, and object interactions in dynamic industrial workflows remains a significant challenge in human-robot collaboration research, especially within complex, real-world environments. Traditional unimodal methods often fall short of capturing the intricacies of these unstructured industrial settings. To address this gap, we present a novel Multimodal Industrial Activity Monitoring (MIAM) dataset that captures realistic assembly and disassembly tasks, facilitating the evaluation of key meta-tasks such as action localization, object interaction, and engagement prediction. The dataset comprises multi-view RGB, depth, and Inertial Measurement Unit (IMU) data collected from 22 sessions, amounting to 290 minutes of untrimmed video, annotated in detail for task performance and operator behavior. Its distinctiveness lies in the integration of multiple data modalities and its emphasis on real-world, untrimmed industrial workflows-key for advancing research in human-robot collaboration and operator monitoring. Additionally, we propose a multimodal network that fuses RGB frames, IMU data, and skeleton sequences to predict engagement levels during industrial tasks. Our approach improves the accuracy of recognizing engagement states, providing a robust solution for monitoring operator performance in dynamic industrial environments. The dataset and code can be accessed from https://github.com/navalkishoremehta95/MIAM/., Comment: Accepted at the 20th International Conference on Human-Robot Interaction (HRI) 2025

This study investigates the feasibility of the phase-matching measurement-device-independent quantum key distribution (PM-MDI QKD) protocol proposed by Lin and L\"utkenhaus for satellite-based quantum communication. The protocol's key rate, known to exceed the repeaterless bound, is evaluated in the asymptotic limit under noisy conditions typical of satellite communications, including loss-only scenarios. The setup involves two ground-based parties connected via fiber (lossonly or noisy) and a space-based third party linked to one of these two ground-based parties through free-space communication. Simulations using the elliptic-beam approximation model the average key rate (AKR) and its probability distribution (PDR) across varying zenith angles and fiber distances. Down-link free-space communication is assessed under day and night conditions, with intensity optimization for each graphical point. Dynamic configurations of satellite and ground stations are also considered. Results indicate that AKR decays more slowly under loss-only conditions, while PDR analysis shows higher key rates produce more concentrated distributions. These findings demonstrate the potential of PM-MDI QKD protocols for achieving reliable key rates in satellitebased quantum communication., Comment: PM-MDI QKD, Free-space communication, Security

The global rotational profile of the solar atmosphere and its variation at different layers, although crucial for a comprehensive understanding of the dynamics of the solar magnetic field, has been a subject to contradictory results throughout the past century. In this study, we thereby unify the results for different parts of the multi-thermal Solar atmosphere by utilizing 13 years of data in 7 wavelength channels of the Atmospheric Imaging Assembly (AIA) atop the Solar Dynamic Observatory (SDO). Using the method of image correlation, we find that the solar atmosphere exhibits a rotational profile that is up to 4.18% and 1.92% faster at the equator and comparatively less differential than that of the photosphere, as derived from Doppler measurements and sunspots, respectively and exhibits variation at different respective heights. Additionally, we find results suggestive of the role played by the rooting of different magnetic field structures on a comparison with helioseismology data., Comment: 4 pages, 2 figures, Proceedings for XXXIInd IAU General Assembly Focused Meeting (FM)-8

With the growing computational capabilities of microcontroller units (MCUs), edge devices can now support machine learning models. However, deploying decentralised federated learning (DFL) on such devices presents key challenges, including intermittent connectivity, limited communication range, and dynamic network topologies. This paper proposes a novel framework, bilayer Gossip Decentralised Parallel Stochastic Gradient Descent (GD PSGD), designed to address these issues in resource-constrained environments. The framework incorporates a hierarchical communication structure using Distributed Kmeans (DKmeans) clustering for geographic grouping and a gossip protocol for efficient model aggregation across two layers: intra-cluster and inter-cluster. We evaluate the framework's performance against the Centralised Federated Learning (CFL) baseline using the MCUNet model on the CIFAR-10 dataset under IID and Non-IID conditions. Results demonstrate that the proposed method achieves comparable accuracy to CFL on IID datasets, requiring only 1.8 additional rounds for convergence. On Non-IID datasets, the accuracy loss remains under 8\% for moderate data imbalance. These findings highlight the framework's potential to support scalable and privacy-preserving learning on edge devices with minimal performance trade-offs.

