December 2025 arXiv papers — page 42

Alexandros Christoforos, Chadbourne Davis

We propose \textbf{MoE-DiffuSeq}, a diffusion-based framework for efficient long-form text generation that integrates sparse attention with a Mixture-of-Experts (MoE) architecture. Existing sequence diffusion models suffer from prohibitive computational and memory costs when scaling to long documents, largely due to dense attention and slow iterative reconst

Arunima Das, Maulik Parikh, Frank Wilczek, Raphaela Wutte

We present a general framework for the production of squeezed quantum states of the gravitational field in linearized quantum gravity. Time-dependent couplings in the quadratic part of the action generically produce squeezed states from the vacuum. Using the harmonic oscillator as an example, we describe three techniques to obtain the squeezing parameter fro

Coen Hutters, Max B. Mendel

In this paper, we demonstrate how multiport network theory can be used as a powerful modeling tool in economics. The critical insight is using the port concept to pair the flow of goods (the electrical current) with the agent's incentive (the voltage) in an economic interaction. By building networks of agents interacting through ports, we create models with

Abdul Malik Al Mardhouf Al Saadi, Amrita Basak

Accurate bead geometry prediction in laser-directed energy deposition (L-DED) is often hindered by the scarcity and heterogeneity of experimental datasets collected under different materials, machine configurations, and process parameters. To address this challenge, a cross-dataset knowledge transfer model based on meta-learning for predicting deposited trac

Vinicius T. V. Date, Leandro M. Zatesko

In the field of compressed string indexes, recent work has introduced suffixient sets and their corresponding repetitiveness measure $\chi$. In particular, researchers have explored its relationship to other repetitiveness measures, notably $r$, the number of runs in the Burrows--Wheeler Transform (BWT) of a string. Navarro et al. (2025) proved that $\chi \l

Luke Conners

We give an invariant construction of reduced HOMFLY homology for arbitrary links reduced at components of arbitrary color and prove some structural properties relating this invariant to unreduced HOMFLY homology. Combined with previous results, this gives a recursive formula for the reduced HOMFLY homology of colored positive torus knots and some colored pos

Yair Glasner, Tobias Hartnick, Waltraud Lederle

We show that countable non-abelian free groups admit uncountably many mutually singular elementwise conservative non-singular random subgroups, which are supported on infinite subgroups of infinite index and singular with respect to every invariant random subgroup. This complements recent rigidity results for elementwise-conservative random subgroups in high

Dhruv Anand, Ehsan Shareghi

We introduce Cube Bench, a Rubik's-cube benchmark for evaluating spatial and sequential reasoning in multimodal large language models (MLLMs). The benchmark decomposes performance into five skills: (i) reconstructing cube faces from images and text, (ii) choosing the optimal next move, (iii) predicting the outcome of a candidate move without applying it, (iv

Angelina Sherman, Ke Fang, Dan Hooper

Several observatories designed to detect ultrahigh-energy neutrinos are planned for the next decade. The most imminent of these is the Payload for Ultrahigh Energy Observations (PUEO), a long-duration balloon-based experiment that will provide unprecedented sensitivity to neutrinos with energies in the range of ~ 1 - 1000 EeV. In this work, we assess the sci

Evgeni Dimitrov

The Airy wanderer line ensembles are infinite-parameter generalizations of the classical Airy line ensemble that arise naturally as scaling limits of inhomogeneous (spiked) models in the Kardar-Parisi-Zhang universality class. In this paper, we establish several structural properties of these ensembles. Our results show their laws depend continuously on the

K. Khokhar, S. Bagchi, Y. Niu, C. Chen

To study the isoscalar giant resonances in a deformed case, background-free $\alpha$-particle inelastic scattering measurements using a 386 MeV $\alpha$ beam were performed on the highly-deformed $^{172}$Yb nucleus using the Grand Raiden spectrometer at the Research Center for Nuclear Physics (RCNP) at very forward angles, including $0^\circ$. The strength d

Sebastian Schenk, Kristof Schmieden, Pedro Schwaller

Similar to axions, gravitational waves (GW) can induce oscillating electromagnetic fields inside electromagnetic cavities. We explore their experimental sensitivity to monochromatic and non-monochromatic GW signals, using the total deposited energy as a primary measure. Focusing on cylindrical and spherical cavities, we present the coupling coefficients of G

İbrahim Oğuz Çetinkaya, Sajad Khodadadian, Taylan G. Topcu

As systems engineering (SE) objectives evolve from design and operation of monolithic systems to complex System of Systems (SoS), the discipline of Mission Engineering (ME) has emerged which is increasingly being accepted as a new line of thinking for the SE community. Moreover, mission environments are uncertain, dynamic, and mission outcomes are a direct f

