April 2024 arXiv papers — page 34

Sooyeong Kim, Hermie Monterde, Bahman Ahmadi, Ada Chan

An $s$-pair state in a graph is a quantum state of the form $\mathbf{e}_u+s\mathbf{e}_v$, where $u$ and $v$ are vertices in the graph and $s$ is a non-zero complex number. If $s=-1$ (resp., $s=1$), then such a state is called a pair state (resp. plus state). In this paper, we develop the theory of perfect $s$-pair state transfer in continuous quantum walks,

Lavínia de Carvalho Moraes, Irene Cristina Silvério, Rafael Alexandre Sousa Marques, Bianca de Castro Anaia

Linguistic ambiguity continues to represent a significant challenge for natural language processing (NLP) systems, notwithstanding the advancements in architectures such as Transformers and BERT. Inspired by the recent success of instructional models like ChatGPT and Gemini (In 2023, the artificial intelligence was called Bard.), this study aims to analyze a

Dominique Mattei, Reinder Meinsma

We investigate obstruction classes of moduli spaces of sheaves on K3 surfaces. We extend previous results by Caldararu, explicitly determining the obstruction class and its order in the Brauer group. Our main theorem establishes a short exact sequence relating the Brauer group of the moduli space to that of the underlying K3 surface. This provides a criterio

Mohammad Akyash, Hadi Mardani Kamali

Automating hardware (HW) security vulnerability detection and mitigation during the design phase is imperative for two reasons: (i) It must be before chip fabrication, as post-fabrication fixes can be costly or even impractical; (ii) The size and complexity of modern HW raise concerns about unknown vulnerabilities compromising CIA triad. While Large Language

Chuan Luo, Federico Ferrari, James K. Guest

Tow steering technologies, such as Automated fiber placement, enable the fabrication of composite laminates with curvilinear fiber, tow, or tape paths. Designers may therefore tailor tow orientations locally according to the expected local stress state within a structure, such that strong and stiff orientations of the tow are (for example) optimized to provi

Rand Asswad, Eugenio Cinquemani, Jean-Luc Gouzé

We address online estimation of microbial growth dynamics in bioreactors from measurements of a fluorescent reporter protein synthesized along with microbial growth. We consider an extended version of standard growth models that accounts for the dynamics of reporter synthesis. We develop state estimation from sampled, noisy measurements in the cases of known

Daniel S. Abdi, Ann Almgren, Francis X. Giraldo, Isidora Jankov

This paper examines the application of adaptive mesh refinement (AMR) in the field of numerical weather prediction (NWP). We implement and assess two distinct AMR approaches and evaluate their performance through standard NWP benchmarks. In both cases, we solve the fully compressible Euler equations, fundamental to many non-hydrostatic weather models. The fi

Bowen Deng, Yihan Zhang, Andrew Parkes, Alex Bentley

Estimation of the optical properties of scattering media such as tissue is important in diagnostics as well as in the development of techniques to image deeper. As light penetrates the sample scattering events occur that alter the propagation direction of the photons in a random manner leading degradation of image quality. The distribution of the scattered l

Anthony Dowling, Ming-Cheng Cheng, Yu Liu

Thermal-Aware Scheduling (TAS) provides methods to manage the thermal dissipation of a computing chip during task execution. These methods aim to avoid issues such as accelerated aging of the device, premature failure and degraded chip performance. In this work, we implement a new TAS algorithm, VTF-TAS, which makes use of a variable temperature threshold to

Xiang Li, Yiqun Yao, Xin Jiang, Xuezhi Fang

Large language models (LLMs) have showcased profound capabilities in language understanding and generation, facilitating a wide array of applications. However, there is a notable paucity of detailed, open-sourced methodologies on efficiently scaling LLMs beyond 50 billion parameters with minimum trial-and-error cost and computational resources. In this repor

Jakob Droste, Hannah Deters, Martin Obaidi, Kurt Schneider

Modern software systems are becoming increasingly complex and opaque. The integration of explanations within software has shown the potential to address this opacity and can make the system more understandable to end-users. As a result, explainability has gained much traction as a non-functional requirement of complex systems. Understanding what type of syst

Nathanaël Berestycki, Ellen Powell

Over fourty years ago, the physicist Polyakov proposed a bold framework for string theory, in which the problem was reduced to the study of certain "random surfaces". He further made the tantalising suggestion that this theory could be explicitly solved. Recent breakthroughs from the last fifteen years have not only given a concrete mathematical basis for th

Miguel Pereira-Santaella, Ismael García-Bernete, Eduardo González-Alfonso, Almudena Alonso-Herrero

