November 2025 arXiv papers — page 72

Dilin Wang, Hyunyoung Jung, Tom Monnier, Kihyuk Sohn

We introduce WorldGen, a system that enables the automatic creation of large-scale, interactive 3D worlds directly from text prompts. Our approach transforms natural language descriptions into traversable, fully textured environments that can be immediately explored or edited within standard game engines. By combining LLM-driven scene layout reasoning, proce

Eva Neu, Brian Dillon, Katrin Erk

Intransitive verbs fall into two different syntactic classes, unergatives and unaccusatives. It has long been argued that verbs describing an agentive action are more likely to appear in an unergative syntax, and those describing a telic event to appear in an unaccusative syntax. However, recent work by Kim et al. (2024) found that human ratings for agentivi

Joseph Kim, Saahith Potluri

Evaluating and measuring AI Safety Level (ASL) threats are crucial for guiding stakeholders to implement safeguards that keep risks within acceptable limits. ASL-3+ models present a unique risk in their ability to uplift novice non-state actors, especially in the realm of biosecurity. Existing evaluation metrics, such as LAB-Bench, BioLP-bench, and WMDP, can

Eyad Gad, Zubair Md Fadlullah, Mostafa M. Fouda

In the context of the growing proliferation of user devices and the concurrent surge in data volumes, the complexities arising from the substantial increase in data have posed formidable challenges to conventional machine learning model training. Particularly, this is evident within resource-constrained and security-sensitive environments such as those encou

Johannes Krotz, Ryan G. McClarren

We present a hybrid method for time-dependent particle transport that combines Monte Carlo (MC) estimation with a deterministic discrete ordinates (\(S_N\)) solve, augmented by quasi-Monte Carlo (QMC) sampling. For spatial discretizations, the MC component computes a piecewise-constant (cell-averaged) solution, while the \(S_N\) stage employs bilinear discon

Bo Yang, Jianke Yang

Spatially-bounded rogue waves, i.e., rogue waves that arise in a limited region of a multi-dimensional space, are interesting and important from both theoretical and applied points of view. In this paper, we determine spatially-bounded rogue waves in the Davey-Stewartson I equation. We show that these rogue waves can be obtained when a single or multiple int

Arash Omidi, Tanmay Mishra, Mads R. Almassalkhi

This paper presents a hybrid energy system (HES) experimental testbed developed at the University of Vermont, featuring a dual-site architecture that integrates on-campus laboratory facility with an off-campus solar and meteorological station. This supports the prototyping and validation of advanced HES control and optimization strategies. The platform integ

Carola Ciaramelletti, Daniel Arrufat-Vicente, Simone Paganelli, Nicolo Defenu

We study the temporal behavior of topological quantum fluids with strong long-range couplings under slow external perturbations, whose rate $\delta$ approaches the quasi-static limit $\delta\to 0$. As expected, due to strong long-range interactions, the system lies in the mean-field universality and the density of defects for drives across the quantum critic

Carl Pomerance, Andreas Weingartner

A famous conjecture of Erd\H os and Straus is that for every integer $n\ge2$, $4/n$ can be represented as $1/x+1/y+1/z$, where $x,y,z$ are positive integers. This conjecture was generalized to $5/n$ by Sierpi\'nski, and then Schinzel conjectured that for every integer $m\ge4$ there is a bound $n_m$ such that the fraction $m/n$ is the sum of 3 unit fractions

Lekha Patel, Craig Ulmer, Stephen J. Verzi, Daniel J. Krofcheck

The estimation of explosive yield from heterogeneous observational data presents fundamental challenges in inverse problems, particularly when combining traditional physical measurements with modern artificial intelligence-interpreted modalities. We present a novel Bayesian fractional posterior framework that fuses seismic waves, crater dimensions, synthetic

Silvia Rondini, Claudia Alvarez-Martin, Paula Angermair-Barkai, Olivier Penacchio

While recent research suggests Large Language Models match human creative performance in divergent thinking tasks, visual creativity remains underexplored. This study compared image generation in human participants (Visual Artists and Non Artists) and using an image generation AI model (two prompting conditions with varying human input: high for Human Inspir

Madalyn F. Chapleski, Yifan Zhou

The L/T transition is a critical evolutionary stage for brown dwarfs and self-luminous giant planets. L/T transition brown dwarfs are more likely to be spectroscopically variable, and their high-amplitude variability probes distributions in their clouds and chemical makeup. This paper presents Hubble Space Telescope Wide Field Camera 3 spectral time series d

