March 2025 arXiv papers — page 107

Anirban Bairagi, Benjamin Wandelt, Francisco Villaescusa-Navarro

How many simulations do we need to train machine learning methods to extract information available from summary statistics of the cosmological density field? Neural methods have shown the potential to extract non-linear information available from cosmological data. Success depends critically on having sufficient simulations for training the networks and appr

Krti Tallam

The rapid evolution of artificial intelligence (AI) has ushered in a new era of integrated systems that merge computational prowess with human decision-making. In this paper, we introduce the concept of Orchestrated Distributed Intelligence (ODI), a novel paradigm that reconceptualizes AI not as isolated autonomous agents, but as cohesive, orchestrated netwo

Avi Kadria, Liam Roditty

In this paper, we study the problem of compact routing schemes in weighted undirected and directed graphs. \textit{For weighted undirected graphs}, more than a decade ago, Chechik [PODC'13] presented a $\approx3.68k$-stretch compact routing scheme that uses $\tilde{O}(n^{1/k}\log{D})$ local storage, where $D$ is the normalized diameter, for every $k>1$. We p

Matthew Zent, Seraphina Yong, Dhruv Bala, Stevie Chancellor

Online community research routinely poses minimal risk to individuals, but does the same hold true for online communities? In response to high-profile breaches of online community trust and increased debate in the social computing research community on the ethics of online community research, this paper investigates community-level harms and benefits of rese

Logan Engstrom, Andrew Ilyas, Benjamin Chen, Axel Feldmann

A major challenge in training large-scale machine learning models is configuring the training process to maximize model performance, i.e., finding the best training setup from a vast design space. In this work, we unlock a gradient-based approach to this problem. We first introduce an algorithm for efficiently calculating metagradients -- gradients through m

Milad Jafarypouria, Stepan Lomov, Sergey Abaimov

Finite element modelling is conducted to simulate the stress redistribution around a broken fibre (BF) in a bundle with experimentally measured fibre diameter distributions (FDD), followed by a parametric study of the influence of the FDD coefficient of variation on the stress concentration factor (SCF) and ineffective length (IL). Two variants of the SCF de

Kasra Borazjani, Payam Abdisarabshali, Naji Khosravan, Seyyedali Hosseinalipour

Federated Learning (FL) has emerged as one of the prominent paradigms for distributed machine learning (ML). However, it is well-established that its performance can degrade significantly under non-IID (non-independent and identically distributed) data distributions across clients. To study this effect, the existing works predominantly emulate data heterogen

Haruo Minami

We consider a compact Lie group as a framed manifold equipped with the left invarianat framing $\mathscr{L}$. In a previous paper we have proved that the Adams $e_\mathbb{C}$-invariant value of $SU(2n)$ $(n\ge 2)$ gives a generator of the image of $e_\mathbb{C}$ by twisting $\mathscr{L}$ by a certain map. In this note we show that in a similar way we can obt

Tung D. Nguyen, Tingting Tang, Amy Veprauskas, Yixiang Wu

We consider the impact of network connectivity on the dynamics of a population in a stream environment. The population is modeled using a graph theoretical framework, with habitats represented by isolated patches. We introduce a change in connectivity into the model through the addition of a bi-directional or one-directional edge between two patches and exam

Sayed Pedram Haeri Boroujeni, Niloufar Mehrabi, Fatemeh Afghah, Connor Peter McGrath

Fire and smoke phenomena pose a significant threat to the natural environment, ecosystems, and global economy, as well as human lives and wildlife. In this particular circumstance, there is a demand for more sophisticated and advanced technologies to implement an effective strategy for early detection, real-time monitoring, and minimizing the overall impacts

Igor Sfiligoi, Yunjin Zhu, Jaime Frey

The scientific and research community has benefited greatly from containerized distributed High Throughput Computing (dHTC), both by enabling elastic scaling of user compute workloads to thousands of compute nodes, and by allowing for distributed ownership of compute resources. To effectively and efficiently deal with the dynamic nature of the setup, the mos

Ali Mollaahmadi Dehaghi, Hossein KhademSohi, Reza Razavi, Steve Drew

Video super-resolution (VSR) aims to enhance low-resolution videos by leveraging both spatial and temporal information. While deep learning has led to impressive progress, it typically requires centralized data, which raises privacy concerns. Federated learning (FL) offers a privacy-friendly solution, but general FL frameworks often struggle with low-level v