We report the detection of extended (>0.5-1kpc) high-ionization [MgIV] 4.487 $\mu$m (80 eV) emission in four local luminous infrared galaxies observed with JWST/NIRSpec. Excluding the nucleus and outflow of the Type 1 active galactic nucleus (AGN) in the sample, we find that the [MgIV] luminosity is well correlated with that of H recombination lines, which m

Prashanta Garain, Erik Lindgren, Alireza Tavakoli

In this paper, we are concerned with the H\"older regularity for solutions of the nonlocal evolutionary equation $$ \partial_t u+(-\Delta_p)^s u = 0. $$ Here, $(-\Delta_p)^s$ is the fractional $p$-Laplacian, $0<s<1$ and $1<p<2$. We establish H\"older regularity with explicit H\"older exponents. We also include the inhomogeneous equation with a bounded inhomo

Xiaoyu Zhang, Heer Zhao

In this article we study the Honda-Tate theory for log abelian varieties over an fs log point $S=(\mathrm{Spec}(\mathbf{k}),M_S)$ for $\mathbf{k}=\mathbb{F}_q$ a finite field, generalizing the classical Honda-Tate theory for abelian varieties over $\mathbf{k}$. For the standard log point $S$, we give a complete description of the isogeny classes of such log

Eric Macias-Fassio, Aythami Morales, Cristina Pruenza, Julian Fierrez

The biomedical field is among the sectors most impacted by the increasing regulation of Artificial Intelligence (AI) and data protection legislation, given the sensitivity of patient information. However, the rise of synthetic data generation methods offers a promising opportunity for data-driven technologies. In this study, we propose a statistical approach

Niclas Popp, Jan Hendrik Metzen, Matthias Hein

Multi-modal foundation models such as CLIP have showcased impressive zero-shot capabilities. However, their applicability in resource-constrained environments is limited due to their large number of parameters and high inference time. While existing approaches have scaled down the entire CLIP architecture, we focus on training smaller variants of the image e

Ji-Cai Liu

Osburn, Sahu and Straub introduced the numbers: \begin{align*} A_n^{(r,s,t)}=\sum_{k=0}^n{n\choose k}^r{n+k\choose k}^s{2k\choose n}^t, \end{align*} for non-negative integers $n,r,s,t$ with $r\ge 2$, which includes two kinds of Ap\'ery numbers and four kinds of Ap\'ery-like numbers as special cases, and showed that the numbers $\{A_n^{(r,s,t)}\}_{n\ge 0}$ sa

Liang Zhang, Anwen Hu, Haiyang Xu, Ming Yan

Charts are important for presenting and explaining complex data relationships. Recently, multimodal large language models (MLLMs) have shown remarkable capabilities in various chart understanding tasks. However, the sheer size of these models in terms of parameters and computational requirements limits their use in resource-constrained environments. In this

Atsuhide Ishida

In a previous work of 2014 on a quantum system governed by the repulsive Hamiltonian, the author proved uniqueness for short-range interactions described by a scattering operator consisting of regular and singular parts. In this paper, the singular part is assumed to have much stronger singularities and the same uniqueness theorem is proved. By applying the

Leonardo Rossi, Akbar Karimi, Andrea Prati

Current state-of-the-art two-stage models on instance segmentation task suffer from several types of imbalances. In this paper, we address the Intersection over the Union (IoU) distribution imbalance of positive input Regions of Interest (RoIs) during the training of the second stage. Our Self-Balanced R-CNN (SBR-CNN), an evolved version of the Hybrid Task C

Naman Kumar

In this letter, we show that the Semiclassical Einstein's Field Equation can be recovered using the generalized entropy $S_{gen}$. This approach is reminiscent of non-equilibrium thermodynamics. Furthermore, contrary to the entanglement equilibrium approach of deriving the semiclassical Einstein's equation, this approach does not require any such assumptions

Siddhant S. Joshi, Preeti Mukherjee, Kirsten A. Davis, James C. Davis

Computing systems face diverse and substantial cybersecurity threats. To mitigate these cybersecurity threats, software engineers need to be competent in the skill of threat modeling. In industry and academia, there are many frameworks for teaching threat modeling, but our analysis of these frameworks suggests that (1) these approaches tend to be focused on

C. B. Oliveira, A. C. Krabbe, O. L. Dors, I. A. Zinchenko

In this work, we investigated the nitrogen and oxygen abundances in a sample of galaxies with Low Ionization Nuclear Emission Regions (LINERs) in their nucleus. Optical spectroscopic data (3 600 - 10 000 {\AA}) of 40 LINERs from the Mapping Nearby Galaxies (MaNGA) survey were considered. Only objects classified as retired galaxies, i.e. whose main ionization

