December 2025 arXiv papers — page 103

Joaquín González-Nuevo, Laura Bonavera, Juan Alberto Cano, David Crespo

Magnification bias, the lensing-induced modification of background source number counts, provides a uniquely powerful probe of the mass density profiles of galaxies and clusters down to kpc scales. Unlike shear-based weak lensing, magnification bias does not rely on galaxy shapes and thus avoids dominant small-scale systematics. Existing studies, however, ar

Laura Bonavera, Joaquin Gonzalez-Nuevo, Juan Alberto Cano, David Crespo

Magnification bias offers a uniquely powerful and independent route to cosmological information. As a gravitational-lensing observable, it probes galaxy-matter correlations without relying on galaxy shapes, PSF modelling, or intrinsic-alignment corrections. Its sensitivity spans both geometry and growth: magnification bias simultaneously responds to the matt

Jonah Berggren, Khrystyna Serhiyenko

$\tau$-tilting theory can be thought of as a generalization of the classical tilting theory which allows mutations at any indecomposable summand of a support $\tau$-tilting pair. Indeed, for any algebra $\Lambda$ its tilting modules $\text{tilt}\,\Lambda$ form a subposet of the support $\tau$-tilting poset $\text{s}\tau-\text{tilt}\,\Lambda$. We show that co

Albert Dorador

Reliable estimation of feature contributions in machine learning models is essential for trust, transparency and regulatory compliance, especially when models are proprietary or otherwise operate as black boxes. While permutation-based methods are a standard tool for this task, classical implementations rely on repeated random permutations, introducing compu

ChunJun Cao, Giuseppe Cotardo, Brad Lackey

This work introduces a symplectic framework for quantum error correcting codes in which local structure is analyzed through an anticode perspective. In this setting, a code is treated as a symplectic space, and anticodes arise as maximal symplectic subspaces whose elements vanish on a prescribed set of components, providing a natural quantum analogue of thei

Charles Marrder, Shuo Sun, Murray J. Holland

Dynamical decoupling seeks to mitigate phase decoherence in qubits by applying a carefully designed sequence of effectively instantaneous electromagnetic pulses. Although analytic solutions exist for pulse timings that are optimal under specific noise regimes, identifying the optimal timings for a realistic noise spectrum remains challenging. We propose a re

Sergei N. Yurchenko, Marco G. Barnfield, Charles A. Bowesman, Ryan P. Brady

Extensive rovibrational line lists are constructed for 12 isotopologues of carbon dioxide: $^{12}$C$^{16}$O$_2$, $^{13}$C$^{16}$O$_2$, $^{12}$C$^{17}$O$_2$, $^{13}$C$^{17}$O$_2$, $^{12}$C$^{18}$O$_2$, $^{13}$C$^{18}$O$_2$, $^{16}$O$^{12}$C$^{17}$O, $^{16}$O$^{12}$C$^{18}$O, $^{16}$O$^{13}$C$^{17}$O, $^{16}$O$^{13}$C$^{18}$O, $^{17}$O$^{12}$C$^{18}$O, and $^{

Hua Lv, Tauqir Shinwari, Kacho Imtiyaz Ali Khan, Jens Herfort

Van der Waals (vdW) heterostructures combining two-dimensional (2D) ferromagnets and semiconducting transition-metal dichalcogenides (TMDCs) offer highly promising opportunities for tailoring 2D magnetism through interfacial proximity effects, enabling unique physical phenomena inaccessible in 3D systems and achieving functionalities beyond conventional spin

Xinfeng Gao, Olivier Pfister, Stefan Bekiranov

The Koopman-von Neumann (KvN) formalism recasts classical mechanics in a Hilbert space framework using complex wavefunctions and linear operators, akin to quantum mechanics. Instead of evolving probability densities in phase space (as in Liouville's equation), KvN uses a Schr\"odinger-like equation for a classical wavefunction, with commuting position and mo

Mohammad Mozaffari, Samuel Kushnir, Maryam Mehri Dehnavi, Amir Yazdanbakhsh

Post-training model pruning is a promising solution, yet it faces a trade-off: simple heuristics that zero weights are fast but degrade accuracy, while principled joint optimization methods recover accuracy but are computationally infeasible at modern scale. One-shot methods such as SparseGPT offer a practical trade-off in optimality by applying efficient, a

V. O. Ramirez-Beltran, Cecilia Uribe Estrada, Mauricio Flores Geronimo, François Lagarde

A macroscopic reconstruction is developed to infer iRPC performance using Geant4 observables and one experimental anchor. The Geant4 energy deposition is used to estimate the primary ionization yield, while the efficiency turn-on is modeled through an induced-charge description encoded in an effective gain G(E). The absolute scale is fixed by calibrating the

