November 2024 arXiv papers — page 37

Gregory Gabadadze, David N. Spergel, Giorgi Tukhashvili

We study inflation in a recently proposed gravitational effective field theory describing the trace anomaly. The theory requires an additional scalar which is massless in the early universe. This scalar -- referenced as an anomalyon -- couples to the familiar matter and radiation through the gauge field trace anomaly. We derive a class of cosmological soluti

Antonios Nathanail, Yosuke Mizuno, Ioannis Contopoulos, Christian M. Fromm

Context. The accretion of magnetized plasma onto black holes is a complex and dynamic process, where the magnetic field plays a crucial role. The amount of magnetic flux accumulated near the event horizon significantly impacts the accretion flow behavior. Resistivity, a measure of how easily magnetic fields can dissipate, is thought to be a key factor influe

Xuweiyi Chen, Zezhou Cheng

Self-supervised learning has emerged as a promising approach for acquiring transferable 3D representations from unlabeled 3D point clouds. Unlike 2D images, which are widely accessible, acquiring 3D assets requires specialized expertise or professional 3D scanning equipment, making it difficult to scale and raising copyright concerns. To address these challe

Yao-Chih Lee, Erika Lu, Sarah Rumbley, Michal Geyer

Given a video and a set of input object masks, an omnimatte method aims to decompose the video into semantically meaningful layers containing individual objects along with their associated effects, such as shadows and reflections. Existing omnimatte methods assume a static background or accurate pose and depth estimation and produce poor decompositions when

Bibandhan Poudyal, David Soriano Panõs, Gourab Ghoshal

Non-pharmaceutical interventions (NPIs) aimed at limiting human mobility have demonstrated success in curbing the transmission of airborne diseases. However, their effectiveness in managing vector-borne diseases remains less clear. In this study, we introduce a framework that integrates mobility data with vulnerability matrices to evaluate the differential i

Xuan-Bac Nguyen, Manuel Serna-Aguilera, Arabinda Kumar Choudhary, Pawan Sinha

Vision-Brain Understanding (VBU) aims to extract visual information perceived by humans from brain activity recorded through functional Magnetic Resonance Imaging (fMRI). Despite notable advancements in recent years, existing studies in VBU continue to face the challenge of catastrophic forgetting, where models lose knowledge from prior subjects as they adap

Zechen Bai, Jianxiong Gao, Ziteng Gao, Pichao Wang

Visual tokenizers are fundamental to image generation. They convert visual data into discrete tokens, enabling transformer-based models to excel at image generation. Despite their success, VQ-based tokenizers like VQGAN face significant limitations due to constrained vocabulary sizes. Simply expanding the codebook often leads to training instability and dimi

Xuweiyi Chen, Markus Marks, Zezhou Cheng

Mid-level vision capabilities - such as generic object localization and 3D geometric understanding - are not only fundamental to human vision but are also crucial for many real-world applications of computer vision. These abilities emerge with minimal supervision during the early stages of human visual development. Despite their significance, current self-su

John Flynn, Michael Broxton, Lukas Murmann, Lucy Chai

We present a novel neural algorithm for performing high-quality, high-resolution, real-time novel view synthesis. From a sparse set of input RGB images or videos streams, our network both reconstructs the 3D scene and renders novel views at 1080p resolution at 30fps on an NVIDIA A100. Our feed-forward network generalizes across a wide variety of datasets and

Sohee Yang, Nora Kassner, Elena Gribovskaya, Sebastian Riedel

We evaluate how well Large Language Models (LLMs) latently recall and compose facts to answer multi-hop queries like "In the year Scarlett Johansson was born, the Summer Olympics were hosted in the country of". One major challenge in such evaluation is that LLMs may have developed shortcuts by encountering the head entity "Scarlett Johansson" and the answer

Seyed Hamidreza Mirpoorian, Karsten Jedamzik, Levon Pogosian

We investigate the extent to which modifying the ionization history at cosmological recombination can relieve the Hubble tension, taking into account all relevant datasets and considering the implications for the galaxy clustering parameter $S_8$ and the matter density fraction $\Omega_m$. We use the linear response approximation to systematically search for

Jin Yao, Hao Gu, Xuweiyi Chen, Jiayun Wang

We propose and study open-vocabulary monocular 3D detection, a novel task that aims to detect objects of any categores in metric 3D space from a single RGB image. Existing 3D object detectors either rely on costly sensors such as LiDAR or multi-view setups, or remain confined to closed vocabularies settings with limited categories, restricting their applicab