Steffen Herbold, Brian Valerius, Anamaria Mojica-Hanke, Isabella Lex

Recent successes in Generative Artificial Intelligence (GenAI) have led to new technologies capable of generating high-quality code, natural language, and images. The next step is to integrate GenAI technology into products, a task typically conducted by software developers. Such product development always comes with a certain risk of liability. Within this

Gina Sohn, Nathan Zhang, Kunle Olukotun

Transformer models serve as the backbone of many state-ofthe-art language models, and most use the scaled dot-product attention (SDPA) mechanism to capture relationships between tokens. However, the straightforward implementation of SDPA has quadratic compute and memory complexity with respect to the sequence length. On processor architectures such as GPUs a

J. S. Vorotyntseva, S. A. Levshakov

We report on the using of torsion-rotational transitions in the CH3OH and (13)CH3OH molecules to evaluate possible variations of the physical constant mu=m_e/m_p - the electron-to-proton mass ratio - from spectral observations of emission lines detected in the microwave range towards the dense molecular cloud Orion-KL. An estimate of the upper limit on the r

Carolyn Abbott, Eduardo Martínez-Pedroza

For a pair $(G,\mathcal{P})$ consisting of a group and finite collection of subgroups, we introduce a simplicial $G$-complex $\mathcal{K}(G,\mathcal{P})$ called the coset intersection complex. We prove that the quasi-isometry type and the homotopy type of $\mathcal{K}(G,\mathcal{P})$ are quasi-isometric invariants of the group pair $(G,\mathcal{P})$. Classic

Jianyu Zheng, Fengfei Fan, Jianquan Li

Unsupervised cross-lingual transfer involves transferring knowledge between languages without explicit supervision. Although numerous studies have been conducted to improve performance in such tasks by focusing on cross-lingual knowledge, particularly lexical and syntactic knowledge, current approaches are limited as they only incorporate syntactic or lexica

Hsiang-nan Li

We have derived previously the relations between the neutrino masses and mixing angles in a dispersive analysis on the mixing of neutral leptonic states. The only involved assumption is that the electroweak symmetry of the Standard Model (SM) is restored at a high energy scale in some new physics scenario, which diminishes the box diagrams responsible for th

St. Raetz, B. Stelzer

Studies of the rotation and activity of M type stars are essential to enhance our understanding of stellar dynamos and angular momentum evolution. Using the outstanding photometric capabilities of space telescopes rotation signals even with low amplitudes can be investigated in up to now unrivaled detail. By combining data of K2 and the TESS prime mission th

Ketil Stølen

A syntax-directed formal system for the development of totally correct programs with respect to an unfair shared-state parallel while-language is proposed. The system can be understood as a compositional reformulation of the Owicki/Gries method for verification of parallel programs. Auxiliary variables are used both as a specification tool to eliminate undes

Michael A. Bender, Alex Conway, Martin Farach-Colton, Hanna Komlos

The list-labeling problem is one of the most basic and well-studied algorithmic primitives in data structures, with an extensive literature spanning upper bounds, lower bounds, and data management applications. The classical algorithm for this problem, dating back to 1981, has amortized cost $O(\log^2 n)$. Subsequent work has led to improvements in three dir

Jer Pelhan, Alan Lukežič, Vitjan Zavrtanik, Matej Kristan

Low-shot counters estimate the number of objects corresponding to a selected category, based on only few or no exemplars annotated in the image. The current state-of-the-art estimates the total counts as the sum over the object location density map, but does not provide individual object locations and sizes, which are crucial for many applications. This is a

Emre Can Acikgoz, Osman Batur İnce, Rayene Bench, Arda Anıl Boz

The integration of Large Language Models (LLMs) into healthcare promises to transform medical diagnostics, research, and patient care. Yet, the progression of medical LLMs faces obstacles such as complex training requirements, rigorous evaluation demands, and the dominance of proprietary models that restrict academic exploration. Transparent, comprehensive a

Mohammad Balal, Shuvam Sarkar, Pramod Bhakuni, Andrei Gloskovskii

Collective plasmon excitations in solids that result from the process of photoemission are an important area of fundamental research. In this study, we identify a significant number ($n$) of multiple bulk plasmons ($n\omega_p$) in the hard x-ray photoelectron spectra of the core levels and valence bands (VBs) of two well-known, nearly free electron metals, a

Yixuan Zhou, Shuoyi Zhou, Shun Lei, Zhiyong Wu

This paper presents the multi-speaker multi-lingual few-shot voice cloning system developed by THU-HCSI team for LIMMITS'24 Challenge. To achieve high speaker similarity and naturalness in both mono-lingual and cross-lingual scenarios, we build the system upon YourTTS and add several enhancements. For further improving speaker similarity and speech quality,