Omer Ben-Neria, Shimon Garti

We study the filter versions of square bracket partition relations, focusing on Jonssonicity and Magidority. We show that the singular cardinals in a Kleinberg sequence above some strong partition cardinal are not Magidor, but the limit of the sequence is Magidor. This is done under AD. We also force over a model of AD to obtain a singular cardinal carrying

Johannes Meier, Louis Inchingolo, Oussema Dhaouadi, Yan Xia

We tackle the problem of monocular 3D object detection across different sensors, environments, and camera setups. In this paper, we introduce a novel unsupervised domain adaptation approach, MonoCT, that generates highly accurate pseudo labels for self-supervision. Inspired by our observation that accurate depth estimation is critical to mitigating domain sh

Tuan H. Nguyen, Raphael F. Ribeiro

Polariton chemistry has emerged as a new approach to directing molecular systems via strong light-matter interactions in confined photonic media. In this work, we implement a classical electrodynamics-molecular dynamics method to investigate collision-induced emission and radiative association in planar microcavities under variable light-matter coupling stre

Milad Jafarypouria, Sergey Abaimov

This research presents a single-walled carbon nanotube (SWCNT)-enabled real-time monitoring system to optimize post-curing conditions (temperature and duration) for epoxy resin. This method can serve as an alternative to traditional methods like Differential Scanning Calorimetry (DSC), which is effective in measuring the degree of cure in polymers during ind

Yuxuan Jiang, Chengxi Zeng, Siyue Teng, Fan Zhang

In recent years, attention mechanisms have been exploited in single image super-resolution (SISR), achieving impressive reconstruction results. However, these advancements are still limited by the reliance on simple training strategies and network architectures designed for discrete up-sampling scales, which hinder the model's ability to effectively capture

Keqi Chen, Vinkle Srivastav, Didier Mutter, Nicolas Padoy

Multi-view person association is a fundamental step towards multi-view analysis of human activities. Although the person re-identification features have been proven effective, they become unreliable in challenging scenes where persons share similar appearances. Therefore, cross-view geometric constraints are required for a more robust association. However, m

Mitra Rezaei, Michael Chappell, Adam Noel

Spherical multi-layered structures are prevalent in numerous biological systems and engineered applications, including tumor spheroids, layered tissues, and multi-shell nanoparticles for targeted drug delivery. Despite their widespread occurrence, there remains a gap in modeling particle propagation through these complex structures from a molecular communica

Haiying Shen, Tanmoy Sen

In this paper, we consider a mixed-prompt scenario for a large language model (LLM) inference serving system that supports diverse applications with both short prompts and long prompts and heterogeneous SLOs for iteration time. To improve throughput when handling long prompts, previous research introduces a chunking method, but has not addressed heterogeneou

Milad Jafarypouria, Sergey Abaimov

Temperature dependence of electrical resistance of single-walled carbon nanotube (SWCNTs)/epoxy nanocomposites, which is characterized by a temperature coefficient of resistance (TCR), is experimentally investigated. In the existing literature, there are biased TCR values with non-monotonic temperature dependence, including both negative and positive values.

M. Gitti, A. Bonafede, F. Brighenti, F. Ubertosi

The massive, hot galaxy cluster PSZ2 G286.98+32.90 (hereafter PLCKG287, z=0.383) hosts a giant radio halo and two prominent radio relics which are signs of a disturbed dynamical state. However, despite optical and radio observations indicate a clear multiple merger, the X-ray emission of the cluster, derived from XMM-Newton observations, shows only moderate

Haoxuan Tang, Zhiyuan Chen, Xin Yao, Zhiping Xu

Low-temperature alloys are important for a wide spectrum of modern technologies ranging from liquid hydrogen, and superconductivity to quantum technology. These applications push the limit of material performance into extreme coldness, often demanding a combination of strength and toughness to address various challenges. Steel is one of the most widely used

Daniil Orel, Dilshod Azizov, Preslav Nakov

Large language models (LLMs) have revolutionized code generation, automating programming with remarkable efficiency. However, these advancements challenge programming skills, ethics, and assessment integrity, making the detection of LLM-generated code essential for maintaining accountability and standards. While, there has been some research on this problem,

Ruohong Li, Andrea Teigelhöfer, Jiguang Li, Jacek Bieroń

High-resolution collinear laser spectroscopy of neutron-rich actinium has been performed at TRIUMF's isotope separator and accelerator facility ISAC. By probing the $7s^2~^1S_0$ $\rightarrow$ $6d7p~^1P_1$ ionic transition, the hyperfine structures and optical isotope shifts in $^{225, 226, 228, 229}\!$Ac$^+$ have been measured. This allows precise determinat

