December 2024 arXiv papers — page 10

Shuai Wang

This paper introduces ProofCloud, a proof retrieval engine for verified proofs in higher order logic. It provides a fast proof searching service for mathematicians and computer scientists for the reuse of proofs and proof packages. In addition, it includes the first complete proof-checking results and benchmarks of the OpenTheory repository.

Nicolas M Cuadrado Avila, Samuel Horváth, Martin Takáč

This work studies the challenge of optimal energy management in building-based microgrids through a collaborative and privacy-preserving framework. We evaluated two common RL algorithms (PPO and TRPO) in different collaborative setups to manage distributed energy resources (DERs) efficiently. Using a customized version of the CityLearn environment and synthe

Yoseth Arciniegas Barreto, Nicol Bermudez Bohorquez, Juanita Pinzón-Caicedo, Luisa Rozo Posada

These notes are an introduction to knot theory from the perspective of surfaces. The notes cover fundamental concepts such as isotopies, Reidemeister moves, torus knots, and (orientable, connected) surfaces with one boundary component. They also present knot invariants defined through Seifert surfaces and their associated matrices, including the 3-genus, the

Pinar Yozgatli, Yavuz Acar, Mehmet Tulumen, Selman Minga

Computer vision technology, which involves analyzing images and videos captured by cameras through deep learning algorithms, has significantly advanced the field of human fall detection. This study focuses on the application of the YoloV8 Nano model in identifying fall incidents within passenger elevators, a context that presents unique challenges due to the

Runteng Chen, Jun Zhang, Zelong Wang, Ke Lu

The long sought cubic gauche polymeric nitrogen (cg-N) consisting of N-N single bonds has been synthesized by a simple route using sodium azide as a precursor at ambient conditions. The recrystallization process was designed to expose crystal faces with low activation energy that facilitates initiating the polymeric reaction at ambient conditions. The azide

Xuejian Zhang, Ruisi He, Bo Ai, Mi Yang

With the development of high-speed railways, 5G for Railways (5G-R) is gradually replacing Global System for the Mobile Communications for Railway (GSM-R) worldwide to meet increasing demands. The large bandwidth, array antennas, and non-stationarity caused by high mobility has made 5G-R channel characterization more complex. Therefore, it is essential to de

Xiaohan Feng, Xixin Wu, Helen Meng

We propose an ontology-grounded approach to Knowledge Graph (KG) construction using Large Language Models (LLMs) on a knowledge base. An ontology is authored by generating Competency Questions (CQ) on knowledge base to discover knowledge scope, extracting relations from CQs, and attempt to replace equivalent relations by their counterpart in Wikidata. To ens

Georgios Dimitroglou Rizell

Here we study several questions concerning Liouville domains that are diffeomorphic to cylinders, so called trivial bi-fillings, for which the Liouville skeleton moreover is smooth and of codimension one; we also propose the notion of a Liouville-Hamiltonian structure, which encodes the symplectic structure of a hypersurface tangent to the Liouville flow, e.

Sagar Gautam, Manil T. Mohan

The convective Brinkman--Forchheimer equations or the Navier--Stokes equations with damping in bounded or periodic domains $\subset\mathbb{R}^d$, $2\leq d\leq 4$ are considered in this work. The existence and uniqueness of a global weak solution in the Leray-Hopf sense satisfying the energy equality to the system: $$\partial_t\boldsymbol{u}-\mu \Delta\boldsy

Tiantian Cheng

Production measurements of charm hadrons, particularly the yield ratios of different hadron species as a function of the transverse momentum, are important to study the charm hadronisation mechanism. In this contribution, measurements of $\rm D^{0}$, $\rm D^{+}$, and $\rm D^{+}_{\rm s}$ meson production, as well as $\Lambda^{+}_{\rm c}$-baryon production at

Yiyuan Chen, Xiaoxiong Liu, Hai-Zhou Lu, X. C. Xie

Switching magnetism using only electricity is of great significance for industrial applications but remains challenging. We find that, altermagnetism, as a newly discovered unconventional magnetism, may open an avenue along this effort. Specifically, to have deterministic switching, i.e., reversing current direction must reverse magnetic structure, parity sy

