November 2025 arXiv papers — page 81

Denis S. Krotov, Sascha Kurz

We present constructions and bounds for additive codes over a finite field in terms of their geometric counterpart, i.e., projective systems. It is known that the maximum number of $(h-1)$-spaces in PG$(2,q)$, such that no hyperplane contains three, is given by $q^h+1$ if $q$ is odd. Those geometric objects are called generalized ovals. We show that cardinal

Eilidh McKemmie, Amol Srivastava

In 1991, Z\'emor proposed a hash function which provides data security using the difficulty of writing a given matrix as a product of generator matrices. Tillich and Z\'emor subsequently provided an algorithm finding short collisions for this hash function. We extend this collision attack to a stronger preimage attack, under the assumption that we can factor

Monu Sharma, Abhishek Jain

Workday is a cloud-based Enterprise Resource Planning-ERP system that brings HR, Finance, Supply Chain functions , Prism Analytics and Extend custom built in application together under an integrated software as a service SaaS environment. As every organization that undergoes digital transformation, the importance of securing sensitive enterprise data in clou

Mohammed A. Y. Mohammed, Hamed Karami, Gerardo Chowell

Mathematical models support inference and forecasting in ecology and epidemiology, but results depend on the estimation framework. We compare Bayesian and Frequentist approaches across three biological models using four datasets: Lotka-Volterra predator-prey dynamics (Hudson Bay), a generalized logistic model (lung injury and 2022 U.S. mpox), and an SEIUR ep

Meiyi Zhu, Caili Guo, Chunyan Feng, Osvaldo Simeone

Online conformal prediction (OCP) wraps around any pre-trained predictor to produce prediction sets with coverage guarantees that hold irrespective of temporal dependencies or distribution shifts. However, standard OCP faces two key limitations: it operates in the output space using simple nonconformity (NC) scores, and it treats all historical observations

Sai Sitharaman, Hassan Karim, Deepti Gupta, Mudit Tyagi

The rapid adoption of multi-cloud environments has amplified risks associated with privileged access mismanagement. Traditional Privileged Access Management (PAM) solutions based on Attribute-Based Access Control (ABAC) exhibit cubic O(n^3) complexity, rendering real-time privilege analysis intractable at enterprise scale. We present a novel PAM framework in

Francesca Bonaiti, Andrea Porro, Sonia Bacca, Achim Schwenk

We compute moments of the isoscalar monopole response of N = Z closed-shell nuclei based on chiral nucleon-nucleon plus three-nucleon interactions. We employ the random phase approximation (RPA) and two ab initio many-body approaches, the in-medium similarity renormalization group (IMSRG) and coupled-cluster theory (CC). In the IMSRG framework, the moments a

Chengxi Zeng, Yuxuan Jiang, Aaron Zhang

The Segment Anything Model 3 (SAM3) advances visual understanding with Promptable Concept Segmentation (PCS) across images and videos, but its unified architecture (shared vision backbone, DETR-style detector, dense-memory tracker) remains prohibitive for on-device use. We present EfficientSAM3, a family of efficient models built on Progressive Hierarchical

Kadja Flore Gali, Hamed Fahandezh Sadi, Jesse C. Anderson, Payton Beeler

Changes in aerosol concentrations can modify cloud brightness, producing a strong but poorly constrained influence on Earth's energy balance. Because cloud reflectivity depends on the size distribution of cloud droplets, and aerosol size strongly governs activation into droplets, one might expect cloud properties to be sensitive to aerosol size distributions

Wei Zhang, Yeying Jin, Xin Li, Yan Zhang

Image-based virtual try-on (VTON) aims to synthesize photorealistic images of a person wearing specified garments. Despite significant progress, building a universal VTON framework that can flexibly handle diverse and complex tasks remains a major challenge. Recent methods explore multi-task VTON frameworks guided by textual instructions, yet they still face

Adam Leon Kesner, Anyi Li, Phillip Koo

Healthcare stands at a critical crossroads. Artificial Intelligence and modern computing are unlocking opportunities, yet their value lies in the data that fuels them. The value of healthcare data is no longer limited to individual patients. However, data stewardship and governance has not kept pace, and privacy-centric policies are hindering both innovation

J. M. Costa Netto, Javier E. Gonzalez, H. H. B. Silva

In this work, we impose observational limits on the product of dark energy chemical potential, $\mu$, and number density, $n$, at the present time in out-of-equilibrium models, considering that particles can be created or destroyed in the fluid at a rate $\Gamma=3\alpha H(a)$, where $\alpha$ is a constant and $H(a)\equiv\dot{a}/a$ is the Hubble parameter. We