Forouzan Fallah, Maitreya Patel, Agneet Chatterjee, Vlad I. Morariu

Generating images with embedded text is crucial for the automatic production of visual and multimodal documents, such as educational materials and advertisements. However, existing diffusion-based text-to-image models often struggle to accurately embed text within images, facing challenges in spelling accuracy, contextual relevance, and visual coherence. Eva

Hirad Alipanah, Feng Zhang, Yongxin Yao, Richard Thompson

The advection-diffusion equation is simulated on a superconducting quantum computer via several quantum algorithms. Three formulations are considered: (1) Trotterization, (2) variational quantum time evolution (VarQTE), and (3) adaptive variational quantum dynamics simulation (AVQDS). These schemes were originally developed for the Hamiltonian simulation of

Lucas Polymeris, Carlos Martinez-Ranero

A linear order $A$ is called strongly surjective if for every non empty suborder $B \preceq A$, there is an epimorphism from $A$ onto $B$ (denoted by $B \trianglelefteq A$). We show, answering some questions of D\'aniel T. Soukup, that under $\mathsf{MA}_{\aleph_{1}}$ there is a strongly surjective Countryman line. We also study the general structure of the

Wesley Calvert, Johanna N. Y. Franklin, Dan Turetsky

In a previous paper, entitled "Structural Highness Notions," we defined several classes of degrees that are high in senses related to computable structure theory. Each class of degrees is characterized by a structural feature (e.g., an isomorphism) that it can compute if such a feature exists. In this paper, we examine each of these classes and characterize

Atharva Deo, Nicholas Matsumoto, Sun Kim, Peter Wager

We present an AI based approach to automate the End-to-end Assessment of Suturing Expertise (EASE), a suturing skills assessment tool that comprehensively defines criteria around relevant sub-skills.1 While EASE provides granular skills assessment related to suturing to provide trainees with an objective evaluation of their aptitude along with actionable ins

Gustavo Z. Bruno, Gabriel M. Almeida, Aloizio Da Silva, Luiz A. DaSilva

The increasing energy consumption of next-generation mobile networks necessitates the adoption of autonomous and energy-aware management strategies. This article proposes a novel adaptive solution leveraging the O-RAN architecture to optimize energy efficiency while managing its trade-off with QoS. The proposed approach introduces a hierarchical O-RAN-aligne

Amritesh Sharma, An-Hsi Chen, Connor P. Dempsey, Amrita Purkayastha

Interest in hybrid electronic devices for quantum science is driving the research into superconductor-semiconductor materials combinations. Here we study InAs nanowires coated with shells of $\beta$-Sn. The wires grow via the vapor-liquid-solid mechanism out from (001) InAs substrates along two orientations, forming a criss-crossing landscape. This allows us

Shristi Das Biswas, Efstathia Soufleri, Arani Roy, Kaushik Roy

Training robust deep video representations has proven to be computationally challenging due to substantial decoding overheads, the enormous size of raw video streams, and their inherent high temporal redundancy. Different from existing schemes, operating exclusively in the compressed video domain and exploiting all freely available modalities, i.e., I-frames

Christoph W. Lerche, Wenwei Bi, Mirjam Schoeneck, Debora Niekaemper

In this study, we propose a fast implementation of a Maximum Likelihood Positioning (MLP) algorithm to estimate the energy and identify the active scintillator pixel in staggered layer scintillation detectors for PET. The staggered layer design with pixelated scintillators enables the determination of the gamma's depth of interaction and facilitates an itera

Sanja Rukavina, Vladimir D. Tonchev

The largest prime p that can be the order of an automorphism of a 2-(35,17,8) design is p=17, and all 2-(35,17,8) designs with an automorphism of order 17 were classified by Tonchev. The symmetric 2-(35,17,8) designs with automorphisms of odd prime order $p<17$ were also classified. In this paper we give the classification of all symmetric 2-(35,17,8) design

Zhenlong Yuan, Zhidong Yang, Yujun Cai, Kuangxin Wu

Recently, patch-deformation methods have exhibited significant effectiveness in multi-view stereo owing to the deformable and expandable patches in reconstructing textureless areas. However, such methods primarily emphasize broadening the receptive field in textureless areas, while neglecting deformation instability caused by easily overlooked edge-skipping,

Cagdas Ulus Agca

BF theory is a topological field theory that appears in different parts of theoretical physics and one of its important uses is in lower dimensional holography settings. While it can be defined as a dimensional reduction of 3D CS theory, it is also equivalent to JT gravity. Moreover, further holographic settings relate BF theory to a particle on group theory