Steven van den Broek, Marc van Kreveld, Wouter Meulemans, Arjen Simons

A linked bar chart is the augmentation of a traditional bar chart where each bar is partitioned into blocks and pairs of blocks are linked using orthogonal lines that pass over intermediate bars. The order of the blocks readily influences the legibility of the links. We study the algorithmic problem of minimizing the vertical length of these links, for a fix

Michael Carl, Takanori Mizowaki, Aishvarya Raj, Masaru Yamada

Building on the Extended Mind (EM) theory and radical enactivism, this article suggests an alternative to representation-based models of the mind. We lay out a novel ABC framework of the translating mind, in which translation is not the manipulation of static interlingual correspondences but an enacted activity, dynamically integrating affective, behavioral,

Lachlan G. M. Rooney, Siân E. Dutton, Nicola D. Kelly

Lanthanide borates are widely studied for their optical and magnetic properties. A wide variety of structures are known with 3, 2, 1 and 0 dimensional connectivity of lanthanide ions. Here, we explore Mg$Ln$B$_5$O$_{10}$, with a quasi-1D arrangement of the $Ln$ ions. Polycrystalline samples of Mg$Ln$B$_5$O$_{10}$ ($Ln$ = La, Pr, Nd, Sm--Er) were synthesised

Noah Caplinger, Daniel N. Levitin

Horocyclic products are a well-studied class of metric spaces that provide models for various solvable Lie groups, Baumslag-Solitar groups, and Lamplighter groups. Let $G$ act geometrically on a horocyclic product $X \bowtie Y$ of $\CAT(-\kappa)$ spaces $X,Y$. We show that every such group is either an ascending HNN extension of a finitely-generated virtuall

Rachel Yovel, Yunhui He, Eran Treister

We present an improved multigrid preconditioner for the acoustic Helmholtz equation with enhanced scalability. Standard multigrid fails to converge for the Helmholtz equation, and the well-known complex shifted Laplacian method overcomes it by adding a complex shift and using the shifted system as a preconditioner. However, the added complex shift grows with

Xiatao Sun, Chen Liang, Qian Wang, Daniel Rakita

3D meshes are a critical building block for applications ranging from industrial design and gaming to simulation and robotics. Traditionally, meshes are crafted manually by artists, a process that is time-intensive and difficult to scale. To automate and accelerate this asset creation, autoregressive models have emerged as a powerful paradigm for artistic me

Radha Kumaran, You-Jin Kim, Emily Machniak, Shane Dirksen

Augmented reality (AR) allows virtual information to be presented in the real world, providing support for numerous tasks including search and navigation. Allowing users access to multiple navigation aids may help leverage the benefits of different navigational guidance methods, but may also have negative perceptual and cognitive impacts. In this study, user

Marek Adamczyk, Michał Dąbrowski

We study a systematic approach to a popular Statistical Arbitrage technique: Pairs Trading. Instead of relying on two highly correlated assets, we replace the second asset with a replication of the first using risk factor representations. These factors are obtained through Principal Components Analysis (PCA), exchange traded funds (ETFs), and, as our main co

Scotty Tilton

We prove that the boundary Dehn twist on $K3\#K3\setminus B^4$ is nontrivial in the smooth mapping class group, providing another example of an exotic diffeomorphism on a simply-connected spin four-manifold. We do so by finding an algebraic criterion that must be satisfied if the two maps are smoothly isotopic. The main tools involved are the $\Pintwo$-equiv

Giuseppe Carrino, Elena Loli Piccolomini, Elisa Riccietti, Theo Mary

Minimizing loss functions is central to machine-learning training. Although first-order methods dominate practical applications, higher-order techniques such as Newton's method can deliver greater accuracy and faster convergence, yet are often avoided due to their computational cost. This work analyzes the impact of finite-precision arithmetic on Newton step

Abdelmalek Boumali

This paper investigates the scattering states of spin-1/2 particles in the spacetime of a spinning cosmic string with spacelike disclination and dislocation, with and without a Coulomb interaction. Working within the tetrad formalism, we solve the Dirac equation for several configurations of the angular momentum density $J_t$ and the torsion parameter $J_z$

Simone De Reggi, Andrea Pugliese, Mattia Sensi, Cinzia Soresina

We investigate a model for a mosquito-borne epidemic in which human hosts may adopt protective behaviour against vector bites in response to information on both past and current disease prevalence. Assuming that mosquitoes can also feed on non-competent hosts (i.e.\ hosts that do not contribute to disease transmission), we first revisit existing results and

Johor D. Peñalba Quispitupa, Guillermo F. Quispe Peña, Jose T. Galvez Ghersi

In previous work, we developed a method for computing two-point correlators by decomposing the mode degrees of freedom into fast and slow components. Building on this framework, we present a numerical implementation to study the evolution of primordial scalar perturbations under controlled state deformations induced by the simplest environment corrections fr