Shaun Fallat, Samir Mondal

In real Lie theory, matrices that admit a real logarithm reside in the identity component $\mathrm{GL}_n(\mathbb{R})_+$ of the general linear group $\mathrm{GL}_n(\mathbb{R})$, with logarithms in the Lie algebra $\mathfrak{gl}_n(\mathbb{R})$. The exponential map \[ \exp : \mnr \to \mathrm{GL}_n(\mathbb{R}) \] provides a fundamental link between the Lie algeb

Demerson N. Gonçalves, Tharso D. Fernandes, Andrias M. M. Cordeiro, Pedro H. G. Lugao

The minimum accuracy heuristic evaluates quantum feature maps without requiring full quantum support vector machine (QSVM) training. However, the original formulation is computationally expensive, restricted to balanced datasets, and lacks theoretical backing. This work generalizes the metric to arbitrary binary datasets and formally proves it constitutes a

Furkan Semih Dündar, Xerxes D. Arsiwalla, Hatem Elshatlawy

We show how representations of finite-dimensional quantum operators can be constructed using nondeterministic rewriting systems. In particular, we investigate Wolfram model multiway rewriting systems based on string substitutions. Multiway systems were proposed by S. Wolfram as generic model systems for multicomputational processes, emphasizing their signifi

Humza Nusrat, Luke Francisco, Bing Luo, Hassan Bagher-Ebadian

Stereotactic radiosurgery (SRS) demands precise dose shaping around critical structures, yet black-box AI systems have limited clinical adoption due to opacity concerns. We tested whether chain-of-thought reasoning improves agentic planning in a retrospective cohort of 41 patients with brain metastases treated with 18 Gy single-fraction SRS. We developed SAG

Nicholas J. Ossi, Barbara Prinari, Jianke Yang

The goal of this work is to revisit the eigenfunction-expansion-based perturbation theory for the defocusing nonlinear Schr\"odinger equation a nonzero background, and develop it to correctly predict the slow-time evolution of the dark soliton parameters, as well as the radiation shelf emerging on the soliton sides. Proof of the closure of the squared eigenf

Sharareh Mirzaei, Stephanie Bunt, Susan M Bogus

As the construction industry undergoes rapid digital transformation, ensuring that new technologies enhance rather than hinder human experience has become essential. The inclusion of Building Information Modeling (BIM) plays a central role in this shift, yet its influence on job satisfaction remains underexplored. In response, this study developed a human-ce

Kyle Hogan, Alishah Chator, Gabriel Kaptchuk, Mayank Varia

In this work, we model the end-to-end pipeline of the advertising ecosystem, allowing us to identify two main issues with the current trajectory of private advertising proposals. First, prior work has largely considered ad targeting and engagement metrics individually rather than in composition. This has resulted in privacy notions that, while reasonable for

Stephane Gaubert, Yiannis Vlassopoulos

We show that the output of a ReLU neural network can be interpreted as the value of a zero-sum, turn-based, stopping game, which we call the ReLU net game. The game runs in the direction opposite to that of the network, and the input of the network serves as the terminal reward of the game. In fact, evaluating the network is the same as running the Shapley-B

Georgios Moustakas, Adonis Bogris, Charis Mesaritakis

Photonic convolutional accelerators have emerged as low-energy alternatives to power-demanding digital convolutional neural networks, though they often face limitations in scalability. In this work, we introduce a convolutional photonic accelerator that employs programmable kernels manifesting as trainable waveforms in the frequency domain to enable low-ener

N. V. Krishnendu

The spin-induced quadrupole moment-based test of black hole nature is routinely used to probe the true nature of detected binary signals, assuming a circular orbit. We extend the applicability of the method to binaries in eccentric orbits. Considering simulated signals of varying masses, spins, and signal strengths, we demonstrate how the systematic errors r

Amirhosein Ghasemabadi, Di Niu

Large language models (LLMs) generate fluent and complex outputs but often fail to recognize their own mistakes and hallucinations. Existing approaches typically rely on external judges, multi-sample consistency, or text-based self-critique, which incur additional compute or correlate weakly with true correctness. We ask: can LLMs predict their own failures

Leslie Barrett, Michael W. Sherman

Hand-tagged training data is essential to many machine learning tasks. However, training data quality control has received little attention in the literature, despite data quality varying considerably with the tagging exercise. We propose methods to evaluate and enhance the quality of hand-tagged training data using statistical approaches to measure tagging