Kourosh Nozari, Hamed Ramezani

In this paper, we study the statistical mechanics within the polymer quantization framework in the semiclassical regime. We apply a non-canonical transformation to the phase space variables. Then, we use this non-canonical transformation to calculate the deformed density of states of the $2n$-dimensional phase space, which encompasses all polymer effects. In

Tuan-Anh Le, Anh Mai Vu, David Yang, Akash Awasthi

IMACT-CXR is an interactive multi-agent conversational tutor that helps trainees interpret chest X-rays by unifying spatial annotation, gaze analysis, knowledge retrieval, and image-grounded reasoning in a single AutoGen-based workflow. The tutor simultaneously ingests learner bounding boxes, gaze samples, and free-text observations. Specialized agents evalu

Mu Niu, Yue Zhang, Ke Ye, Pokman Cheung

In real-world applications, data often reside in restricted domains with unknown boundaries, or as high-dimensional point clouds lying on a lower-dimensional, nontrivial, unknown manifold. Traditional Gaussian Processes (GPs) struggle to capture the underlying geometry in such settings. Some existing methods assume a flat space embedded in a point cloud, whi

Fumika Mochizuki, Tetsuro Yamazaki, Shigeru Chiba

Virtual machines (VMs) are highly beneficial for microcontroller development. In particular, interactive programming environments greatly facilitate iterative development processes, and higher execution speeds expand the range of applications that can be developed. However, due to their limited memory size, microcontroller VMs provide a limited set of featur

Ashton Wiersdorf, Ben Greenman

We built Chorex, a language that brings choreographic programming to Elixir as a path toward robust distributed applications. Chorex is unique among choreographic languages because it tolerates failure among actors: when an actor crashes, Chorex spawns a new process, restores state using a checkpoint, and updates the network configuration for all actors. Cho

Bohdan Liesnikov, David Binder, Tim Süberkrüb

The expression problem describes a fundamental tradeoff between two types of extensibility: extending a type with new operations, such as by pattern matching on an algebraic data type in functional programming, and extending a type with new constructors, such as by adding a new object implementing an interface in object-oriented programming. Most dependently

Zachary Murray

A significant amount of work has been devoted to the study of small binary solar system objects. The majority of these binaries, especially among the near-earth or main belt asteroids have small radius ratios, implying a large difference in size between the primary and its companion. Farther from the sun, the binary fraction increases, with the Kuiper Belt h

Mehryar Mohri, Yutao Zhong

We introduce a new low-noise condition for classification, the Model Margin Noise (MM noise) assumption, and derive enhanced $\mathcal{H}$-consistency bounds under this condition. MM noise is weaker than Tsybakov noise condition: it is implied by Tsybakov noise condition but can hold even when Tsybakov fails, because it depends on the discrepancy between a g

Renata Kallosh, Andrei Linde

The textbook N=1 supergravity has an F-term potential depending on a superpotential $W(z_i)$ and a Kahler potential $K(z^i, \bar z^{\bar i})$, with the scalar potential $V(z^i, \bar z^{\bar i})=e^K (|DW|^2 - 3 |W|^2)$. In this approach, it is not always easy to find the potential $V(z^i, \bar z^{\bar i})$ with the required properties. We show that in supergr

B. Dalla Barba, L. Foschini, M. Berton, E. Järvelä

We report the results of the optical follow-up of a sample of $\gamma$-ray-emitting active galactic nuclei (AGN). New high-quality optical spectra were obtained using Gran Telescopio Canarias with Optical System for Imaging and low- Intermediate-Resolution Integrated Spectroscopy and the European Southern Observatory Very Large Telescope Unit Telescope 1 wit

Mireia Mollar-Gumbau, Aleix Alcacer, Rafael Benitez, Vicente J. Bolos

Multidimensional scaling visualizes dissimilarities among objects and reduces data dimensionality. While many methods address symmetric proximity data, asymmetric and especially three-way proximity data (capturing relationships across multiple occasions) remain underexplored. The h-plot enables the analysis of asymmetric and non-reflexive relationships by em

Luke Dosiek, Akaash Karn, Frank Liu

This paper describes a new approach for using changepoint detection (CPD) to estimate the starting and stopping times of a forced oscillation (FO) in measured power system data. As with a previous application of CPD to this problem, the pruned exact linear time (PELT) algorithm is used. However, instead of allowing PELT to automatically tune its penalty para

Alexander Schwenke, Wolfram Brenig

We apply the numerical linked cluster expansion (NLCE) to study thermodynamic properties of the proximate Kitaev magnet $\alpha$-RuCl$_3$ on the honeycomb lattice in the presence of a magnetic field. Using the extended spin-1/2 $J$-$K$-$\Gamma$ model and based on documented exchange and magnetoelastic coupling parameters, we present results for the internal