Jonas Golde, Patrick Haller, Alan Akbik

Recent multilingual named entity recognition (NER) work has shown that large language models (LLMs) can provide effective synthetic supervision, yet such datasets have mostly appeared as by-products of broader experiments rather than as systematic, reusable resources. We introduce FiNERweb, a dataset-creation pipeline that scales the teacher-student paradigm

Philipp Fleig

We propose a renormalization group (RG) approach to compare and collapse eigenvalue densities of random matrix models of complex systems across different system sizes. The approach is to fix a natural spectral scale by letting the model normalization run with size, turning raw spectra into comparable, collapsed density curves. We demonstrate this approach on

Shilpa Mahato, Rajibul Islam

Holographic beam shaping is a powerful approach for generating individually addressable optical spots for controlling atomic qubits, such as those in trapped-ion quantum processors. However, its application in qubit control is limited by residual intensity crosstalk at neighboring sites and by a nonzero background floor in the far wings of the addressing bea

Mathilde Bouvier, Yiqing Song, Michael Romano, Anelise Audibert

Submillimetre molecular lines (e.g., CO, HCN, SiO) provide a uniquely powerful view of the physical and chemical processes that govern star formation (SF) and galaxy evolution. Yet, our current picture of the molecular universe beyond the Milky Way remains strikingly incomplete: broad chemical inventories exist for only a handful of galaxies, typically more

Henry Gray, Tom Yotam, Octavian Udrea

Translating algorithms from high-level languages like MATLAB to hardware description languages (HDLs) is a resource-intensive but necessary step for deployment on FPGAs and ASICs. While large language models (LLMs) offer a path to automation, their limited training on HDL code makes end-to-end transpilation brittle and prone to syntax errors. We compare two

Geofrey Owino, Bernard Shibwabo

Infant cry classification can aid early assessment of infant needs. However, deployment of such solutions is limited by privacy concerns around audio data, sensitivity to background noise, and domain shift across recording environments. We present an end-to-end infant cry analysis pipeline that integrates a denoising autoencoder (DAE), a convolutional tokeni

Ishan Banerjee, Faye Jackson, Anne Larsen, Sam Payne

We study the universal PGL_n character variety over M_g whose fiber over a point [C] is the space of PGL_n-local systems on the curve C. We use nonabelian Hodge theory and properties of Saito's mixed Hodge modules to show that the Leray-Serre spectral sequence for the projection to M_g degenerates at E_2. As an application, we prove that the rational coh

Soham Chakraborty

It is known to experts that certain regular inclusions of von Neumann algebras arise as crossed products with cocycle actions of the canonical quotient groupoids associated with the inclusions. Similarly, `strongly normal' inclusions of standard equivalence relations arise as semi-direct products with cocycle actions of the quotient groupoids. However, to th

Ian M. Hayes, Elliot Fang, Shanta R. Saha, Vivek Mishra

One of the recurring hurdles in studying unconventional superconductivity is the challenge of efficiently and conclusively identifying the symmetry of the superconducting order parameter in a new material. Uranium ditelluride (UTe$_2$) exhibits an unprecedented number of superconducting phases as a function of pressure and magnetic field, each presumably cha

Ye Zhang, Qi Chen, Wenyou Huang, Rui Liu

Detection Transformers (DETR) formulate object detection as a set prediction problem and enable end-to-end training without post-processing. However, object queries in DETR interact through symmetric self-attention, which enforces uniform competition among all query pairs. This often leads to inefficient query dynamics, where multiple queries converge to the

Michael C. Stanley, Peter W. Spaeth, James E. Warner, Matthew R. Webster

As bonded composite materials are used more frequently for aerospace applications, it is necessary to certify that parts achieve desired levels of certain physical characteristics (e.g., strength) for safety and performance. Nondestructive evaluation (NDE) of adhesively bonded structures enables verification of bond physical characteristics, but uncertainty

Anastasia Mavridou, Marie Farrell, Gricel Vázquez, Tom Pressburger

Integrating autonomous and adaptive behavior into software-intensive systems presents significant challenges for software development, as uncertainties in the environment or decision-making processes must be explicitly captured. These challenges are amplified in safety- and mission-critical systems, which must undergo rigorous scrutiny during design and deve

Przemek Pospieszny, Dominika P. Brodowicz

In recent years, advances in artificial intelligence (AI), particularly generative AI (GenAI) and large language models (LLMs), have made human-computer interactions more frequent, efficient, and accessible across sectors ranging from banking to healthcare. AI tools embedded in digital devices support decision-making and operational management at both indivi