Vladislav Loktev, Sofia V. Forsblom, Sergey S. Tsygankov, Juri Poutanen

The Imaging X-ray Polarimetry Explorer (IXPE) observations of accreting X-ray pulsars (XRPs) continue to provide novel insights into the physics and geometry of these sources. We present the first X-ray polarimetric study of the persistent wind-fed XRP 4U 1538-52, based on five IXPE observations totaling 360 ks, conducted in March and October 2024. We detect

Victor Maura, Ben A. Stefanek, Tevong You

Single Higgs production at FCC-ee probes the Higgs self-coupling at next-to-leading order (NLO). Extracting a bound requires a global analysis accounting for other possible new physics contributions up to NLO. We determine the FCC-ee sensitivity to Higgs self-coupling modifications $\delta\kappa_\lambda$ within the Standard Model Effective Field Theory (SMEF

Andy Gray, Alma Rahat, Stephen Lindsay, Jen Pearson

Ensuring transparency in educational assessment is increasingly critical, particularly post-pandemic, as demand grows for fairer and more reliable evaluation methods. Comparative Judgement (CJ) offers a promising alternative to traditional assessments, yet concerns remain about its perceived opacity. This paper examines how Bayesian Comparative Judgement (BC

Alexey Kokotov, Dmitrii Korikov

Let $P$ be a convex polygon in ${\mathbb C}$ and let $\Delta_{D, P}$ be the operator of the Dirichlet boundary value problem for the Lapalcian $\Delta=-4\partial_z\partial_{\bar z}$ in $P$. We derive a variational formula for the logarithm of the $\zeta$-regularized determinant of $\Delta_{D, P}$ for arbitrary infinitesimal deformations of the polygon $P$ in

Tomasz Świsłocki, Krzysztof Gawryluk, Mirosław Brewczyk, Tomasz Karpiuk

In this work we define, analyze, and compare different numerical schemes that can be used to study the ground state properties of Bose-Fermi systems, such as mixtures of different atomic species under external forces or self-bound quantum droplets. The bosonic atoms are assumed to be condensed and are described by the generalized Gross-Pitaevskii equation. T

Yasser G. Alqaham, Jing Cheng, Zhenyu Gan

Galloping is a common high-speed gait in both animals and quadrupedal robots, yet its energetic characteristics remain insufficiently explored. This study systematically analyzes a large number of possible galloping gaits by categorizing them based on the number of flight phases per stride and the phase relationships between the front and rear legs, followin

Stephen M. Barnett, Sonja Franke-Arnold, Fiona C. Speirits

We replace the familiar Stokes vector by a tensor. This allows us to introduce, for example, polar-coordinate components of the Stokes vector. From the tensor we can derive the skyrmion field for mapping the polarization in structured light beams. These ideas have wider application in optics and in electromagnetic theory. We illustrate this with an example f

Borros Arneth

A new method in which the energy and mass of elementary particles can be calculated is presented. Gluon gluon interactions within a single elementary particle are considered, and the number of possible interactions per particle is determined. This procedure can be formalized and standardized via a newly introduced microcanonical partition function. The possi

Marius Bothe, Eloise Lardet, Alexei Poliakov, Gunnar Pruessner

The phenomenon of cell sorting/segregation, by which cells organise spatially into clusters of specific cell type or function, is essential for tissue morphogenesis. This self-organization process involves an interplay between mechanical, biochemical, and cellular mechanisms that act across various spatial and temporal scales. Several mechanisms for cell sor

Songyuan Wei, Jagat Kafle, James Y-K. Cho

We extend the description of equivalent-barotropic equations for exoplanets to the diabatic case -- that is, with explicit heating and/or cooling representation, rather than with a stationary deflection of the bottom bounding surface. In the diabatic case, the equation for potential temperature (or entropy) is directly forced and cannot be decoupled from the

Aurélien Drezet

We respond briefly to the recent comment by Jay Lawrence, Marcin Markiewicz and Marek \'{Z}ukowski [arXiv:2210.09025 and Found. Phys. \textbf{54}, 45 (2024)] regarding our work defending RQM against their previous assessment. We refute the analysis proposed by the authors and rephrase our previous study in order to clarify the remaining ambiguities in our re

Shaghayegh Yaraghi, Oussama Mhibik, Murat Yessenov, J. Keith Miller

Introducing elements into an optical cavity that modify the transverse spatial field structure can also impact the cavity spectral response. In particular, an intra-cavity spatial mode-converter is expected to induce modal runaway: unrestricted ladder-up in the modal order, concomitantly thwarting coherent field interference, thereby altogether suppressing t