Jiaxiang Wang, Yinchao Yang, Zhaohui Yang, Chongwen Huang

This paper investigates a novel generative artificial intelligence (GAI) empowered multi-user semantic communication system called semantic feature multiple access (SFMA) for video transmission, which comprises a base station (BS) and paired users. The BS generates and combines semantic information of several frames simultaneously requested by paired users i

Aaqib Zahoor, Iqra Altaf Gillani, Janib ul Bashir

Influence maximization in temporal social networks presents unique challenges due to the dynamic interactions that evolve over time. Traditional diffusion models often fall short in capturing the real-world complexities of active-inactive transitions among nodes, obscuring the true behavior of influence spread. In dynamic networks, nodes do not simply transi

Qinghui Li, Lizhen Hu, Panpan Zhang, Chuanzheng Miao

The spin-12 three-leg antiferromagnetic Heisenberg spin ladder is studied under open boundary condition (OBC) and cylinder boundary condition (CBC), using the density matrix renormalization group and matrix product state methods, respectively. Specifically, we calculate the energy density, entanglement entropy, and concurrence while discussing the effects of

Saber Jafarizadeh

Of stochastic differential equations, diffusion processes have been adopted in numerous applications, as more relevant and flexible models. This paper studies diffusion processes in a different setting, where for a given stationary distribution and average variance, it seeks the diffusion process with optimal convergence rate. It is shown that the optimal dr

Gianluca Corrado, Michael Uhl, Rolf Backofen, Andrea Passerini

CLIP-seq methods are valuable techniques to experimentally determine transcriptome-wide binding sites of RNA-binding proteins. Despite the constant improvement of such techniques (e.g. eCLIP), the results are affected by various types of noise and depend on experimental conditions such as cell line, tissue, gene expression levels, stress conditions etc., pav

Jorge Alda, Carlo Broggini, Giuseppe Di Carlo, Luca Di Luzio

We investigate the time modulation of weak nuclear decays as a method to probe axion dark matter. To this end, we develop a theoretical framework to compute the $\theta$-dependence of weak nuclear decays, including electron capture and $\beta$ decay, which enables us to predict the time variation of weak radioactivity in response to an oscillating axion dark

Sergey Mironov, Andrey Morozov

While there is a general consensus about the structure of one qubit operations in topological quantum computer, two qubits are as usual a more difficult and complex story of different attempts with varying approaches, problems and effectiveness. In this paper we discuss how to construct an efficient realization of a two qubit gate in topological quantum comp

Ren-Xin Zhao

Hard Attention Mechanisms (HAMs) effectively filter essential information discretely and significantly boost the performance of machine learning models on large datasets. Nevertheless, they confront the challenge of non-differentiability, which raises the risk of convergence to a local optimum. Quantum Annealing (QA) is expected to solve the above dilemma. W

Linda M. van Manen

We discuss the decoherence in a quantum system induced by interaction with gravitational degrees of freedom that are part of a higher derivative theory. The deformation of a mass distribution due to gravitational waves acquires naturally a mass quadrupole moment. This adds higher derivative dynamics of the quadrupole moment to the unitary evolution of the sy

De-Ye Tao, Bo Zhou

The reduced-width amplitude, as a cluster overlap amplitude, is one important physical quantity for analyzing clustering in the nucleus depending on specified channels and has been calculated and applied widely in nuclear cluster physics. In this review, we briefly revisit the theoretical framework for calculating the reduced-width amplitude, as well as the

Junxiao Xue, Quan Deng, Fei Yu, Yanhao Wang

Multimodal large language models (MLLMs), such as GPT-4o, Gemini, LLaVA, and Flamingo, have made significant progress in integrating visual and textual modalities, excelling in tasks like visual question answering (VQA), image captioning, and content retrieval. They can generate coherent and contextually relevant descriptions of images. However, they still f