E. A. Zaborowski, P. Taylor, K. Honscheid, A. Cuceu

The physical size of the sound horizon at recombination is a powerful source of information for early-time measurements of the Hubble constant $H_0$, and many proposed solutions to the Hubble tension therefore involve modifications to this scale. In light of this, there has been growing interest in measuring $H_0$ independently of the sound horizon. We prese

Yuanyang Yin, Yaqi Zhao, Mingwu Zheng, Ke Lin

Achieving optimal performance of video diffusion transformers within given data and compute budget is crucial due to their high training costs. This necessitates precisely determining the optimal model size and training hyperparameters before large-scale training. While scaling laws are employed in language models to predict performance, their existence and

Hanhui Wang, Yihua Zhang, Ruizheng Bai, Yue Zhao

Recent advancements in diffusion models have made generative image editing more accessible, enabling creative edits but raising ethical concerns, particularly regarding malicious edits to human portraits that threaten privacy and identity security. Existing protection methods primarily rely on adversarial perturbations to nullify edits but often fail against

Amulya Mohan, Hanmeng Zhan

We study the discrete quantum walk on a regular graph $X$ that assigns negative identity coins to marked vertices $S$ and Grover coins to the unmarked ones. We find combinatorial bases for the eigenspaces of the transtion matrix, and derive a formula for the average vertex mixing matrix $\AMM$. We then find bounds for entries in $\AMM$, and study when these

Mahdi Zamani

This short text tried to establish a big picture of what evidential statistics is about and how an ideal inference method should behave. Moreover, by examining shortcomings of some of the currently used methods for measuring evidence and utilizing some intuitive principles, we motivated the Relative Belief Ratio as the primary method of characterizing statis

Shouvik Sur, Lei Chen, Yiming Wang, Chandan Setty

In topological materials, Berry curvature leads to intrinsic Hall responses. Focusing on time-reversal symmetric systems with broken inversion symmetry, a spontaneoous (zero magnetic field) Hall effect is expected to develop under an applied electric field. Motivated by recent developments in Weyl-Kondo semimetals, here we advance a fully nonequilibrium (FNE

Jieshuang Wang, Brian Reville, Frank M. Rieger, Felix A. Aharonian

Radio galaxies have long been considered as potential sources of ultra-high-energy cosmic rays (UHECRs). Recent analyses of the UHECR spectrum, composition, and arrival directions indicate that the nearest radio galaxy, Centaurus A, could be linked to the reported dipole anisotropy, though the mechanism underlying the acceleration remains elusive. In this Le

Atakan Hilmi Fırat, Raji Ashenafi Mamade

We supplement the string field theory action with boundary terms to make its variational principle well-posed. Central to our considerations is the violation of the stress-energy tensor conservation in non-compact CFTs due to the boundary terms. This manifests as the failure of the cyclicity of the BRST operator, which encodes the target space integration by

Ray Shang

A classical fact is that through any $d+3$ general points in $\mathbb{P}_\mathbb{C}^d$ there exists a unique rational normal curve of degree $d$ passing through them. We generalize this by proving the following: when $n$ is odd, for any $\binom{n+2}{2} + n+1$ general points in $\mathbb{P}_\mathbb{C}^{\binom{n+2}{2} - 1}$, there exist at least $2^{n(n-1)}$ de

Francisco J. Muñoz, Juan Carlos Nuño

We investigate a variation of the classical voter model in which the set of influencing agents depends on an individual's current opinion. The initial population consists of a random sample of equally sized sub-populations for each state, and two types of interactions are considered: (i) direct neighbors, and (ii) second neighbors (friends of direct neighbor

Harshit Sharma, Udaysinh T. Bhosale

Sharma and Bhosale [\href{https://journals.aps.org/prb/abstract/10.1103/PhysRevB.109.014412}{Phys. Rev. B \textbf{109}, 014412 (2024)}; \href{https://journals.aps.org/prb/abstract/10.1103/PhysRevB.110.064313}{Phys. Rev. B \textbf{110}, 064313,(2024)}] recently introduced an $N$-spin Floquet model with infinite-range Ising interactions. There, we have shown t

Chethan Krishnan, Sarthak Talukdar

In 1+1 dimensions, the equations of motion of the Horowitz-Polchinski (HP) effective string have a re-writing in terms of a first order system. This is attributed to FZZ duality. In this note, we observe that a similar re-writing exists in higher dimensions, so that the degree of the dilaton-winding subsystem reduces to first order. The 1+1 first order equat