Amin Faghih, Marc Van Barel, Niel Van Buggenhout, Raf Vandebril

In this paper, we generate the recursion coefficients for rational functions with prescribed poles that are orthonormal with respect to a continuous Sobolev inner product. Using a rational Gauss quadrature rule, the inner product can be discretized, thus allowing a linear algebraic approach. The presented approach involves reformulating the problem as an inv

Iryna Repinetska, Anna Hilsmann, Peter Eisert

Photo-realistic rendering and novel view synthesis play a crucial role in human-computer interaction tasks, from gaming to path planning. Neural Radiance Fields (NeRFs) model scenes as continuous volumetric functions and achieve remarkable rendering quality. However, NeRFs often struggle in large, low-textured areas, producing cloudy artifacts known as ''flo

Yushan Jiang, Kanghui Ning, Zijie Pan, Xuyang Shen

Multi-modal time series analysis has recently emerged as a prominent research area in data mining, driven by the increasing availability of diverse data modalities, such as text, images, and structured tabular data from real-world sources. However, effective analysis of multi-modal time series is hindered by data heterogeneity, modality gap, misalignment, an

Kwabena Adu-Duodu, Stanly Wilson, Yinhao Li, Aanuoluwapo Oladimeji

Efficient management of end-of-life (EoL) products is critical for advancing circularity in supply chains, particularly within the construction industry where EoL strategies are hindered by heterogenous lifecycle data and data silos. Current tools like Environmental Product Declarations (EPDs) and Digital Product Passports (DPPs) are limited by their depende

Saket Gurukar, Asim Kadav

Long-form video understanding is essential for various applications such as video retrieval, summarizing, and question answering. Yet, traditional approaches demand substantial computing power and are often bottlenecked by GPU memory. To tackle this issue, we present Long-Video Memory Network, Long-VMNet, a novel video understanding method that employs a fix

Yuriel Núñez-Fernández, Maxime Debertolis, Serge Florens

We introduce a numerically exact real-time evolution scheme for quantum impurities in a macroscopically large bath. The algorithm is few-body revealing, namely it identifies the electronic orbitals that can be made inactive (in a trivial product state) by a time-dependent orbital rotation. Following a quench, we show that both the number of active orbitals a

Kathleen West, Fabian Lehmann, Vasilis Bountris, Ulf Leser

Scientific workflows are widely used to automate scientific data analysis and often involve processing large quantities of data on compute clusters. As such, their execution tends to be long-running and resource intensive, leading to significant energy consumption and carbon emissions. Meanwhile, a wealth of carbon-aware computing methods have been proposed,

Sai Coumar, Gilbert Chang, Nihar Kodkani, Zachary Kingston

Many applications in robotics require primitive spherical geometry, especially in cases where efficient distance queries are necessary. Manual creation of spherical models is time-consuming and prone to errors. This paper presents Foam, a tool to generate spherical approximations of robot geometry from an input Universal Robot Description Format (URDF) file.

Nicola J. Fairbairn, Olga Vodianova, Gordon J. Hedley

The number of excitons that conjugated polymers can support at any one time underpins their optoelectronic performance in light emitting diodes and as laser gain media, as it sets a natural limit on exciton density. Here we have measured the time-resolved photon statistics of single chains of polyfluorene to extract the absolute number of independent emittin

Logan A. Becker, Francois Baccelli, Thibaud Taillefumier

Even when driven by the same stimulus, neuronal responses are well-known to exhibit a striking level of spiking variability. In-vivo electrophysiological recordings also reveal a surprisingly large degree of variability at the subthreshold level. In prior work, we considered biophysically relevant neuronal models to account for the observed magnitude of memb

Noah Miller

The $\alpha$-vacua are a 1-parameter family of quantum field vacua in de Sitter space which are invariant under the isometry group $SO(1,d)$. In this work give a path integral construction of the de Sitter $\alpha$-vacua. We explain that these states can be prepared by acting on the Bunch-Davies vacuum with a certain non-local charge operator. While most con

Alessandro Lehmann, Wendy Lowen

We define a notion of categorical first order deformations for (enhanced) triangulated categories. For a category $\mathcal{T}$, we show that there is a bijection between $\operatorname{HH}^2(\mathcal{T})$ and the set of categorical deformations of $\mathcal{T}$. We show that in the case of curved deformations of dg algebras considered in arXiv:2406.04945, t