Emily H. Dickey, Noah A. Rosenberg

In mathematical phylogenetics, labeled histories describe the sequences by which sets of labeled lineages coalesce to a shared ancestral lineage. We study labeled histories for at-most-$r$-furcating trees. Consider a rooted leaf-labeled tree in which internal nodes each have $i$ offspring, and $i$ is permitted to range from 2 to $r$ across internal nodes, fo

Thomas Philippe, Yijian Wu, Aymane Graini

Molecular dynamics simulations are widely used to investigate nucleation in first-order phase transitions. Brute-force simulations, though popular, are limited to conditions of high metastability, where the critical cluster and the nucleation barrier are small. The seeding method has recently emerged as a powerful alternative for exploring lower supersaturat

Carolina Gallardo-Pavesi, Yaime Fernández, Javier E. Soto, Cecilia Hernández

Identifying the largest K flows in network traffic is an important task for applications such as flow scheduling and anomaly detection, which aim to improve network efficiency and security. However, accurately estimating flow frequencies is challenging due to the large number of flows and increasing network speeds. Hardware accelerators are often used in thi

Liuyuan Jiang, Quan Xiao, Lisha Chen, Tianyi Chen

Penalty-based methods have become popular for solving bilevel optimization (BLO) problems, thanks to their effective first-order nature. However, they often require inner-loop iterations to solve the lower-level (LL) problem and small outer-loop step sizes to handle the increased smoothness induced by large penalty terms, leading to suboptimal complexity. Th

Ehsan Ahmed Dhrubo, Mohammad Mahmudul Alam, Edward Raff, Tim Oates

Multiple Instance Learning (MIL) tasks impose a strict logical constraint: a bag is labeled positive if and only if at least one instance within it is positive. While this iff constraint aligns with many real-world applications, recent work has shown that most deep learning-based MIL approaches violate it, leading to inflated performance metrics and poor gen

Victor Sanchez, Sawyer Remillard, Bachir A. Abeid, Lehu Bu

The high-fidelity characterization of soft, tissue-like materials under ultra-high-strain-rate conditions is critical in engineering and medicine. Still, it remains challenging due to limited optical access, sensitivity to initial conditions, and experimental variability. Microcavitation techniques (e.g., laser-induced microcavitation) have emerged as a viab

Preyas S. Desai, Jessie Liu

Businesses often react to external events by sending pro-social messages on social media that show the sender's alignment with the underlying prosocial cause and enhance their brand image. Consumers are uncertain about the authenticity of such messages because a company can choose to send prosocial messages even when their alignment with the social cause is

Mona Khalil, Alberto Blanco-Justicia, Najeeb Jebreel, Josep Domingo-Ferrer

Membership inference attacks (MIAs) against machine learning (ML) models aim to determine whether a given data point was part of the model training data. These attacks may pose significant privacy risks to individuals whose sensitive data were used for training, which motivates the use of defenses such as differential privacy, often at the cost of high accur

Joseph M. Jones, M. W. Long

The Baker-Campbell-Hausdorff formula was recently resummed exactly in one variable, and left as a power series in the other (Moodie and Long 2021 J. Phys. A: Math. Theor. 54 015208). The coefficients of the power series were provided as a sum of products of three hyperbolic functions that are analogous to the familiar commutator expansion. We find a new form

Félix del Teso, David Gómez-Castro

This article provides an accessible introduction to fractional derivatives, a concept that extends classical calculus by allowing derivatives of non-integer order. It explores both the fundamental definitions and some of the most relevant properties and applications of this mathematical tool. It was originally published in Spanish in the Gaceta de la Real So

Homer Dávila Gutiérrez

We present a comprehensive analysis of Solar Cycle 25 aimed at precisely constraining the interval of its activity maximum using multiple observational parameters: sunspot number (SSN), Wolf number, the 10.7 cm solar radio flux (F10.7), the occurrence rate and speed of coronal mass ejections (CMEs), the statistics of X-ray flares, and the reversal of the glo

Hossain Shaikh Saadi, Faria Alam, Mario Sanz-Guerrero, Minh Duc Bui

This paper presents JGU Mainz's winning system for the BLP-2025 Shared Task on Code Generation from Bangla Instructions. We propose a multi-agent-based pipeline. First, a code-generation agent produces an initial solution from the input instruction. The candidate program is then executed against the provided unit tests (pytest-style, assert-based). Only the

