November 2025 arXiv papers — page 80

Zoha Laraib, Sherwood Richers

Neutrino flavor evolution in dense astrophysical environments is inherently nonlinear and sensitive to many-body (MB) quantum effects beyond the mean-field (MF) approximation. Existing MB studies are constrained by small system sizes, closed boundaries, and highly idealized symmetry assumptions. We present a unified tensor-network framework that enables simu

Zhi-Jie Liu, Hao-Nan Qiang, Jie Zhou, Mi Xie

The $W$ state, a canonical representative of multipartite quantum entanglement, plays a crucial role in quantum information science due to its robust entanglement properties. Quantum uncertainty relations, on the other hand, are a fundamental cornerstone of quantum mechanics. This paper introduces a novel approach to Identifying tripartite $W$ states by leve

V. E. Timofeev, D. A. Bedyaev, D. N. Aristov

The band structure of elementary excitations of skyrmion crystal in thin ferromagnetic film with Dzyaloshinskii-Moriya interaction and uniaxial magnetic anisotropy under external magnetic field is studied. In the absence of anisotropy there is a topological transition in the spectrum of skyrmion crystal: the gap between breathing and counter-clock-wise modes

Abhishek Mandal, Joy Ghosh, Maruthi Manoj Brundavanam, Shailendra K Varshney

In this work, we investigate the emergence and control of genuine tripartite entanglement in a hybrid cavity quantum electrodynamics architecture consisting of two linearly coupled single mode resonators, one of which interacts coherently with a two level atom. An analytical framework is developed in a weak driving regime, where the system dynamically suppor

Lasse Hohmeyer, Mihaela Popescu, Ivan Bergonzani, Dennis Mronga

Humanoid robots have great potential for a wide range of applications, including industrial and domestic use, healthcare, and search and rescue missions. However, bipedal locomotion in different environments is still a challenge when it comes to performing stable and dynamic movements. This is where state estimation plays a crucial role, providing fast and a

Bernhard Heim, Johann Stumpenhusen

The Lehmer conjecture states that the non-constant Fourier coefficients of the 24th power of the Dedekind eta function are non-zero. In a recent preprint, Neuhauser and the first author exploited an easily accessible tool from algebraic number theory, namely the Dedekind--Kummer Theorem, to prove the non-vanishing of the Fourier coefficients of certain power

Marcel S. Claro, Francisco Rivadulla

We report the successful growth of epitaxial layers of van der Waals (vdW) lead oxide (PbO) polymorphs on different substrates, via pulsed laser deposition. A thin layer of vdW $α$-PbO (~5 nm) was subsequently used as a virtual substrate to grow thin films of perovskites BaTiO$_3$, SrTiO$_3$, and the spinel CoFe$_2$O$_4$ with a crystal quality comparable to

Vincenzo Pomponi, Paolo Franceschi, Stefano Baraldo, Loris Roveda

Learning robust manipulation policies typically requires large and diverse datasets, the collection of which is time-consuming, labor-intensive, and often impractical for dynamic environments. In this work, we introduce DynaMimicGen (D-MG), a scalable dataset generation framework that enables policy training from minimal human supervision while uniquely supp

Zheng Zheng, Sajjad Azimi, Florian Reetz, Tobias M. Schneider

In the inclined layer convection system, thermal convection in a Rayleigh--Bénard cell tilted against gravity, the flow is subject to competing buoyancy and shear forces. For varying inclination angle ($γ$) and Rayleigh number ($Ra$), a variety of spatio-temporal patterns is observed. We investigate the switching diamond panes (SDP) pattern, observed at $(γ,

Paul A. Johnson, Charles-Émile Fecteau, Samuel Nadeau, Mauricio Rodríguez-Mayorga

Slater determinants underpin most electronic structure methods, but orbital-based approaches often struggle to describe strong correlation efficiently. Geminal-based theories, by contrast, naturally capture static correlation in bond-breaking and multireference problems, though at the expense of implementation complexity and limited treatment of dynamic effe

Nilaksha Barman, Debarati Chatterjee

In this work, we present an equation of state formalism for hot Neutron Stars (NSs) which consistently includes the effects of finite temperature, hyperons as well as neutrino trapping, relevant for the study of proto-neutron stars, binary neutron star mergers and supernova explosions. Within a non-linear relativistic mean field description, the framework al

Marco Benini, Victor Carmona, Pieter Naaijkens, Alexander Schenkel

This paper presents a conceptual and efficient geometric framework to encode the algebraic structures on the category of superselection sectors of an algebraic quantum field theory on the $n$-dimensional lattice $\mathbb{Z}^n$. It is shown that, under the typical assumption of Haag duality, the monoidal $C^\ast$-categories of localized superselection sectors