Claude Draude, Dominik Dürrschnabel, Johannes Hirth, Viktoria Horn

With our work, we contribute towards a qualitative analysis of the discourse on controversies in online news media. For this, we employ Formal Concept Analysis and the economics of conventions to derive conceptual controversy maps. In our experiments, we analyze two maps from different news journals with methods from ordinal data science. We show how these m

Dylan Johnston

Let $G$ be an affine algebraic group over an algebraically closed field of positive characteristic. Recent work of Hardesty, Nakano, and Sobaje gives necessary and sufficient conditions for the existence of so-called mock injective $G$-modules, that is, modules which are injective upon restriction to all Frobenius kernels of $G$. In this paper, we give analo

Jean-Eric Campagne

This paper aims to explore the evolution of image denoising in a pedagological way. We briefly review classical methods such as Fourier analysis and wavelet bases, highlighting the challenges they faced until the emergence of neural networks, notably the U-Net, in the 2010s. The remarkable performance of these networks has been demonstrated in studies such a

Renjin Jiang, Sibei Yang

Let $n\ge2$ and $\mathcal{L}=-\mathrm{div}(A\nabla\cdot)$ be an elliptic operator on $\mathbb{R}^n$. Given an exterior Lipschitz domain $\Omega$, let $\mathcal{L}_D$ be the elliptic operator $\mathcal{L}$ on $\Omega$ subject to the Dirichlet boundary condition. Previously it was known that the Riesz operator $\nabla \mathcal{L}_D^{-1/2}$ is not bounded for $

Haorui Xiang, Zhichang Wu, Guoxu Li, Rong Wang

Ordinal regression is a specialized supervised problem where the labels show an inherent order. The order distinguishes it from normal multi-class problem. Support Vector Ordinal Regression, as an outstanding ordinal regression model, is widely used in many ordinal regression tasks. However, like most supervised learning algorithms, the design of SVOR is bas

Sören Christensen, Oskar Hallmann, Maike Klein

Let $W$ be a standard Brownian motion with $W_0 = 0$ and let $b\colon[0,\infty) \to \mathbb{R}$ be a continuous function with $b(0) > 0$. In this article, we look at the classical First Passage Time (FPT) problem, i.e., the question of determining the distribution of $\tau := \inf \{ t\in [0,\infty)\colon W_t \geq b(t) \}.$ More specifically, we revisit the

Emin Karayel

Derandomization techniques are often used within advanced randomized algorithms. In particular, pseudorandom objects, such as hash families and expander graphs, are key components of such algorithms, but their verification presents a challenge. This work shows how such algorithms can be expressed and verified in Isabelle and presents a pseudorandom objects l

Daniele Angioletti, Stefano Raniolo, Vittorio Limongelli

Molecular simulations have assumed a paramount role in the fields of chemistry, biology, and material sciences, being able to capture the intricate dynamic properties of systems. Within this realm, coarse-grained (CG) techniques have emerged as invaluable tools to sample large-scale systems and reach extended timescales by simplifying system representation.

J. A. de la Torre, J. Sánchez-Rodríguez, Pep Español

Intrinsic thermal fluctuations within a real solid challenge the rigid body assumption that is central to Euler's equations for the motion of a free body. Recently, we have introduced a dissipative and stochastic version of Euler's equations in a thermodynamically consistent way (European Journal of Mechanics - A/Solids 103, 105184 (2024)). This framework de

Chenxi Liu, Gan Sun, Wenqi Liang, Jiahua Dong

Pre-trained large text-to-image (T2I) models with an appropriate text prompt has attracted growing interests in customized images generation field. However, catastrophic forgetting issue make it hard to continually synthesize new user-provided styles while retaining the satisfying results amongst learned styles. In this paper, we propose MuseumMaker, a metho

Shizhao He, Jungang Ge, Ying-Chang Liang, Dusit Niyato

The space-air-ground integrated network (SAGIN) is a pivotal architecture to support ubiquitous connectivity in the upcoming 6G era. Inter-operator resource and service sharing is a promising way to realize such a huge network, utilizing resources efficiently and reducing construction costs. Given the rationality of operators, the configuration of resources

Subhrasish Chakraborty, Chhavi Tyagi, Haiyan Qiao, Wenge Guo

Conformal prediction is a general distribution-free approach for constructing prediction sets combined with any machine learning algorithm that achieve valid marginal or conditional coverage in finite samples. Ordinal classification is common in real applications where the target variable has natural ordering among the class labels. In this paper, we discuss