Yaoxin Yang, Peng Ye, Xudong Tan, Chongjun Tu

Multimodal large language models suffer from substantial inference overhead since multimodal KV Cache grows proportionally with the visual input length. Existing multimodal KV Cache compression methods mostly rely on attention score to reduce cache size, which makes them are incompatible with established efficient attention kernels (e.g., FlashAttention) and

Rafael Wagner

In this thesis, we explore the intersection of two fundamental subfields of quantum information theory: quantum coherence and contextuality. Despite their apparent differences, both areas address key issues relevant to the foundations and applications of quantum theory. By developing a novel graph-theoretic approach, extending a framework recently introduced

Ahmed Shaikh, Phanibhusan Singha Mahapatra, Eva Y. Andrei

Though research on graphene by itself has waned, the interest in moire materials, materials made with stacked layers of graphene with a rotational twist between the layers, has exploded in popularity. These layered devices show a key feature, flat bands. Flat bands localize electrons, which in turn leads to the expression of correlated states such as Mott in

Chen Liang, Jiawen Zheng, Yufeng Zeng, Yi Tan

This paper introduces Generative Augmented Reality (GAR) as a next-generation paradigm that reframes augmentation as a process of world re-synthesis rather than world composition by a conventional AR engine. GAR replaces the conventional AR engine's multi-stage modules with a unified generative backbone, where environmental sensing, virtual content, and inte

Ross Griebenow

We describe a construction of invariant train tracks with irreducible transition matrix for pseudo-Anosov homeomorphisms. This fills what seems to be a gap in the literature concerning the existence of such train tracks. The construction starts with an invariant train track associated to the veering triangulation of the mapping torus of the homeomorphism and

T. Jarmuzek, R. Gore

We set out a general methodology for producing tableau systems for propositional logics via a tableau metatheory that provides general and formal notions for different tableau systems that vary by semantics or formulae. Moreover, by dint of these general notions, some facts, independent of their applications to a particular propositional logic, can be proved

Robert J. S Airey, Paul Chote, James A. Blake, James McCormac

Active debris removal techniques are posed to become an important tool in maintaining the safety of the near-Earth space environment. These techniques rely on a clear understanding of the rotational motion of the debris targets, which is challenging to constrain from unresolved imaging. The Ajisai satellite provides an ideal test case for developing and demo

K. I. Kellermann

The NRAO 59th Karl Jansky Lecture was presented on 24 October 2024, 22 November 2024, and 4 December 2024 in Charlottesville, Virginia, Socorro, New Mexico, and Green Bank, West Virginia, respectively. The lecture covered the circumstances of the author's start in radio astronomy, the demographics of radio astronomers, discussions of the outstanding, mostly

Yating Ren, Yikun Ban, Huobin Tan

Recently, structure-text contrastive learning has shown promising performance on text-attributed graphs by leveraging the complementary strengths of graph neural networks and language models. However, existing methods typically rely on homophily assumptions in similarity estimation and hard optimization objectives, which limit their applicability to heteroph

Ali Tehranian, Jordan Budhu, Casey Perkowski, Lance Sookdeo

A hemispherical multilayer wide-band (7-13 GHz) band-pass frequency selective surface (FSS) is reported. A new design technique based on a Goldberg discretization and unit cell scaling technique is introduced to accommodate the curved profile of the FSS. The FSS is additively manufactured by sequentially printing dielectric layers and metallic patterns until

Yuhao Wang, Yao Hao, Hongyu An, H Michael Gach

Stereotactic Arrhythmia Radiotherapy (STAR) treats ventricular tachycardia (VT) but requires internal target volume (ITV) expansions to compensate for cardiorespiratory motion. Current clinical r4DCT imaging methods are limited, and the reconstructed r4DCTs suffer from unmanaged cardiac motion artifacts that affect the quantitative assessment of respiratory

Jan Kára, Liliana Rivera Sandoval, Wendy Mendoza, Thomas J. Maccarone

AM CVn stars are ultra-compact semi-detached binaries consisting of a white dwarf primary and a hydrogen-depleted secondary. In this paper we present spectroscopic and photometric results of 15 transient sources pre-classified as AM CVn candidates. Our analysis confirms 9 systems of the type AM CVn, 3 hydrogen-rich cataclysmic variables (accreting white dwar

Daanish Aleem Qureshi, Rafay Chaudhary, Kok Seng Tan, Or Maoz

As digital communication grows in importance when connecting with healthcare providers, traditional behavioral and content message features are imbued with renewed significance. If one is to meaningfully connect with them, it is crucial to understand what drives them to engage and respond. In this study, the authors analyzed several million text messages sen

Yunhan Mou, Fan Li, Denise Esserman, Yuan Huang

Composite endpoints are widely used in cardiovascular clinical trials to improve statistical efficiency while preserving clinical relevance. The Win Ratio (WR) measure and more general frameworks of Win Statistics have emerged as increasingly popular alternatives to traditional time-to-first-event analyses. Although analytic sample size formulas for WR have