Jonathan Auerbach

We estimate the number of street vendors in New York City. First, we summarize the process by which vendors receive licenses and permits to operate legally in New York City. We then describe a survey that was administered by the Street Vendor Project while distributing coronavirus relief aid to vendors operating in New York City both with and without a licen

Paolo Aschieri

We study the differential and Riemannian geometry of algebras $A$ endowed with an action of a triangular Hopf algebra $H$ and noncommutativity compatible with the associated braiding. The modules of one forms and of braided derivations are modules in a compact closed category of $H$-equivariant $A$-bimodules, whose internal morphisms correspond to tensor fie

Stephen D. H. Hsu

We use the Tomonaga-Schwinger (TS) formulation of quantum field theory to determine when state-dependent additions to the local Hamiltonian density (i.e., modifications to linear Schrodinger evolution) violate relativistic covariance. We derive new operator integrability conditions required for foliation independence, including the Frechet derivative terms t

Danny Smyl

Numerical simulations of physical systems exhibit discrepancies arising from unmodeled physics and idealizations, as well as numerical approximation errors stemming from discretization and solver tolerances. This article reviews techniques developed in the past several decades to approximate and account for model errors, both implicitly and explicitly. Begin

Jiahe Wang

We show that the Jordan constant for the volume-preserving plane Cremona group $\mathrm{Bir}(\mathbb P^2, \Delta)$ is $12$. We provide a Jordan bound of $144$ for the three-dimensional volume-preserving Cremona group $\mathrm{Bir}(\mathbb P^3,\Delta)$. We also provide a weak geometric Jordan bound of $2^{11} \cdot 3^2$ for $\mathrm{Bir}(\mathbb P^2)$.

Changin Oh, Kathleen P. Wilkie

The move towards personalized treatment and digital twins for cancer therapy requires a complete understanding of the mathematical models upon which these optimized simulation-based strategies are formulated. This study investigates the influence of mathematical model selection on the optimization of chemotherapy and radiotherapy protocols. By examining thre

Yifan Song, Nabiha Hasan, Susumu Takahashi

Spins in solids and molecules are promising for applications of quantum sensing technology. The sensitivity of the quantum sensing depends on how precisely spin observables can be determined in the measurement, and is intrinsically limited by the uncertainties of the observables. The use of a spin-squeezed state in a quantum sensor can reduce the uncertainty

Valery Ortiz Jimenez, Paul M. Haney, Farzad Mahfouzi, Ngoch Thanh Mai Tran

The quantum anomalous Hall effect shows great promise for realization of the ohm without the need for an external magnetic field. The most mature material platform is magnetically doped topological insulators. In these materials, precise quantization is limited to low temperatures, with the activation energy for dissipative transport typically in the range o

Jesus E. Vazquez, Yanyuan Ma, Karen Marder, Tanya P. Garcia

Across health applications, researchers model outcomes as a function of time to an event, but the event time is right-censored for participants who exit the study or otherwise do not experience the event during follow-up. When censoring depends on the outcome-as in neurodegenerative disease studies where dropout is potentially related to disease severity-sta

Austin Spizzirri

Static content-based AI value alignment is insufficient for robust alignment under capability scaling, distributional shift, and increasing autonomy. This holds for any approach that treats alignment as optimizing toward a fixed formal value-object, whether reward function, utility function, constitutional principles, or learned preference representation. Th

Akash Singha Roy

The Landau-Selberg-Delange method gives precise asymptotic formulas for the partial sums $\sum_{n \le x} \, a_n$ of a Dirichlet series $\sum_n \, a_n/n^s$ that behaves like a complex power of the Riemann zeta function. However, situations often arise when the Dirichlet series behaves like a product of complex powers of several Dirichlet $L$-functions to a mo

Belle, Belle II Collaborations, :, M. Abumusabh

Using data samples collected by the Belle and Belle II experiments at the $\Upsilon(4S)$ resonance with integrated luminosities of 571 fb$^{-1}$ and 365 fb$^{-1}$, respectively, we measure the pseudoscalar $B$-meson mass difference to be $m(B^0)-m(B^+) = (0.495\pm0.024\pm0.005)$ MeV/c$^2$. The results are based on a simultaneous fit to the variable $\tilde{M

Fronefield Crawford, Haoyang Xu

We have reprocessed the available archival radio pulsar search observations of SNR 1987A taken with the Parkes 64-m telescope, some of which have not been previously published. We conducted a standard periodicity search on these data as well as a single pulse search at a range of dispersion measures. We found no convincing candidate signals, and we calculate