Yegor Zenkevich

We apply the spiralling branes technique introduced in arXiv:2312.16990 to many-body integrable systems. We start by giving a new R-matrix description of the trigonometric Ruijsenaars-Schneider (RS) Hamiltonians and eigenfunctions using the intertwiners of quantum toroidal algebra. We then consider elliptic deformations of the RS system, elucidate how Shirai

Jiaqi Yang, Xiaohua Xu, Wei Xie

Quantum process tomography (QPT) is a fundamental tool for fully characterizing quantum systems. It relies on querying a set of quantum states as input to the quantum process. Previous QPT methods typically employ a straightforward strategy for randomly selecting quantum states, overlooking differences in informativeness among them. In this work, we propose

Satya Swaroop Gudipudi, Sreeram Vipparla, Harpreet Singh, Shashwat Goel

Instruction fine-tuning of large language models (LLMs) is a powerful method for improving task-specific performance, but it can inadvertently lead to a phenomenon where models generate harmful responses when faced with malicious prompts. In this paper, we explore Low-Rank Adapter Fusion (LoRA) as a means to mitigate these risks while preserving the model's

Zijie Fang, Yifeng Wang, Peizhang Xie, Zhi Wang

Tissue semantic segmentation is one of the key tasks in computational pathology. To avoid the expensive and laborious acquisition of pixel-level annotations, a wide range of studies attempt to adopt the class activation map (CAM), a weakly-supervised learning scheme, to achieve pixel-level tissue segmentation. However, CAM-based methods are prone to suffer f

Darren Butler, Conrad Borchers, Michael W. Asher, Yongmin Lee

The Doer Effect states that completing more active learning activities, like practice questions, is more strongly related to positive learning outcomes than passive learning activities, like reading, watching, or listening to course materials. Although broad, most evidence has emerged from practice with tutoring systems in Western, Industrialized, Rich, Educ

Antonio Smecca, Gert Aarts, Chris Allton, Ryan Bignell

In the QCD phase diagram, the dependence of the pseudo-critical temperature, $T_{\rm{pc}}$, on the baryon chemical potential, $\mu_B$, is of fundamental interest. The variation of $T_{\rm{pc}}$ with $\mu_B$ is normally captured by $\kappa$, the coefficient of the leading (quadratic) term of the polynomial expansion of $T_{\rm{pc}}$ with $\mu_B$. In this work

Ya-Juan Zheng

We extend the standard top-quark Yukawa coupling with a dimension-6 operator in order to accommodate a CP violating complex phase with manifest gauge invariance. This leads to a new $ttHH$ contact interaction, along with many Goldstone boson couplings. We investigate the impact of the new interactions on a muon collider process $\mu^-\mu^+\to \nu_\mu\bar{\nu

Haohong Che, Li You, Jue Wang, Zhenzhou Jin

Extremely large-scale multiple-input multiple-output (XL-MIMO) is critical to future wireless networks. The substantial increase in the number of base station (BS) antennas introduces near-field propagation effects in the wireless channels, complicating channel parameter estimation and increasing pilot overhead. Channel charting (CC) has emerged as a potent

Marzieh Baradaran, Pavel Exner, Andrii Khrabustovskyi

We consider a periodic quantum graph in the form of a rectangular lattice with the $\delta$-coupling of strength $\gamma$ in the vertices perturbed by changing the latter at an infinite straight array of vertices to a $\widetilde\gamma\ne\gamma$. We analyze the band spectrum of the system and show that it remains preserved as a set provided $\widetilde\gamma

Yang Chen, Chih-Li Sung, Arpan Kusari, Xiaoyang Song

Deep neural networks (DNNs) are often constructed under the closed-world assumption, which may fail to generalize to the out-of-distribution (OOD) data. This leads to DNNs producing overconfident wrong predictions and can result in disastrous consequences in safety-critical applications. Existing OOD detection methods mainly rely on curating a set of OOD dat