Debabrota Basu, Udvas Das, Brahim Driss, Uddalak Mukherjee

Post-deployment machine learning algorithms often influence the environments they act in, and thus shift the underlying dynamics that the standard reinforcement learning (RL) methods ignore. While designing optimal algorithms in this performative setting has recently been studied in supervised learning, the RL counterpart remains under-explored. In this pape

Matias von Bell, Cesar Ceballos

Flow polytopes of acyclic oriented graphs arise naturally in combinatorial optimization, and the study of their volumes and triangulations has revealed intriguing connections across combinatorics, geometry, algebra, and representation theory. In this work, we introduce the framing lattice associated with a framed graph, whose Hasse diagram is dual to a frame

M. Navabi, R. Carrera, N. E. D. Noël, C. Gallart

The near-infrared Calcium II Triplet (CaT), around 850nm, is a key metallicity indicator for red giant stars. We present a revised [Fe/H] calibration as a function of CaT line strengths and four luminosity indicators, including the $Gaia$ $G$-band, together with the classical $V$, $I$, and $K_s$ bandpasses. For this purpose, we used a sample of 366 red giant

Rui Pan, Zhuofu Chen, Hongyi Liu, Arvind Krishnamurthy

Diffusion Large Language Models (dLLMs) offer fast, parallel token generation, but their standalone use is plagued by an inherent efficiency-quality tradeoff. We show that, if carefully applied, the attributes of dLLMs can actually be a strength for drafters in speculative decoding with autoregressive (AR) verifiers. Our core insight is that dLLM's speed fro

Brendan Juba, Kuldeep S. Meel

Given a Boolean relational specification between inputs and outputs, the problem of functional synthesis is to construct a function that maps each assignment of the input to an assignment of the output such that each tuple of input and output assignments meets the specification. The past decade has witnessed significant improvement in the scalability of func

Brennan Romero, D. G. Perera

In this paper, our goal is to reproduce the basic functionalities of a regular oscilloscope, using the Nuvoton NUC-140 embedded systems development platform as the front-end and display method. A custom-built daughter board connects the NUC-140 to a variety of peripherals, including two BNC scope-probe connections, an external nine-button keypad, and a calib

Emilian Dudas, Susha Parameswaran, Marco Serra

We present a string theory construction in which the particle physics contributions to the one-loop vacuum energy exactly cancel, whilst the gravitational contributions are suppressed in the size of one or two large extra dimensions. This provides an ultraviolet realisation of the Dark Dimension and Supersymmetric Large Extra Dimensions scenarios, with, more

Yanhong Li, Songlin Yang, Shawn Tan, Mayank Mishra

Distilling pretrained softmax attention Transformers into more efficient hybrid architectures that interleave softmax and linear attention layers is a promising approach for improving the inference efficiency of LLMs without requiring expensive pretraining from scratch. A critical factor in the conversion process is layer selection, i.e., deciding on which l

Kevin Wang, Ian MacPhail-Bartley, Cameron E. Peters, Valery Milner

We outline the design and characterization of a laser pulse shaper, which creates an ``ultraslow optical centrifuge'' - a linearly polarized field whose polarization vector rotates with arbitrarily low angular acceleration. By directly recording this rotation in time with nonlinear cross-correlation, we demonstrate the tunability of such centrifuge (both in

Emily Micklethwaite, Adam Lowe

Radial basis function (RBF) networks are expanded to incorporate quantum kernel functions enabling a new type of hybrid quantum-classical machine learning algorithm. Using this approach, synthetic examples are introduced which allow for proof of concept on interpolation and classification applications. Quantum kernels have primarily been applied to support v

Abhishek Bhattacharjee, Hemanadhan Myneni, Manoj K. Harbola, Prasanjit Samal

Orbital-Free Density Functional Theory (OFDFT) has re-emerged as a viable alternative to Kohn-Sham DFT, driven by recent advances in kinetic energy density functionals (KEDFs). Nonlocal (NL) KEDFs have significantly extended OFDFT's applicability, particularly for bulk solids, but their high computational cost and dependence of system-specific parameters lim

Long Nguyen, Micha Fauth, Bernhard Jaeger, Daniel Dauner

Simulators can generate virtually unlimited driving data, yet imitation learning policies in simulation still struggle to achieve robust closed-loop performance. Motivated by this gap, we empirically study how misalignment between privileged expert demonstrations and sensor-based student observations can limit the effectiveness of imitation learning. More pr