Bernd Von Gimborn, Philipp Ausserlechner, Markus Vincze, Stefan Thalhammer

Zero-shot object pose estimation enables the retrieval of object poses from images without necessitating object-specific training. In recent approaches this is facilitated by vision foundation models (VFM), which are pre-trained models that are effectively general-purpose feature extractors. The characteristics exhibited by these VFMs vary depending on the t

Leo Gold, Adam Bienkowski, David Sidoti, Krishna Pattipati

The Multi-Objective Shortest-Path (MOS) problem finds a set of Pareto-optimal solutions from a start node to a destination node in a multi-attribute graph. The literature explores multi-objective A*-style algorithmic approaches to solving the NP-hard MOS problem. These approaches use consistent heuristics to compute an exact set of solutions for the goal nod

Jiaan Han, Junxiao Chen, Yanzhe Fu

We introduce CatNet, an algorithm that effectively controls False Discovery Rate (FDR) and selects significant features in LSTM. CatNet employs the derivative of SHAP values to quantify the feature importance, and constructs a vector-formed mirror statistic for FDR control with the Gaussian Mirror algorithm. To avoid instability due to nonlinear or temporal

Or Hirschorn, Shai Avidan

Category-Agnostic Pose Estimation (CAPE) localizes keypoints across diverse object categories with a single model, using one or a few annotated support images. Recent works have shown that using a pose graph (i.e., treating keypoints as nodes in a graph rather than isolated points) helps handle occlusions and break symmetry. However, these methods assume a s

Yu-Tong Wang, Qi-Hang Ye, Jun-Yong Yan, Yufei Qiao

Quantum emitters are a key component in photonic quantum technologies. Enhancing their single-photon emission by engineering the photonic environment using cavities can significantly improve the overall efficiency in quantum information processing. However, this enhancement is often constrained by the need for precise nanoscale control over the emitter's pos

Ray Shang

A classical fact is that normal bundles of rational normal curves are well-balanced. We generalize this by proving that all Veronese normal bundles are slope semistable. We also determine the line bundle decomposition of the restriction of degree 2 Veronese normal bundles to lines and rational normal curves.

Charita Dellaporta, Patrick O'Hara, Theodoros Damoulas

Decision making under uncertainty is challenging as the data-generating process (DGP) is often unknown. Bayesian inference proceeds by estimating the DGP through posterior beliefs on the model's parameters. However, minimising the expected risk under these beliefs can lead to suboptimal decisions due to model uncertainty or limited, noisy observations. To ad

Yanqing Liu, Xianhang Li, Zeyu Wang, Bingchen Zhao

Previous works show that noisy, web-crawled image-text pairs may limit vision-language pretraining like CLIP and propose learning with synthetic captions as a promising alternative. Our work continues this effort, introducing two simple yet effective designs to better leverage richly described synthetic captions. Firstly, by observing a strong inverse effect

Jianlei Huang, Marc Härkönen, Markus Lange-Hegermann, Bogdan Raiţă

Working with systems of partial differential equations (PDEs) is a fundamental task in computational science. Well-posed systems are addressed by numerical solvers or neural operators, whereas systems described by data are often addressed by PINNs or Gaussian processes. In this work, we propose Boundary Ehrenpreis--Palamodov Gaussian Processes (B-EPGPs), a n

Gabriel Okasa, Alberto de León, Michaela Strinzel, Anne Jorstad

Peer review in grant evaluation informs funding decisions, but the contents of peer review reports are rarely analyzed. In this work, we develop a thoroughly tested pipeline to analyze the texts of grant peer review reports using methods from applied Natural Language Processing (NLP) and machine learning. We start by developing twelve categories reflecting c

O. S. Potiienko, D. V. Zhuravel, D. M. Riabov, N. O. Chudak

A comprehensive review of the single diffraction dissociation duality-based model at low missing masses have been presented. The distinguishing feature of the model is the nonlinear Regge proton trajectory used to account for the resonances contributions to the cross-sections. It helps classify and understand the spectrum of excited states of proton and thei

Eneko Lazpita, Andrea Mares, Pedro Quintero, Jesús Garicano-Mena

In this study, we present a comprehensive numerical analysis of blood flow within human left ventricle models, with particular emphasis on optimizing simulation conditions to enhance the realism and computational efficiency of heart flow dynamics. The objective is to determine the most effective mesh configurations, flow conditions, and boundary settings nec

Edoardo Di Martino, Alessandro Galeazzi, Michele Starnini, Walter Quattrociocchi

The entertainment-driven nature of social media encourages users to engage with like-minded individuals and consume content aligned with their beliefs, limiting exposure to diverse perspectives. Simultaneously, users migrate between platforms, either due to moderation policies like de-platforming or in search of environments better suited to their preference

