December 2024 arXiv papers — page 76

Ido Cohen, Daniela Gottesman, Mor Geva, Raja Giryes

Vision-language models (VLMs) excel at extracting and reasoning about information from images. Yet, their capacity to leverage internal knowledge about specific entities remains underexplored. This work investigates the disparity in model performance when answering factual questions about an entity described in text versus depicted in an image. Our results r

Hugo Gangloff, Nicolas Jouvin

jinns is an open-source Python library for physics-informed neural networks, built to tackle both forward and inverse problems, as well as meta-model learning. Rooted in the JAX ecosystem, it provides a versatile framework for efficiently prototyping real-problems, while easily allowing extensions to specific needs. Furthermore, the implementation leverages

Franco Nieto, Luis S. Mayorga

Modeling and simulation are transforming all fields of biology. Tools like AlphaFold have revolutionized structural biology, while molecular dynamics simulations provide invaluable insights into the behavior of macromolecules in solution or on membranes. In contrast, we lack effective tools to represent the dynamic behavior of the endomembrane system. Static

Maria F. Gamal'

A question if a polynomially bounded operator is similar to a contraction was posed by Halmos and was answered in the negative by Pisier. His counterexample is an operator of infinite multiplicity, while all its restrictions on invariant subspaces of finite multiplicity are similar to contractions. In the paper, cyclic polynomially bounded operators which ar

Eduard Hogea, Darian M. Onchis, Ana Coporan, Adina Magda Florea

Recent advancements in Vision Transformers (ViT) have demonstrated exceptional results in various visual recognition tasks, owing to their ability to capture long-range dependencies in images through self-attention mechanisms. However, the complex nature of ViT models requires robust explainability methods to unveil their decision-making processes. Explainab

Xuan Wang, Tianxi Cai, Lu Tian, Layla Parast

Clinical trials or studies oftentimes require long-term and/or costly follow-up of participants to evaluate a novel treatment/drug/vaccine. There has been increasing interest in the past few decades in using short-term surrogate outcomes as a replacement of the primary outcome i.e., in using the surrogate outcome, which can potentially be observed sooner, to

Robert Florido, Núria Fagella

We present an application of quasiconformal (QC) surgery for holomorphic maps fibered over an irrational rotation of the unit circle, also known as quasiperiodically forced (QPF) maps. It consists of modifying the fibered multiplier of an attracting invariant curve for a QPF hyperbolic polynomial. This is the analogue of the classical change of multiplier of

Igor Volobuev, Vadim Egorov

The differential probability of the process of Compton ionization of a hydrogen atom by a cylindrical electromagnetic wave is calculated taking into account the finite size of the target, which resulted in the appearance of a dependence of this value on the angular momentum of the cylindrical wave. It is shown that the use of a cylindrical wave instead of a

Francesco Comberiati, Leonardo de la Cruz

We study the deflection of light rays in a cold, non-magnetized plasma using the worldline framework. Starting from Synge's Hamiltonian formalism, we construct a position-space action and use it perturbatively to calculate light bending angles. In the homogeneous case, the action reduces to that of a massive particle, allowing us to extract the bending angle

Vladimir Rovenski

Recent interest among geometers in $f$-structures of K. Yano is due to the study of topology and dynamics of contact foliations, which generalize the flow of the Reeb vector field on contact manifolds to higher dimensions. Weak metric structures introduced by V. Rovenski and R. Wolak as a generalization of Hermitian and K\"{a}hler structures, as well as $f$-

Xuan Wang, Jie Zhou, Layla Parast, Tom Greene

In clinical trials where long follow-up is required to measure the primary outcome of interest, there is substantial interest in using an accepted surrogate outcome that can be measured earlier in time or with less cost to estimate a treatment effect. For example, in clinical trials of chronic kidney disease (CKD), the effect of a treatment is often demonstr

Martin Jirásek, Tomáš Sieger, Gabriela Chaloupková, Lucia Nováková

Objective: To assess the effect of overall, between- and within-day subjectively rated fluctuations in motor and non-motor symptoms in people with functional motor disorder (FMD) on the health-related quality of life (HRQoL). Background: FMD is a complex condition characterized by fluctuating motor and non-motor symptoms that may negatively impact HRQoL. Met

Guillaume Astruc, Nicolas Gonthier, Clement Mallet, Loic Landrieu

Geospatial models must adapt to the diversity of Earth observation data in terms of resolutions, scales, and modalities. However, existing approaches expect fixed input configurations, which limits their practical applicability. We propose AnySat, a multimodal model based on joint embedding predictive architecture (JEPA) and scale-adaptive spatial encoders,