Anne Broadbent, Alex B. Grilo, Nagisa Hara, Arthur Mehta

In a proof of knowledge (PoK), a verifier becomes convinced that a prover possesses privileged information. In combination with zero-knowledge proof systems, PoKs play an important role in security protocols such as in digital signatures and authentication schemes, as they enable a prover to demonstrate possession of certain information (such as a private ke

Logan W. Grove, Pratik J. Barge, Kevin Valson Jacob

Characterizing quantum processes is indispensable for the implementation of any task in quantum information processing. In this paper, we develop an efficient method to fully characterize arbitrary Gaussian processes in continuous-variable quantum systems. This is done by directly obtaining all elements of the symplectic matrix that describes the process. On

Roussel Rahman

Traditionally, experimental effects on humans are investigated at the group level. In this work, we present a distributional ``spotlight'' to investigate experimental effects at the individual level. Specifically, we estimate the effects on individuals through the changes in the probability distributions of their experimental data across conditions. We test

Luke C Adams, Gregory R Werner, John R Cary

When the Debye length is not resolved in a simulation using the most common particle-in-cell (PIC) algorithm, the plasma will unphysically heat until the Debye length becomes resolved via a phenomenon known as grid heating. This article presents detailed numerical measurements of grid heating for several explicit PIC algorithms including the first systematic

Sebastian Calonico, Matias D. Cattaneo, Max H. Farrell, Filippo Palomba

Empirical studies using Regression Discontinuity (RD) designs often explore heterogeneous treatment effects based on pretreatment covariates, even though no formal statistical methods exist for such analyses. This has led to the widespread use of ad hoc approaches in applications. Motivated by common empirical practice, we develop a unified, theoretically gr

Siavash Khodakarami, Vivek Oommen, Aniruddha Bora, George Em Karniadakis

Neural operators have emerged as powerful surrogates for modeling complex physical problems. However, they suffer from spectral bias making them oblivious to high-frequency modes, which are present in multiscale physical systems. Therefore, they tend to produce over-smoothed solutions, which is particularly problematic in modeling turbulence and for systems

Cyril Nicaud, Carine Pivoteau, Stéphane Vialette

We analyze the classical Morris-Pratt and Knuth-Morris-Pratt pattern matching algorithms through the lens of computer architecture, investigating the impact of incorporating a simple branch prediction mechanism into the model of computation. Assuming a fixed pattern and a random text, we derive precise estimates of the number of mispredictions these algorith

Eitan Shaar, Ariel Shaulov, Gal Chechik, Lior Wolf

In the domain of audio-visual event perception, which focuses on the temporal localization and classification of events across distinct modalities (audio and visual), existing approaches are constrained by the vocabulary available in their training data. This limitation significantly impedes their capacity to generalize to novel, unseen event categories. Fur

Lukas Juhrich

This thesis is expository in nature. We analyze the connection between abstract minions, which can be described as functors from the category of finite ordinals to sets, and concrete minions, which are sets $\mathrm{Pol}(A, B)$ of polymorphisms $A^k \to B$ between relational structures $A$ and $B$. The functorial structure arises because a function $\alpha\c

Alexei M. Frolov

Total energies and other bound state properties of the weakly-bound (1,1)-states and rotationally excited (2,0)-states in the three-body muonic molecular $d d \mu, d t \mu$ and $t t \mu$ ions are determined to high numerical accuracy and investigated. Our current numerical accuracy achieved for the total and binding energies of the weakly-bound (1,1)-states

Alain M. Dikande, H. Ntahombagana Matabaro

The Behrens-Feichtinger model provides a deterministic picture for the co-evolution of sales of two firms, producing the same goods and competing in a common market. The model involves an active investment strategy such that the temporary investment of each of the two firms depends on its relative position in the market. In this work we are interested in a s

Shiva Heidari, Shervin Parsi, Pouyan Ghaemi

We study the effects of strain on exciton dynamics in transition metal dichalcogenide (TMD) nanoribbons. Using the Bethe-Salpeter formalism, we derive the exciton dispersion relation in strained TMDs and demonstrate that strain-induced pseudo-gauge fields significantly influence exciton transport and interactions. Our results show that low-energy excitons oc

Jan Bronec, Jindřich Helcl

We present a submission to the SemEval 2025 shared task on unlearning sensitive content from LLMs. Our approach employs negative preference optimization using low-rank adaptation. We show that we can utilize this combination to efficiently compute additional regularization terms, which help with unlearning stabilization. The results of our approach significa