Yashar Mousavi, Mahsa Tavasoli, Ibrahim Beklan Kucukdemiral, Umit Cali

This paper proposes a cyber-resilient secure control framework for autonomous vehicles (AVs) subject to false data injection (FDI) threats as actuator attacks. The framework integrates data-driven modeling, event-triggered communication, and fractional-order sliding mode control (FSMC) to enhance the resilience against adversarial interventions. A dynamic mo

Evelia R. García Barroso, Hernán Neciosup-Puican

In this paper, we study nilpotent holomorphic foliations in complex dimension $n+1$, at the origin, defined by germs of integrable 1-forms whose linear part is given by \(zdz\). These foliations generalize the classical nilpotent foliations in dimension two. We show that every nilpotent foliation in higher dimensions can be described as the pullback of Taken

Meilong Xu, Di Fu, Jiaxing Zhang, Gong Yu

Vision Language Models (VLMs) are becoming increasingly integral to multimedia understanding; however, they often struggle with domain-specific video classification tasks, particularly in cases with limited data. This stems from a critical \textit{rationale gap}, where sparse domain data is insufficient to bridge the semantic distance between complex spatio-

K. E. Castoria, H. Byeon, N. R. Beysengulov, E. O. Glen

Electrons bound to the surface of liquid helium are an emerging quantum computing platform, offering the potential for highly mobile spin qubits that can be manipulated using CMOS-fabricated devices. Here, as a step toward realizing this technology, we demonstrate selective two-dimensional shuttling of electrons across a helium film condensed on the surface

Chelsea Zou, Yiheng Yao, Basant Khalil

This project develops a self correcting framework for large language models (LLMs) that detects and mitigates hallucinations during multi-step reasoning. Rather than relying solely on final answer correctness, our approach leverages fine grained uncertainty signals: 1) self-assessed confidence alignment, and 2) token-level entropy spikes to detect unreliable

Oma Makhija

We study the factorization of Schubert polynomials into elementary symmetric polynomials. We conjecture that this occurs when the permutation corresponding to the Schubert polynomial does not contain the patterns $1432$, $1423$, $4132$, and $3142$. We prove one direction of this and provide progress towards the second direction, including obstructions arisin

Indrila Ganguly, Ying Huang

In cancer biomarker development, a key objective is to evaluate whether a new biomarker, when combined with an established one, improves early cancer detection compared to using the established biomarker alone. Incremental value is often quantified by changes at specific points on the ROC curve, such as an increase in sensitivity at a fixed specificity, whic

Austin E Schumacher, Jon Wakefield

Improving health in the most disadvantaged populations requires reliable estimates of health and demographic indicators to inform policy and interventions. Low- and middle-income countries with the largest burden of disease and disability tend to have the least comprehensive data, relying primarily on household surveys. Subnational estimates are increasingly

Alize Sucsuzer, Mark P. Hertzberg, Michiru Uwabo-Niibo

New long range forces acting on ordinary matter are highly constrained. However it is possible such forces act on dark matter, as it is less constrained observationally. In this work, we consider dark matter to be made of light bosons, such as axions. We introduce a mediator that communicates a new force between dark matter particles, in addition to gravity.

Genghan Zhang, Shaowei Zhu, Anjiang Wei, Zhenyu Song

We present AccelOpt, a self-improving large language model (LLM) agentic system that autonomously optimizes kernels for emerging AI acclerators, eliminating the need for expert-provided hardware-specific optimization knowledge. AccelOpt explores the kernel optimization space through iterative generation, informed by an optimization memory that curates experi

Debasmita Ghose, Oz Gitelson, Ryan Jin, Grace Abawe

For effective human-robot collaboration, a robot must align its actions with human goals, even as they change mid-task. Prior approaches often assume fixed goals, reducing goal prediction to a one-time inference. However, in real-world scenarios, humans frequently shift goals, making it challenging for robots to adapt without explicit communication. We propo

Natalia de Jesús Baz-Pérez, Dany Page, Simon Guichandut, Martin Nava-Callejas

We model early accretion of light elements, He, C, and O, onto a new-born neutron star using the public stellar evolution code MESA, simulating what may happen during the first few years of its life. We find that, under the appropriate conditions, significant amounts of these elements can be accreted up to densities of 10^9 g/cc without triggering a nuclear

Gabriel M. Arantes, Vinícius Salem, Danilo Cius, Bárbara Amaral

In this work, we present a novel method to express the stabilizer of a k-uniform complete hypergraph state as a linear combination of local operators. Quantum hypergraph states generalize graph states and exhibit properties that are not shared by their graph counterparts, most notably, their stabilizers are intrinsically nonlocal, as hyperedges can involve a