Adam Carter, Eleanor K. R. Mackay, Brennan Sprinkle, Alice L. Thorneywork

The collective diffusion coefficient $D_\mathrm{coll}$ is a key quantity for describing the macroscopic transport properties of soft matter systems. However, measuring $D_\mathrm{coll}$ is a fundamental experimental and numerical challenge, as it either relies on nonequilibrium techniques that are hard to interpret or, at equilibrium, on Fourier-based approa

Stephen F. King, Soumen Kumar Manna, Rishav Roshan, Arunansu Sil

We discuss a model of neutrino mass based on the type I seesaw mechanism embedded in a spontaneously broken global lepton number framework with a $Z_2$ symmetry. We show that the resulting Majoron is a viable freeze-in dark matter candidate. Two right-handed neutrinos are assumed to have dominant off-diagonal masses suggesting resonant leptogenesis as the or

Jérémie Bettinelli, Éric Fusy, Baptiste Louf

We construct growth bijections for bipolar oriented planar maps and for Schnyder woods. These give direct combinatorial proofs of several counting identities for these objects. Our method mainly uses two ingredients. First, a slit-slide-sew operation, which consists in slightly sliding a map along a well-chosen path. Second, the study of the orbits of natura

Arshia Zolghadr, Joao F. Santos, Luiz A. DaSilva, Jacek Kibiłda

The Open Radio Access Network (O-RAN) architecture enables the deployment of third-party applications on the RAN Intelligent Controllers (RICs). However, the operation of third-party applications in the Near Real-Time RIC (Near-RT RIC), known as xApps, may result in conflicting interactions. Each xApp can independently modify the same control parameters to a

Ziyang Xu, Huangxuan Zhao, Wenyu Liu, Xinggang Wang

The rapid and accurate direct multi-frame interpolation method for Digital Subtraction Angiography (DSA) images is crucial for reducing radiation and providing real-time assistance to physicians for precise diagnostics and treatment. DSA images contain complex vascular structures and various motions. Applying natural scene Video Frame Interpolation (VFI) met

Lorenzo Dania, Oscar Schmitt Kremer, Johannes Piotrowski, Davide Candoli

Exploiting quantum effects of mechanical motion, such as backaction evading measurements or squeezing, requires preparation of the oscillator in a high-purity state. The largest state purities in optomechanics to date have relied on cryogenic cooling, combined with coupling to electromagnetic resonators driven with a coherent radiation field. In this work, w

Jun Wu, Jingrui He

Transfer learning aims to transfer knowledge or information from a source domain to a relevant target domain. In this paper, we understand transfer learning from the perspectives of knowledge transferability and trustworthiness. This involves two research questions: How is knowledge transferability quantitatively measured and enhanced across domains? Can we

Luc Bojorquez-Lopez, Matheus Hostert, Carlos A. Argüelles, Zhen Liu

Muon colliders provide an exciting new direction to expand the energy frontier of particle physics. We point out a new use of these facilities for neutrino and beyond the Standard Model physics using their main detectors. Muon decays along the accelerator rings create an intense and highly collimated neutrino beam that crosses a thin slice of the kt-scale de

Amir Hossein Houshmand Almani, Ali Mortezapour, Alireza Nourmandipour

In this paper, we delve into the issue of Quantum Synchronization in a driven two-level (qubit) system situated within a structured environment. Our findings have practical implications as we discover that adding a time-dependent periodic modulation to the transition frequency of the qubit can significantly enhance quantum synchronization. We first discovere

Amit Kumar, Dharm Veer Singh, Sudhaker Upadhyay

We find an exact black hole solution for the Einstein gravity in the presence of Ay\'on--Beato--Garc\'ia non-linear electrodynamics and a cloud of strings. The resulting black hole solution is singular, and the solution becomes non-singular when gravity is coupled with Ay\'on--Beato--Garc\'ia non-linear electrodynamics only. This solution interpolates betwee

Md Sayed Tanveer, Dhruvik Patel, Hunter E. Schweiger, Kwaku Dad Abu-Bonsrah

With the recent advancements in artificial intelligence, researchers and industries are deploying gigantic models trained on billions of samples. While training these models consumes a huge amount of energy, human brains produce similar outputs (along with other capabilities) with massively lower data and energy requirements. For this reason, more researcher

Shuang Guo, Guillermo Gallego

We tackle the problem of bundle adjustment (i.e., simultaneous refinement of camera poses and scene map) for a purely rotating event camera. Starting from first principles, we formulate the problem as a classical non-linear least squares optimization. The photometric error is defined using the event generation model directly in the camera rotations and the s