J. J. Ruiz-Lorenzo, M. Dudka, M. Krasnytska, Yu. Holovatch

Usually, the impact of structural disorder on the magnetic phase transition in the 3D Ising model is analyzed within the framework of quenched dilution by a non-magnetic component, where some lattice sites are occupied by Ising spins, while others are non-magnetic. This kind of quenched dilution, according to the Harris criterion, leads to a change in the cr

Amirhesam Abedsoltan, Siyuan Ma, Parthe Pandit, Mikhail Belkin

Classical kernel machines have historically faced significant challenges in scaling to large datasets and model sizes--a key ingredient that has driven the success of neural networks. In this paper, we present a new methodology for building kernel machines that can scale efficiently with both data size and model size. Our algorithm introduces delayed project

Zun Wang, Jialu Li, Han Lin, Jaehong Yoon

Storytelling video generation (SVG) aims to produce coherent and visually rich multi-scene videos that follow a structured narrative. Existing methods primarily employ LLM for high-level planning to decompose a story into scene-level descriptions, which are then independently generated and stitched together. However, these approaches struggle with generating

Lucas Leclerc, Constantin Dalyac, Pascale Bendotti, Rodolphe Griset

In the quantum optimization paradigm, variational quantum algorithms face challenges with hardware-specific and instance-dependent parameter tuning, which can lead to computational inefficiencies. The promising potential of parameter transferability across problem instances with similar local structures has been demonstrated in the context of the quantum app

Madjda Kamel, Abdelaali Boudjemaa

We study the stationary and dynamical properties of three-dimensional trapped Bose-Einstein condensates with attractive interactions subjected to a random potential. To this end, a variational method is applied to solve the underlying Gross-Pitaevskii equation. We derive analytical predictions for the energy, the equilibrium width, and evolution laws of the

Serena An, Katherine Tung, Yuchong Zhang

The M-convexity of dual Schubert polynomials was first proven by Huh, Matherne, M\'esz\'aros, and St. Dizier in 2022. We give a full characterization of the supports of dual Schubert polynomials, which yields an elementary alternative proof of the M-convexity result, and furthermore strengthens it by explicitly characterizing the vertices of their Newton pol

Jordi Pérez-Guijarro, Alba Pagès-Zamora, Javier R. Fonollosa

To address the challenge posed by noise in real quantum devices, quantum error mitigation techniques play a crucial role. These techniques are resource-efficient, making them suitable for implementation in noisy intermediate-scale quantum devices, unlike the more resource-intensive quantum error correction codes. A notable example of such a technique is Clif

Yunfei He, David C. Moore, Yubo Wang, Spencer Ware

Ferroelectric (Fe) materials-based devices show great promise for non-volatile memory applications, yet few demonstrate reliable operation at elevated temperatures. In this work, we demonstrate Ni/Al0.68Sc0.32N/4H-SiC metal-ferroelectric-semiconductor capacitors for high-temperature non-volatile memory applications. Our 30-nm thick ferroelectric Al0.68Sc0.32

Kirill Sokolov

We consider the simultaneous optimal transportation of measures, where the target marginal is not necessarily fixed. For this problem, we prove the existence of a solution for completely regular spaces and investigate the structure of the discrete problem. We establish a connection between the Monge problem and the Kantorovich problem by showing that their f

Aleteia Araujo, Breno Costa, Joao Bachiega, Leonardo R. Carvalho

Fog Computing provides computational resources close to the end user, supporting low-latency and high-bandwidth communications. It supports IoT applications, enabling real-time data processing, analytics, and decision-making at the edge of the network. However, the high distribution of its constituent nodes and resource-restricted devices interconnected by h

Yehia Lalili, Meriem Halimi, Toufik Bouden

Under Partial shading conditions (PSC), traditional MPPT methods such as, P&O, IncCon and SMC, cannot track down the Global MPP. Thus, the energy conversion of the PV modules will decrease. To overcome this drawback, two evolutionary algorithms; PSO and CS, were presented. Also, the study introduces a hybrid optimization method to enhance the overall perform

Yaqi Zhao, Yuanyang Yin, Lin Li, Mingan Lin

Does seeing always mean knowing? Large Vision-Language Models (LVLMs) integrate separately pre-trained vision and language components, often using CLIP-ViT as vision backbone. However, these models frequently encounter a core issue of "cognitive misalignment" between the vision encoder (VE) and the large language model (LLM). Specifically, the VE's represent