Jordi A. Montañà-López, Andreas Elben, Joonhee Choi, Rahul Trivedi

As quantum simulators are scaled up to larger system sizes and lower noise rates, non-Markovian noise channels are expected to become dominant. While provably efficient protocols for Markovian models of quantum simulators, either closed system models (described by a Hamiltonian) or open system models (described by a Lindbladian), have been developed, it rema

Le-Chris Wang, Zafar Rustamkulov, David K. Sing, Joshua Lothringer

We conduct a reanalysis of the JWST NIRISS/SOSS observation of the hot-Saturn WASP-96 b. Initial analysis of this data revealed an enhanced Rayleigh scattering slope at the blue end of the transmission spectrum, suggesting the presence of hazes at high altitudes. In this work, we report non-detection of this slope, confirming an atmosphere clear of high-alti

Thomas Y. Adams, Bruce Barrios, Michael Ziegenfus, Hui Cai

Metal halide perovskites continue to lead in optoelectronic applications, but the toxicity of lead has driven efforts to identify environmentally benign alternatives. Cesium tin iodide is one such, with a direct bandgap and near-infrared emission, though its performance is limited by instability. We show that phthalimide (PTM) passivation during single cryst

Johan Sebastián Galindez-Acosta, Juan José Giraldo-Huertas

This study explores the dynamics of trust in artificial intelligence (AI) agents, particularly large language models (LLMs), by introducing the concept of "deferred trust", a cognitive mechanism where distrust in human agents redirects reliance toward AI perceived as more neutral or competent. Drawing on frameworks from social psychology and technology accep

Haotian Xu, Yuning You, Tengfei Ma

Graphs provide a unified representation of semantic content and relational structure, making them a natural fit for domains such as molecular modeling, citation networks, and social graphs. Meanwhile, large language models (LLMs) have excelled at understanding natural language and integrating cross-modal signals, sparking interest in their potential for grap

Kohei Tsujio, Mohammad Abdullah Al Faruque, Yasser Shoukry

Detecting kinetic vulnerabilities in Cyber-Physical Systems (CPS), vulnerabilities in control code that can precipitate hazardous physical consequences, is a critical challenge. This task is complicated by the need to analyze the intricate coupling between complex software behavior and the system's physical dynamics. Furthermore, the periodic execution of co

Seth Gagnon, Yichao Lin, Alexander Lange, Hui Yang

We present multi-wavelength analysis of 1LHAASO J1740+0948u and its surroundings including the pulsar wind nebula of middle-aged pulsar PSR J1740+1000. Although a dozen X-ray sources are found within the UHE emission site, careful analysis shows that they are unlikely to produce the observed UHE emission. The most likely particle accelerator is pulsar J1740+

Bogdan Norkin, Vladimir Norkin

The paper considers the problems of optimal vaccination control in the classical SIR model under constraints on the resource capabilities of the insurance medical system, in particular under constraints on the possible absolute rate of vaccination of the population and the limitation on the available number of vaccines. The application of classical optimal c

Mohamed Amin Loualidi, Salah Nasri, Maximiliano A. Rivera

This study presents a radiative three-loop model for neutrino mass generation, employing an asymmetric Yukawa coupling between two new scalar $SU(2)_L$ doublets and vectorlike lepton doublets. Dark matter candidates arise from one of the scalar doublets and contribute to neutrino mass generation through the mass splitting between its neutral components. The

L. V. Da Conceição, W. LF. Marcolino, V. Maria

The radiation field of central stars of planetary nebulae (CSPNe) is crucial for determining the physical conditions of planetary nebulae (PNe). Many studies in the literature model PNe using the blackbody approximation (bb) or plane-parallel (p-p) atmospheres as the ionizing source. However, these approaches become inconsistent when the central star is a Wo

Eric Vansteenberhge

We present the Pioneer Detection Method, a supervisory tool we developed to enhance resilience in insurance markets facing the challenges posed by climate change. Based on a theoretical model of the insurance industry, we consider a scenario in which independent experts determine premiums according to their individual risk assessments. Due to the segmented n

Isiah M. Holt, M. Coleman Miller, Alexander J. Dittmann, Frederick K. Lamb

Accurate and precise measurements of neutron star radii provide invaluable information about the cold, dense matter in neutron star cores. Analyses of synthetic X-ray pulse waveform data similar to the data obtained from non-accreting neutron stars using the Neutron star Interior Composition Explorer (NICER) have indicated that mass and radius estimates made