Sahil Khan, Abhinav Anand, Kenneth R. Brown, Jonathan M. Baker

Modular trapped-ion quantum computing hardware, known as QCCDs require shuttling operations in order to maintain effective all-to-all connectivity. Each module or trap can perform only one operation at a time, resulting in low intra-trap parallelism, but there is no restriction on operations happening on independent traps, enabling high inter-trap parallelis

J. Cristobal, A. Z. Zain Aldeen, M. Izadi, R. Faieghi

This paper presents the design of a gimballed rotor mechanism as a modular and efficient solution for constructing omnidirectional quadrotors. Unlike conventional quadrotors, which are underactuated, this class of quadrotors achieves full actuation, enabling independent motion in all six degrees of freedom. While existing omnidirectional quadrotor designs of

Iván Caamaño

For Lipschitz maps between a metric measure space and a metric space, combining the ideas of Kirchheim's metric differentiability and Cheeger's differentiable structures leads to a Rademacher-type theorem for a notion of metric differentiability with respect to a rectifiable chart, and in this paper we prove the validity of a Stepanov-type generalization of

Matthieu Kirchmeyer, Pedro O. Pinheiro, Emma Willett, Karolis Martinkus

Generative models for structure-based drug design are often limited to a specific modality, restricting their broader applicability. To address this challenge, we introduce FuncBind, a framework based on computer vision to generate target-conditioned, all-atom molecules across atomic systems. FuncBind uses neural fields to represent molecules as continuous a

Andreia Chapouto, Guopeng Li, Tadahiro Oh, Tengfei Zhao

We continue our study on the convergence issue of the intermediate long wave equation (ILW) on both the real line and the circle. In particular, we establish convergence of the scaled ILW dynamics to that of the Korteweg-de Vries equation (KdV) in the shallow-water limit at the $L^2$-level. Together with the recent work by the first three authors and D. Pilo

Gözde Sert, Abhishek Chakrabortty, Anirban Bhattacharya

We propose a semiparametric Bayesian methodology for estimating the average treatment effect (ATE) within the potential outcomes framework using observational data with high-dimensional nuisance parameters. Our method introduces a Bayesian debiasing procedure that corrects for bias arising from nuisance estimation and employs a targeted modeling strategy bas

Issei Kobayashi, Hiroyuki Kurokawa, Laura Schaefer, Satoshi Okuzumi

Short-period sub-Neptunes are common in extrasolar systems. These sub-Neptunes are generally thought to have primary atmospheres of protoplanetary-disk gas origin. However, atmospheric escape followed by degassing from their interiors can lead to the transition to secondary atmospheres depleted in gases less-soluble to magma, such as helium. These primary an

Roman Dolgopolyi, Antonis Chatzipanagiotou

An advanced emotion classification model was developed using a CNN-Transformer architecture for emotion recognition from EEG brain wave signals, effectively distinguishing among three emotional states, positive, neutral and negative. The model achieved a testing accuracy of 91%, outperforming traditional models such as SVM, DNN, and Logistic Regression. Trai

Mário J. de Oliveira

We investigate the properties of a Kolmogorov equation governing the time evolution of the probability distribution defined in phase space. Energy is strictly conserved along a trajectory in phase space, meaning the equation is appropriate to describe an isolated system, and the stationary state is the Gibbs microcanonical distribution. The equation predicts

Clayton McDonald, Allison N. Miller

We give a flexible construction for knots in the 3-sphere that bound surfaces of unexpectedly low genus in punctured open books on 3-manifolds. We use this construction to give the first examples of knots whose genus differs in different $\mathbb{Z}/2\mathbb{Z}$ homology balls. We also establish that every knot bounds a M{\"o}bius band in a rational homology

Ciprian Demeter, William O'Regan

We use recent advances in the theory of Furstenberg sets to prove new incidence results of Szemer\'edi--Trotter strength for $\delta$-discretized structures with Cartesian product flavor. We use these results to make progress on a number of problems that include energy estimates and Fourier decay of fractal measures supported on curves, as well as various su

Rahul Krishna Thomas, Arka Pal

Speculative sampling reduces the latency of autoregressive decoding for target model LLMs without sacrificing inference quality, by using a cheap draft model to suggest a candidate token and a verification criterion to accept or resample this token. To improve acceptance and decoding efficiency, recent work has explored the multi-draft extension, where at ea