Bill Clintone Oyomo, Leah Wairimu Mungai, Geoffrey Arusei, Michael Atambo

MAX phases are used on an industrial scale in the transportation, armour, and furnace development sectors, among others. However, data on the dynamical properties of these materials under varying temperature and pressure conditions are rare or unavailable. This study reports on the dynamical properties of the elastic constants of Ti2AlC, under these conditio

Diya Vatsavai, Anya Iyer, Ashwin A. Nair

Parkinsons disease, the fastest growing neurodegenerative disorder globally, has seen a 50 percent increase in cases within just two years. As speech, memory, and motor symptoms worsen over time, early diagnosis is crucial for preserving patients quality of life. While machine-learning-based detection has shown promise, relying on a single feature for classi

Shashwat Kumar, Xinyuan You, Xanthe Croot, Tianpu Zhao

Qubits that are intrinsically insensitive to depolarization and dephasing errors promise to significantly reduce the overhead of fault-tolerant quantum computing. At their optimal operating points, the logical states of these qubits exhibit both exponentially suppressed matrix elements and sweet spots in energy dispersion, rendering the qubits immune to depo

Yuri Kozitsky, Michael Röckner

An infinite population of point entities dwelling in the habitat $X=\mathds{R}^d$ is studied. Its members arrive in and depart from $X$ at random. The departure rate has a term corresponding to a logistic-type interaction between the entities. Thereby, the corresponding Kolmogorov operator $L$ has an additive quadratic term, which usually produces essential

Yue Yu, Zhengxing Chen, Aston Zhang, Liang Tan

Reward modeling is crucial for aligning large language models (LLMs) with human preferences, especially in reinforcement learning from human feedback (RLHF). However, current reward models mainly produce scalar scores and struggle to incorporate critiques in a natural language format. We hypothesize that predicting both critiques and the scalar reward would

Dietmar Jannach, Alan Said, Marko Tkalčič, Markus Zanker

In the area of recommender systems, the vast majority of research efforts is spent on developing increasingly sophisticated recommendation models, also using increasingly more computational resources. Unfortunately, most of these research efforts target a very small set of application domains, mostly e-commerce and media recommendation. Furthermore, many of

Ian Dunn, David R. Koes

Deep generative models that produce novel molecular structures have the potential to facilitate chemical discovery. Flow matching is a recently proposed generative modeling framework that has achieved impressive performance on a variety of tasks including those on biomolecular structures. The seminal flow matching framework was developed only for continuous

Matias Alvarado, Patricio Pérez-Piña

We prove an equidistribution result about Hecke orbits on the Picard group of Shimura curves coming from definite quaternion algebras over function fields. In particular, we show the equidistribution of Hecke orbits of supersingular Drinfeld modules of rank 2. Our approach is via the automorphic method, using bounds for coefficients of cuspidal automorphic f

Jean Marie Tshimula, Xavier Ndona, D'Jeff K. Nkashama, Pierre-Martin Tardif

Jailbreak prompts pose a significant threat in AI and cybersecurity, as they are crafted to bypass ethical safeguards in large language models, potentially enabling misuse by cybercriminals. This paper analyzes jailbreak prompts from a cyber defense perspective, exploring techniques like prompt injection and context manipulation that allow harmful content ge

Fakrul Islam Tushar

Background: AI-based classification models are essential for improving lung cancer diagnosis. However, the relative performance of lesion-level versus chest-region models in internal and external datasets remains unclear. Purpose: This study evaluates the performance of lesion-level and chest-region models for lung cancer classification, comparing their effe

Bikram Bir, Harsha Hutridurga, Amiya K. Pani

This paper deals with a fully discrete numerical scheme for the incompressible Chemotaxis(Keller-Segel)-Navier-Stokes system. Based on a discontinuous Galerkin finite element scheme in the spatial directions, a semi-implicit first-order finite difference method in the temporal direction is applied to derive a completely discrete scheme. With the help of a ne

Ghorbanali Haghighatdoost

In this work we study the invariant optimal control problem on Lie groupoids. We show that any invariant optimal control problem on a Lie groupoid reduces to its co-adjoint Lie algebroid. In the final section of the paper, we present an illustrative example.