Jakob Schoenleber, Raza Sabbir Sufian, Taku Izubuchi, Yi-Bo Yang

We identify the matrix elements necessary to determine the leading-twist gluon generalized parton distributions (GPDs) $H_g,~E_g,~\wt{H}_g,~\wt{E}_g,~H^T_g,~E^T_g, \wt{H}^T_g ,~\wt{E}^T_g$ in lattice QCD calculations. We present a method to achieve a Lorentz-covariant parameterization of the matrix elements in terms of a linearly independent basis of tensor

Yang Pu, Zhiyuan Dai, Yifan Zhou, Ning Jia

Machine learning (ML) has been extensively employed in planar perovskite photovoltaics to screen effective organic molecular additives, while encountering predictive biases for novel materials due to small datasets and reliance on predefined descriptors. Present work thus proposes an effective approach, Co-Pilot for Perovskite Additive Screener (Co-PAS), an

Diogo Lameira, Filipa Ferraz

Advances in imaging technologies have revolutionised the medical imaging and healthcare sectors, leading to the widespread adoption of PACS for the storage, retrieval, and communication of medical images. Although these systems have improved operational efficiency, significant challenges remain in effectively retrieving DICOM images, which are essential for

C. Branchina, V. Branchina, F. Contino, A. Pernace

Considering the Einstein-Hilbert truncation for the running action in (euclidean) quantum gravity, we derive the renormalization group equations for the cosmological and Newton constant. We find that these equations admit only the Gaussian fixed point with a UV-attractive and a UV-repulsive eigendirection, and that there is no sign of the non-trivial UV-attr

C. Martínez-Sebastián, S. Simón-Díaz, H. Jin, Z. Keszthelyi

There is increasing evidence that single-star evolutionary models are inadequate to reproduce all observational properties of massive stars. Binary interaction has emerged as a key factor in the evolution of a significant fraction of massive stars. In this study, we investigate the helium ($Y_{\mathrm He}$) and nitrogen ($\epsilon_{\mathrm N}$) surface abund

Guillermo Ballesteros, Jesús Gambín Egea, Thomas Konstandin, Alejandro Pérez Rodríguez

We study the non-Gaussian tail of the curvature fluctuation, $\zeta$, in an inflationary scenario with a transient ultra slow-roll phase that generates a localized large enhancement of the spectrum of $\zeta$. To do so, we implement a numerical procedure that provides the probability distribution of $\zeta$ order by order in perturbation theory. The non-Gaus

Elijah Borodin, Afonso D. M. Barroso, Andrey P. Jivkov

Microstructural changes in solids, driven by energy flows, do not develop in a static continuous space, such as the space considered in conventional plasticity models. The applied forces create an evolving internal energy landscape, which is constrained by crystallography but has characteristic spatial and temporal scales that form dynamically. To describe t

Yuto Sugimoto, Shoichi Sasaki

Anisotropic Tensor Renormalization Group (ATRG) is a powerful algorithm for four-dimensional tensor network calculations. However, the larger bond dimensions are known to be difficult to achieve in practice due to the higher computational cost. Adopting the methods of the minimally decomposed TRG and its triad prescriptions, we construct a triad representati

Rémi Marsal, Alexandre Chapoutot, Philippe Xu, David Filliat

The recent development of \emph{foundation models} for monocular depth estimation such as Depth Anything paved the way to zero-shot monocular depth estimation. Since it returns an affine-invariant disparity map, the favored technique to recover the metric depth consists in fine-tuning the model. However, this stage is not straightforward, it can be costly an

Yincheng Shi, Fengwen Wang, Dennis Høj, Ole Sigmund

High quality mechanical resonators are critical for driving advances in quantum information technologies, precision sensing, and optomechanics. However, achieving compact resonator designs that maintain high performance is a key challenge. In this study, we present a new class of compact resonators optimized to operate at higher-order eigenmodes, achieving b

Christopher P. Murray, Daniyar Mamyraimov, Mugahid Ali, Clive Downing

Next-generation heat-assisted magnetic recording (HAMR) relies on fast, localized heating of the magnetic medium during the write process. Au plasmonic near-field transducers are an attractive solution to this challenge, but increased thermal stability of Au films is required to improve long-term reliability. This work compares the effect of nanoscale Al, Al

Bijay Adhikari, Pratibha Kulung, Jakesh Bohaju, Laxmi Kanta Poudel

Automating brain tumor segmentation using deep learning methods is an ongoing challenge in medical imaging. Multiple lingering issues exist including domain-shift and applications in low-resource settings which brings a unique set of challenges including scarcity of data. As a step towards solving these specific problems, we propose Convolutional adapter-ins