Alessio Devoto, Simone Petruzzi, Jary Pomponi, Paolo Di Lorenzo

In this paper, we propose a novel design for AI-native goal-oriented communications, exploiting transformer neural networks under dynamic inference constraints on bandwidth and computation. Transformers have become the standard architecture for pretraining large-scale vision and text models, and preliminary results have shown promising performance also in de

Jiaying Lin, Jiajun Wen, Mengyuan Liu, Jinfu Liu

The task of spatiotemporal action localization in chaotic scenes is a challenging task toward advanced video understanding. Paving the way with high-quality video feature extraction and enhancing the precision of detector-predicted anchors can effectively improve model performance. To this end, we propose a high-performance dual-stream spatiotemporal feature

Xi Guo, Miguel Angel Martin Contreras, Xun Chen, Dong Xiang

In this work, we discuss the description of neutral $\Sigma$ baryons with $I(J^P)=1(1/2^+)$ and $I(J^P)=1(3/2^+)$ using two bottom-up approaches: the deformed background and the static dilaton. In both models, we consider a non-linear Regge trajectory extension motivated by the \emph{strange} nature that $\Sigma$ baryons have. We found that both models descr

Mahmoud Raeisi, Aymen Khaleel, Mehmet Cagri Ilter, Majid Gerami

Integrating reconfigurable intelligent surfaces (RISs) in emerging communication systems is a fast-growing research field that has recently earned much attention. While implementing RISs near the base station (BS), i.e., BS-side RIS, or user equipment (UE), i.e., UE-side RIS, exhibits optimum performance, understanding the differences between these two deplo

Allard K. Veenstra, Jorge I. Zuluaga, Jaime A. Alvarado-Montes, Mario Sucerquia

We explore the potential of polarimetry as a tool for detecting and characterizing exorings. For that purpose, we have improved the publicly available photometric code Pryngles by adding the results of radiative transfer calculations that fully include polarization and scattering by irregularly shaped particles. With this improved code, we compute the total

Vikas Rathore, Sudhir Kumar Nema

The study investigates the potential of Plasma-Activated Water (PAW) as a nitrogen supplement in hydroponic cultivation (HS-N+PAW), specifically focusing on radish seed germination and plant growth. PAW, produced using a dielectric barrier discharge pencil plasma jet using air as plasma forming gas, is compared against conventional hydroponic solution (HS) a

Cecile Monthus

Continuity equations associated to continuous-time Markov processes can be considered as Euclidean Schr\"odinger equations, where the non-hermitian quantum Hamiltonian $\bold{H}={\bold{div}}{\bold J}$ is naturally factorized into the product of the divergence operator ${\bold {div}}$ and the current operator ${\bold J}$. For non-equilibrium Markov jump proce

Lennon Ó Náraigh

We introduce two models of industrial drying - a simplified one-equation model, and a detailed three-equation model. The purpose of the simplified model is rigorous validation of numerical methods for PDE-constrained optimal control. The purpose of the detailed model is to be able to predict and control the behaviour of an industrial disk drier. For both mod

S. A. Khrapak, A. G. Khrapak

It is shown that the transport coefficients (self-diffusion, shear viscosity, and thermal conductivity) of the Weeks-Chandler-Anderson (WCA) fluid along isotherms exhibit a freezing density scaling (FDS). The functional form of this FDS is essentially the same or closely related to those in the Lennard-Jones fluid, hard-sphere fluid, and some liquefied noble

G. C. Ricarte, C. S. Barroso, L. S. Tavares

This paper studies Schauder theory to transmission problems modelled by fully nonlinear uniformly elliptic equations of second order. We focus on operators F that fails to be concave or convex in the space of symmetric matrices. In a first scenario, it is considered that F enjoys a small ellipticity aperture. In our second case, we study regularity results w

Meseret Asrat

In this paper we consider certain rigidly rotating closed string configurations in an asymptotically non-AdS string background. The string background is a deformation of $AdS_3 \times {\cal M}_7$. It interpolates between $AdS_3 $ and asymptotically linear dilaton ${\rm I\!R} \times S^1 \times {\rm I\!R}$ spacetime (times the internal compact manifold ${\cal

Naman Kumar

In this paper, we study the relativistic correction to Bekenstein-Hawking entropy in the canonical ensemble and isothermal-isobaric ensemble and apply it to the cases of non-rotating BTZ and AdS-Schwarzschild black holes. This is realized by generalizing the equations obtained using Boltzmann-Gibbs(BG) statistics with its relativistic generalization, Kaniada

Yang Zhang, Ling-Fang Lin, Adriana Moreo, Thomas A. Maier

Motivated by the recently proposed alternating single-layer trilayer stacking structure for the nickelate La$_3$Ni$_2$O$_7$, we comprehensively study this system using {\it ab initio} and random-phase approximation techniques. Our analysis unveils similarities between this novel La$_3$Ni$_2$O$_7$ structure and other Ruddlesden-Popper nickelate superconductor