Pierce Giffin, Andrew Liu, Jeremias Boucsein, Akaxia Cruz

Long-range interactions in the dark sector can give rise to collective plasma phenomena that are capable of modifying the evolution of dark matter halos. We present the first study of gravitational collapse in a secluded dark $U(1)_D$ model using a magnetohydrodynamic description of the dark matter. We show that dark magnetic fields generate an anisotropic p

Arnab Sarkar, Eric D. Miller, Brian McNamara, Ming Sun

We present new measurements of the chemical abundance pattern in the core of the nearby galaxy cluster Abell~2029, based on XRISM observations with Resolve (37 ks) and Xtend (500 ks), combined with archival data from XMM-Newton (EPIC, RGS) and Chandra. Fe abundances derived from Resolve, Xtend, and EPIC are broadly consistent, while RGS gives systematically

Niusha Ahvazi, Andrew B. Pace, Christopher T. Garling, Xiaowei Ou

We investigate the formation and observable properties of faint satellite galaxies (M$_\rm V > -3$) in Milky Way-like halos using the semi-analytic galaxy formation model Galacticus. The ability of the smallest dark matter halos to form stars depends sensitively on the balance between gas cooling and reionization heating. To quantify how this balance shapes

Bhagyesh Kumar, A S Aravinthakashan, Akshat Satyanarayan, Ishaan Gakhar

Adversarially perturbed images of text can cause sophisticated OCR systems to produce misleading or incorrect transcriptions from seemingly invisible changes to humans. Some of these perturbations even survive physical capture, posing security risks to high-stakes applications such as document processing, license plate recognition, and automated compliance s

Angelos Pelecanos, Jack Spilecki, Ewin Tang, John Wright

A longstanding belief in quantum tomography is that estimating a mixed state is far harder than estimating a pure state. This is borne out in the mathematics, where mixed state algorithms have always required more sophisticated techniques to design and analyze than pure state algorithms. We present a new approach to tomography demonstrating that, contrary to

Jens Rupprecht, Leon Fröhling, Claudia Wagner, Markus Strohmaier

The use of Large Language Models (LLMs) for simulating human perspectives via persona prompting is gaining traction in computational social science. However, well-curated, empirically grounded persona collections remain scarce, limiting the accuracy and representativeness of such simulations. Here, we introduce the German General Social Survey Personas (GGSS

Jieqiu Shao, Diego A. R. Dalvit, Lukasz Cincio, Bharath Hebbe Madhusudhana

Bosonic systems, such as photons and ultracold atoms, have played a central role in demonstrating quantum-enhanced sensing. Quantum entanglement, through squeezed and GHZ states, enables sensing beyond classical limits. However, such a quantum advantage has so far been confined to two-mode bosonic systems, as analogous multi-mode squeezed states are non-triv

Raditya Weda Bomantara

We propose a class of periodically driven (Hermitian) modified bosonic Kitaev chains that effectively hosts rich nonHermitian Floquet topological phenomena. Two particular models are investigated in details as case studies. The first of these represents a minimal topologically nontrivial model in which nonHermitian skin effect, topological zero modes, and to

Luca Chiantini, Łucja Farnik, Giuseppe Favacchio, Brian Harbourne

Given two distinct reduced, irreducible curves of given degrees, contained in projective space but whose union is not contained in a hyperplane, what is the largest number of points of intersection they can have? When the projective space is the plane, this is trivial. For projective 3 space this problem was solved independently by Diaz and by Giuffrida in 1

Ben Craps, Gabriele Pascuzzi, Juan F. Pedraza, Le-Chen Qu

We establish a direct correspondence between Krylov and Nielsen complexity by choosing the Krylov basis to be part of the elementary gate set of Nielsen geometry and selecting a Nielsen complexity metric compatible with the Krylov metric. Up to normalization, the Krylov complexity of a Hermitian operator then equals the length squared of a straight-line traj

Ali Rostami-Shirazi, Narges Rostami, Hosein Haghi, Akram Hasani Zonoozi

We analyzed the spatial distribution of globular cluster (GC) systems across 37 host galaxies in a two dimensional parameter space defined by projected galactocentric distance Rg and metallicity Fe/H. We identified a universal triangular depleted region characterized by a lack of metal poor GCs in the inner parts of host galaxies. The morphology of this depl

Mariana Carrillo Gonzalez, Valerio De Luca, Alice Garoffolo, Julio Parra-Martinez

Gravitational waves propagating across gravitational potentials undergo lensing effects that, in the wave-optics regime, manifest as frequency-dependent amplitude and phase modulations. In this work, we revisit the diffraction integral formalism of gravitational lensing and demonstrate that it admits a natural and transparent interpretation within the framew

Alexandre M. Pombo, Lorenzo Pizzuti

We introduce SpectralPINN, a hybrid pseudo-spectral/physics-informed neural network (PINN) solver for Kerr quasinormal modes that targets the Teukolsky equation in both the separated (radial/angular) and joint two-dimensional formulations. The solver replaces standard neural activation functions with Chebyshev polynomials of the first kind and supports both