Leandro Da Rold, Manuel Epele, Anibal D. Medina, Nicolás I. Mileo

We investigate di-Higgs production in the $b\bar{b}\gamma\gamma$ final state at the LHC, focusing on scenarios where the gluon fusion process is enhanced by new colored scalars, which could be identified as squarks or leptoquarks. We consider two benchmarks characterized by the mass of the lightest colored scalar, BM$_{\mathrm{L}}$ and BM$_{\mathrm{H}}$, cor

Ying Jin, José Zubizarreta

Causal inference starts with a simple idea: compare groups that differ by treatment, not much else. Traditionally, similar groups are constructed using only observed covariates; however, it remains a long-standing challenge to incorporate available outcome data into the study design while preserving valid inference. In this paper, we study the general proble

Ivan Chulo, Ananya Joshi

Recent work shows activation steering substantially improves language models' Theory of Mind (ToM) (Bortoletto et al. 2024), yet the mechanisms of what changes occur internally that leads to different outputs remains unclear. We propose decomposing ToM in LLMs by comparing steered versus baseline LLMs' activations using linear probes trained on 45 cognitive

Martin Pico, Oscar Varela

A new family of $D=4$ $\mathcal{N}=8$ gauged supergravities is introduced, consisting in a mixture of Scherk-Schwarz and dyonic CSO gaugings that involves the trombone scaling symmetry. A specific theory in this class is shown to admit supersymmetric anti-de Sitter vacua, argued to be related to various wrapped M5-brane configurations. The mass spectrum of t

G. K. Skinner, J. F. Krizmanic

It is argued that the lens described in the paper commented upon has a focussing efficiency of less than 0.03% and an angular resolution for broadband radiation that is an order of magnitude worse that the diffraction limit. Furthermore incident radiation that is not focussed will lead to background fog in the image plane.

Anuradha Gupta

Ten years ago, the first direct detection of gravitational waves (GWs) from the merger of two black holes, GW150914, provided the very first opportunity to test Einstein's general theory of relativity (GR) in the extreme gravity regime, where the gravitational field is strong, characteristic speeds are highly relativistic, and spacetime is dynamical. Such a

Daniele Ravasio, Bestem Abdulaziz, Marcello Farina, Andrea Ballarino

This paper addresses the offset-free tracking problem for nonlinear systems described by a class of recurrent neural networks (RNNs). To compensate for constant disturbances and guarantee offset-free tracking in the presence of model-plant mismatches, we propose a novel reformulation of the RNN model in velocity form. Conditions based on linear matrix inequa

Xiubin Chen

The Multi-Traveling Salesman Problem (MTSP) is a commonly used mathematical model for multi-agent task allocation. However, as the number of agents and task targets increases, existing optimization-based methods often incur prohibitive computational costs, posing significant challenges to large-scale coordination in unmanned systems. To address this issue, t

Elizabeth Pratt, Kexin Wang

We study real linear spaces in projective space that avoid the real points of a non-degenerate projective variety. For a variety $X \subset \mathbb{P}^{n-1}$ with a real smooth point, we define the avoidance locus $\mathcal{A}_k(X)$ as the subset of the real Grassmannian $\mathrm{Gr}(k,n)_{\mathbb{R}}$ consisting of linear spaces that meet $X$ transversely b

Jeremias Ferrao, Ezgi Basar, Khondoker Ittehadul Islam, Mahrokh Hassani

This study investigates the attribution patterns underlying Chain-of-Thought (CoT) reasoning in multilingual LLMs. While prior works demonstrate the role of CoT prompting in improving task performance, there are concerns regarding the faithfulness and interpretability of the generated reasoning chains. To assess these properties across languages, we applied

Keaton Naff, Tristan Ozuch

We show that the recently discovered BCCD shrinking soliton is linearly unstable, by extending the approach of \cite{chi04} and \cite{hm11}, via recent work the \cite{cm21} on gradient shrinking Ricci solitons. On the other hand, we prove that the weighted $L^2$-spectra of the weighted Lichnerowicz Laplacians of steady and expanding K\"ahler Ricci solitons a

Yintao Ma, Sajjad Pakdamansavoji, Charles Eret, Rui Heng Yang

Recovering the 9D pose of objects, both their 6D pose and 3D dimensions, under clutter and occlusion is a core requirement for warehouse automation, logistics, and manufacturing. Model-based methods are accurate but assume an instance-specific CAD model for every object, which is costly to maintain as inventories change. Model-free and category-level methods

Oliver Schlotterer, Yoann Sohnle, Yi-Xiao Tao

The low-energy expansion of genus-one string amplitudes produces infinite families of non-holomorphic modular forms after each step of integrating over a point on the torus worldsheet which are known as elliptic modular graph forms (eMGFs). We solve the differential equations of eMGFs depending on a single point $z$ and the modular parameter $\tau$ via itera