Kavindu Gunathilake, Indrajith Ekanayake

Microservice architecture is widely adopted among distributed systems. It follows the modular approach that decomposes large software applications into independent services. Kubernetes has become the standard tool for managing these microservices. It stores sensitive information like database passwords, API keys, and access tokens as Secret Objects. There ar

Sanjana Ramprasad, Byron C. Wallace

Modern LLMs can now produce highly readable abstractive summaries, to the point that traditional automated metrics for evaluating summary quality, such as ROUGE, have saturated. However, LLMs still sometimes introduce inaccuracies into summaries, i.e., information inconsistent with or unsupported by the corresponding source. Measuring the occurrence of these

George Dimopoulos, Sabrina De Los Angeles Reverol Parra, Parmita Mondal, Michael Udin

Subarachnoid hemorrhage (SAH), typically due to intracranial aneurysms, demands precise imaging for effective treatment. Digital Subtraction Angiography (DSA), despite being the gold standard, broadly visualizes cerebral blood flow, potentially masking key details in areas. This study introduces an approach integrating a 3D vascular atlas with 2D DSA images

Bhavya Bandaru

In order to find quantum corrections to the de Sitter entropy, a new approach to higher loop Feynman integral computations on the sphere is presented. Arbitrary scalar Feynman integrals on a spherical background are brought into the generalized Euler integral (A-hypergeometric series/GKZ system) form by expressing the massive scalar propagator as a quotient

Zhi Wang, Li He, Bumho Kim, Bo Zhen

Strong coupling between light and matter in an optical cavity provides a pathway to giant polariton nonlinearity, where effective polariton-polariton interactions are mediated by materials' nonlinear responses. The pursuit of such enhanced nonlinearity at low optical excitations, potentially down to the single-particle level, has been a central focus in the

Riccardo Bartocci, Philipp Böer, Tobias Hurth

We derive and solve the renormalisation-group (RG) equation of the shape function $g_{17}(\omega,\omega_1;\mu)$, which appears at subleading power in the factorization of the inclusive decays $\bar{B} \to X_s \gamma$ and $\bar B \to X_s \ell^+\ell^-$. Our results provide the first ingredient for a next-to-leading order analysis of the respective resolved-pho

André H. A. Malavazi, Rishav Sagar, Borhan Ahmadi, Pedro R. Dieguez

Quantum batteries are emerging as highly efficient energy storage devices that can exceed classical performance limits. Although there have been significant advancements in controlling these systems, challenges remain in stabilizing stored energy and minimizing losses due to inevitable environmental interaction. In this paper, we propose a protocol that empl

Luis Sánchez Cano, Ginés Carrascal de las Heras, Guillermo Botella Juan, Alberto del Barrio García

Current asymmetric cryptography is based on the principle that while classical computers can efficiently multiply large integers, the inverse operation, factorization, is significantly more complex. For sufficiently large integers, this factorization process can take in classical computers hundreds or even thousands of years to complete. However, there exist

Ghorbanali Haghighatdoost, Rezvaneh Ayoubi

As we said in our previous work [4], the main idea of our research is to introduce a class of Lie groupoids by means of co-adjoint representation of a Lie groupoid on its isotropy Lie algebroid, which we called coadjoint Lie groupoids. In this paper, we will examine the relationship between structural mappings of the Lie algebroid associated to Lie groupoid

Emil J. Martinec, Yoav Zigdon

An effective action for NS5-branes coupled to supergravity is used to derive the full 10d form of horizon-free BPS solutions of fivebranes carrying momentum waves, including both transverse scalar and internal gauge excitations of the branes. When internal modes are highly excited, we find solutions that plausibly mediate the transition between the Coulomb p

Yiran Sun, Osama Mawlawi

Positron emission tomography (PET) is widely utilized for cancer detection due to its ability to visualize functional and biological processes in vivo. PET images are usually reconstructed from histogrammed raw data (sinograms) using traditional iterative techniques (e.g., OSEM, MLEM). Recently, deep learning (DL) methods have shown promise by directly mappi

Giovanni Canestrari

We consider discontinuous perturbations of smooth endomorphisms and show that if the perturbed family satisfies uniform mixing assumptions on standard pairs the physical measure is Lipschitz in the parameter defying the perturbation. We also study the problem of linear response for this class of perturbations. Finally we discuss the applicability of the abst

Yanwei Wang, Lirui Wang, Yilun Du, Balakumar Sundaralingam

Generative policies trained with human demonstrations can autonomously accomplish multimodal, long-horizon tasks. However, during inference, humans are often removed from the policy execution loop, limiting the ability to guide a pre-trained policy towards a specific sub-goal or trajectory shape among multiple predictions. Naive human intervention may inadve

Yuchen Li, Zhizhong Chen, Chuhan Deng, Boyan Dong

This study establishes a unified framework for interpreting dynamic capacitive responses in InGaN-based light-emitting diodes (LEDs) through forward-bias capacitance-voltage-frequency spectroscopy. A hybrid impedance model integrating series RL components and parallel C-G networks was developed to resolve distinct frequency-dependent capacitive regimes. The