Jitesh Jain, Jialuo Li, Zixian Ma, Jieyu Zhang

As humans, we are natural any-horizon reasoners, i.e., we can decide whether to iteratively skim long videos or watch short ones in full when necessary for a given task. With this in mind, one would expect video reasoning models to reason flexibly across different durations. However, SOTA models are still trained to predict answers in a single turn while pro

Kamil Ciosek, Nicolò Felicioni, Sina Ghiassian, Juan Elenter Litwin

We make two contributions to the problem of estimating the $L_1$ calibration error of a binary classifier from a finite dataset. First, we provide an upper bound for any classifier where the calibration function has bounded variation. Second, we provide a method of modifying any classifier so that its calibration error can be upper bounded efficiently withou

Shaun Sweeney, Robert Shorten, Mark O'Malley

This thesis presents a fundamental rethink of electricity market design at the wholesale and balancing layers. Rather than treating markets as static spot clearing mechanisms, it reframes them as a continuously online, event driven dynamical control system: a two sided marketplace operating directly on grid physics. Existing energy only, capacity augmented,

Ricardo Gonçalves Molinari, Leonardo Abdala Elias

Restoring hand function requires simultaneous and proportional control (SPC) of multiple degrees of freedom (DoFs). This study evaluated the multichannel linear descriptors-based block field method (MLD-BFM) against conventional feature extraction approaches for continuous decoding of five finger-joint DoFs using high-density surface electromyography (HD sEM

Tianyu Zhou, Zihao Liang, Zehui Lu, Shaoshuai Mou

This paper proposes a Safe Online Control-Informed Learning framework for safety-critical autonomous systems. The framework unifies optimal control, parameter estimation, and safety constraints into an online learning process. It employs an extended Kalman filter to incrementally update system parameters in real time, enabling robust and data-efficient adapt

Mostafa Darvishi

This paper presents a pipeline stage resolved timing characterization of a 32-bit RISC V processor implemented on a 20 nm FPGA and a 7 nm FinFET ASIC platform. A unified analysis framework is introduced that decomposes timing paths into logic, routing, and clocking components and maps them to well-defined pipeline stage transitions. This approach enables sys

Simion Filip

We describe recent work that extends some of the measure and topological rigidity results in dynamical systems from situations homogeneous under a Lie group to quite general manifolds.

Stephen Finbow, Gary MacGillivray

For a graph $G$ and a positive integer $k$, the $k$-Bell colour graph of $G$ is the graph whose vertices are the partitions of $V$ into at most $k$ independent sets, with two of these being adjacent if there exists a vertex $x$ such that the partitions are identical when restricted to $V - \{x\}$. The $k$-Stirling Colour graph of $G$ is defined similarly, bu

Alex L. Wang

We study the iteration complexity of Lipschitz convex optimization problems satisfying a general error bound. We show that for this class of problems, subgradient descent with either Polyak stepsizes or decaying stepsizes achieves minimax optimal convergence guarantees for decreasing distance-to-optimality. The main contribution is a novel lower-bounding arg

Karina Marin, Mauricio Poletti

In this survey we talk about what is known as Invariance Principle in dynamical systems. It states that the disintegration of measures with zero center Lyapunov exponents admits some extra invariance by holonomies. We focus on explaining the basic definitions and ideas behind a series of results about the Invariance Principle and give some basic applications

J. De Miguel, E. Hatziminaoglou, J. Prieto-Polo, J. D. Marrero-Falcón

The magnetospheres of neutron stars in the Galactic Center provide an exceptional environment to search for dark matter axions through their resonant conversion into photons. The combination of extreme magnetic fields and high dark matter density in this region creates ideal conditions for axion-photon conversion across the centimetre-to-submillimetre wavele

Henger Li, Shuangjie You, Flavio Di Palo, Yiyue Qian

Tool calling enables large language models (LLMs) to interact with external environments through tool invocation, providing a practical way to overcome the limitations of pretraining. However, the effectiveness of tool use depends heavily on the quality of the associated documentation and knowledge base context. These materials are usually written for human

Daiki Goto, Hector Manuel Lopez Rios, Monika Scholz, Suriyanarayanan Vaikuntanathan

Classical autoassociative memory models have been central to understanding emergent computations in recurrent neural circuits across diverse biological contexts. However, they typically neglect neuromodulatory agents that are known to strongly shape memory capacity and stability. Here we introduce a minimal, biophysically motivated associative memory network

Brendan Rhyno, Kuei Sun, Jude Bedessem, Naceur Gaaloul

Shell-shaped Bose-Einstein condensates (BECs) represent a paradigmatic instance of quantum fluids in hollow geometries exhibiting phenomena that bridge from ultracold atomic to astrophysical realms. In this work, we present a comprehensive survey of the dynamics, thermodynamics, and collective excitations of shell-shaped BECs, synthesizing two decades of our