Ana Senkić, Rachael Keneipp, Petra Ivatović, Namrata Pradeep

Controlling the crystal phase of two-dimensional (2D) transition metal dichalcogenides (TMDs) is essential for tailoring their optical and electronic properties. While phase transitions in monolayer TMDs and semiconductor-to-metal conversions have been widely studied, structural transitions between semiconducting polytypes - particularly in bilayer (2L) syst

Luis M. Moreno-Ramírez, Luis Sánchez-Tejerina, Óscar Alejos, Victorino Franco

The usefulness of modeling magnetocaloric materials expands from the understanding of their behavior to the prediction of new materials, playing a fundamental role in the optimization of their performance. In contrast with other areas of magnetic materials research, micromagnetic simulations of magnetocaloric materials are scarce due to the difficulty of mod

David Calvert, Michael Redle, Bibek Gautam, Charles J. Stapleford

It is understood in a general sense that turbulent fluid motion below the shock front in a core-collapse supernova stiffens the effective equation of state of the fluid and aids in the revival of the explosion. However, when one wishes to be precise and quantify the amount of turbulence in a supernova simulation, one immediately encounters the problem that t

Douglas P. Finkbeiner, Joshua S. Speagle, Tanveer Karim

Spectral data reduction pipelines deal with a wide variety of challenges including masking cosmic rays, calibrating wavelength solutions, and estimating background noise while trying to remain model-agnostic. Traditional methods rely on hardware-specific code or pre-calculated stellar model templates to solve this problem, making them model-dependent and not

Martina Torsello, Marcella Massardi, Elisabetta Liuzzo, Gayathri Gururajan

We present ViSta, a Visibility Stacking method to combine interferometric observations in the Fourier domain at radio to sub-millimeter wavelengths for galaxies. The goal of our method is to maximize the exploitation of available archival interferometric data. By stacking visibilities of galaxies with secure spectroscopic redshifts directly in the Fourier do

Beryl Hovis-Afflerbach, Allison L. Strom, Alberto Saldana-Lopez, Sophia R. Flury

Our understanding of massive stars remains incomplete. Many high-z galaxies and nearby analogs exhibit strong He II emission, indicating an abundance of photons with energies >54.4 eV that standard single-star population models cannot explain. Recent studies show that binary evolution and non-solar abundance patterns are required to explain the distinct spec

Henry Shao, Kasidis Arunruangsirilert

Demands for uplink on mobile networks are increasing with the rapid development of social media platforms, 4K/8K content creation, IoT applications, and Fixed Wireless Access (FWA) broadband. As a result, Uplink MIMO (UL-MIMO) and Uplink Carrier Aggregation (UL-CA) have been widely deployed for the first time on commercial 5G networks. UL-MIMO enables the tr

Miquel Llorens-Monteagudo, Alejandro Torres-Forné, José A. Font

Deep-learning methods are becoming increasingly important in gravitational-wave data analysis, yet their performance often relies on large training datasets and models whose internal representations are difficult to interpret. Sparse dictionary learning (SDL) offers a complementary approach: it performs well in scarce-data regimes and yields physically inter

Shivani Harer, Maxime Vincent, Hubert Halloin, Ouali Acef

The Laser Interferometer Space Antenna (LISA) observatory is a future L3 mission of the European Space Agency (ESA) to detect gravitational waves, set to launch in 2035. The detector constellation will conduct interferometry to picometer stability over an unprecedented arm length of 2.5 million km. In this paper, we present the development and testing result

Andrea Placidi, Luca Sebastiani, Gianluca Grignani

We derive the gauge-general expressions of the two gyro-gravitomagnetic functions entering the spin-orbit sector of the effective-one-body (EOB) Hamiltonian up to the fifth-and-half post-Newtonian (5.5PN) order. Our results include both local and nonlocal-in-time contributions, providing the most general analytical formulation of the linear-in-spin conservat

Thomas R. Beauchamp, Scarlett Gauthier, Stephanie Wehner

The aim of a quantum network is to enable the generation of end-to-end entangled links between end nodes of the network, so that they can execute quantum network applications. To facilitate this, it is desirable to have robust control of the network in order to be able to provide a reliable service to the end nodes. In recent work arXiv:2503.12582, we propos

C. Yamila Yaryura, Mario G. Abadi, Noam I. Libeskind, Stefan Gottlöber

The intrinsic properties of galaxies are influenced by their environments, underscoring the environment's critical role in galaxy formation and evolution. Traditionally, these environments are categorized into four fixed classifications: knots, filaments, walls, and voids, which collectively describe the complex organization of galaxies within large-scale st