Ilias Ftouhi

We prove that for every planar convex set $\Omega$, the function $t\in (-r(\Omega),+\infty)\longmapsto \sqrt{|\Omega_t|}h(\Omega_t)$ is monotonically decreasing, where $r$, $|\cdot|$ and $h$ stand for the inradius, the measure and the Cheeger constant and $(\Omega_t)$ for parallel bodies of $\Omega$. The result is shown to not hold when the convexity assumpt

Han Zhou, Wei Dong, Xiaohong Liu, Yulun Zhang

Although significant progress has been made in enhancing visibility, retrieving texture details, and mitigating noise in Low-Light (LL) images, the challenge persists in applying current Low-Light Image Enhancement (LLIE) methods to real-world scenarios, primarily due to the diverse illumination conditions encountered. Furthermore, the quest for generating e

Amir Babak Aazami

We analyze oriented Riemannian 4-manifolds whose Weyl tensors $W$ satisfy the conformally invariant condition $W(T,\cdot,\cdot,T) = 0$ for some nonzero vector $T$. While this can be algebraically classified via $W$'s normal form, we find a further geometric classification by deforming the metric into a Lorentzian one via $T$. We show that such a $W$ will hav

Haoran Sun, Zimu Wang, Qiuyi Chen, Jianjun Chen

In recent years, user-generated audio content has proliferated across various media platforms, creating a growing need for efficient retrieval methods that allow users to search for audio clips using natural language queries. This task, known as language-based audio retrieval, presents significant challenges due to the complexity of learning semantic represe

Sang Hui Im, Krzysztof Jodłowski

Extra dimensions with a bulk dilaton field can be power-law warped, unlike the exponential warping in the Randall-Sundrum (RS) model. We show that this mildly warped extra dimension can address the hierarchy problem with a novel Kaluza-Klein (KK) spectrum characterized by lighter feebly coupled KK modes compared to the KK modes in the RS model. We investigat

C. K. Chan, Hao-Yun Hsu

Motions of visually coupled zebrafish pairs are studied to understand the effects of information exchange on their behavior as a function of their minimal separation ($d$). We find that when $d$ is small, the pair can display a leader-follower relation (LFR) with trajectories of almost synchronized form. However, with larger $d$, although the same LFR is sti

Shaoqing Xu, Fang Li, Peixiang Huang, Ziying Song

Accurate multi-view 3D object detection is essential for applications such as autonomous driving. Researchers have consistently aimed to leverage LiDAR's precise spatial information to enhance camera-based detectors through methods like depth supervision and bird-eye-view (BEV) feature distillation. However, existing approaches often face challenges due to t

Alexander I. Bufetov

For rescaled additive functionals of the sine-process, upper bounds are obtained for their speed of convergence to the Gaussian distribution with respect to the Kolmogorov-Smirnov metric. Under scaling with coefficient $R$ the Kolmogorov-Smirnov distance is bounded from above by $c/\log R$ for a smooth function and by $c/R$ for a function holomorphic in a ho

Neha Malik, Steven Spallone

Let $q$ be an odd prime power, and $G=\text{Sp}(2n,q)$ the finite symplectic group. We give an expression for the total Stiefel-Whitney Classes (SWCs) for orthogonal representations $\pi$ of $G$, in terms of character values of $\pi$ at elements of order $2$. We give "universal formulas'' for the fourth and eighth SWCs. For $n=2$, we compute the subring of t

Xudong Wang, Tingting Xiang

The Gaussian surface area measures for $C$-pseudo-cones are studied in this paper. Using the variational arguments and the approximation methods of Schneider, we obtain the existence of solutions to the Gaussian-Minkowski problem for $C$-pseudo-cones with small co-volume.