D. Kleiner, P. Serra, A. Loni, S. H. A. Rajohnson

We present the deepest HI mass Function (HIMF) ever measured, outside the Local Group. The observations are part of the MeerKAT Fornax Survey and cover a 4 x 4 deg^2 field, corresponding to ~ Rvir. The 3$\sigma$ detection limit is log(MHI/Msun) = 5.7 for a 50 km/s-wide point source. We detect HI in 35 galaxies and 44 clouds with no optical counterparts. Usin

Pouya Asadi, David Cyncynates, Stefania Gori

The QCD axion may offer a unified origin for the baryon asymmetry and dark matter through axiogenesis. However, in the minimal QCD axion scenario, axiogenesis either underproduces baryons or overproduces dark matter, and the required kinetic misalignment initial conditions are in tension with axion quality. In this \textit{Letter}, we demonstrate that the ax

Ming-Yu Lei, Bei Zhou, Xiaoyuan Huang

The existence of dark matter (DM) is supported by various macroscopic observations, but its microscopic nature remains elusive. The Galactic Center GeV gamma-ray excess (GCE) has been a leading candidate signal for particle DM annihilation. However, an unresolved population of millisecond pulsars (MSPs) in the bulge provides the alternative explanation for t

Jasleen Matharu, Lu Shen, Irene Shivaei, Pascal A. Oesch

[abridged] The previously inaccessible star formation tracer Pa$\alpha$ can now be spatially resolved by JWST NIRCam slitless spectroscopy in distant galaxies up to cosmic noon. In the first study of its kind, we combine JWST NGDEEP NIRISS and FRESCO NIRCam slitless spectroscopy to provide the first direct comparison of spatially resolved dust-obscured (trac

Luke R. Holden, Daniel J. B. Smith, Marina I. Arnaudova, Clive. N. Tadhunter

To explain the properties of the local galaxy population, theoretical models require active galactic nuclei (AGN) to inject energy into host galaxies, thereby expelling outflows of gas that would otherwise form stars. Observational tests of this scenario rely on determining outflow masses, which requires measuring the electron density ($n_e$) of ionised gas.

Kierthika Chathirathas, Thomas Schwetz

We assume axion-like particles (ALPs) to provide the full dark matter abundance and derive various lower bounds on the ALP mass. We contrast the post- and pre-inflationary symmetry breaking cases and present allowed regions in the plane of ALP mass and energy scale of inflation. For the post-inflationary case, we revisit bounds from isocurvature perturbation

Fabio Fontanot, Roberto Decarli, Gabriella De Lucia, Olga Cucciati

We discuss the properties of a sample of z>6 bright (bolometric luminosity L$_{\rm bolo}$>10$^{46.25}$ erg/s) Quasars drawn from a realisation of the GAlaxy Evolution and Assembly (GAEA) model coupled with the Planck Millennium Simulation. We focus on the properties and environment of host galaxies on a physical scale of 10 cMpc, and their evolution down to

Theophilus Ansah-Narh, Jordan Lontsi Tedongmo, Joseph Bremang Tandoh, Nia Imara

The classification of radio galaxies is central to understanding galaxy evolution, active galactic nuclei dynamics, and the large-scale structure of the universe. However, traditional manual techniques are inadequate for processing the massive, heterogeneous datasets generated by modern radio surveys. In this study, we present a probabilistic machine learnin

Renata Frelikh, Ruth A. Murray-Clay

We develop a flexible one-dimensional code to model the escape of hydrogen and helium from a hot Jupiter as a result of photoionization from extreme-ultraviolet (EUV) radiation. We include stellar spectrum heating and ionization, radiative cooling by Lyman-$\alpha$ and H$_3^+$, heat conduction, tidal gravity, a H-He reaction network, and account for the seco

S. Zarattini, A. Biviano, I. Bartalucci, J. A. L. Aguerri

Fossil groups (FGs) are groups or clusters of galaxies with a single, massive, central galaxy and with a clear lack of L* galaxies. The physical reason for their large magnitude gap (dm12) may arise from early FG formation, which allowed all L galaxies to merge with the central one, and/or it could be related to the fact that galaxies accreting on the FGs mo

Andrea Caputo, Jaeyoung Park, Seokhoon Yun

We investigate cosmological and astrophysical constraints on dark photons with masses $\sim 10^{-1}$-$10^3$ MeV. These dark photons can be copiously produced either in the early universe or during core-collapse supernovae, potentially leaving distinct observational signatures. First, we derive updated constraints from cosmological and astrophysical observabl