Stef Baas, Yaron Racah, Elad Berkman, Sofia S. Villar

Traditional hypothesis tests for differences between binomial proportions are at risk of being too liberal (Wald test) or overly conservative (Fisher's exact test). This problem is exacerbated in small samples. Regulators favour exact tests, which provide robust type I error control, even though they may have lower power than non-exact tests. To target an ex

Maryam Norouzi, Mingxi Zhou, Chengzhi Yuan

Modern unmanned systems, including aerial, terrestrial, and underwater vehicles, are increasingly utilized in dynamic and unpredictable environments, where the presence of modeling uncertainties necessitates the development of robust and adaptive control strategies. In this work, we address the formation control problem for a team of unmanned systems with co

A. Selvioğlu, V. Adanova, M. Atagoziev

With the rise of advanced natural language models like GPT, distinguishing between human-written and GPT-generated text has become increasingly challenging and crucial across various domains, including academia. The long-standing issue of plagiarism has grown more pressing, now compounded by concerns about the authenticity of information, as it is not always

Razvan Gabriel Iagar, David Puertas-Centeno

We introduce a pair of transformations, which are mutually inverse, acting on rather general classes of probability densities in R. These transformations have the property of interchanging the main informational measures such as p-moments, Shannon and R\'enyi entropies, and Fisher information. We thus apply them in order to establish extensions and generaliz

Rui Wen

We study topological holography for 2+1-D gapped and gapless phases with generalized symmetries using tools from higher linear algebra and higher condensation theory. We focus on bosonic fusion 2-category symmetries, where the Symmetry Topological Field Theory (SymTFT) are 3+1D Dijkgraaf-Witten theories. (1). Gapped phases are obtained from the sandwich cons

Minghan Li, Chenxi Xie, Yichen Wu, Lei Zhang

Numerous text-to-video (T2V) editing methods have emerged recently, but the lack of a standardized benchmark for fair evaluation has led to inconsistent claims and an inability to assess model sensitivity to hyperparameters. Fine-grained video editing is crucial for enabling precise, object-level modifications while maintaining context and temporal consisten

Hamza M. Haddad, M. Haluk Seçuk, Özgür Delice

We investigate the dynamics of charged particles in the spacetime of a global monopole swallowed by a Reissner-Nordstr\"om (RN) black hole in the presence of an external, weak, asymptotically homogeneous magnetic field. We carefully analyze and deduce the conditions to have such a magnetic field around this black hole and show that this is indeed possible in

Renata Kallosh, Andrei Linde

The concept of attractors, well-known in classical mechanics, proved to be very productive in supergravity, in the theory of black holes and inflationary cosmology. We start with attractors in supersymmetric black holes and discuss also non-BPS black hole attractors. Recently the non-BPS case helped to explain, via enhanced dualitiy symmetry, mysterious canc

Theodorus Dapamede, Aisha Urooj, Vedant Joshi, Gabrielle Gershon

Women are underdiagnosed and undertreated for cardiovascular disease. Automatic quantification of breast arterial calcification on screening mammography can identify women at risk for cardiovascular disease and enable earlier treatment and management of disease. In this retrospective study of 116,135 women from two healthcare systems, a transformer-based neu

Qu Luo, Jing Zhu, Gaojie Chen, Pei Xiao

Sparse code multiple access (SCMA) and multiple input multiple output (MIMO) are considered as two efficient techniques to provide both massive connectivity and high spectrum efficiency for future machine-type wireless networks. This paper proposes a single sparse graph (SSG) enhanced expectation propagation algorithm (EPA) receiver, referred to as SSG-EPA,

H. T. Özer, Aytül Filiz

This study investigates the asymptotic symmetry algebras (ASA) of Jackiw-Teitelboim (JT) gravity within the framework of sl(3,R) symmetry. By explicitly constructing this algebra, we explore how the presence of the dilaton field influences the structure of asymptotic symmetries and symmetry breaking mechanisms at the AdS(2) boundary. For the sl(3,R) model, t

Risheng Xu, Philipp Sieweck, Hermann von Hasseln, Dirk Nowotka

We introduce preti, a novel framework for predicting software execution time during the early stages of development. preti leverages an LLVM-based simulation environment to extract timing-related runtime information, such as the count of executed LLVM IR instructions. This information, combined with historical execution time data, is utilized to train machin

Roberto Biondo, Davide Castelnovo, Fabio Gadducci

The use of rewriting-based visual formalisms is on the rise. In the formal methods community, this is due also to the introduction of adhesive categories, where most properties of classical approaches to graph transformation, such as those on parallelism and confluence, can be rephrased and proved in a general and uniform way.E-graphs (EGGs) are a formalism