Sida Chen, Jessica K. Barrett, Marco Palma, Jianxin Pan

There is growing interest in the role of within-individual variability (WIV) in biomarker trajectories for assessing disease risk and progression. A trajectory-based definition that has attracted recent attention characterises WIV as the curvature-based roughness of the latent biomarker trajectory (TB-WIV). To rigorously evaluate the association between TB-W

Ben Zindorf, Lorenzo Braccini, Debarshi Das, Sougato Bose

To perform meaningful computations, Quantum Computers (QCs) must scale to macroscopic levels - i.e., to a large number of qubits - an objective pursued by most quantum companies. How to efficiently test their quantumness at these scales? We show that the violation of Macrorealism (MR), being the fact that classical systems possess definite properties that ca

Lorenzo Braccini, Debarshi Das, Ben Zindorf, Stephen D. Hogan

We propose an experimental scheme to test the nonclassicality of a macroscopic ensemble of qubits, through the violation of the classical notion of macrorealism (MR) via the fundamental measurement-induced disturbance of quantum systems. An electromagnetic resonator is used to probe the parity of the qubit-ensemble. The action of sequential measurements allo

Antonino Ficarra

Let $K$ be a field of characteristic zero, let $I \subset S = K[x_1,\dots,x_n]$ be a homogeneous ideal, and let $\partial(I)$ be its gradient ideal. We study the relationship between $\mathrm{reg}\,I$ and $\mathrm{reg}\,\partial(I)$. While earlier work by Bus\'e, Dimca, Schenck, and Sticlaru showed these regularities are generally incomparable for hypersurfa

Friedjof Tellkamp

We establish an integral representation for the Dirichlet generating function of the coefficients of Euler's pentagonal number theorem. The Bromwich-type integral enables analytic continuation to the entire complex plane, filling a gap in the literature and providing a new framework for studying the sequence's analytic structure. Furthermore, we derive the a

Ghaura Mahabaduge, Michael Simkin

We prove that with high probability $G(n,p)$ with $p \geq n^{-4/11 + o(1)}$ admits a fractional triangle decomposition (FTD), i.e., a nonnegative weighting of its triangles such that for each edge, the total weight of the triangles containing it equals one. This improves on the state of the art, due to Delcourt, Kelly, and Postle, that $p \geq n^{-1/3+o(1)}$

Pascal Baseilhac, Azat M. Gainutdinov, Guillaume Lemarthe

Let $A_q$ be the alternating central extension of the q-Onsager algebra, a comodule algebra over the quantum loop algebra of $sl_2$. We classify one-dimensional representations of $A_q$, and show that spin-j K-operators constructed in arXiv:2301.00781 act as K-matrices previously obtained in the literature. Using these K-operators and K-matrices, we construc

Jared Grossman, Evan Halloran, Shouhong Wang

This article examines the dynamic phase transitions and pattern formations attributed to binary systems modeled by the Cahn-Hilliard equation. In particular, we consider a two-dimensional lattice structure and determine how different choices of the spanning vectors influence the resulting dynamical tramsitions and pattern formations. As the basic steady-stat

Patrick Barlatier, Richard Dapoigny

During the last decade, the domain of Qualitative Spatial Reasoning, has known a renewal of interest for mereogeometry, a theory that has been initiated by Tarski. Mereogeometry relies on mereology, the Lesniewski's theory of parts and wholes that is further extended with geometrical primitives and appropriate definitions. However, most approaches (i) depart

Lukas Arzoumanidis, Julius Knechtel, Jan-Henrik Haunert, Youness Dehbi

The automated analysis of historical documents, particularly maps, has drastically benefited from advances in deep learning and its success across various computer vision applications. However, most deep learning-based methods heavily rely on large amounts of annotated training data, which are typically unavailable for historical maps, especially for those b

Sajjad Pakdamansavoji, Yintao Ma, Amir Rasouli, Tongtong Cao

Accurate 6D object pose estimation is vital for robotics, augmented reality, and scene understanding. For seen objects, high accuracy is often attainable via per-object fine-tuning but generalizing to unseen objects remains a challenge. To address this problem, past arts assume access to CAD models at test time and typically follow a multi-stage pipeline to

Shannon Kelley, Aleksandr M. Kazachkov, Ted Ralphs

Many applications require solving sequences of related mixed-integer linear programs. We introduce a class of parametric disjunctive inequalities (PDIs), obtained by reusing the disjunctive proofs of optimality from prior solves to construct cuts valid for perturbed instances. We describe several methods of generating such cuts that navigate the tradeoff bet