Kamer Ali Yuksel

Large language models (LLMs) are increasingly used to evolve programs and multi-agent systems, yet most existing approaches rely on overwrite-based mutations that maintain only a single candidate at a time. Such methods discard useful variants, suffer from destructive edits, and explore a brittle search space prone to structural failure. We introduce EvoLatt

Dima Arinkin, Joshua Mundinger

We construct the Cartier duality equivalence for affine commutative group schemes $G$ whose coordinate ring is a flat Mittag-Leffler module over an arbitrary base ring $R$. The dual $G^\vee$ of $G$ turns out to be an ind-finite ind-scheme over $R$. When $R$ is Noetherian and admits a dualizing complex, we construct a Fourier-Mukai transform between quasicohe

Ujjwal Mishra, Vinita Shukla, Praful Hambarde, Amit Shukla

Adapting Vision Language Segmentation Models (VLSMs) to medical imaging domains requires significant computational overhead when using conventional fine-tuning approaches. Existing Parameter-Efficient Fine-Tuning (PEFT) methods apply uniform adapter dimensions across all transformer layers, leading to suboptimal parameter allocation and reduced adaptation ef

Francesco Bei, Mauro Spreafico

Motivated by the work of Cappell, Deturck, Gluch and Miller, we extend the notion of cohomology of harmonic forms (of a compact manifold with boundary) to the abstract setting of Hilbert complexes. Then, we present some geometric applications of our construction to incomplete Riemannian manifolds with particular interest to the case of smoothly stratified Th

Jelena Losic

Graph Neural Networks (GNNs) have become the standard for graph representation learning but remain vulnerable to structural perturbations. We propose a novel framework that integrates persistent homology features with stability regularization to enhance robustness. Building on the stability theorems of persistent homology \cite{cohen2007stability}, our metho

Jong In Han, Sijong Kwak, Euisung Park

Varieties of minimal degree and del Pezzo varieties are basic objects in projective algebraic geometry. Those varieties have been characterized and classified for a long time in many aspects. Motivated by the question "which varieties are the most basic and simplest except the above two kinds of varieties in view of geometry and syzygies?", we give an upper

Adam Cushman

We provide a new exponent for the Sum-Product conjecture on $\mathbb{R} $. Namely for $A \subset \mathbb{R}$ finite, \[ \max \left\{ \left\lvert A+A \right\rvert , \left\lvert AA \right\rvert \right\} \gg_{\epsilon} \left\lvert A \right\rvert ^{\frac{4}{3} + \frac{10}{4407} - \epsilon} .\] We also provide new exponents for $A \subset \mathbb{R} $ finite and

Mufhumudzi Muthivhi, Terence L van Zyl, Hairong Wang

Sequential recommendation models aim to learn from users evolving preferences. However, current state-of-the-art models suffer from an inherent popularity bias. This study developed a novel framework, BiCoRec, that adaptively accommodates users changing preferences for popular and niche items. Our approach leverages a co-attention mechanism to obtain a popul

Roman Krivonos, Silvia Manconi, Vadim Arefiev, Andrei Bykov

Searches for the putative large-scale X-ray halo around the Geminga pulsar have been extensively performed using various narrow field-of-view X-ray telescopes. In this paper, we present wide-field scanning observation of Geminga with SRG/ART-XC. Our X-ray analysis provides, for the first time, direct imaging of a $3.5^\circ \times 3.5^\circ$ region in the $4

Lars T. Kyllingstad

When two simulation units in a continuous-time co-simulation are connected via some variable $q$, and both simulation units have an internal state which represents the time integral of $q$, there will generally be a discrepancy between those states due to extrapolation errors. Normally, such extrapolation errors diminish if the macro time step size is reduce

Hiten Prakash Kothari, R. Michael Buehrer

This paper proposes a U-Net-based autoencoder framework for mitigating interference in communication signals corrupted by noise and diverse interference sources. The approach targets scenarios involving both signal-plus-noise and signal-plus-interference-plus-noise mixtures, including sinusoidal interferers, LFM chirps, QPSK interferers with different sampli

Hakkim Vovusha, Puspamitra Panigrahi, Yash Pal, Muhammad J. A. Shiddiky

Nanosensors are critical in environmental monitoring, industrial safety, and public health by detecting specific hazardous gases like CO, NO, SO_2, and CH_4 at trace levels. This study uses density functional theory (DFT) calculations to examine the gas-sensing capabilities of chromium diselenide (CrSe_2) and chromium ditelluride (CrTe_2) monolayers through

Daniel Green, Kshitij Gupta

The local physics of light scalar fields in de Sitter space is well described by classical random walks, as expressed through the framework of Stochastic Inflation. Recent work has clarified how this formalism arises from quantum field theory (QFT) and the renormalization group (RG), allowing for corrections to this formalism to be determined order by order.