Adeel Yousaf, Joseph Fioresi, James Beetham, Amrit Singh Bedi

Improving the safety of vision-language models like CLIP via fine-tuning often comes at a steep price, causing significant drops in their generalization performance. We find this trade-off stems from rigid alignment strategies that force unsafe concepts toward single, predefined safe targets, disrupting the model's learned semantic structure. To address this

Samuel Frank, James Halverson, Anindita Maiti, Fabian Ruehle

We introduce fermionic neural network field theories via Grassmann-valued neural networks. Free theories are obtained by a generalization of the Central Limit Theorem to Grassmann variables. This enables the realization of the free Dirac spinor at infinite width and a four fermion interaction at finite width. Yukawa couplings are introduced by breaking the s

Johan Henriksson, Stefanos R. Kousvos, Jasper Roosmale Nepveu

The renormalization of composite operators is a fundamental aspect of quantum field theory, relevant for the description of phase transitions and high energy phenomenology. We calculate the anomalous dimensions of a large set of operators in any scalar $\phi^4$ theory in $d=4-\varepsilon$ dimensions, up to five loops in most cases. The results have applicati

Kevin J. Joven, Elin Ranjan Das, Joel Bierman, Aishwarya Majumdar

Significant developments made in quantum hardware and error correction recently have been driving quantum computing towards practical utility. However, gaps remain between abstract quantum algorithmic development and practical applications in computational sciences. In this Perspective article, we propose several properties that scalable quantum computationa

M. Leemker, S. Facchini, P. Curone, L. Rampinelli

Water is one of the central molecules for the formation and habitability of planets. In particular, the region where water freezes-out, the water snowline, could be a favorable location to form planets in protoplanetary disks. We use high resolution ALMA observations to spatially resolve H$_2$O, H$^{13}$CO$^+$ and SO emission in the HL Tau disk. A rotational

David Wierichs, Korbinian Kottmann, Nathan Killoran

We present quantum circuits with a brick wall structure using the optimal number of parameters and two-qubit gates to parametrize $SU(2^n)$, and provide evidence that these circuits are universal for $n\leq 5$. For this, we successfully compile random matrices to the presented circuits and show that their Jacobian has full rank almost everywhere in the domai

An Le, Christopher L. Baldwin

Adiabatic reverse annealing (ARA) is an improvement to conventional quantum annealing (QA) that uses an initial guess at the desired ground state to circumvent problematic phase transitions. Despite encouraging results in the closed-system setting, Ref. [1] has suggested on the basis of numerical simulations that ARA may lose its advantage in the presence of

Luigi Zallio, Giovanni P. Rosotti, Miguel Vioque, Anna Miotello

We present measurements of key protoplanetary disk properties inferred from parametric models of ALMA 12CO spectral line visibilities. We derive gas-disk radii, integrated fluxes, optically thick emission layers, and brightness temperature profiles for the disk population of the old (4 - 14 Myr) Upper Scorpius star-forming region. We measure CO emission size

Ivanna Langan, Gergö Popping, Michele Ginolfi, Simon Weng

The flow of baryons in and out of galaxies is the primary driver for galaxy evolution. In addition to depleting the gas reservoir of galaxies, outflows also enrich their circumgalactic medium (CGM) with processed gas -- which can further impact the next stages of gas accretion, resulting in the presence of molecular gas beyond the stellar component of galaxi

So Chigusa, Masashi Hazumi, Ernst David Herbschleb, Yuichiro Matsuzaki

The excellent sensitivities of quantum sensors are a double-edged sword: minuscule quantities can be observed, but any undesired signal acts as noise. This is challenging when detecting quantities that are obscured by such noise. Decoupling sequences improve coherence times and hence sensitivities, though only AC signals in narrow frequency bands are disting

Vijay Balasubramanian, Hanzhi Jiang, Simon F. Ross

We study the real-time dynamics of multi-party entanglement signals in chaotic quantum many-body systems including but not necessarily restricted to holographic conformal field theories. We find that scrambling dynamics generates multiparty entanglement with rich structure including: (a) qualitatively different dynamical behaviours for different signals, lik

Mario G. Abadi, Gabriela Castelletti, Namir E. Kassim

The radio continuum spectra of pulsars (PSRs) exhibit a wide variety of shapes, that are interpreted as pure and broken power laws, power laws with turnovers or cut-offs, and logarithmic-parabolic profiles. A notable fraction of these have well-defined power laws with $\nu^{-2.1}$ exponential turnovers, indicative of free-free thermal absorption along the li