Yingzhen Yang

We study the problem of learning a low-degree spherical polynomial of degree $\ell_0 = \Theta(1) \ge 1$ defined on the unit sphere in $\RR^d$ by training an over-parameterized two-layer neural network (NN) with channel attention in this paper. Our main result is the significantly improved sample complexity for learning such low-degree polynomials. We show th

Kaitong Cai, Jusheng Zhang, Jing Yang, Yijia Fan

Large vision-language models (VLMs) typically process hundreds or thousands of visual tokens per image or video frame, incurring quadratic attention cost and substantial redundancy. Existing token reduction methods often ignore the textual query or rely on deep attention maps, whose instability under aggressive pruning leads to degraded semantic alignment. W

Adrien Reingruber, Maksim Ulybyshev, Kitinan Pongsangangan

Transport properties of strongly correlated materials have contributions from quasiparticle excitations such as electrons and holes as well as emerging collective excitations such as plasmonic sound-like modes which are sustained by interactions. As was shown in Phys. Rev. B 106, 205127, the thermal excitation of the long-lived plasmons in graphene provides

David Christian Ohnmacht, Wolfgang Belzig, Juan Carlos Cuevas

We demonstrate that the charge value of transport mechanisms heavily impacts the validity of thermodynamic uncertainty relations (TURs). Specifically, we show within the framework of full counting statistics, that the recently established quantum TUR can be violated by the presence of transport processes that carry more than one charge, like Andreev reflecti

Shengchao Zhou, Yuxin Chen, Yuying Ge, Wei Huang

Vision-language models (VLM) excel at general understanding yet remain weak at dynamic spatial reasoning (DSR), i.e., reasoning about the evolvement of object geometry and relationship in 3D space over time, largely due to the scarcity of scalable 4D-aware training resources. To bridge this gap across aspects of dataset, benchmark and model, we introduce DSR

Mingwei Tang, Jiahao Nie, Guang Yang, Ziqing Cui

Image fusion aims to synthesize a single high-quality image from a pair of inputs captured under challenging conditions, such as differing exposure levels or focal depths. A core challenge lies in effectively handling disparities in dynamic range and focus depth between the inputs. With the advent of vision-language models, recent methods incorporate textual

Ross Jenkinson

We develop a probability-level, manifestly causal formalism for calculations in QFT. The approach involves an implicit summation over final states, which makes causality manifest since retarded propagators emerge naturally. This inclusive summation over final states may also offer insights into the cancellation of IR divergences in physical observables withi

Miguel Palma, Shuwen Kan, Wenqi Wei, Juntao Chen

The rapid expansion of quantum cloud services has led to long job queues due to single-tenant execution models that underutilize hardware resources. Quantum multi-programming (QMP) mitigates this by executing multiple circuits in parallel on a single device, but existing methods target superconducting systems with limited connectivity, high crosstalk, and lo

David S. Pereira, José Pedro Mimoso

We show that in single--scalar theories of the form $\mathcal{L}=F(\Phi,X)R+G(\Phi,X)$, a generic nonminimal coupling $F(\Phi,X)$ induces, in the scalar--comoving frame, an additional transverse contribution to the effective heat flux, proportional to $(F_X/8\pi F)V_{\perp a}$, where $V_a \equiv h_a{}^c\nabla_c\nabla_d X\,u^d$ and $V_{\perp a}$ denotes the c

S. D. Savenkov, A. O. Svetlichnyi, I. A. Pshenichnov

The construction of modern detectors used in high-energy physics experiments is typically guided by modeling with the Geant4 toolkit to evaluate detector performance in terms of geometrical acceptance and detection efficiency. Several hadronic models are available in Geant4 for modeling nuclear reactions induced by fast nucleons. It is shown that they result

Sung En Chiang, Zhaolu Liu, Robert L. Peach, Mauricio Barahona

Analyzing causality in multivariate systems involves establishing how information is generated, distributed and combined. Traditional causal discovery frameworks are capable of multivariate reasoning but their intrinsic pairwise graph topology restricts them to do so only indirectly by integrating multivariate information across pairwise edges. Higher-order

Miltiadis Karakikes, Sotiris Karanikolopoulos, Aristides Kontogeorgis, Dimitrios Noulas

We establish a unified group-theoretic framework bridging the arithmetic homotopy exact sequence of a variety and the Birman exact sequence of a surface. Within this framework, we reinterpret classical arithmetic notions - such as the descent of varieties and of covers - and construct their topological analogues. We formalize the parallel setting between clo

Vinayak Regmi, Christos Mousas

This paper presents a system for procedurally generating agent-based narratives using large language models (LLMs). Users could drag and drop multiple agents and objects into a scene, with each entity automatically assigned semantic metadata describing its identity, role, and potential interactions. The scene structure is then serialized into a natural langu