Haidar Al-Naseri, Gert Brodin

For many purposes, classical plasma dynamics models can work surprisingly well even for strong electromagnetic fields, approaching the Schwinger critical fields, and high frequencies, approaching the Compton frequency. However, the applicability of classical models tends to depend rather sensitively on the details of the problem. In the present paper, we stu

Evgenii E. Narimanov, Eugene A. Demler

Achieving strong coherent interaction between qubits separated by large distances holds the key to many important developments in quantum technology, including new designs of quantum computers, new platforms for quantum simulations and implementation of large scale quantum optical networks. However, the inherent mismatch between the spatial dimensions of a q

Jihye Choi, Jayaram Raghuram, Yixuan Li, Somesh Jha

Advancements in foundation models (FMs) have led to a paradigm shift in machine learning. The rich, expressive feature representations from these pre-trained, large-scale FMs are leveraged for multiple downstream tasks, usually via lightweight fine-tuning of a shallow fully-connected network following the representation. However, the non-interpretable, black

Prakhyat Khati, Ajay Kumar Shrestha, Julita Vassileva

Blockchain technology has emerged as a transformative tool for data management in a variety of industries, including fintech, research and healthcare. We have developed a workable blockchain based system that utilizes non fungible tokens NFTs to tokenize and prove ownership of the academic institutions credentials. This makes it easier to create provenance a

Farshad Amani, Amin Kargarian

This paper presents a quantum-enhanced optimization approach for solving optimal power flow (OPF) by integrating the interior point method (IPM) with a coherent variational quantum linear solver (CVQLS). The objective is to explore the applicability of quantum computing to power systems optimization and address the associated challenges. A comparative analys

P. J. Fitzsimmons

We prove the Martingale Convergence Theorem by using the work of L. Dubins and I. Monroe about embedding a given discrete-time martingale in the sample paths of a Brownian motion.

Shai M. Chester, Ross Dempsey, Silviu S. Pufu

We study higher-derivative corrections to the graviton scattering amplitude in M-theory, via the stress tensor correlator of 3d $\mathcal{N} =8$ $\text{U}(N)_k\times \text{U}(N)_{-k}$ ABJM theory (dual to graviton scattering in M-theory on $\text{AdS}_4\times S^7/\mathbb{Z}_k$). We use the conformal bootstrap combined with an integral constraint derived from

Ryan Greenblatt, Carson Denison, Benjamin Wright, Fabien Roger

We present a demonstration of a large language model engaging in alignment faking: selectively complying with its training objective in training to prevent modification of its behavior out of training. First, we give Claude 3 Opus a system prompt stating it is being trained to answer all queries, even harmful ones, which conflicts with its prior training to

The H1 collaboration, V. Andreev, M. Arratia, A. Baghdasaryan

In deep-inelastic positron-proton scattering, the lepton-jet azimuthal angular asymmetry is measured using data collected with the H1 detector at HERA. When the average transverse momentum of the lepton-jet system, $\lvert \vec{P}_\perp \rvert $, is much larger than the total transverse momentum of the system, $\lvert \vec{q}_\perp \rvert$, the asymmetry bet

Yassine El Maazouz, Yelena Mandelshtam

The Pl\"ucker positive region $\mathrm{OGr}_+(k,2k)$ of the orthogonal Grassmannian emerged as the positive geometry behind the ABJM scattering amplitudes. In this paper we initiate the study of the positive orthogonal Grassmannian $\mathrm{OGr}_+(k,n)$ for general values of $k,n$. We determine the boundary structure of the quadric $\mathrm{OGr}_+(1,n)$ in $

Hassan Al-Hamdo, Tobias Wagner, Philipp Schwenke, Gutenberg Kendzo

We investigate spin dynamics in $\alpha$-Fe$_{2}$O$_{3}$/Ni$_{80}$Fe$_{20}$ (Py) heterostructures, uncovering a robust mechanism for in-situ modulation of ferromagnetic resonance (FMR) through precise control of temperature, applied magnetic field and crystal orientation. Employing cryogenic ferromagnetic resonance spectroscopy, we demonstrate that the inter

Suyash Vishnoi, Akhil Shetty, Iveel Tsogsuren, Neha Arora

This work develops a compute-efficient algorithm to tackle a fundamental problem in transportation: that of urban travel demand estimation. It focuses on the calibration of origin-destination travel demand input parameters for high-resolution traffic simulation models. It considers the use of abundant traffic road speed data. The travel demand calibration pr