Alek Bedroya, Paul J. Steinhardt

We show that holography imposes strong and general constraints on scalar field potentials in the string landscape, determined by the asymptotic structure of the underlying spacetime. Applying these holographic consistency conditions, we identify broad classes of scalar potentials that are incompatible with a well-defined dual description. These include poten

Vinícius Bernardes, Theodore Erler, Atakan Hilmi Fırat

We use a new formula for symplectic structure to compute the momentum of an analytic lump solution moving at constant velocity in Witten's open string field theory. The computation gives a new way to determine the D-brane tension in string field theory. Using homotopy algebra technology, we prove that this tension must agree with the value implied by the on-

David Berenstein, Ziyi Li

We construct the higher spin wave functions in the embedding space of anti-de Sitter Lorentzian spacetime. These wave functions are built from a primary wave functions that has a simple structure expressed in terms of the special conformal generator vector fields in AdS. We compute the eigenvalue of the quadratic Casimir for the symmetric traceless states, a

Ian Pang, Darius A. Faroughy, David Shih, Ranit Das

Beyond the practical goal of improving search and measurement sensitivity through better jet tagging algorithms, there is a deeper question: what are their upper performance limits? Generative surrogate models with learned likelihood functions offer a new approach to this problem, provided the surrogate correctly captures the underlying data distribution. In

Violeta Kastreva, Philip Whittington, Dennis Komm, Tiago Pimentel

Recent works have shown that tokenisation is NP-complete. However, these works assume tokenisation is applied to inputs with unboundedly large alphabets -- an unrealistic assumption, given that in practice tokenisers operate over fixed-size alphabets, such as bytes or Unicode-characters. We close this gap by analysing tokenisation over bounded alphabets, con

Kevin P. Lucht, J. H. Pixley, Pavel A. Volkov

We demonstrate the emergence of gapped phases driven by the moir\'{e} superlattice that trivialize the topological states in twisted nodal superconductors. The effect arises from umklapp tunneling between non-adjacent Dirac points in momentum space close to specific twist angles or chemical potentials, determined by the Fermi surface geometry. We confirm the

Nachiketa Sarkar

We introduce a Principal Component Analysis (PCA)--Bayesian framework for extracting chemical freeze-out conditions in relativistic heavy-ion collisions that resolves long-standing ambiguities in hadron-ratio--based analyses. By constructing all possible hadron-yield ratios from a chosen set of species and transforming them into an orthogonal PCA basis, the

Yikun Wang, Zuyan Liu, Ziyi Wang, Han Hu

Current research on agentic visual reasoning enables deep multimodal understanding but primarily focuses on image manipulation tools, leaving a gap toward more general-purpose agentic models. In this work, we revisit the geolocalization task, which requires not only nuanced visual grounding but also web search to confirm or refine hypotheses during reasoning

Xiongyi Cai, Ri-Zhao Qiu, Geng Chen, Lai Wei

Egocentric videos are a valuable and scalable data source to learn manipulation policies. However, due to significant data heterogeneity, most existing approaches utilize human data for simple pre-training, which does not unlock its full potential. This paper first provides a scalable recipe for collecting and using egocentric data by categorizing human data

Beichen Zhang, Yuhang Zang, Xiaoyi Dong, Yuhang Cao

Abstract reasoning from minimal examples remains a core unsolved problem for frontier foundation models such as GPT-5 and Grok 4. These models still fail to infer structured transformation rules from a handful of examples, which is a key hallmark of human intelligence. The Abstraction and Reasoning Corpus for Artificial General Intelligence (ARC-AGI) provide

Yu-Feng Li, Andong Wang, Ya Xu, Jing-yu Zhu

The JUNO Collaboration has recently released its first reactor antineutrino oscillation result, achieving unprecedented precision in the measurement of $\Delta m^2_{21}$ and $\sin^2\theta_{12}$. We emphasize that the accurate determination and modeling of the terrestrial matter density profile are fundamental for extracting the oscillation parameters and pro

Fiona McCarthy, Boryana Hadzhiyska, J. Richard Bond, William R. Coulton

Over the last year, kinematic Sunyaev--Zel'dovich (kSZ) velocity reconstruction -- the measurement of the large-scale velocity field using the anisotropic statistics of the small-scale kSZ-galaxy overdensity correlation -- has emerged as a statistically significant probe of the large-scale Universe. In this work, we perform a 2-dimensional tomographic recons

Jingxi Chen, Zongxia Li, Zhichao Liu, Guangyao Shi

What role does the first frame play in video generation models? Traditionally, it's viewed as the spatial-temporal starting point of a video, merely a seed for subsequent animation. In this work, we reveal a fundamentally different perspective: video models implicitly treat the first frame as a conceptual memory buffer that stores visual entities for later r