Jialin Liu, Yongyuan He, Zhihan Zheng, Yi Bu

The dominance of English in global science has long created significant barriers for non-native speakers. The recent emergence of generative artificial intelligence (GenAI) dramatically reduces drafting and revision costs, but, simultaneously, raises a critical question: how is the technology being adopted by the global scientific community, and is it mitiga

Özgür Ökcü

In this paper, combining the thermodynamical arguments of the horizon with the quadratic generalised uncertainty principle (GUP), we heuristically obtain the modified equipartition law of energy. Employing this modified equipartition law of energy, we derive the Friedmann equations in Verlinde's entropic gravity. We find a maximum energy density at the begin

Qiming Guo, Bishal Khatri, Wenbo Sun, Jinwen Tang

Underground pipeline leaks and infiltrations pose significant threats to water security and environmental safety. Traditional manual inspection methods provide limited coverage and delayed response, often missing critical anomalies. This paper proposes AquaSentinel, a novel physics-informed AI system for real-time anomaly detection in urban underground water

Kaelee S. Parker, Danielle A. Berg, John Chisholm, Simon Gazagnes

The Epoch of Reionization (EoR) provides critical insights into the role of early galaxies in shaping the ionization state of the universe. However, because of the opacity of the intergalactic medium, it is often not possible to make direct measurements of the ionizing photon escape fraction ($f_{\mathrm{esc}}^{\: \mathrm{LyC}}$) of high-redshift ($z \gtrsim

Julio Guillen-Garcia, Manuel F. Fernández, Roberto Gallardo-Cava

The current general form of the well-known Eigenvalue Interlacing Theorem states that, given an $N \times N$ Hermitian matrix $P$, the eigenvalues of the matrix product $Q^{H} P Q$ will interlace those of $P$ if the columns of the $N \times L$ matrix $Q$ (with $L \le N$) are unitary. This note further generalizes this theorem to include pseudo-similarity tra

Chenyin Gao, Han Chen, Anru R. Zhang, Shu Yang

Marginal Structural Models (MSMs) are popular for causal inference of sequential treatments in longitudinal observational studies, which however are sensitive to model misspecification. To achieve flexible modeling, we envision the potential outcomes to form a three-dimensional tensor indexed by subject, time, and treatment regime and propose a tensorized hi

Thomas Donlon, Lawrence M. Widrow, Sukanya Chakrabarti

We introduce a new, non-parametric method for estimating the mass enclosed within a sphere of arbitrary radius centered on the Sun. The method is based on the divergence theorem as applied to measurements of the line-of-sight accelerations of millisecond pulsars. We describe a procedure for inferring the mean mass density within a sphere of a given radius ce

Fuensanta Aroca, Annel Ayala, Oscar Castañón, Diana Mendez Penagos

It is known that the normalization of a quasi-ordinary complex singularity is a Hirzebruch-Jung, see [Gon00; Pop04; AS05]. We extend this result to Puiseux hypersurfaces. Moreover, we prove that Hirzebruch-Jung singularities are precisely normalizations of Puiseux hypersurfaces. Our result holds over an algebraically closed field whose characteristic does no

Devang Kulshreshtha, Wanyu Du, Raghav Jain, Srikanth Doss

This paper introduces a novel framework for simulating and analyzing how uncooperative behaviors can destabilize or collapse LLM-based multi-agent systems. Our framework includes two key components: (1) a game theory-based taxonomy of uncooperative agent behaviors, addressing a notable gap in the existing literature; and (2) a structured, multi-stage simulat

Arman Mollakhani, Jerayu Tiamraj, Shu-Jie Cao, Dongning Guo

End-to-end latency in large low-Earth-orbit (LEO) constellations is dominated by propagation delay, making total delay roughly proportional to the network diameter, the longest shortest path in hops. Current inter-satellite link (ISL) layouts have rarely been optimized to minimize network diameter while simultaneously satisfying physical and operational cons

Xusheng Zhu, Kai-Kit Wong, Boyi Tang, Wen Chen

The concept of fluid reconfigurable intelligent surface (FRIS) upgrades the conventional reconfigurable intelligent surface (RIS) paradigm by empowering its reflecting elements with positioning reconfigurability. This letter aims to investigate the use of FRIS to enhance physical-layer security in a system, in which a multi-antenna access point (AP) communic

Hina Saeeda, Mazen Mohamad, Eric Knauss, Jennifer Horkoff

High-quality data annotation requirements are crucial for the development of safe and reliable AI-enabled perception systems (AIePS) in autonomous driving. Although these requirements play a vital role in reducing bias and enhancing performance, their formulation and management remain underexplored, leading to inconsistencies, safety risks, and regulatory co