A. B. Yelikar, R. O' Shaughnessy, J. Lange, A. Z. Jan

Accurate information from gravitational wave signals from coalescing binary neutron stars provides essential input to downstream interpretations, including inference of the neutron star population and equation of state. However, even adopting the currently most accurate and physically motivated models available for parameter estimation (PE) of BNSs, these mo

Sophie Dabo-Niang, Camille Frévent

In a world increasingly awash with data, the need to extract meaningful insights from data has never been more crucial. Functional Data Analysis (FDA) goes beyond traditional data points, treating data as dynamic, continuous functions, capturing ever-changing phenomena nuances. This article introduces FDA, merging statistics with real-world complexity, ideal

Usman A. Javid, Michal Chojnacky, Kartik Srinivasan, Gregory Moille

The generation of controlled and arbitrarily tunable terahertz radiation, essential for many applications, has proven challenging due to the complexity of experimental setups and fabrication techniques. We introduce a new strategy involving control over a terahertz repetition rate integrated frequency comb, using Kerr-induced synchronization, that results in

Michael C. Chavrimootoo

This short note outlines some of the issues in Czerwinski's paper [Cze23] claiming that NP-hard problems are not in BQP. We outline one major issue and two minor issues, and conclude that their paper does not establish what they claim it does.

Guang Jia, Zhongwei Bian, Tianshu Li, Shi Bai

Magnetic particle imaging (MPI) is an in-vivo imaging method to detect magnetic nanoparticles for blood vessel imaging and molecular target imaging. Compared with conventional molecular imaging devices (such as nuclear medicine imaging PET and SPECT), magnetic nanoparticles have longer storage periods than radionuclides without ionizing radiation. MPI has hi

Mahammad Tahir, Subhakanta Das, Mukul Gupta, Rohit Medwal

The use of graphene in spintronic devices is contingent on its ability to convert a spin current into a charge current. We have systematically investigated the spin pumping induced spin-to-charge current conversion at the Graphene/FM interface and the effect of interface modification through high spin orbit coupling (SOC) material (Pt) as an interlayer (IL)

Jun-Yi Wu, Shin-Tza Wu

We propose a linear-optical scheme that allows encoding grid-state quantum bits (qubits) into a bosonic mode using cat state and post-selection as sources of non-Gaussianity in the encoding. As a linear-optical realization of the quantum-walk encoding scheme in [Lin {\em et al.}, Quantum Info. Processing {\bf 19}, 272 (2020)], we employ the cat state as a qu

Edouard Sonin

The analysis in the present paper is based on the most known concept introduced by the brilliant physicist Alexander Andreev: Andreev bound states in a normal metal sandwiched between two superconductors. The paper presents results of direct calculations of {\em ab initio} expressions for the currents in a long ballistic SNS junction. The expressions are exp

Melvin H. Friedman, Brian L. Mark, Nathan H. Gartner

This paper describes a traffic signal control strategy that allows motorists who travel at a recommended speed on suburban arterial two-way roads with a common cycle time to make every traffic signal. A road-to-traveler-feedback-device (RTFD) advises motorists how fast they should travel to do this. Signalized arterial roads where vehicles that travel at the

Emma de Oña Wilhelmi, Rubén López-Coto, Felix Aharonian, Elena Amato

Ultrarelativistic particles called cosmic rays permeate the Milky Way, propagating through the Galactic turbulent magnetic fields. The mechanisms under which these particles increase their energy can be reasonably described by current theories of acceleration and propagation of cosmic rays. There are, however, still many open questions as to how to reach pet

Sebastien Origer, Dario Izzo

We improve the accuracy of Guidance & Control Networks (G&CNETs), trained to represent the optimal control policies of a time-optimal transfer and a mass-optimal landing, respectively. In both cases we leverage the dynamics of the spacecraft, described by Ordinary Differential Equations which incorporate a neural network on their right-hand side (Neural ODEs

Samuel Stockman, Daniel J. Lawson, Maximilian J. Werner

Performing Bayesian inference for the Epidemic-Type Aftershock Sequence (ETAS) model of earthquakes typically requires MCMC sampling using the likelihood function or estimating the latent branching structure. These tasks have computational complexity $O(n^2)$ with the number of earthquakes and therefore do not scale well with new enhanced catalogs, which can

Jun Nishimura, Katsuta Sakai, Atis Yosprakob

The generalized Lefschetz thimble method is a promising approach that attempts to solve the sign problem in Monte Carlo methods by deforming the integration contour using the flow equation. Here we point out a general problem that occurs due to the property of the flow equation, which extends a region on the original contour exponentially to a region on the