Jingkai Ying, Zhijin Qin, Yulong Feng, Liejun Wang

In recent years, the Transformer architecture has achieved outstanding performance across a wide range of tasks and modalities. Token is the unified input and output representation in Transformer-based models, which has become a fundamental information unit. In this work, we consider the problem of token communication, studying how to transmit tokens efficie

Naveen Raman, Jingwu Tang, Zhiyu Chen, Zheyuan Ryan Shi

Food rescue organizations simultaneously tackle food insecurity and waste by working with volunteers to redistribute food from donors who have excess to recipients who need it. Volunteer feedback allows food rescue organizations to identify issues early and ensure volunteer satisfaction. However, food rescue organizations monitor feedback manually, which can

Gao Mo, Naveen Raman, Megan Chai, Cindy Peng

Behavioral health conditions, which include mental health and substance use disorders, are the leading disease burden in the United States. Peer-run behavioral health organizations (PROs) critically assist individuals facing these conditions by combining mental health services with assistance for needs such as income, employment, and housing. However, limite

Bahaa Al Sayegh, Wissam Chemissany

We investigate the critical behavior and real-time scattering dynamics of the interacting $\phi^4$ quantum field theory in (1+1)-dimensions using uniform matrix product states (uMPS) and the time-dependent variational principle (TDVP). A finite-entanglement scaling analysis at $\lambda = 0.8$ bounds the critical mass-squared to $\mu_c^2 \in ]-0.2595,-0.2594[

Zuo Lin

We prove an effective equidistribution theorem for orbits of certain unipotent subgroups in arithmetic quotients of perfect Lie groups with a polynomial error term. Even for semisimple quotients, our result provides the first infinite family of examples where effective equidistribution with polynomial error rate is obtained for non-horospherical unipotent su

Víctor M. Patiño-Álvarez, Jonhatan U. Guerrero-González, Vahram Chavushyan, Douglas E. Monjardin-Ward

Aims. This study investigates the relationship between the Mg II {\lambda}2798 {\AA} emission line and the 3000 {\AA} continuum luminosity, as well as the Baldwin Effect, in a sample of 40,685 radio-quiet (RQ) quasars and 441 Flat Spectrum Radio Quasars (FSRQs). Methods. We perform a comprehensive re-evaluation of the Mg II-3000 {\AA} correlation, explicitly

Paulina Tworek, Miłosz Bargieł, Yousef Khan, Tomasz Pełech-Pilichowski

Extracting structured medical insights from unstructured clinical text using Natural Language Processing (NLP) remains an open challenge in healthcare, particularly in non-English contexts where resources are scarce. This study presents a comparative analysis of NLP low-compute rule-based methods and Large Language Models (LLMs) for information extraction fr

Medha Kumar, Zifei Xu, Xin Wang, Tristan Webb

Strong reasoning capabilities can now be achieved by large-scale reinforcement learning (RL) without any supervised fine-tuning. Although post-training quantization (PTQ) and quantization-aware training (QAT) are well studied in the context of fine-tuning, how quantization impacts RL in large reasoning models (LRMs) remains an open question. To answer this q

Odilon Lourenço, Everson H. Rodrigues, Carline Biesdorf, Mariana Dutra

In this work, we investigate how short-range correlations affect relativistic hadronic models at high densities, with direct consequences for the structure of neutron stars, both with and without dark matter content. Two versions of the model are examined: one with vector self-interactions up to second order ($\omega_0^2$) and another including a fourth-orde

Yushi Huang, Zining Wang, Zhihang Yuan, Yifu Ding

Mixture-of-Experts (MoE) Multimodal large language models (MLLMs) excel at vision-language tasks, but they suffer from high computational inefficiency. To reduce inference overhead, expert skipping methods have been proposed to deactivate redundant experts based on the current input tokens. However, we find that applying these methods-originally designed for

Tiemo Pedergnana, Florian Kogelbauer

Vortices are swirling regions of fluid that structure motion in gases and liquids across a wide range of scales, from laboratory-scale experiments to vast atmospheric currents. They play a key role in mixing, transport, and energy transfer, yet their reliable identification in unsteady flows remained a major challenge. Most existing approaches rely on local,

Marek Lewicki, Ville Vaskonen

We compute the gravitational wave spectra from strongly supercooled first-order phase transitions, explicitly incorporating the evolution of the background metric across the transition from thermal inflation to radiation domination. We find that the spectral shape remains largely unchanged apart from a causality-induced super-horizon tail. However, in contra

A. Uryson

The propagation of cosmic iron nuclei with energies above 10^19 eV from their sources to the Galaxy is discussed by assuming that cosmic rays at ultra-high energies are of extragalactic origin. In extragalactic space, cosmic nuclei interact with background emissions and inevitably fragment. An analysis is performed of the fraction of iron nuclei reaching the