Anthony Wise, Xinyi Zhou, Martin Reimann, Anind Dey

Similar to social media bots that shape public opinion, healthcare and financial decisions, LLM-based ChatBots like ChatGPT can persuade users to alter their behavior. Unlike prior work that persuades via overt-partisan bias or misinformation, we test whether framing alone suffices. We conducted a crowdsourced study, where 336 participants interacted with a

Peter Sharpe

We introduce GLOBE, a new neural surrogate for homogeneous PDEs that draws inductive bias from boundary-element methods and equivariant ML. GLOBE represents solutions as superpositions of learnable Green's-function-like kernels evaluated from boundary faces to targets, composed across multiscale branches and communication hyperlayers. The architecture is tra

V. Manuilov

We expose a class of discrete metric spaces, for which bounded geometry is equivalent to the property A of G. Yu. This class includes the coarse disjoint union of $(\mathbb Z/2\mathbb Z)^n$, $n\in\mathbb N$, and consists of spaces of simple paths in a class of graphs that includes cactus graphs, with the metric defined as the number of edges in the symmetric

Steven Adams, Elize Alwash, Luca Laurenti

We present discretize_distributions, a Python package that efficiently constructs discrete approximations of Gaussian mixture distributions and provides guarantees on the approximation error in Wasserstein distance. The package implements state-of-the-art quantization methods for Gaussian mixture models and extends them to improve scalability. It further int

Rebecca Gjini, Matthias Morzfeld, Oliver R. A. Dunbar, Tapio Schneider

Ensemble Kalman methods were initially developed to solve nonlinear data assimilation problems in oceanography but are now popular in applications far beyond their original use cases. Of particular interest is climate model calibration. As hybrid physics and machine-learning models advance, the number of parameters and complexity of parameterizations in clim

Monu Sharma

The adoption of cloud-based Enterprise Resource Planning (ERP) platforms such as Workday has transformed healthcare operations by integrating financial, supply-chain, and workforce processes into a unified ecosystem. However, traditional workflow logic in ERP systems often lacks the adaptability required to manage event-driven and data-intensive healthcare e

Zachary J. Hoelscher, Thomas W. Kephart, Robert J. Scherrer, Kelly Holley-Bockelmann

The Dark Energy Spectroscopic Instrument (DESI) second data release shows a moderate preference for dark energy with a time-varying equation of state parameter, suggesting that the standard $\Lambda$CDM model may need to be revised. In particular, DESI favors dark energy whose equation of state parameter can drop below $-1$, violating the null energy conditi

David G. Radcliffe

We prove logarithmic lower bounds on digital sums of powers, multiples of powers, factorials, and the least common multiple of $\{1,\ldots, n\}$, using only elementary number theory. We conclude with an expository proof of Stewart's theorem on digital sums of powers, which uses Baker's theorem on linear forms in logarithms.

Fei Tian, Xiangyu Tony Zhang, Yuxin Zhang, Haoyang Zhang

Recent advances in reasoning models have demonstrated remarkable success in text and vision domains through extended chain-of-thought deliberation. However, a perplexing phenomenon persists in audio language models: they consistently perform better with minimal or no reasoning, raising a fundamental question - can audio intelligence truly benefit from delibe

Alexander Bakumenko, Janine Hoelscher, Hudson Smith

Early identification of intensive care patients at risk of in-hospital mortality enables timely intervention and efficient resource allocation. Despite high predictive performance, existing machine learning approaches lack transparency and robustness, limiting clinical adoption. We present a lightweight, transparent multimodal ensemble that fuses physiologic

Charlotte Stix, Annika Hallensleben, Alejandro Ortega, Matteo Pistillo

This research report addresses the absence of an actionable definition for Loss of Control (LoC) in AI systems by developing a novel taxonomy and preparedness framework. Despite increasing policy and research attention, existing LoC definitions vary significantly in scope and timeline, hindering effective LoC assessment and mitigation. To address this issue,

Shaon Mandal Chakraborty, Bibhut Sahoo, Peter Sollich, Rituparno Mandal

All the fundamental interactions (such as gravity or electromagnetic interactions) are reciprocal in nature. However, in the macroscopic world, in particular outside equilibrium, non-reciprocal or non-mutual interactions are quite ubiquitous. Understanding the impact of such non-reciprocal interactions has drawn a significant amount of interest in physics an

Christoph Grüner

Surface simulations are important for accurately modeling particle interactions in experiments where background contributions from surface contaminants can significantly affect detector performance. In rare event searches, such as dark matter or neutrinoless double beta decay experiments, standard Geant4 simulations typically assume perfectly smooth surfaces