Ramakanta Chapai, Alexei E. Koshelev, Matthew P. Smylie, Duck Young Chung

Van Hove singularities (vHs) located close to the Fermi level in Kagome superconductors AV3Sb5 (A = K, Rb, Cs) have profound influence on their electronic and transport characteristics. Specifically, magneto-transport and susceptibility measurements on CsV3Sb5 reveal an anomalous temperature dependence of the upper critical field H_c2 (T), characterized by a

Shiqiang Zhang, Christian W. Feldmann, Frederik Sandfort, Miriam Mathea

Mixed-integer programming (MIP) is a well-established framework for computer-aided molecular design (CAMD). By precisely encoding the molecular space and score functions, e.g., a graph neural network, the molecular design problem is represented and solved as an optimization problem, the solution of which corresponds to a molecule with optimal score. However,

Weilin Xu, Sebastian Szyller, Cory Cornelius, Luis Murillo Rojas

Adversarial examples in the digital domain against deep learning-based computer vision models allow for perturbations that are imperceptible to human eyes. However, producing similar adversarial examples in the physical world has been difficult due to the non-differentiable image distortion functions in visual sensing systems. The existing algorithms for gen

Carlo De Michele, Ayaboe K. Edoh, Gennaro Coppola

This paper introduces a family of entropy-conserving finite-difference discretizations for the compressible flow equations. In addition to conserving the primary quantities of mass, momentum, and total energy, the methods also preserve kinetic energy and pressure equilibrium. The schemes are based on finite-difference (FD) representations of the logarithmic

William Sarem

Let $\Gamma$ be a discrete and torsion-free subgroup of $\mathrm{PU}(n,1)$, the group of biholomorphisms of the unit ball in $\mathbb{C}^{n}$, denoted by $\mathbb{H}^{n}_{\mathbb{C}}$. We show that if $\Gamma$ is Abelian, then $\mathbb{H}^{n}_{\mathbb{C}}/\Gamma$ is a Stein manifold. If the critical exponent $\delta(\Gamma)$ of $\Gamma$ is less than 2, a con

Zhichao Zhang, Wei Sun, Xinyue Li, Yunhao Li

AI-driven video generation techniques have made significant progress in recent years. However, AI-generated videos (AGVs) involving human activities often exhibit substantial visual and semantic distortions, hindering the practical application of video generation technologies in real-world scenarios. To address this challenge, we conduct a pioneering study o

Kaustubh Ponkshe, Venkatapathy Subramanian, Natwar Modani, Ganesh Ramakrishnan

Most state-of-the-art techniques for Language Models (LMs) today rely on transformer-based architectures and their ubiquitous attention mechanism. However, the exponential growth in computational requirements with longer input sequences confines Transformers to handling short passages. Recent efforts have aimed to address this limitation by introducing selec

Boris Ter-Avanesov, Gunter A. Meissner

Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign currencies each with a different strike price in the payoff function. We carry out a comparative performance analysis of different stochastic vola

Maxim Khomiakov, Michael Riis Andersen, Jes Frellsen

In remote sensing there exists a common need for learning scale invariant shapes of objects like buildings. Prior works relies on tweaking multiple loss functions to convert segmentation maps into the final scale invariant representation, necessitating arduous design and optimization. For this purpose we introduce the GeoFormer, a novel architecture which pr

Yizhu Chen

Graph pooling is a family of operations which take graphs as input and produce shrinked graphs as output. Modern graph pooling methods are trainable and, in general inserted in Graph Neural Networks (GNNs) architectures as graph shrinking operators along the (deep) processing pipeline. This work proposes a novel procedure for pooling graphs, along with a nod

Konrad Norowski, Marek Foltyn, Alexander Savin, Maciej Zgirski

We use time-resolved thermometry to monitor the decay of nonequilibrium quasiparticles in superconducting Al in the temperature range from $0.3\,$K to $1.2\,$K. The quasiparticle lifetime at higher temperatures ($T>0.7\,$K) agrees well with the calculated energy flow from electrons to phonons, but at lower temperatures it is significantly shorter than the th

Iacopo Ghinassi, Lin Wang, Chris Newell, Matthew Purver

Linear Text Segmentation is the task of automatically tagging text documents with topic shifts, i.e. the places in the text where the topics change. A well-established area of research in Natural Language Processing, drawing from well-understood concepts in linguistic and computational linguistic research, the field has recently seen a lot of interest as a r