Benedikt Wilde, Mohamad Kazouini, Timo Kern, Kevin Uhl

The development of nonlinear and frequency-tunable superconducting microwave circuits for operation in large magnetic fields is of high relevance for hybrid quantum systems such as spin resonance spectrometers, microwave quantum magnonics, dark matter axion detectors or flux-mediated optomechanics. With these exciting perspectives in mind, we investigate nio

Haonan Zheng, Fangzhou Jiang, Shihong Liao, Noam I. Libeskind

We present our investigation of HI-rich 'Dark' galaxiEs in Simulations (HIDES), specifically using the Hestia and Auriga simulations in this work. We select galaxies that are faint ($M_g > -10$) and contain sufficient HI ($M_\mathrm{HI} > 10^5\,M_\odot$), and identify 89 such objects, only one of which is completely starless. Their demographics generally con

Luca Brunelli

A novel mechanism to produce a cosmic network of fundamental superstrings based on a time-varying string tension has been recently proposed. It has been found that fundamental superstrings can grow in a kinating background driven by the rolling of the volume modulus of Type IIB string compactifications towards the minimum of its potential. In this talk, I wi

Nothando Khumalo, Aman Mehta, William Munizzi, Prineha Narang

We present a machine learning framework to study the dynamics of entropy vectors and quantum resources, including entanglement and magic, focusing on violations of entropy inequalities. Using a reinforcement learning agent formulated as a Markov decision process, we identify quantum circuits that optimally navigate the entropy vector space to generate violat

Melissa van Beekveld, Luca Buonocore, Silvia Ferrario Ravasio, Pier Francesco Monni

We introduce a class of collider observables, named Lund-Tree Shapes (LTS), defined from declustering trees originating from the Lund jet plane representation of the QCD radiation pattern in multi-jet scattering processes. At the differential level, they are continuous global variables akin classical event shapes and $n\to n+1$ jet-resolution parameters, whi

Frances E. Rigby, Nikku Madhusudhan

Sub-Neptune planets, with no analogue in our solar system, provide a wealth of information about exoplanet diversity, formation & evolution, and habitability. Their robust characterisation requires the coupling of physically informed atmosphere and interior models with precise atmospheric data to break compositional degeneracies. Recent JWST observations of

Saavanth Velury, Yuxuan Wang

We propose a momentum-space based variational quantum eigensolver (VQE) framework for simulating quasiparticle excitations in interacting quantum many-body systems on near-term quantum devices. Leveraging translational invariance and other symmetries of the Hamiltonian, we reconstruct the momentum-resolved quasiparticle excitation spectrum through targeted s

Mark Gorski, Lena Murchikova

Carbon monoxide (CO) emission is a widely used tracer of molecular hydrogen (H$_2$) in the interstellar medium (ISM), owing to its abundance, low excitation energy, and ease of detection in cold molecular environments, in contrast to $\mathrm{H}_2$ itself. While the CO-to-$\mathrm{H}_2$ conversion factor is often assumed to be constant across the disks of ga

George Cazenavette, Antonio Torralba, Vincent Sitzmann

The task of dataset distillation aims to find a small set of synthetic images such that training a model on them reproduces the performance of the same model trained on a much larger dataset of real samples. Existing distillation methods focus on synthesizing datasets that enable training randomly initialized models. In contrast, state-of-the-art vision appr

Nicolas Carion, Laura Gustafson, Yuan-Ting Hu, Shoubhik Debnath

We present Segment Anything Model (SAM) 3, a unified model that detects, segments, and tracks objects in images and videos based on concept prompts, which we define as either short noun phrases (e.g., "yellow school bus"), image exemplars, or a combination of both. Promptable Concept Segmentation (PCS) takes such prompts and returns segmentation masks and un

Jing Wen, Alexander G. Schwing, Shenlong Wang

We tackle the task of recovering an animatable 3D human avatar from a single or a sparse set of images. For this task, beyond a set of images, many prior state-of-the-art methods use accurate "ground-truth" camera poses and human poses as input to guide reconstruction at test-time. We show that pose-dependent reconstruction degrades results significantly if

Ziyu Guo, Renrui Zhang, Hongyu Li, Manyuan Zhang

Recent advances in visual generation have increasingly explored the integration of reasoning capabilities. They incorporate textual reasoning, i.e., think, either before (as pre-planning) or after (as post-refinement) the generation process, yet they lack on-the-fly multimodal interaction during the generation itself. In this preliminary study, we introduce

Chenyu Lin, Cheng Chi, Jinlin Wu, Sharon Li

When faced with complex problems, we tend to engage in slower, more deliberate thinking. In contrast, for simple questions we give quick, intuitive responses. This dual-system thinking approach allows us to allocate cognitive resources efficiently, reserving deeper analytical effort for tasks that truly require it. However, existing reasoning-oriented visual