Lucas Dal'Col, Miguel Oliveira, Vítor Santos

Perception and prediction modules are critical components of autonomous driving systems, enabling vehicles to navigate safely through complex environments. The perception module is responsible for perceiving the environment, including static and dynamic objects, while the prediction module is responsible for predicting the future behavior of these objects. T

Matej Martinc, Hanh Thi Hong Tran, Senja Pollak, Boshko Koloski

Keyword extraction involves identifying the most descriptive words in a document, allowing automatic categorisation and summarisation of large quantities of diverse textual data. Relying on the insight that real-world keyword detection often requires handling of diverse content, we propose a novel supervised keyword extraction approach based on the mixture o

Simone Giombi, Elizabeth Himwich, Andrei Katsevich, Igor Klebanov

The dimensional continuation approach to calculating the free energy of $d$-dimensional Euclidean CFT on the round sphere $S^d$ has been used to develop its $4-\epsilon$ expansion for a number of well-known non-supersymmetric theories, such as the $O(N)$ model. The resulting estimate of the sphere free energy $F$ in the 3D Ising model has turned out to be in

Markus Dablander

Video games are a natural and synergistic application domain for artificial intelligence (AI) systems, offering both the potential to enhance player experience and immersion, as well as providing valuable benchmarks and virtual environments to advance AI technologies in general. This report presents a high-level overview of five promising research pathways f

Yasha Savelyev

We give a reframing of Godel's first and second incompleteness theorems that applies even to some undefinable theories of arithmetic. The usual Hilbert-Bernays provability conditions and the diagonal lemma are replaced by a more direct diagonalization argument, from first principles, based in category theory and in a sense analogous to Cantor's original argu

Mohamed Naqbi, Sebastien Loranger, Gunes Karabulut Kurt

The increasing focus on lunar exploration requires innovative power solutions to support scientific research, mining, and habitation in the Moon's extreme environment. Optical power beaming (OPB) has emerged as a promising alternative to conventional systems. However, the impact of lofted lunar dust (LLD) on optical transmissions remains poorly understood. T

Huatian Hu, Gonzalo Álvarez-Pérez, Antonio Valletta, Marialilia Pea

We propose a microscopic mechanism to electrically reconfigure the Kerr nonlinearity by modulating the concentration of free electrons in heavily doped semiconductors under a static bias. Our theory incorporates electrostatic and hydrodynamic frameworks to describe the electronic dynamics, demonstrating electrically tunable linear and nonlinear modulations.

Claudio Llosa Isenrich, Konstantinos Tsouvalas

For every positive integer $n$ we construct an example of a subgroup $L< G$ of a linear ${\rm CAT}(0)$ group $G$ such that $L$ is of finiteness type $\mathcal{F}_{n-1}$ and not $\mathcal{F}_n$, and $L$ does not admit a representation into $\mathsf{GL}_d(k)$ which is a quasi-isometric embedding for any local field $k$. We further prove that there is a faithfu

Sébastien Andreina, Pascal Zimmer, Ghassan Karame

Although distributed machine learning (distributed ML) is gaining considerable attention in the community, prior works have independently looked at instances of distributed ML in either the training or the inference phase. No prior work has examined the combined robustness stemming from distributing both the learning and the inference process. In this work,

András Gunyhó, Kassius Kohvakka, Qi-Ming Chen, Jean-Philippe Girard

The measurement of energy is a fundamental tool used, for example, in exploring the early universe, characterizing particle decay processes, as well as in quantum technology and computing. Some of the most sensitive energy detectors are thermal, i.e., bolometers and calorimeters, which operate by absorbing incoming energy, converting it into heat, and readin

Sumanta Bhandary, Emiliano Poli, Gilberto Teobaldi, David D. O'Regan

Transition-metal phthalocyanine molecules have attracted considerable interest in the context of spintronics device development due to their amenability to diverse bonding regimes and their intrinsic magnetism. The latter is highly influenced by the quantum fluctuations that arise at the inevitable metal-molecule interface in a device architecture. In this s

Rida Qadri, Piotr Mirowski, Aroussiak Gabriellan, Farbod Mehr

This paper proposes dialogue as a method for evaluating generative AI tools for culturally-situated creative practice, that recognizes the socially situated nature of art. Drawing on sociologist Howard Becker's concept of Art Worlds, this method expands the scope of traditional AI and creativity evaluations beyond benchmarks, user studies with crowd-workers,

Paul Soulos, Henry Conklin, Mattia Opper, Paul Smolensky

Neural networks continue to struggle with compositional generalization, and this issue is exacerbated by a lack of massive pre-training. One successful approach for developing neural systems which exhibit human-like compositional generalization is \textit{hybrid} neurosymbolic techniques. However, these techniques run into the core issues that plague symboli