Eduardo Gutiérrez-Peña, Carlos Octavio Pérez-Mendoza, Alan Riva Palacio, Arno Siri-Jégousse

In this article, we present a novel inference framework for estimating the parameters of Continuous-State Branching Processes (CSBPs). We do so by leveraging their subordinator representation. Our method reformulates the estimation problem by shifting the stochastic dynamics to the associated subordinator, enabling a parametric estimation procedure without r

Pramit Bhattacharyya, Arnab Bhattacharya

In this paper, we present a comprehensive corpus-driven analysis of Bangla literary and newspaper texts to investigate their lexical diversity, structural complexity and readability. We undertook Vacaspati and IndicCorp, which are the most extensive literature and newspaper-only corpora for Bangla. We examine key linguistic properties, including the type-tok

William Cocke, Mark L. Lewis, Ryan McCulloch

We consider the M\"obius function on the poset of element centers and obtain some new results regarding centralizers in a $p$-group.

Adam Brček, Ryosuke Hirai, Ilya Mandel, Harmony Lower

Stars spend most of their lifetime on the main sequence (MS), where hydrogen burning establishes the internal chemical structure that governs the subsequent evolution. In massive stars, mass loss through winds and binary interactions can significantly modify this structure during the MS. We present a new MS evolution framework suitable for rapid binary popul

Shicheng Liu, Siyuan Xu, Wenjie Qiu, Hangfan Zhang

A common and effective strategy for humans to improve an unsatisfactory outcome in daily life is to find a cause of this outcome and correct the cause. In this paper, we investigate whether this human improvement strategy can be applied to improving reinforcement learning from human feedback (RLHF) for alignment of language models (LMs). In particular, it is

Naman Balbir Singh Makkar

Recent years have seen significant advances in real-time object detection, with the release of YOLOv10, YOLO11, YOLOv12, and YOLOv13 between 2024 and 2025. This technical report presents the VajraV1 model architecture, which introduces architectural enhancements over existing YOLO-based detectors. VajraV1 combines effective design choices from prior YOLO mod

Isabel Garcia Garcia, Elliot Maderazo

We argue that the electromagnetic $\theta$-term is a physical parameter of the Standard Model coupled to gravity. Specifically, in the context of 4-dimensional Einstein-Maxwell theory we show that there exist Euclidean field configurations that have finite action, are asymptotically flat, and feature non-zero electromagnetic second Chern number. These ``grav

Dandan Hu, Yuan Yuan

In this work, we investigate the dynamical properties of a reaction-diffusion system arising from tumor-therapy modelling that features both nonlinear interactions and nonlocal delay. By applying the Lyapunov-Schmidt reduction, we establish the existence of a nontrivial steady-state solution bifurcating from the trivial solution. In particular, we derive an

G. Battaglia, J. M. Arroyo Polonio, R. Pascale, M. Benito

Unveiling the fundamental nature of non-baryonic dark matter (DM) has profound implications for our understanding of the Universe and of the physical laws that govern it. Its manifestation as an additional source of matter necessary to explain astrophysical and cosmological observations indicates either a breakdown of General Relativity or that the current S

Dylan Bissuel, Léo Orveillon, Benjamin Arrondeau, Paulo Almeida De Mendonça

A computing solution combining the GNU Guix functional package manager with the Apptainer container system is presented. This approach provides fully declarative and reproducible software environments suitable for computational materials science. Its versatility and performance enable the construction of complete frameworks integrating workflow managers such

Jacob Taylor, Haining Pan, Sankar Das Sarma

In unsupervised learning, the training data for deep learning does not come with any labels, thus forcing the algorithm to discover hidden patterns in the data for discerning useful information. This, in principle, could be a powerful tool in identifying topological order since topology does not always manifest in obvious physical ways (e.g., topological sup

R. Pascale, G. Battaglia

Intermediate-mass black holes (IMBHs), with masses between roughly $10^2\,M_\odot$ and $10^5\,M_\odot$, represent a largely uncharted component of the black-hole (BH) population. They are theoretically predicted to form in several early-Universe pathways, including the remnants of massive Population III stars, the runaway collapse of dense stellar clusters,