Julian Erhard, Manuel Bentele, Matthias Heizmann, Dominik Klumpp

Static analyzers are typically complex tools and thus prone to contain bugs themselves. To increase the trust in the verdict of such tools, witnesses encode key reasoning steps underlying the verdict in an exchangeable format, enabling independent validation of the reasoning by other tools. For the correctness of concurrent programs, no agreed-upon witness f

Borja Pérez-Díaz, Enrique Pérez-Montero, Igor A. Zinchenko, José M. Vílchez

The chemical enrichment in low-ionization nuclear emission-line regions (LINERs) is still an issue with spatial resolution spectroscopic data due to the lack of studies and the uncertainties in the nature of their ionizing source, despite being the most abundant type of active galaxies in the nearby Universe. Considering different scenarios for the ionizing

A. Alexandrou Himonas, Fangchi Yan

This work studies the initial-boundary value problem for both the linear Schr\"odinger equation and the cubic nonlinear Schr\"odinger equation on the half-space in higher dimensions ($n\ge 2$). First, the forced linear problem is solved on the half-space via the Fokas method and then using the obtained solution formula new and interesting linear estimates ar

Ansgar Scherp, Thomas Franz, Carsten Saathoff, Steffen Staab

The lack of a formal model of events hinders interoperability in distributed event-based systems. In this paper, we present a formal model of events, called Event-Model-F. The model is based on the foundational ontology DOLCE+DnS Ultralite (DUL) and provides comprehensive support to represent time and space, objects and persons, as well as mereological, caus

Viswa Narayanan Sankaranarayanan, Achilleas Santi Seisa, Akshit Saradagi, Sumeet Satpute

In this article, we propose a control architecture for the safe, coordinated operation of a multi-agent system with aerial (UAVs) and ground (UGVs) robots in a confined task space. We consider the case where the aerial and ground operations are coupled, enabled by the capability of the aerial robots to land on moving ground robots. The proposed method uses t

Silvia Orlanducci, Giuseppe Ammirati, Alessandro Bellucci, Daniele Catone

An efficient source of hydrated electrons generated by visible light has the potential to have a major impact on solar homogeneous catalysis. Diamond has potentially a high capability of emitting hydrated electrons, but only using ultraviolet light (lambda<225 nm). In this work, we demonstrate the efficient absorption of visible light by nanocomposites consi

Jochen Schirmer

Time-dependent density-functional theory (TDDFT) is deemed to be a formally rigorous way of dealing with the time-evolution of a many-electron system at the level of electron densities rather than the underlying wavefunctions, which in turn provides an, in principle, exact density-based approach to the treatment of electron excitations in atoms and molecules

Ziteng Wang, Nanda Rea, Tong Bao, David L. Kaplan

Recently, a class of long-period radio transients (LPTs) has been discovered, exhibiting emission on timescales thousands of times longer than radio pulsars. Several models had been proposed implicating either a strong magnetic field neutron star, isolated white dwarf pulsar, or a white dwarf binary system with a low-mass companion. While several models for

Shankar A. Deka, Umesh Vaidya

Representing nonlinear dynamical systems using the Koopman Operator and its spectrum has distinct advantages in terms of linear interpretability of the model as well as in analysis and control synthesis through the use of well-studied techniques from linear systems theory. As such, efficient computation of Koopman eigenfunctions is of paramount importance to

Shuang-Yong Zhou

Solitons in relativistic field theories are not necessarily topologically charged. In particular, non-topological solitons -- known as Q-balls -- arise naturally in nonlinear field theories endowed with attractive interactions and internal symmetries. Even without stabilizing internal symmetries, quasi-solitons known as oscillons, which are long-lived, can a

Giacomo Marmorini, Takeshi Fukuhara, Daisuke Yamamoto

Quantum state tomography serves as a key tool for identifying quantum states generated in quantum computers and simulators, typically involving local operations on individual particles or qubits to enable independent measurements. However, this approach requires an exponentially larger number of measurement setups as quantum platforms grow in size, highlight

Ronghuan Wu, Wanchao Su, Jing Liao

Scalable Vector Graphics (SVG) has become the de facto standard for vector graphics in digital design, offering resolution independence and precise control over individual elements. Despite their advantages, creating high-quality SVG content remains challenging, as it demands technical expertise with professional editing software and a considerable time inve

Sonja Hohloch, Pedro Santos

We adapt and generalize McDuff&#39;s method of probes from toric system to so called semitoric integrable systems and apply it to study the (non)displaceability properties of the fibers of $3$ examples of semitoric integrable systems.