Ruben Turkenburg, Harsh Beohar, Clemens Kupke, Jurriaan Rot

Bisimilarity is a central notion for coalgebras. In recent work, Geuvers and Jacobs suggest to focus on apartness, which they define by dualising coalgebraic bisimulations. This yields the possibility of finite proofs of distinguishability for a wide variety of state-based systems. We propose behavioural apartness, defined by dualising behavioural equivalenc

Zhihao Zhu, Ninglu Shao, Defu Lian, Chenwang Wu

Large language models (LLMs) show early signs of artificial general intelligence but struggle with hallucinations. One promising solution to mitigate these hallucinations is to store external knowledge as embeddings, aiding LLMs in retrieval-augmented generation. However, such a solution risks compromising privacy, as recent studies experimentally showed tha

Theo Juncker von Buchwald, Karl Michael Ziems, Erik Rosendahl Kjellgren, Stephan P. A. Sauer

The prediction of spectral properties via linear response (LR) theory is an important tool in quantum chemistry for understanding photo-induced processes in molecular systems. With the advances of quantum computing, we recently adapted this method for near-term quantum hardware using a truncated active space approximation with orbital rotation, named quantum

Xing Cheng, Yunrui Zheng

We consider the viscous incompressible fluids in a three-dimensional horizontally periodic domain bounded below by a fixed smooth boundary and above by a free moving surface. The fluid dynamics are governed by the Navier-Stokes equations with the effect of gravity and surface tension on the free surface. We develop a global well-posedness theory by a nonline

B. Leimkuhler, A. Sharma, M. V. Tretyakov

We derive and analyze numerical methods for underdamped (kinetic) Langevin dynamics in a domain with elastic reflection at the boundary. First-order approximations are based on an Euler-type scheme incorporating collision-handling at the boundary. To achieve second order, composition schemes are derived based on decomposition of the generator into collisiona

Christopher J. Geoga

We provide in this work an algorithm for approximating a very broad class of symmetric Toeplitz matrices to machine precision in $\mathcal{O}(n \log n)$ time with applications to fitting time series models. In particular, for a symmetric Toeplitz matrix $\mathbf{\Sigma}$ with values $\mathbf{\Sigma}_{j,k} = h_{|j-k|} = \int_{-1/2}^{1/2} e^{2 \pi i |j-k| \ome

Nobuaki Monma, Hideaki Yamamoto, Naoya Fujiwara, Hakuba Murota

Hierarchically modular organization is a canonical network topology that is evolutionarily conserved in the nervous systems of animals. Within the network, neurons form directional connections defined by the growth of their axonal terminals. However, this topology is dissimilar to the network formed by dissociated neurons in culture because they form randoml

Kaixin Shen, Ruijie Quan, Linchao Zhu, Jun Xiao

Audio-driven visual scene editing endeavors to manipulate the visual background while leaving the foreground content unchanged, according to the given audio signals. Unlike current efforts focusing primarily on image editing, audio-driven video scene editing has not been extensively addressed. In this paper, we introduce AudioScenic, an audio-driven framewor

Zhiguang Cheng, Gaohang Yu, Xiaohao Cai, Liqun Qi

Large tensors are frequently encountered in various fields such as computer vision, scientific simulations, sensor networks, and data mining. However, these tensors are often too large for convenient processing, transfer, or storage. Fortunately, they typically exhibit a low-rank structure that can be leveraged through tensor decomposition. However, performi

Thomas Gaudelet, Alice Del Vecchio, Eli M Carrami, Juliana Cudini

Interventions play a pivotal role in the study of complex biological systems. In drug discovery, genetic interventions (such as CRISPR base editing) have become central to both identifying potential therapeutic targets and understanding a drug's mechanism of action. With the advancement of CRISPR and the proliferation of genome-scale analyses such as transcr

Kaixin Shen, Ruijie Quan, Linchao Zhu, Jun Xiao

Maintaining temporal stability is crucial in multi-agent trajectory prediction. Insufficient regularization to uphold this stability often results in fluctuations in kinematic states, leading to inconsistent predictions and the amplification of errors. In this study, we introduce a framework called Multi-Agent Trajectory prediction via neural interaction Ene

Risto Ojala, Eerik Alamikkotervo

In below freezing winter conditions, road surface friction can greatly vary based on the mixture of snow, ice, and water on the road. Friction between the road and vehicle tyres is a critical parameter defining vehicle dynamics, and therefore road surface friction information is essential to acquire for several intelligent transportation applications, such a