Jinning Liang, Fangzhou Jiang, Houjun Mo, Andrew Benson

We investigate how galactic disk structures connect to the detailed properties of their host dark-matter halos using the TNG50 simulation. From the hydrodynamic and matched dark-matter-only runs, we measure a comprehensive list of halo properties describing density structure, angular momentum, shape, assembly history, and environment. Using the morphological

Subramanyam Sahoo

Large language models (LLMs) increasingly generate code with minimal human oversight, raising critical concerns about backdoor injection and malicious behavior. We present Cross-Trace Verification Protocol (CTVP), a novel AI control framework that verifies untrusted code-generating models through semantic orbit analysis. Rather than directly executing potent

Kyrill Michaelsen, Felix Tellander

We study the generalized hypergeometric systems, in the sense of Gel'fand, Kapranov, and Zelevinsky, associated with one-loop Feynman integrals, and determine when their rank is independent of space-time dimension and propagator powers. This is equivalent to classifying when the associated affine semigroup ring is Cohen-Macaulay. For massive one-loop integra

Pu Gao, Theodore Morrison

We study the satisfiability threshold and solution-space geometry of random constraint satisfaction problems defined over uniquely extendable (UE) constraints. Motivated by a conjecture of Connamacher and Molloy, we consider random $k$-ary UE-SAT instances in which each constraint function is drawn, according to a certain distribution $\pi$, from a specified

Luca Di Mascolo, Tony Mroczkowski, Joshiwa van Marrewijk, Rémi Adam

Baryons heat to temperatures above $>\!\!10^5\,\mathrm{K}$ as they accrete onto massive overdensities -- galaxies, groups, clusters, and filaments -- where they ionize and become optically transparent. Deep mm-wave observations such as those with ALMA have begun to probe a handful ($\sim\,$4) of massive systems at $z\!\sim\!2-4$, while low-resolution mm-wave

Hiroki Nakabayashi, Hayato Kinkawa, Takano Taira, Naomichi Hatano

It has been shown for various systems that the decay rate of an unstable quantum system deviates from exponential behavior in short- and long-time regimes associated with memory effects. In particular, it is widely believed that in the short-time regime, the decay is quadratic, inducing the quantum Zeno effect, in which the decay is suppressed by rapidly rep

Zhaoyu Bai, Vitor Cardoso, Yifan Chen, Yuyan Li

Ultralight bosons such as axions and dark photons are well-motivated hypothetical particles, whose couplings to ordinary matter can be effectively constrained by stellar cooling. Limits on these interactions can be obtained by demanding that their emission from the stellar interior does not lead to excessive energy loss. An intriguing question is whether the

Bibhushan Shakya

This paper examines frameworks and phenomenology of ultrarelativistic Higgs vacuum bubble collisions in a first-order phase transition associated with the Standard Model Higgs field in the early Universe. Such collisions act as a cosmic scale Higgs collider, providing access to energy scales far beyond any temperature reached in our cosmic history, potential

Lisa Wölfer, Andrés F. Izquierdo, Alice Booth, Stefano Facchini

HD100546 represents a particularly interesting target to study dynamical planet-disk interactions as various features have been observed in both the dust and gas that provide direct and indirect evidence for ongoing planet formation. In this work, we aim to characterize the gas kinematics of five molecular CO emission lines observed with ALMA in HD 100546, t

Sven Wedemeyer, Stefaan Poedts, Stanislav Gunár, Manuela Temmer

Societal dependence on space-based services demands major advances in predicting the impacts of eruptive solar events. Millimeter-wavelength observations offer uniquely direct access to the time-dependent physical conditions in the atmospheric layers of the Sun where these events originate. A facility capable of full-disk, high-cadence, multi-frequency imagi

Darin Jeff, Eytan Modiano

We consider a computation offloading system where jobs are processed sequentially at a local server followed by a higher-capacity cloud server. The system offers two service modes, differing in how the processing is split between the servers. Our goal is to design an optimal policy for assigning jobs to service modes and partitioning server resources in orde

Matthew Bunney, Lucca Marchetti, Domenico Di Sante, Carsten Honerkamp

A third monolayer of tin atoms on the semiconductor substrate Si(111) has been shown to become superconducting upon six to ten percent hole doping. Experiments have reported promising results hinting at a superconducting chiral $d$-wave order parameter. Here we examine Sn/Si(111) by combining most recent ab initio results, quasi-particle interference calcula

Hong Liu

Despite its successes, the large-$N$ holographic dictionary remains incomplete. Key features of gravitational path integrals--most notably Euclidean wormholes and the associated failure of factorization--lack a clear interpretation in the standard large-$N$ framework. A related challenge is the possibility of erratic $N$-dependence in CFT observables, behavi