Mehrnoush Ghazanfariharandi, Robert Mieth

Value-oriented forecasts for two-stage power system operational problems have been demonstrated to reduce cost, but prove to be computationally challenging for large-scale systems because the underlying optimization problem must be internalized into the forecast model training. Therefore, existing approaches typically scale poorly in the usable training data

Minoru Kusaba, Megumi Iwayama, Ryo Yoshida

In supervised learning, the output variable to be predicted is often represented as a function, such as a spectrum or probability distribution. Despite its importance, functional output regression remains relatively unexplored. In this study, we propose a novel functional output regression model based on kernel methods. Unlike conventional approaches that in

Jiayu Ding, Rohit Jakkula, Tom Xiao, Zhenyu Gan

Modular robotics enables the development of versatile and adaptive robotic systems with autonomous reconfiguration. This paper presents a modular robotic system in which each module has independent actuation, battery power, and control, allowing both individual mobility and coordinated locomotion. A hierarchical Central Pattern Generator (CPG) framework gove

Andy Zeyi Liu, Debbie Leung

Measures of quantum nonlocality traditionally assume perfect local computation. In real experiments, however, each computational primitive is imperfect. Fault-tolerant techniques enable arbitrarily accurate quantum computation but do not necessarily preserve optimized measures of nonlocality. We examine the impact of low noise on quantum nonlocality in nonlo

Kittithat Krongchon, Tawfiqur Rakib, Daniel Palmer, Elif Ertekin

The interaction between graphene and hexagonal boron nitride (hBN) plays a pivotal role in determining the electronic and structural properties of graphene-based devices. In this work, we employ quantum Monte Carlo (QMC) to study the interlayer interactions and stacking-fault energy (SFE) between graphene and hBN. We generated QMC energies for several rigid

Wen-Tan Xue, Fei Song, Yu-Min Hu, Zhong Wang

The non-Hermitian skin effect, i.e., the localization of nominally bulk modes, not only drastically reshapes the spectral properties of non-Hermitian systems, but also dramatically modifies the real-time dynamics therein. Here we investigate the time evolution of waves (or quantum-mechanical particles) initialized around the edge of non-Hermitian lattices. T

Guillem Domènech, Jens Chluba

Finite mean free paths of light particles, like photons and neutrinos, lead to dissipative effects and damping of small-scale density fluctuations in the early universe. We study the impact of damping on the spectral density of gravitational waves induced by primordial fluctuations in the radiation-dominated universe. We show that the most important effects

Jonas F. G. Santos

Quantum metrology employs quantum properties to enhance the precision of physical parameters, in order to characterize quantum states as well as channels. Frequency and temperature estimations are of fundamental importance for these tasks and have been considerably treated in quantum sensing strategies. From the set of quantum features that can be exploited

Luciano M. Abreu, Juan M. Torres-Rincon

The femtoscopic $D \bar D $ correlations correlation functions are investigated to predict the signature of the not-yet-established $X(3700)$ state. Here it is interpreted as a bound state generated by solving the coupled-channel Bethe-Salpeter equations with the local hidden-gauge formalism. We prospect how the relevant properties and observables characteri

Ivan I. Shevchenko

We calculate the maximum Lyapunov exponent of the motion in the separatrix map's chaotic layer, along with calculation of its width, as functions of the adiabaticity parameter $\lambda$. The separatrix map is set in natural variables; and the case of the layer's least perturbed border is considered, i.~e., the winding number of the layer's border (the last i

Serhii Bardyla

A regular separable first-countable countably compact space is called a Nyikos space. In this paper, we give a partial solution to an old problem of Nyikos by showing that each locally compact Nyikos inverse topological semigroup is compact. Also, we show that a topological semigroup $S$ that contains a dense inverse subsemigroup is a topological inverse sem

Márk Oláh, Csaba Vincze

A Randers space is a differentiable manifold equipped with a Randers metric. It is the sum of a Riemannian metric and a one-form on the base manifold. The compatibility of a linear connection with the metric means that the parallel transports preserve the Randers norm of tangent vectors. The existence of such a linear connection is not guaranteed in general.

Fabian Ballar Trigueros, Vighnesh Dattatraya Naik, Markus Heyl

Defects and interfaces are essential to understand the properties of matter. However, studying their dynamics in the quantum regime remains a challenge in particular concerning the regime of two spatial dimensions. Recently, it has been shown that a quantum counterpart of the hard-disk problem on a lattice yields defects and interfaces, which are stable just