Assessment of the density of mitotic figures (MFs) in histologic tumor sections is an important prognostic marker for many tumor types, including breast cancer. Recently, it has been reported in multiple works that the quantity of MFs with an atypical morphology (atypical MFs, AMFs) might be an independent prognostic criterion for breast cancer. AMFs are an indicator of mutations in the genes regulating the cell cycle and can lead to aberrant chromosome constitution (aneuploidy) of the tumor cells. To facilitate further research on this topic using pattern recognition, we present the first ever publicly available dataset of atypical and normal MFs (AMi-Br). For this, we utilized two of the most popular MF datasets (MIDOG 2021 and TUPAC) and subclassified all MFs using a three expert majority vote. Our final dataset consists of 3,720 MFs, split into 832 AMFs (22.4%) and 2,888 normal MFs (77.6%) across all 223 tumor cases in the combined set. We provide baseline classification experiments to investigate the consistency of the dataset, using a Monte Carlo cross-validation and different strategies to combat class imbalance. We found an averaged balanced accuracy of up to 0.806 when using a patch-level data set split, and up to 0.713 when using a patient-level split.

This article reports the development of a versatile high-speed reciprocating drive system (HRDS) with interchangeable probe heads to characterize the edge plasma region of ADITYA-U tokamak. This reciprocating probe drive system consisting of Langmuir and magnetic probe heads, is designed, fabricated, installed, and operated for studying the extent of fuel/impurity gas propagation and its influence on plasma dynamics in the far-edge region inside the last closed magnetic flux surface (LCFS). The HRDS is driven by a highly accurate, easy-to-control, dynamic, brushless, permanently excited synchronous servo motor operated by a PXI-commanded controller. The system is remotely operated and allows for precise control of the speed, acceleration, and distance traveled of the probe head on a shot-to-shot basis, facilitating seamless control of operations according to experimental requirements. Using this system, consisting of a linear array of Langmuir probes, measurements of plasma density, temperature, potential, and their fluctuations revealed that the fuel gas-puff impact these mean and fluctuating parameters up to three to four cm inside the LCFS. Attaching an array of magnetic probes to this system led to measurements of magnetic fluctuations inside the LCFS. The HRDS system is fully operational and serves as an important diagnostic tool for ADITYA-U tokamak.

We present 50-fs, single-shot measurements of the x-ray thermal diffuse scattering (TDS) from copper foils that have been shocked via nanosecond laser-ablation up to pressures above 135~GPa. We hence deduce the x-ray Debye-Waller (DW) factor, providing a temperature measurement. The targets were laser-shocked with the DiPOLE 100-X laser at the High Energy Density (HED) endstation of the European X-ray Free-Electron Laser (EuXFEL). Single x-ray pulses, with a photon energy of 18 keV, were scattered from the samples and recorded on Varex detectors. Despite the targets being highly textured (as evinced by large variations in the elastic scattering), and with such texture changing upon compression, the absolute intensity of the azimuthally averaged inelastic TDS between the Bragg peaks is largely insensitive to these changes, and, allowing for both Compton scattering and the low-level scattering from a sacrificial ablator layer, provides a reliable measurement of $T/\Theta_D^2$, where $\Theta_D$ is the Debye temperature. We compare our results with the predictions of the SESAME 3336 and LEOS 290 equations of state for copper, and find good agreement within experimental errors. We thus demonstrate that single-shot temperature measurements of dynamically compressed materials can be made via thermal diffuse scattering of XFEL radation., Comment: 17 pages, 9 figures in main article; 10 pages, 5 figures in supplementary material

The Solar Ultraviolet Imaging Telescope (SUIT) is an instrument on the Aditya-L1 mission of the Indian Space Research Organization (ISRO) launched on September 02, 2023. SUIT continuously provides, near-simultaneous full-disk and region-of-interest images of the Sun, slicing through the photosphere and chromosphere and covering a field of view up to 1.5 solar radii. For this purpose, SUIT uses 11 filters tuned at different wavelengths in the 200{--}400~nm range, including the Mg~{\sc ii} h~and~k and Ca~{\sc ii}~H spectral lines. The observations made by SUIT help us understand the magnetic coupling of the lower and middle solar atmosphere. In addition, for the first time, it allows the measurements of spatially resolved solar broad-band radiation in the near and mid ultraviolet, which will help constrain the variability of the solar ultraviolet irradiance in a wavelength range that is central for the chemistry of the Earth's atmosphere. This paper discusses the details of the instrument and data products., Comment: 37 pages, Accepted for Publication in Solar Physics