Yash Prajapati

This paper examines public goods and evaluates the mechanism through the game theory. Public goods are characterized by nonexclusivity and nonrivalry and this creates fundamental challenges for allocation. We analyze why competitive markets undersupply public goods by deriving the inefficiency formally through Nash equilibrium. The paper evaluates theoretica

Eric Haag, Yuhao Chen, Giri Venkataramanan, Manish K. Singh

The rapid growth of large data center loads and inverter-based generation is increasing the stress on transmission networks, while expanding grid capacity at the required pace remains challenging. Power flow controllers (PFCs) that adjust effective line reactances to redistribute flows are often viewed as an interim solution to improve transmission network u

Yao Fu, Raymond Brock, Daniel Hayden, Chien-Peng Yuan

Uncertainties in the parametrization of Parton Distribution Functions are a serious limiting systematic uncertainty in Large Hadron Collider searches for Beyond the Standard Model physics. This is especially true for measurements at high scales induced by quark and anti-quark collisions, where Drell-Yan continuum backgrounds are dominant. In Phys. Rev. D99,

Xinyi Huang, Sze Chai Leung, H. Jane Bae

Data-driven subgrid-scale (SGS) modeling in the large-eddy simulations (LES) suffers from the inconsistency between the \textit{a priori} tests and the a posteriori tests, which make training accurate SGS models a difficult task. We study the difference in filtered high-fidelity data and LES to identify the numerical deviation between the two cases, which is

Akshay Gaikwad, Manuel Sebastian Torres, Anton Frisk Kockum

Drawing inspiration from gradient-descent methods developed for data processing in quantum state tomography [\href{https://iopscience.iop.org/article/10.1088/2058-9565/ae0baa}{Quantum Sci.~Technol.~\textbf{10} 045055 (2025)}] and quantum process tomography [\href{https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.130.150402}{Phys.~Rev.~Lett.~\textbf{1

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

A measurement of the branching fraction for the decay $\mathit{\Lambda} \to p \mu^- \overline{\nu}_{\mu}$ is presented using $\textit{pp}$ collision data collected by the LHCb experiment at a centre-of-mass energy of 13 TeV. The analysis is based on data recorded between 2016 and 2018, corresponding to an integrated luminosity of $5.4 \ \text{fb}^{-1}$. The

S M Mehedi Zaman, Kiran Garimella

Prime-time cable news programs are a highly influential part of the American media landscape, with top-rated opinion shows attracting millions of politically attentive viewers each night. In an era of intense political polarization, a critical question is whether these widely-watched "debate" shows foster genuine discussion or have devolved into partisan ech

Danwen Ji, Botao 'Amber' Hu

After the pandemic, a new form of "pop-up city" has emerged -- co-living gatherings of 100-200 people for 4-8 weeks that differ from conferences and hack houses. These temporary intentional communities leverages existing urban infrastructure, blending daily life (housing, meals, care) with self-organized activities like learning, creating, and socializing. T

Jianqiao Mao, Max A. Little

Front-door adjustment gives a simple closed-form identification formula under the classical front-door criterion, but its applicability is often viewed as narrow. By contrast, the general ID algorithm can identify many more causal effects in arbitrary graphs, yet typically outputs algebraically complex expressions that are hard to estimate and interpret. We

Shang-Shun Zhang, Anish Bhardwaj, S. M. Koohpayeh, D. M. Pajerowski

We present an experimental and theoretical study of the anisotropic pyrochlore phase diagram. Inelastic field-dependent neutron scattering on Yb$_2$Ti$_2$O$_7$ shows intrinsic broadening and a flat low-energy magnon mode which is partially captured by interacting magnon models. Exact diagonalization reveals the existence of an emergent quantum phase between

Aarav Shah, M. Yu. Khlopov, M. Krasnov

We investigate torsion-driven cosmological dynamics within the framework of Einstein-Cartan gravity using the De Donder-Weyl Hamiltonian formalism, where the tetrad and Lorentz connection act as independent variables and the Hamiltonian includes quadratic Riemann Cartan corrections. Embedding this theory in an FLRW background, we derive the corresponding tor

Jing Qian, George X. Wang, Xiangyu Li, Yunge Wen

Mixed reality (XR) environments offer vast spatial possibilities, but current window management systems require users to manually place, resize, and organize multiple applications across large 3D spaces. This creates cognitive and interaction burdens that limit productivity. We introduce DuoZone, a mixed-initiative XR window management system that combines u

Sejuti Rahman, Swakshar Deb, MD. Sameer Iqbal Chowdhury, MD. Jubair Ahmed Sourov

Depression is a prevalent global mental health disorder, characterised by persistent low mood and anhedonia. However, it remains underdiagnosed because current diagnostic methods depend heavily on subjective clinical assessments. To enable objective detection, we introduce a gold standard dataset of 103 clinically assessed participants collected through a tr