Jaime E. Muñoz Rivera, Maria Grazia Naso

The existence of global attractors is investigated for the Signorini problem with pointwise dissipation. It is shown that both the semilinear Signorini problem and the elastic obstacle problem with normal compliance exhibit exponential decay to zero and admit compact global attractors. To establish these results, the original problem is approximated by a hyb

Zhiyi Duan, Xiangren Wang, Hongyu Yuan, Qianli Xing

Teachers' emotional states are critical in educational scenarios, profoundly impacting teaching efficacy, student engagement, and learning achievements. However, existing studies often fail to accurately capture teachers' emotions due to the performative nature and overlook the critical impact of instructional information on emotional expression. In this pap

Finnegan Buckley, Alexander Vladimirsky

We introduce a new type of Mean Field Game epidemiological models, in which subpopulations have different behavioral patterns: some are viewed as "highly rational" (choosing Nash-equilibrium long-term strategies) while others follow pre-specified "non-rational" patterns (e.g., either sticking to their usual habits or trying to mimic those around them). Our m

Hanna Döring, Adélie Garin, Christian Hirsch, Nikolaj Nyvold Lundbye

In this paper, we study two specific types of $d$-dimensional Poisson functionals: a double-sum type and a sum-log-sum type, both over pairs of Poisson points. On these functionals, we impose column-type dependence, i.e., local behavior in the first $k$ directions and allow non-local, yet stabilizing behavior in the remaining $d-k$ directions. The main contr

D. K. Korliakov, B. I. Bantysh, A. S. Borisenko, I. V. Zalivako

Channel spectrum benchmarking (CSB) provides a robust framework for characterizing quantum gate fidelities while remaining insensitive to state preparation and measurement (SPAM) errors. Yet, current CSB implementations encounter fundamental challenges when reconstructing noisy eigenvalues, particularly in the presence of spectral degeneracies and off-diagon

Vahid Asadi, Akram Hasani Zonoozi, Hosein Haghi

Traditional spectral energy distribution (SED)-fitting methods for stellar mass estimation face persistent challenges including systematic biases and computational constraints. We present a controlled comparison of machine learning (ML) and SED-fitting methods, assessing their accuracy, robustness, and computational efficiency. Using a sample of COSMOS-like

Lothar Maisenbacher

Precision spectroscopy of atomic hydrogen is an important way to test bound-state quantum electrodynamics (QED), one of the building blocks of the Standard Model. In its simplest form, such a test consists of the comparison of a measured transition frequency with its QED prediction, which can be calculated with very high precision for the hydrogen atom. Howe

Austin R. Ellis-Mohr, Max Hartman, Lav R. Varshney

Large reasoning models (LRMs) have heterogeneous inference energy costs based on which model is used and how much it reasons. To reduce energy, it is important to choose the right LRM and operate it in the right way. As a result, the performance of systems that dispatch tasks to different individual LRMs depend on the balance between mean energy provisioning

Ze Zhang, Hongwei Jiang, Hongyue Xiao, Meiling Guan

Optical pin beams (OPBs) represent a novel class of structured light fields engineered for resilient, long-distance propagation. Their exceptional stability and strong resistance to atmospheric turbulence make them a compelling alternative to conventional Gaussian and other structured beams for free-space optical systems. This review provides a comprehensive

Nathanaël Berestycki, Marcin Lis, Mingchang Liu, Eveliina Peltola

We consider a uniform spanning tree in a $\delta$-square grid approximation of a planar domain $\Omega$. For given integer $n\ge 2$, we condition the tree on the following $n$-arm event: we pick $n$ branches, emanating from $n$ points microscopically close to a given interior point, and condition them to connect to the boundary $\partial \Omega$ without inte

Sai Cui, Yi-Jie Li, Guang-Zhi Xu, Kui-Yong Liu

Within the framework of nonrelativistic quantum chromodynamics (NRQCD) factorization, we compute the $\mathcal{O}(v^{4})$ relativistic corrections to the fragmentation of a heavy quark into the color-singlet $^{1}S_{0}^{[1]}$ and $^{3}S_{1}^{[1]}$ quarkonium states. Using the Collins--Soper definition of the fragmentation function, we reproduce the known $\m

Alex Chen Yi Zhang, Pablo Mateu Hoyos, David Brückner, Gašper Tkačik

In many developmental systems, cells differentiate into a tissue by reading out morphogen concentration fields, a process fundamentally limited by noise. How much can the precision of this process be improved by nonlocal information, e.g., via cell-cell communication? Using a Bayes-optimal framework, we show that positional inference depends crucially on mor