Linheng Ruan, Iryna Rybak

Flow interaction between a plain-fluid region in contact with a porous layer attracted significant attention from modelling and analysis sides due to numerous applications in biology, environment and industry. In the most widely used coupled model, fluid flow is described by the Stokes equations in the free-flow domain and Darcy's law in the porous medium, a

Maria Vasilyeva

In this work, we present an efficient way to decouple the multicontinuum problems. To construct decoupled schemes, we propose Implicit-Explicit time approximation in general form and study them for the fine-scale and coarse-scale space approximations. We use a finite-volume method for fine-scale approximation, and the nonlocal multicontinuum (NLMC) method is

Jun-Zhang Wang, Zi-Yang Lin, Yan-Ke Chen, Lu Meng

The $X(3872)$, as the first and the most crucial member in the exotic charmoniumlike $XYZ$ family, has been studied for a long time. However, its dynamical origin, whether stemming from a $D\bar{D}^*$ hadronic molecule or the first excited $P$-wave charmonium $\chi_{c1}(2P)$, remains controversial. In this Letter, we demonstrate that the $X(3872)$ definitely

Ulme Wennberg, Gustav Eje Henter

It has been found that Transformer-based language models have the ability to perform basic quantitative reasoning. In this paper, we propose a method for studying how these models internally represent numerical data, and use our proposal to analyze the ALBERT family of language models. Specifically, we extract the learned embeddings these models use to repre

Haotian Yan, Ming Wu, Chuang Zhang

Multi-scale learning is central to semantic segmentation. We visualize the effective receptive field (ERF) of canonical multi-scale representations and point out two risks in learning them: scale inadequacy and field inactivation. A novel multi-scale learner, varying window attention (VWA), is presented to address these issues. VWA leverages the local window

Maximilian K. Egger, Wenyue Ma, Davide Mottin, Panagiotis Karras

Can we assess a priori how well a knowledge graph embedding will perform on a specific downstream task and in a specific part of the knowledge graph? Knowledge graph embeddings (KGEs) represent entities (e.g., "da Vinci," "Mona Lisa") and relationships (e.g., "painted") of a knowledge graph (KG) as vectors. KGEs are generated by optimizing an embedding score

Zhiwei Wang, Ying Zhou, Shiquan He, Ting Li

Photometric constraint is indispensable for self-supervised monocular depth estimation. It involves warping a source image onto a target view using estimated depth&pose, and then minimizing the difference between the warped and target images. However, the endoscopic built-in light causes significant brightness fluctuations, and thus makes the photometric con

Chris Nagele, Hideyuki Umeda, Keiichi Maeda

SN2018ibb is a recently observed hydrogen poor super-luminous supernova which appears to be powered by the decay of $30\;\rm{M_\odot}$ of radioactive nickel. This supernova has been suggested to show hybrid signatures of a pair instability supernova and an interacting supernova. In a previous paper, we found that rotating, metal enriched pair instability sup

Johannes Falk, Edwin Eichler, Katja Windt, Marc-Thorsten Hütt

Recently, we proposed polycontextural networks as a model of evolving systems of interacting beliefs. Here, we present an analysis of the phase transition as well as the scaling properties. The model contains interacting agents that strive for consensus, each with only subjective perception. Depending on a parameter that governs how responsive the agents are

Arshad Mehmood, Myles C. Silfies, Andrew S. Durden, Thomas K. Allison

Transient absorption spectroscopy (TAS) is among the most common ultrafast photochemical experiments, but its interpretation remains challenging. In this work, we present an efficient and robust method for simulating TAS signals from first principles. Excited-state absorption and stimulated emission (SE) signals are computed using time-dependent complete act

A. del Pino, C. López-Sanjuan, A. Hernán-Caballero, H. Domínguez-Sánchez

With its 12 optical filters, the Javalambre-Photometric Local Universe Survey (J-PLUS) provides an unprecedented multicolor view of the local Universe. The third data release (DR3) covers 3,192 deg$^2$ and contains 47.4 million objects. However, the classification algorithms currently implemented in its pipeline are deterministic and based solely on the sour

Alessandro Coretti, Sebastian Falkner, Jan Weinreich, Christoph Dellago

The paper by No\'e et al. [F. No\'e, S. Olsson, J. K\"ohler and H. Wu, Science, 365:6457 (2019)] introduced the concept of Boltzmann Generators (BGs), a deep generative model that can produce unbiased independent samples of many-body systems. They can generate equilibrium configurations from different metastable states, compute relative stabilities between d

Kai Gao, Weiwei Xu, Wenhao Yang, Minghui Zhou

A package's source code repository records the development history of the package, providing indispensable information for the use and risk monitoring of the package. However, a package release often misses its source code repository due to the separation of the package's development platform from its distribution platform. Existing tools retrieve the releas