Shuo Sun, Meng Qi, Zuo-Jun Max Shen

In this work, we consider an online robust Markov Decision Process (MDP) where we have the information of finitely many prototypes of the underlying transition kernel. We consider an adaptively updated ambiguity set of the prototypes and propose an algorithm that efficiently identifies the true underlying transition kernel while guaranteeing the performance

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

A measurement of the $CP$-violating parameters in $B_s^0 \to D_s^{\mp} K^{\pm}$ decays is reported, based on the analysis of proton-proton collision data collected by the LHCb experiment corresponding to an integrated luminosity of $6\,\mathrm{fb}^{-1}$ at a centre-of-mass energy of $13 \,\mathrm{TeV}$. The measured parameters are obtained with a decay-time

Tiago de Lima, Emiliano Lorini, Elise Perrotin, François Schwarzentruber

We introduce a novel language for reasoning about agents' cognitive attitudes of both epistemic and motivational type. We interpret it by means of a computationally grounded semantics using belief bases. Our language includes five types of modal operators for implicit belief, complete attraction, complete repulsion, realistic attraction and realistic repulsi

A. Strugarek, A. García Muñoz, A. S. Brun, A. Paul

Exoplanets on close-in orbit are subject to intense X-ray and ultraviolet (XUV) irradiation from their star. Their atmosphere therefore heats up, sometimes to the point where it thermally escapes from the gravitational potential of the planet. Nonetheless, XUV is not the only source of heating in such atmospheres. Indeed, close-in exoplanets are embedded in

Wei Zhang, Mingjian Tang, Haoxuan Mu, Xingzi Yang

In many biological materials such as nacre and bone, the material structure consists of hard grains and soft interfaces, with the interfaces playing a significant role in the material's mechanical behavior. This type of structures has been utilized in the design of various bio-inspired composite materials. Such applications often require the materials to exh

Benjamin Landon

We consider the characteristic function of linear spectral statistics of generalized Wigner matrices. We provide an expansion of the characteristic function with error $\mathcal{O} ( N^{-1})$ around its limiting Gaussian form, and identify sub-leading non-Gaussian corrections of size $\mathcal{O} (N^{-1/2})$. Prior expansions with this error rate held only f

John Fullerton, Naëmi Leo, Jakub Jurczyk, Claire Donnelly

Magnetic skyrmions are chiral spin textures with rich physics and great potential for unconventional computing. Typically, skyrmions form in bulk crystals with reduced symmetry or ultrathin film multilayers involving heavy metals. Here, we demonstrate the formation of fractional Bloch skyrmion tubes at room temperature by 3D printing ferromagnetic double-hel

Rafael Haag Petasny, Thaísa Tamusiunas

We introduce partial semigroupoid actions on sets and demonstrate that each such action admits universal globalization. Our construction extends the universal globalization for partial category actions given by P. Nystedt (Lundstr\"om) and the tensor product globalization for strong partial semigroup actions given by G. Kudryavtseva and V. Laan, thereby unif

Claudio Bonanno, Pietro Butti, Margarita García Pérez, Antonio González-Arroyo

We present the first lattice determination of the SUSY $\mathrm{SU}(N)$ Yang-Mills gluino condensate at large $N$. We exploit large-$N$ twisted volume reduction, and present two determinations based on the Banks-Casher relation and on a Gell-Mann-Oakes-Renner-like formula, both giving perfectly compatible results. By expressing the lattice results in the Nov

Yung-Yeh Chang, Kazuma Saito, Chen-Hsuan Hsu

Twisted bilayer graphene exhibits prominent correlated phenomena in two distinct regimes: a Kondo lattice near the magic angle, resembling heavy fermion systems, and a triangular correlated domain wall network under interlayer bias, akin to sliding Luttinger liquids previously introduced for cuprates. Combining these characteristics, here we investigate a sy

Bruno W. Mintz, Itai Y. Pinheiro, Rui Aquino

The axioms of Quantum Mechanics require that the hamiltonian of any closed system is self-adjoint, so that energy levels are real and time evolution preserves probability. On the other hand, non-hermitian hamiltonians with ${\cal{PT}}$-symmetry can have both real spectra and unitary time evolution. In this paper, we study in detail a pair of quantum oscillat

Kyle Thompson, Nuno Saavedra, Pedro Carrott, Kevin Fisher

Formal verification using proof assistants, such as Coq, enables the creation of high-quality software. However, the verification process requires significant expertise and manual effort to write proofs. Recent work has explored automating proof synthesis using machine learning and large language models (LLMs). This work has shown that identifying relevant p