Michele Lorenzo, Idilio Drago, Dario Salvadori, Fabio Romolo Vayr

Role-Based Access Control (RBAC) struggles to adapt to dynamic enterprise environments with documents that contain information that cannot be disclosed to specific user groups. As these documents are used by LLM-driven systems (e.g., in RAG) the problem is exacerbated as LLMs can leak sensitive data due to prompt truncation, classification errors, or loss of

Javier Navarro, Simon Morelli, Mikel Sanz, Mohammad Mehboudi

Famously, the quantum Fisher information -- the maximum Fisher information over all physical measurements -- is additive for independent copies of a system and the optimal measurement acts locally. We are left to wonder: does the same hold when the set of accessible measurements is constrained? Such constraints are necessary to account for realistic experime

Kyriakos Stylianopoulos, Paolo Di Lorenzo, George C. Alexandropoulos

Goal-oriented communications offer an attractive alternative to the Shannon-based communication paradigm, where the data is never reconstructed at the Receiver (RX) side. Rather, focusing on the case of edge inference, the Transmitter (TX) and the RX cooperate to exchange features of the input data that will be used to predict an unseen attribute of them, le

Anthony Leverrier, Wouter Rozendaal, Gilles Zémor

Quantum Tanner codes are a class of quantum low-density parity-check codes that provably display a linear minimum distance and a constant encoding rate in the asymptotic limit. When built from left--right Cayley complexes, they can be described through a lifting procedure and a base code, which we characterize. We also compute the dimension of quantum Tanner

Kaitong Cai, Jensen Zhang, Jing Yang, Keze Wang

We introduce SirenPose, a geometry-aware loss formulation that integrates the periodic activation properties of sinusoidal representation networks with keypoint-based geometric supervision, enabling accurate and temporally consistent reconstruction of dynamic 3D scenes from monocular videos. Existing approaches often struggle with motion fidelity and spatiot

N. Barišić, D. K. Sunko

Murunskite K$_2$Cu$_3$FeS$_4$ is a representative sulfosalt, isostructural to the pnictides, but with electronic properties more similar to the insulating parent compounds of the cuprates. We use it as a bridge to compare the chemical and physical roles of metal and ligand orbitals in cuprates and pnictides. In cuprates, ionicity, covalency, and metallicity

Viktor Christiansson, Karsten Held

In a recent experiment [Nature 642, 58 (2025)], a new record for the superconducting critical temperature $T_c$ among infinite-layer nickelates has been reported in doped SmNiO$_2$. Here, we use the cutting-edge dynamical vertex approximation (D$\Gamma$A), and qualitatively as well as quantitatively reproduce the $T_c$ vs. doping dome for this compound. Enco

Joanna L. P. Wolff, Loïc Moczko, Jérémy Thoraval, Michelangelo Romeo

Layered magnetic and strongly correlated materials present a rich platform for condensed matter physics with intrinsic properties intertwined by magnetism and low-dimensionality. A suspended light-emitting 2D antiferromagnetic membrane forms a highly controllable hybrid system in which the interplay between spin ordering, optical and mechanical degrees of fr

A. L. Zibinskiy, S. Cronenberger, B. Gribakin, R. Baye

The spin dynamics of localized electrons in bulk semiconductors is governed by the interplay of effective nuclear field fluctuations, spin exchange between electrons, and spin transitions into the conduction band. Using spin noise spectroscopy, we reveal this interplay for donor-bound electrons in a CdTe/CdMgTe quantum well and spectrally separate electron s

Xiao-Peng Wang, Yi-Jie Li, Guang-Zhi Xu, Kui-Yong Liu

Within the framework of nonrelativistic QCD (NRQCD) factorization, we investigate the relativistic corrections to the production of double $B_c$ mesons in $e^+e^-$ annihilation. The study covers center-of-mass energies from the production threshold up to $2m_Z$, considering both the photon and $Z^0$-boson propagated processes. We find that the relativistic c

Valeriy A. Buryachenko

We consider static linear elastic composite materials (CMs) with periodic structure. The core of the proposed methodology is the generation of a novel dataset using specially designed body force fields with compact support (BFCS), enabling a new RVE concept that reduces the infinite periodic medium to a finite domain without boundary artifacts. This function

Masao Oi

We establish an explicit formula for twisted Harish-Chandra characters of toral supercuspidal representations of p-adic reductive groups under several technical assumptions. Our setup especially includes the case of a quasi-split group equipped with an involution.