Mesoscopic active systems exhibit various unique behaviours - absent in passive systems - due to the forces generated by the corresponding constituents by converting their available free energies. However, finding out these forces - which are also stochastic and remain intertwined with the thermal noise - is especially non-trivial. Here, we introduce a technique to extract such fluctuating active forces, with statistical accuracy, acting on a passive particle immersed in an active bath by filtering out the related thermal noise. First, we test the efficacy of our method under numerical scenarios and then apply it to the experimental trajectories of a microscopic particle (optically) trapped inside an active bath consisting of motile E.Coli. bacteria. We believe that our approach would be rather effective in the actual measurement of unknown active forces, which are a crucial component in processes involving living matter., Comment: 9 pages, 5 figures

Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of General Relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO--Virgo--KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering the single-harmonic and the dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the asymmetry in the neutron star mass distribution. For the single-harmonic emission model, 29 targets have the upper limit on the amplitude below the theoretical spin-down limit. The lowest upper limit on the amplitude is $6.4\!\times\!10^{-27}$ for the young energetic pulsar J0537-6910, while the lowest constraint on the ellipticity is $8.8\!\times\!10^{-9}$ for the bright nearby millisecond pulsar J0437-4715. Additionally, for a subset of 16 targets we performed a narrowband search that is more robust regarding the emission model, with no evidence of a signal. We also found no evidence of non-standard polarizations as predicted by the Brans-Dicke theory., Comment: main paper: 12 pages, 6 figures, 4 tables

We here propose and study theoretically a non-equilibrium mechanism for the superconducting diode effect, which applies specifically to the case where time-reversal-symmetry -- a prerequisite for the diode effect -- is spontaneously broken by the superconducting electrons themselves. We employ a generalized time-dependent Ginzburg-Landau formalism to capture dissipation effects in the non-equilibrium current-carrying state via phase slips and show that the coupling of the resistive current to the symmetry-breaking order is enough to induce a diode effect. Depending on parameters, the critical current asymmetry can be sizeable, asymptotically reaching a perfect diode efficiency; the competition of symmetry-breaking order, superconducting and resistive currents gives rise to rich physics, such as current-stabilized, non-equilibrium superconducting correlations. Although our mechanism is more general, the findings are particularly relevant to twisted trilayer and rhombohedral tetralayer graphene, where the symmetry-breaking order parameter refers to the imbalance of the two valleys of the systems.

We study the real-time bulk AdS$_3$ two-into-two scattering amplitude of conical defects. This is done through means of a previously developed method of systematic approximation of the monodromy problem for the Virasoro blocks of the four-point HHHH correlator in 2d CFT in the large central charge regime. We find that dialing the external scaling dimension triggers a transition from a scattering phase to an intermediate black hole phase. This transition occurs before the individual heavy operators exceed the BTZ mass gap., Comment: 27 pages, 8 figures, 1 appendix

We prove that the space of algebraic maps between two smooth projective varieties, under certain conditions, admit a configuration space model, thereby obtaining an algebro-geometric analogue of Bendersky-Gitler's result on topological function spaces. Our result is a natural higher dimensional counterpart of \cite[Theorem 3]{Ban24}., Comment: 22 pages. Comments are welcome!

Any local unitary 3d $\mathcal{N}=4$ superconformal field theory (SCFT) has a corresponding "universal" relevant deformation that takes it to a gapped phase. This deformation preserves all continuous internal symmetries, $\mathcal{S}$, and therefore also preserves any 't Hooft anomalies supported purely in $\mathcal{S}$. We describe the resulting phase diagram in the case of SCFTs that arise as the endpoints of renormalization group flows from 3d $\mathcal{N}=4$ Abelian gauge theories with any number of $U(1)$ gauge group factors and arbitrary integer charges for the matter fields. We argue that the universal deformations take these QFTs to Abelian fractional quantum Hall states in the infrared (IR), and we explain how to match 't Hooft anomalies between the non-topological ultraviolet theories and the IR topological quantum field theories (TQFTs). Along the way, we give a proof that 3d $\mathcal{N}=4$ mirror symmetry of our Abelian gauge theories descends to a duality of these TQFTs. Finally, using our anomaly matching discussion, we describe how to connect, via the renormalization group, abstract local unitary 3d $\mathcal{N}=4$ SCFTs with certain 't Hooft anomalies for their internal symmetries to IR phases (partially) described by Abelian spin Chern-Simons theories., Comment: 50 pages; 4 figures

In both smooth and analytic categories, we construct examples of diffeomorphisms of topological entropy zero with intricate ergodic properties. On any smooth compact connected manifold of dimension 2 admitting a nontrivial circle action, we construct a smooth diffeomorphism whose differential is weakly mixing with respect to a smooth measure in the projectivization of the tangent bundle. In case of the 2-torus, we also obtain the analytic counterpart of such a diffeomorphism. The constructions are based on a quantitative version of the ``Approximation by Conjugation'' method, which involves explicitly defined conjugation maps, partial partitions, and the adaptation of a specific analytic approximation technique., Comment: 43 pages, 2 figures