Siegfried Ludwig, Stylianos Bakas, Konstantinos Barmpas, Georgios Zoumpourlis

Deep learning for decoding EEG signals has gained traction, with many claims to state-of-the-art accuracy. However, despite the convincing benchmark performance, successful translation to real applications is limited. The frequent disconnect between performance on controlled BCI benchmarks and its lack of generalisation to practical settings indicates hidden

Luca Chiantini, Fulvio Gesmundo, Sara Marziali

We determine the Waring rank of homogeneous polynomials of the form $x^ky^kz^k + \ell^{3k}$ where $\ell$ is a linear form. The result is based on the study of the Hilbert function and the resolution of special configurations of points in $\mathbb{P}^2$. As a byproduct of our result, we show that the monomial $x^ky^kz^k$ does not have irredundant decompositio

Yuchan Wang, Sownak Bose, Carlos Frenk, Adrian Jenkins

The internal structure of dark matter haloes encodes their assembly history and offers critical insight into the nature of dark matter and structure formation. Analytical studies and high-resolution simulations have recently predicted the formation of 'prompt cusps' - steep power-law density profiles that emerge rapidly from the monolithic collapse of primor

Alexander Altland, Francisco Divi, Tobias Micklitz, Maedeh Rezaei

Free probability provides a framework for describing correlations between non-commuting observables in complex quantum systems whose Hilbert-space states follow maximum-entropy distributions. We examine the robustness of this framework under a minimal deviation from freeness: the coupling of a single ancilla qubit to a Haar-distributed quantum circuit of dim

Simone Scaringi, Domitilla de Martino, Anna F. Pala, Andrea Sanna

Understanding how mass and angular momentum flow through accretion discs remains a fundamental unsolved problem in astrophysics. Accreting white dwarfs offer an ideal laboratory for addressing this question: their variability occurs on accessible timescales of seconds to minutes, and their optical spectra contain continuum and emission-line components that t

Sujatha Ramakrishnan, Francisco J. Castander, Elizabeth J. Gonzalez, Martin Eriksen

A critical step to create realistic mock catalogs that support large-scale photometric and spectroscopic sky surveys is the production of cosmological simulations that accurately model the survey observables taking into account the redshift-dependent galaxy formation and evolution processes. Here we develop an efficient framework, HOLCon (Halo Optimised Ligh

Jonathan Harper, Taishi Kawamoto, Ryota Maeda, Nanami Nakamura

We extensively explore the connections between time-like entanglement and non-hermitian density matrices in quantum many-body systems. We classify setups where we encounter non-hermitian density matrices into two types: one is due to causal influences under unitary evolutions, and the other is due to non-unitary evolutions in non-hermitian systems. We provid

Partha Konar, Sudipta Show

Freeze-in dark matter has recently garnered significant attention as a promising framework due to its feeble interactions, which are consistent with the null results from dark matter experiments. While previous studies have extensively investigated the production of dark matter through the decay of heavy particles, they overlook the cosmological role of the

Shyam Balaji, Damon Cleaver, Pedro De la Torre Luque

Recent COMPTEL data analysis reveals a $\sim$ 2 MeV continuum excess whose spatial distribution closely matches the long-standing 511 keV line observed by INTEGRAL/SPI, indicating a common population of low-energy positrons that is difficult to reconcile with known astrophysical sources or standard thermal dark matter (DM). We show that a minimal Excited Dar

Victor Rong, Jan Held, Victor Chu, Daniel Rebain

Though Gaussian splatting has achieved impressive results in novel view synthesis, it requires millions of primitives to model highly textured scenes, even when the geometry of the scene is simple. We propose a representation that goes beyond point-based rendering and decouples geometry and appearance in order to achieve a compact representation. We use surf

Wayne J. Chetcuti, Anna Minguzzi, Juan Polo, Luigi Amico

The nodal surfaces of the many-body wavefunction are fundamental geometric features that encode critical information regarding particle statistics and their interaction. Directly probing these structures, particularly in correlated quantum systems, remains a significant experimental challenge. Here, we provide rigorous results on the structure of the many-bo

Piotr Bargiela, Hjalte Frellesvig, Robin Marzucca, Roger Morales

We provide a complete classification of the Feynman-integral geometries at two-loop order in four-dimensional Quantum Field Theory with standard quadratic propagators. Concretely, we consider a finite basis of integrals in the 't Hooft--Veltman scheme, i.e. with $D$-dimensional loop momenta and four-dimensional external momenta, which belong to 79 independen

Hui Yang, Ya-Hui Zhang

The discovery of high-temperature superconductivity in bilayer nickelate La$_{3}$Ni$_{2}$O$_{7}$ necessitates a minimal theoretical model that unifies the superconducting phase with the spin-density-wave (SDW) phase without external pressure or strain. We propose a model where half-filled $d_{z^{2}}$ local moments interact with itinerant $d_{x^{2}-y^{2}}$ el