Masahiro Kato

We propose ScoreMatchingRiesz, a family of Riesz representer estimators based on score matching. The Riesz representer is a key nuisance component in debiased machine learning, enabling $\sqrt{n}$-consistent and asymptotically efficient estimation of causal and structural targets via Neyman-orthogonal scores. We formulate Riesz representer estimation as a sc

Amedeo M. Favitta

Axions are hypothetical pseudoscalar particles introduced initially as a solution to the Strong CP problem in Quantum Chromodynamics (QCD), and they also arise naturally in a broad class of low-energy compactifications of string theory. Astrophysical, cosmological, and laboratory constraints require axions to be extremely weakly coupled to Standard Model par

Chehak Malhotra, Mehak Gopal, Akshaya Devadiga, Pradeep Singh

With the advent of LLMs, various tasks across the natural language processing domain have been transformed. However, their application in predictive tasks remains less researched. This study compares large language models, including GatorTron-Base (trained on clinical data), Llama 8B, and Mistral 7B, against models like BioBERT, DocBERT, BioClinicalBERT, Wor

Aritra Kundu

We identify the transition from the oscillatory Rabi regime to the localized Zeno/Anti-Zeno regime in continuous measurement and feedback of a qubit as a quantum analogue of Motility-Induced Phase Separation (MIPS). A mapping between a biased monitored qubit and a classical ``Run-and-Tumble" active particle is studied. We demonstrate that the competition bet

Yuting Cai, Ruthav Sadali, Korok Ray, Chao Tian

Most current assessments use ex post proxies that miss uncertainty and fail to consistently capture the rapid change in bitcoin mining. We introduce a unified, ex ante statistical model that derives expected return, downside risk, and upside potential profit from the first principles of mining: Each hash is a Bernoulli trial with a Bitcoin block difficulty-b

Aleš Flandera, David Kofroň, Tomáš Ledvinka

We revisit the near-horizon description of the Kerr space-time in the isolated horizon formalism using a non-twisting null geodesic congruence and eliminate the coordinate and geodesic pathologies that arise when the Carter constant of motion is globally fixed to a single constant. Adopting instead a previously proposed choice of the Carter constant which de

Javier Otero Martinez, Ana Garcia Armada, Yi Li, Christian Nijhuis

Gallium alloys are promising materials in biomedical engineering, electronics, and wireless communications, thanks to their good conductivity, non toxicity and their ability to sustain large deformations. They can be transported in capillaries using purely electric means by continuous electrowetting (CEW). Current models of CEW-driven flows do not address th

Haibo Wang

In this study, we introduce an analytics framework, the Bank Risk Interlinkage with Dynamic Graph and Event Simulations (BRIDGES), to capture the systemic risks associated with the growing economic influence of the BRICS nations. This framework includes a Dynamic Time Warping (DTW) method to construct a dynamic network of 551 BRICS banks with their annual ba

Matthias Hertel, Sebastian Pütz, Ralf Mikut, Veit Hagenmeyer

Time-series forecasts are essential for planning and decision-making in many domains. Explainability is key to building user trust and meeting transparency requirements. Shapley Additive Explanations (SHAP) is a popular explainable AI framework, but it lacks efficient implementations for time series and often assumes feature independence when sampling counte

Tyler Clark, Christine Evers, Jonathon Hare

Recurrent off-policy deep reinforcement learning models achieve state-of-the-art performance but are often sidelined due to their high computational demands. In response, we introduce RISE (Recurrent Integration via Simplified Encodings), a novel approach that can leverage recurrent networks in any image-based off-policy RL setting without significant comput

J. Fransson, B. C. Sanders, A. P. Sowa

We investigate the concept of macroscopically distinguishable superpositions within an infinite array of boson sites. Our approach is rigorous within the frame of Hilbert space theory. In this context, it is natural to differentiate between states -- and corresponding dynamics -- that involve only finitely many degrees of freedom, referred to as local, and t

F. M. Brady

This paper computes the Jones polynomial and the invariants obstructing cosmetic surgery which are derived from it for two infinite families of knots, proving they satisfy the Purely Cosmetic Surgery Conjecture. Both the method of computation and the method for generating families of knots extend.