Simon Thorne

Generative AI and Large Language Models (LLMs) hold promise for automating spreadsheet formula creation. However, due to hallucinations, bias and variable user skill, outputs obtained from generative AI cannot be assumed to be accurate or trustworthy. To address these challenges, a trustworthiness framework is proposed based on evaluating the transparency an

Frank Obernosterer, Raimund Meyer, Robert Koch, Gerd Kilian

In quantum computing systems the quantum states of qubits can be modified among others by applying light pulses. In order to achieve low computing error rates these pulses have to be precisely shaped in magnitude and phase. In practical applications, both acousto-optic (AOM) and electro-optic modulators (EOM) are used for this purpose. The advantages of EOMs

Jingwei Guo, Tao Jiang, Zuoqin Wang, Xuerui Yang

The purpose of this paper is twofold. One is to investigate the properties of the zeros of cross-products of Bessel functions or derivatives of ultraspherical Bessel functions, as well as the properties of the zeros of the derivative of the first-kind ultraspherical Bessel function. The properties we study include asymptotics (with uniform and nonuniform rem

Xinghang Li, Peiyan Li, Long Qian, Minghuan Liu

To utilize Foundation Vision Language Models (VLMs) for robotic tasks and motion planning, the community has proposed different methods for injecting action components into VLMs and building the Vision-Language-Action models (VLAs). In this work, we disclose the key factors that significantly influence the performance of VLA on robot manipulation problems an

Carlos Caleiro, Pedro Filipe, Sérgio Marcelino

The notion of a non-deterministic logical matrix (where connectives are interpreted as multi-functions) extends the traditional semantics for propositional logics based on logical matrices (where connectives are interpreted as functions). This extension allows for finitely characterizing a much wider class of logics, and has proven decisive in a myriad of re

Shilin Sun, Wenbin An, Feng Tian, Fang Nan

Artificial intelligence (AI) has rapidly developed through advancements in computational power and the growth of massive datasets. However, this progress has also heightened challenges in interpreting the "black-box" nature of AI models. To address these concerns, eXplainable AI (XAI) has emerged with a focus on transparency and interpretability to enhance h

Jorge David Castaño-Yepes, Enrique Muñoz

In this article, we analyze the effects of stochastic magnetic fluctuations with respect to an intense magnetic field background over the yields for photon and dilepton emission processes in a thermalized quark-gluon plasma phase. Such stochastic fluctuations model the effects of nearly random initial conditions for the nuclei participating in non-central he

Kevin You

Text Normalization and Semantic Parsing have numerous applications in natural language processing, such as natural language programming, paraphrasing, data augmentation, constructing expert systems, text matching, and more. Despite the prominent achievements of deep learning in Large Language Models (LLMs), the interpretability of neural network architecture

Will Sawin

We give results on the asymptotic in Waring's problem over function fields that are stronger than the results obtained over the integers using the main conjecture in Vinogradov's mean value theorem. Similar estimates apply to Manin's conjecture for Fermat hypersurfaces over function fields. Following an idea of Pugin, rather than applying analytic methods to

Igor G. Smit, Yaoxin Wu, Pavel Troubil, Yingqian Zhang

Neural combinatorial optimization (NCO) has gained significant attention due to the potential of deep learning to efficiently solve combinatorial optimization problems. NCO has been widely applied to job shop scheduling problems (JSPs) with the current focus predominantly on deterministic problems. In this paper, we propose a novel attention-based scenario p

Sumukh Bhanushali, Debnath Maiti, Phaneendra Bikkina, Esko Mikkola

This work presents a supervised machine-learning (ML) approach for blind digital calibration of SAR ADCs without requiring prior knowledge of errors. A low-speed reference ADC is used to train a shallow neural network (NN) to estimate errors in a high-speed ADC by comparing the outputs of the ADCs when their sampling instants align and subtracting these erro

Vera Neplenbroek, Arianna Bisazza, Raquel Fernández

Recent generative large language models (LLMs) show remarkable performance in non-English languages, but when prompted in those languages they tend to express higher harmful social biases and toxicity levels. Prior work has shown that finetuning on specialized datasets can mitigate this behavior, and doing so in English can transfer to other languages. In th

Sasha Allegrini, Loris Del Grosso, Antonio J. Iovino, Alfredo Urbano

In this work, we investigate the generation of primordial black holes (PBHs) within the framework of single-field inflationary models and their compatibility with the cosmological history of the Universe. Our results suggest that, depending on the masses of the formed PBHs, single-field inflation models require more than fine-tuning a potential to induce ult