The problem of quickest detection of a change in the distribution of a sequence of random variables is studied. The objective is to detect the change with the minimum possible delay, subject to constraints on the rate of false alarms and the cost of observations used in the decision-making process. The post-change distribution of the data is known only within a distribution family. It is shown that if the post-change family has a distribution that is least favorable in a well-defined sense, then a computationally efficient algorithm can be designed that uses an on-off observation control strategy to save the cost of observations. In addition, the algorithm can detect the change robustly while avoiding unnecessary false alarms. It is shown that the algorithm is also asymptotically robust optimal as the rate of false alarms goes to zero for every fixed constraint on the cost of observations. The algorithm's effectiveness is validated on simulated data and real public health data.

Humblebragging is a phenomenon where individuals present self-promotional statements under the guise of modesty or complaints. For example, a statement like, "Ugh, I can't believe I got promoted to lead the entire team. So stressful!", subtly highlights an achievement while pretending to be complaining. Detecting humblebragging is important for machines to better understand the nuances of human language, especially in tasks like sentiment analysis and intent recognition. However, this topic has not yet been studied in computational linguistics. For the first time, we introduce the task of automatically detecting humblebragging in text. We formalize the task by proposing a 4-tuple definition of humblebragging and evaluate machine learning, deep learning, and large language models (LLMs) on this task, comparing their performance with humans. We also create and release a dataset called HB24, containing 3,340 humblebrags generated using GPT-4o. Our experiments show that detecting humblebragging is non-trivial, even for humans. Our best model achieves an F1-score of 0.88. This work lays the foundation for further exploration of this nuanced linguistic phenomenon and its integration into broader natural language understanding systems., Comment: Under review at ARR

Near the horizon of extremal charged black holes, an accidental symmetry is known to act on zero-temperature perturbations, transforming them into finite-temperature ones. In this paper, we uncover the corresponding accidental symmetry of the vacuum Einstein equation near the horizon of extremal spinning black holes. To do so, we first devise a new method of deriving the symmetry near the ${\rm AdS}_2 \times S^2$ near-horizon geometry of extreme Reissner-Nordstr\"om, using a new scaling coordinate transformation that unifies the near-horizon limits of extremal and near-extremal black holes in a way that is regular at zero temperature. We use our new method to obtain the accidental symmetry in the near-horizon of extreme Kerr (NHEK). We show that accidental symmetries combine neatly with the near-horizon isometries inside a Virasoro algebra., Comment: 18 pages

Qutrit-based quantum circuits could help reduce the overall circuit depths, and hence the noise, when the system of interest has local dimension of three. Accessing second excited states in superconducting transmons provides a straightforward hardware realization of three-level systems, or qutrits, useful for such ternary encoding. In this work, we successfully calibrate pulse gates to a low error rate to obtain transmon qutrits. We use these qutrits to simulate one-dimensional spin-1 AKLT states (Affleck, Lieb, Kennedy, and Tasaki) which exhibit a multitude of interesting phenomena such as topologically protected ground states, string order and the existence of a robust Berry phase. We demonstrate the efficacy of qutrit-based simulation by preparing high-fidelity ground states of the AKLT Hamiltonian with open boundaries for various chain lengths. We then use ground state preparations of the perturbed AKLT Hamiltonian with periodic boundaries to calculate the Berry phase and illustrate non-trivial ground state topology. We further present scalable methods for preparing the AKLT state and computing its Berry phase, and use tensor network simulations to establish the advantage of qutrit-based implementation over qubit-based ones in the presence of noise. Our work provides a pathway toward more general spin-1 physics simulations using transmon qutrits, with applications in chemistry, magnetism, and topological phases of matter.

We present a measurement of the branching fraction and fraction of longitudinal polarization of $B^0 \to \rho^+ \rho^-$ decays, which have two $\pi^0$'s in the final state. We also measure time-dependent $CP$ violation parameters for decays into longitudinally polarized $\rho^+ \rho^-$ pairs. This analysis is based on a data sample containing $(387\pm6) \times 10^6$ \BBbar pairs collected with the Belle~II detector at the SuperKEKB asymmetric-energy $e^+e^-$ collider in 2019-2022. We obtain ${B}(B^0\to\rho^+\rho^-) = (2.88 ^{+0.23}_{-0.22} {}^{+0.29}_{-0.27}) \times 10^{-5}, f_{L} = 0.921 ^{+0.024}_{-0.025} {}^{+0.017}_{-0.015}$, $S = -0.26\pm0.19\pm0.08$, and $C = -0.02\pm0.12^{+0.06}_{-0.05}$, where the first uncertainties are statistical and the second are systematic. We use these results to perform an isospin analysis to constrain the CKM angle $\phi_2$ and obtain two solutions; the result consistent with other Standard Model constraints is $\phi_2 = (92.6^{+4.5}_{-4.8})^\circ$.