Marco Ballarin, Juan José García-Ripoll, David Hayes, Michael Lubasch

For the preparation of high-dimensional functions on quantum computers, we introduce tensor network algorithms that are efficient with regard to dimensionality, optimize circuits composed of hardware-native gates and take gate errors into account during the optimization. To avoid the notorious barren plateau problem of vanishing gradients in the circuit opti

Jun Yan

Let $n\geq\nu$, let $T$ be an $n$-vertex tree with bipartition class sizes $t_1\geq t_2$, and let $S$ be a $\nu$-vertex tree with bipartition class sizes $\tau_1\geq\tau_2$. Using four natural constructions, we show that the Ramsey number $R(T,S)$ is lower bounded by $\underline{R}(T,S)=\max\{n+\tau_2,\nu+\min\{t_2,\nu\},\min\{2t_1,2\nu\},2\tau_1\}-1$. Our m

Mihir Rao

Scientific discovery can be framed as a thermodynamic process in which an agent invests physical work to acquire information about an environment under a finite work budget. Using established results about the thermodynamics of computing, we derive finite-budget bounds on information gain over rounds of sequential Bayesian learning. We also propose a metric

Akhlesh Lakhtakia

The concept of geometric phase was applied to initiate the geometric-phase portrayal of electromagnetic scattering by a three-dimensional object in free space. Whereas the incident electromagnetic field is that of an arbitrarily polarized plane wave, the direction-dependent far-zone scattering amplitude is used to define direction-dependent Stokes parameters

Bartosz Bieganowski, Daniel Strzelecki

We study the existence of solutions for the nonlinear scalar field equation $$-\Delta u - \frac{(N-2)^2}{4|x|^2} u = g(u), \quad \mbox{in } \mathbb{R}^N \setminus \{0\},$$ where the potential $-\frac{(N-2)^2}{4|x|^2}$ is the critical Hardy potential and $N \geq 3$. The nonlinearity $g$ is continuous and satisfies general subcritical growth assumptions of the

Natalia Oliveros-Gomez, Elena Manjavacas, Theodora Karalidi, Myrla Phillippe

We present a new analysis of the spectroscopic variability of WISE~J104915.57$-$531906.1AB (WISE~1049AB, L7.5+T0.5), observed using the NIRSpec instrument onboard the James Webb Space Telescope (GO 2965 - PI: Biller). We explored the variability of the dominant molecular bands present in their 0.6--5.3~$\mu$m spectra (H$_2$O, CH$_4$, CO), finding that the B

Huixiang Zhang, Mahzabeen Emu

Precisely controlling Large Language Models (LLMs) to generate efficient and concise code is a central challenge in software engineering. We introduce a framework based on Test-Driven Development (TDD) that transforms code specification into a combinatorial optimization task. The framework first prompts an LLM to generate a test suite, then formulates the Te

Timur Obolenskiy

We to define a Path Integral in Lorentzian time by restricting the relevant domain of integration on $C([0,1],M)$ over a Riemannian configuration manifold $(M,g)$ and considering the dynamics of a particle evolving between to fixed endpoints with a referential non-degenerate classical trajectory, formulating a framework around a quadratic Lagrangian. Through

Houssam Abdul-Rahman, Christopher Cedzich, Günter Stolz, Albert H. Werner

We establish exact scalings for the maximal group velocity of translation-invariant quantum walks in periodic electric fields. Our main result shows that the maximal group velocity decays exponentially with the period of the field in the whole parameter range, thus affirming a conjecture of arXiv:2302.01869 and at the same time augmenting it to an exact equa

Claudio Agostini, Nick Chapman, Luca Motto Ros, Beatrice Pitton

Generalizing classical descriptive set theory opens foundational questions about the Borel hierarchy. In this paper we systematically study those questions, working in the general framework of Polish-like spaces relative to an uncountable cardinal $\kappa$, possibly singular, satisfying $2^{<\kappa}=\kappa$. We provide fundamental properties of the $\kappa^+

Kostiantyn Drach, Zhi Fu, Vadim Kaloshin, Zhiqiang Li

For a smooth expanding circle map, we show that the empirical distribution of Lyapunov exponents of periodic points of any fixed period is close to normal, with an error that decreases as the period grows. This establishes a version of the Central Limit Theorem for such finite periodic orbits.

Yicheng He, Chengsong Huang, Zongxia Li, Jiaxin Huang

Reinforcement learning (RL) provides a principled framework for improving Vision-Language Models (VLMs) on complex reasoning tasks. However, existing RL approaches often rely on human-annotated labels or task-specific heuristics to define verifiable rewards, both of which are costly and difficult to scale. We introduce VisPlay, a self-evolving RL framework t