Ayush Khot, Xihaier Luo, Ai Kagawa, Shinjae Yoo

Uncertainty quantification (UQ) methods play an important role in reducing errors in weather forecasting. Conventional approaches in UQ for weather forecasting rely on generating an ensemble of forecasts from physics-based simulations to estimate the uncertainty. However, it is computationally expensive to generate many forecasts to predict real-time extreme

Rui Ma, Olga Lyraki, Daniel Wehner, Jochen Guck

Selective plane illumination microscopy (SPIM), also known as light sheet fluorescence microscopy, provides high specificity through fluorescence labeling. However, it lacks complementary structural information from the surrounding context, which is essential for the comprehensive analysis of biological samples. Here, we present a high-resolution, multimodal

ATLAS Collaboration

A search for exotic decays of the 125 GeV Higgs boson into a pair of new spin-0 particles, $H \to aa$, where one decays into a photon pair and the other into a $\tau$-lepton pair, is presented. Hadronic decays of the $\tau$-leptons are considered and reconstructed using a dedicated tagger for collimated $\tau$-lepton pairs. The search uses 140 fb$^{-1}$ of p

Rishabh B. Mishra, Wedyan Babatain, Nazek El-Atab, Aftab M. Hussain

In this work, a large area, low cost and flexible polymer/paper-based double touch mode capacitive pressure sensor is demonstrated. Garage fabrication processes are used which only require cutting, taping and assembly of aluminum (Al) coated polyimide (PI) foil, PI tape and double-sided scotch tape. The presented pressure sensor operates in different pressur

Kelly E. Miller, Dionysis I. Foustoukos, George Cody, Conel M. O'D. Alexander

Titan's abundant atmospheric N2 and CH4 gases are notable characteristics of the moon that may help constrain its origins and evolution. Previous work suggests that atmospheric CH4 is lost on geologically short timescales and may be replenished from an interior source. Isotopic and noble gas constraints indicate that N2 may derive from a mixture of NH3 ice a

Maria Dias Astros, Stefan Vogl

Sterile neutrinos are a simple yet compelling addition to the Standard Model. For right-handed neutrinos with masses below the electroweak scale, leptogenesis can proceed through CP-violating oscillations of the sterile neutrinos. This is known as ARS or freeze-in leptogenesis. However, the ARS scenario requires the right-handed neutrinos to have a high degr

Erdenebayar Bayarmagnai, Fatemeh Mohammadi, Rémi Prébet

Loop invariants are properties of a program loop that hold both before and after each iteration of the loop. They are often used to verify programs and ensure that algorithms consistently produce correct results during execution. Consequently, generating invariants becomes a crucial task for loops. We specifically focus on polynomial loops, where both the lo

Danila Rukhovich, Elona Dupont, Dimitrios Mallis, Kseniya Cherenkova

Computer-Aided Design (CAD) models are typically constructed by sequentially drawing parametric sketches and applying CAD operations to obtain a 3D model. The problem of 3D CAD reverse engineering consists of reconstructing the sketch and CAD operation sequences from 3D representations such as point clouds. In this paper, we address this challenge through no

Anna Naumkina, Ramón G. Plaza

A family of generalized Korteweg-de Vries-Burgers equations in one space dimension with a nonlinear source is considered. The purpose of this contribution is twofold. On one hand, the local well-posedness of the Cauchy problem on periodic Sobolev spaces and the regularity of the data-solution map are established. On the other hand, it is proved that periodic

Mustapha Amara, Chaala Katar, Maroua Ltifi

In this paper, we prove the global existence, uniqueness and the continuity in $L^2$ of the incompressible Navier-Stokes equations with damping $f(|u|)u$, where $f$ is an increasing, convex and differentiable function on $\mathbb{R}^+$, null at zero.

Adi Shuchami, Teddy Lazebnik

Large-scale crises, including wars and pandemics, have repeatedly shaped human history, and their simultaneous occurrence presents profound challenges to societies. Understanding the dynamics of epidemic spread during warfare is essential for developing effective containment strategies in complex conflict zones. While research has explored epidemic models in

Héctor M. Castro-Beltrán, Ricardo Román-Ancheyta

We obtain time-resolved spectra of spontaneous emission and resonance fluorescence of a single multilevel emitter where two antiparallel transitions interfere and cause quantum beats. After rising as a single broad peak, the spontaneous emission spectrum turns into a doublet of subnatural peaks and then fades for long times. For strong field resonance fluore

S. Taheri Monfared

This work reviews recent developments in the Parton Branching (PB) method, focusing on its application to Transverse Momentum Dependent (TMD) parton distributions and the implementation of TMD evolution equations in Monte Carlo generators. Key advancements include the inclusion of photon and heavy electroweak boson radiation in the evolution equations and th