Ritesh Ghosh, Igor A. Shovkovy

Using first-principles quantum field-theoretical methods, we investigate the shear and bulk viscosities of strongly magnetized relativistic plasmas. The analysis is performed within the weak-coupling approximation and utilizes known results for the fermion damping rates in the Landau-level representation, $\Gamma_{n}(p_{z})$, which are dominated by one-to-tw

Luke Harvey, Kate Maguire, Alexander Holas, Joseph P. Anderson

Appearing as secondary higher-velocity absorption components, high-velocity features (HVFs) have been observed in several absorption lines in many Type Ia supernovae (SNe Ia). The frequency and ubiquity of these components in silicon and calcium features specifically indicates that the mechanism through which they form must be common occurrence among the maj

Yannick Stade, Lukas Burgholzer, Robert Wille

Zoned neutral atom architectures are emerging as a promising platform for large-scale quantum computing. Their growing scale, however, creates a critical need for efficient and automated compilation solutions. Yet, existing methods fail to scale to the thousands of qubits these devices promise. State-of-the-art compilers, in particular, suffer from immense m

Lorenzo Santarelli, Marco Palla, Alessio Mucciarelli, Lorenzo Monaco

We present the chemical abundances of Fe, alpha- and neutron-capture elements in 12 metal-poor Small Magellanic Cloud (SMC) giant stars, observed with the high-resolution spectrographs UVES/VLT and MIKE/Magellan. These stars have [Fe/H] between -2.3 and -1.4 dex, 10 of them with [Fe/H]<-1.8 dex. According to theoretical age-metallicity relations for this gal

Fabian Pichler, Clemens Kuhlenkamp, Michael Knap

Dynamical control of quantum matter is a challenging, yet promising direction for probing strongly correlated states. Motivated by recent experiments in twisted MoTe$_2$ that demonstrated optical control of magnetization, we propose a protocol for probing magnetization dynamics in flat-band ferromagnets. We investigate the nucleation and dynamical growth of

Raniere de Menezes, Francesco Massaro, Elisa Visentin, Federico Di Pierro

The eponymous BL Lac object BL Lacertae is one of the most well-monitored active galactic nuclei, frequently observed from radio to gamma rays. Its relatively soft $\gamma$-ray spectrum peaks near 500~MeV, and since 2020 it has undergone an exceptional series of flaring episodes. The observed emission is well described by synchrotron self-Compton (SSC) model

Gautham N. Sabhahit, Jorick S. Vink, Andreas A. C. Sander

Radiation-driven winds are ubiquitous in massive stars, but in Very Massive Stars (VMSs), mass loss dominates their evolution, chemical yields, and ultimate fate. Theoretical predictions have often relied on extrapolations of O star prescriptions, likely underestimating true VMS mass-loss rates. In the first of a series of papers on VMS wind properties, we i

Audrey Lindsay, Tomasz R. Taylor

We discuss the symmetry aspects of quantum field theory in global four-dimensional de Sitter spacetime linked to $SO(1,4)$ isometries. For the unitary irreducible representations relevant to elementary particles, we obtain explicit transformation laws for the symmetry generators acting on one-particle states in a basis adapted to the $SU(2) \times SU(2)'$ de

B. Bellazzini, J. Berman, G. Isabella, F. Riva

We introduce infrared finite, analytic, crossing symmetric, Regge behaved, and Lorentz invariant amplitudes $\mathcal{M}_{\mathcal {E}}$, labeled by the experimental energy resolution $\mathcal{E}$ for detecting soft photons and gravitons. For $\mathcal{E}$ exponentially smaller than any hard scale, they also satisfy unitarity and their associated cross sect

Lillian Santos-Olmsted, Rebecca K. Leane, Carlos Blanco, John F. Beacom

It was recently shown that standard sub-GeV dark matter candidates can be effectively probed by large neutrino observatories via annual modulation of the total photomultiplier hit rate. That work focused on the production of light by the excitation of scintillator molecules and considered the JUNO detector, surpassing limits from dedicated dark-matter detect

V. Markov, M. Bradač, V. Estrada-Carpenter, G. Desprez

Lyman $\alpha$ emission is highly sensitive to dust and neutral hydrogen and is therefore expected to be strongly suppressed in dusty or gas-rich galaxies during the epoch of reionization (EoR). Nevertheless, numerous moderately dusty Ly$\alpha$ emitters (LAEs) are observed at this epoch, suggesting that complex interstellar medium (ISM) geometries and feedb