Jan M. Pawlowski, Fabian Rennecke, Franz R. Sattler

QCD at large densities exhibits a moat regime in the scalar-pseudoscalar sector. The resolution of its dynamics is pivotal for the access to the onset of new phases including the potential critical endpoint of QCD. In this work we present the first selfconsistent analysis of this regime with the functional renormalisation group approach to QCD. We map out th

Sanjay Pant, Himanshu Parihar, Pradeep Kumar Sharma

We investigate holographic entanglement negativity (HEN) as a probe of mixed state quantum correlations in a deformed AdS black hole background with backreaction sourced by a string cloud. The bulk geometry is dual to a strongly coupled large-$N_c$ gauge theory at finite temperature, backreacted by a finite density of heavy static fundamental quarks. We anal

Kiyan Naderi, Noema Nicolussi

We introduce and study Laplacians on a finite metric graph endowed with generalized densities, that is, measures of finite mass. One important motivation is that this setting provides a common framework for several interesting classes of operators: discrete graph Laplacians, Kirchhoff Laplacians and Dirichlet-to-Neumann operators on graphs. Our main interest

Qiuyang Li, Anton Shubnic, Nishkarsh Agarwal, Adam Alfrey

Moir\'e superlattices in van der Waals materials have revolutionized the study of electronic and excitonic systems by creating periodic electrostatic potentials. Extending this concept to magnetic materials promises new pathways in merging spintronics with photonics. While moir\'e magnetism has been revealed with near-field probes and nonlinear optical techn

Oscar Demeulenaere, Nikita Ustimenko, Athanasios G. Athanassiadis, Lovish Gulati

Acoustic metamaterials enhance traditional material properties through microstructure engineering, providing new opportunities to shape sound fields in applications ranging from biomedical imaging, clinical therapy to non-destructive testing. However, at the MHz frequency ranges, only a few metamaterial architectures exist. They are often highly attenuating

Ioana Ciotir, Nicolas Forcadel, Piero Visconti, Hasnaa Zidani

We study a class of optimal control problems governed by nonlinear stochastic equations of monotone type under certain coercivity and linear growth conditions. We give first order necessary conditions of optimality. A stochastic Pontryagin principle can be recovered in the case that the diffusion doesn't depend on the control. We give several applications, m

Thomas Cavallazzi, Alexandre Richard, Milica Tomasevic

The Keller--Segel PDE is a model for chemotaxis known to exhibit possible finite-time blow-up. Following a seminal work by Tello and Winkler, a logistic damping term is added in this PDE and local well-posedness of mild solutions is proven. When the space dimension is $2$ or when the damping is strong enough, the solution is global in time. In the second par

Paul Rosa

The nonparametric regression model with normal errors has been extensively studied, both from the frequentist and Bayesian viewpoint. A central result in Bayesian nonparametrics is that under assumptions on the prior, the data-generating distribution (assuming a true frequentist model) and a semi-metric $\rho(.,.)$ on the space of regression functions that s

Joseph E. Bonavia

Gelatin is often used as an analog for studying soft and biological materials in order to understand the mechanics of behavior of biological tissue in events like traumatic brain injuries. The material properties of gelatin change with the ratio of water to gelatin powder used to make a given sample. Characterizing the relationship between this ratio and the

Gorjan Radevski

This manuscript explores multimodal alignment, translation, fusion, and transference to enhance machine understanding of complex inputs. We organize the work into five chapters, each addressing unique challenges in multimodal machine learning. Chapter 3 introduces Spatial-Reasoning Bert for translating text-based spatial relations into 2D arrangements betwee

Oleg O. Novikov, Andrey A. Shavrin

The s-wave approximation to the black hole dynamics has attracted considerable attention recently. However, the near-AdS2 geometry of the near-horizon region and decoupling of the non-s-wave modes usually requires a small-temperature limit. In this work we propose the new limit based on the large number of dimensions in which the temperature remains finite,

Cho Win Aung, Thandar Zaw Win, Subhalaxmi Nayak, Sabyasachi Ghosh

The present article has addressed the finite magnetic field extension of the previous work by Cho et al. (Phys. Rev. B 108, 235172, 2023) on microscopic calculation of shear viscosity for electron fluid in graphene system. Our calculation is based on the kinetic theory approach in the relaxation time approximation. In the absence of a magnetic field, transpo

Luigi De Masi

We show that the set of points where the blow-up, in the sense of Preiss, of a signed Radon measure on $\mathbb{R}^n$ is unique and its invariant subspace has dimension $k$ is $k$-rectifiable. As simple applications, we obtain a rectifiability criterion for signed Radon measures and the extension of a result, due to Mattila, on measures having unique blow-up

Taige Wang, Kaiyuan Gu, Anzhou Wang, Zhentang Wang

Ferrofluids exhibit two canonical interfacial instabilities, a static Rosensweig (normal-field) instability that produces a lattice of peaks and a dynamical Faraday instability that produces parametrically excited standing waves. Here we present a systematic phase diagram of ferrofluid surface states driven by a purely AC vertical magnetic field with zero me