We study multiplicative Chern insulators (MCIs) as canonical examples of multiplicative topological phases of matter. Constructing the MCI Bloch Hamiltonian as a symmetry-protected tensor product of two topologically non-trivial parent Chern insulators (CIs), we study two-dimensional (2D) MCIs and introduce 3D mixed MCIs, constructed by requiring the two 2D parent Hamiltonians share only one momentum component. We study the 2D MCI response to time reversal symmetric flux insertion, observing a $4\pi$ Aharonov-Bohm effect, relating these topological states to fractional quantum Hall states via the effective field theory of the quantum skyrmion Hall effect. As part of this response, we observe evidence of quantisation of a proposed topological invariant for compactified many-body states, to a rational number, suggesting higher-dimensional topology may also be relevant. Finally, we study effects of bulk perturbations breaking the symmetry-protected tensor product structure of the child Hamiltonian, finding the MCI evolves adiabatically into a topological skyrmion phase., Comment: 4 pages main text with 4 figures plus 3 pages supplementary with 3 figures; Companion papers are Patil et al. (arXiv:2412.19565), Ay et al. (arXiv:2412.19568)

We generalize a recent ``AdS S-matrix" formulation for interacting massive scalars on AdS spacetimes to the case of massive vector fields. This method relies on taking the infinite radius limit for scattering processes perturbatively, which is analyzed using Witten diagrams in the momentum space formulation of global AdS with embedding space coordinates. It recovers the S-matrix with subleading corrections in powers of the inverse AdS radius about a flat spacetime region within the bulk. We first derive the massive vector bulk-to-boundary and bulk-to-bulk propagators within this perturbation theory. As an example, we consider the Abelian Higgs Model in a certain regime of the coupling parameter space to model an interacting Proca theory on AdS spacetimes. We specifically compute the AdS S-matrix for a process involving massive external vector fields mediated by a massive scalar. We lastly discuss possible massless limit of propagators within this perturbative framework., Comment: 35 pages, 4 figures

Given a graph $G$, the Laplacian matrix of $G$, $L(G)$ is the difference of the adjacency matrix $A(G)$ and $\text{Deg}(G)$, where $\text{Deg}(G)$ is the diagonal matrix of vertex degrees. The distance Laplacian matrix $D^L({G})$ is the difference of the transmission matrix of $G$ and the distance matrix of $G$. In the given paper, we first obtain the Laplacian and distance Laplacian spectrum of generalized fan graphs. We then introduce a new graph class which is denoted by $\mathcal{NC}(F_{m,n})$. Finally, we determine the Laplacian spectrum and the distance Laplacian spectrum of $\mathcal{NC}(F_{m,n})$., Comment: 15 Pages, 4 Figures, Accepted for Publication

We show how Carrollian symmetries become important in the construction of one-dimensional fermionic systems with all flat-band spectra from first principles. The key ingredient of this construction is the identification of Compact Localised States (CLSs), which appear naturally by demanding $\textit{supertranslation}$ invariance of the system. We use CLS basis states, with inherent $\textit{ultra-local}$ correlations, to write down an interacting theory which shows a non-trivial phase structure and an emergent Carroll conformal symmetry at the gapless points. We analyze this theory in detail for both zero and finite chemical potential.

Multimodal learning, a rapidly evolving field in artificial intelligence, seeks to construct more versatile and robust systems by integrating and analyzing diverse types of data, including text, images, audio, and video. Inspired by the human ability to assimilate information through many senses, this method enables applications such as text-to-video conversion, visual question answering, and image captioning. Recent developments in datasets that support multimodal language models (MLLMs) are highlighted in this overview. Large-scale multimodal datasets are essential because they allow for thorough testing and training of these models. With an emphasis on their contributions to the discipline, the study examines a variety of datasets, including those for training, domain-specific tasks, and real-world applications. It also emphasizes how crucial benchmark datasets are for assessing models' performance in a range of scenarios, scalability, and applicability. Since multimodal learning is always changing, overcoming these obstacles will help AI research and applications reach new heights.