Kai Schmitz, Tobias Schroeder

Cosmic strings represent an attractive source of gravitational waves (GWs) from the early Universe. However, numerical computation of the GW signal from cosmic strings requires the evaluation of complicated integral and sum expressions, which can become computationally costly in large parameter scans. This motivates us to rederive the GW signal from a networ

Guillermina Fongi, María Celeste Gonzalez

In this article we study different aspects of Hermitian operators applying the concept of positive decompositions. On the one hand, we characterize the positivity of an Hermitian operator by means of a norm condition where the factors of certain pseudo polar decomposition of the operator, are involved. On the other hand, we relate the concept of positive ort

Roman Geiko

There are families of physical systems that cannot be adiabatically evolved to the trivial system uniformly across the parameter space, even if each system in the family belongs to the trivial phase. The obstruction is measured by higher Berry class. We analyze families of topological systems in 1+1d using families of invertible TQFTs and families of RG fixe

Zhiqiang Yuan, Ting Zhang, Ying Deng, Jiapei Zhang

Approximately 200 million individuals around the world suffer from varying degrees of visual impairment, making it crucial to leverage AI technology to offer walking assistance for these people. With the recent progress of vision-language models (VLMs), applying VLMs to offer walking guidance has become popular. However, the existing methods of walking guida

Alexander I. Bufetov

An explicit expression for the expected value of a regularized multiplicative functional under the sine-process is obtained by passing to the scaling limit in the Borodin-Okounkov-Geronimo-Case formula.

Ting Zhang, Zhiqiang Yuan, Yeshuang Zhu, Jinchao Zhang

High-quality animated stickers usually contain transparent channels, which are often ignored by current video generation models. To generate fine-grained animated transparency channels, existing methods can be roughly divided into video matting algorithms and diffusion-based algorithms. The methods based on video matting have poor performance in dealing with

M. A. Sofi

In the literature surrounding the theory of Banach spaces, considerable effort has been invested in exploring the conditions on a Banach space X that characterise X as being an inner product space or as a linearly isomorphic copy of a Hilbert space. On the other hand, a different theory emerges when the class of Banach spaces is looked upon as a Lipschitz ca

Zhili He, Yu-Hsing Wang

Generative AIBIM, a successful structural design pipeline, has proven its ability to intelligently generate high-quality, diverse, and creative shear wall designs that are tailored to specific physical conditions. However, the current module of Generative AIBIM that generates designs, known as the physics-based conditional diffusion model (PCDM), necessitate

Hiromu Nakano

We discuss the tensor structure on the category of modules of the $N=1$ triplet vertex operator superalgebra $\mathcal{SW}(m)$ introduced by Adamovi\'{c} and Milas. Based on the theory of vertex tensor supercategories, we determine the structure of fusion products between the simple and projective $\mathcal{SW}(m)$-modules and show that the tensor supercateg

Leonid M. Satarov, Igor N. Mishustin, Horst Stoecker

Equation of state of uncharged bosonic matter is studied within a field-theoretical approach in the mean-field approximation. Interaction of bosons is described by a scalar field $\sigma$ with a Skyrme-like potential which contains both attractive and repulsive terms. Additionally we introduce the derivative interaction by including factor $(1+\lambda\sigma)

Heng Wu, Yaojia Wang, Mazhar N. Ali

Superconductivity has been investigated for over a century, but there are still open questions about what determines the critical current; the maximum current a superconductor can carry before switching to its normal state. For a given superconductor, the zero-field critical current is widely believed to be determined by its inherent properties and be relate

Niels Justesen, Maria Kaselimi, Sam Snodgrass, Miruna Vozaru

Artificial intelligence (AI) has enabled agents to master complex video games, from first-person shooters like Counter-Strike to real-time strategy games such as StarCraft II and racing games like Gran Turismo. While these achievements are notable, applying these AI methods in commercial video game production remains challenging due to computational constrai

Zhengbo Wang, Jian Liang, Lijun Sheng, Ran He

So far, efficient fine-tuning has become a popular strategy for enhancing the capabilities of foundation models on downstream tasks by learning plug-and-play modules. However, existing methods overlook a crucial issue: if the underlying foundation model is updated, are these plug-and-play modules still effective? In this paper, we first conduct a detailed an

Velmurugan S

Let $ (\rho, V) $ be an irreducible representation of the symmetric group $ S_n$ (or the alternating group $ A_n$), and let $ g $ be a permutation on $n$ letters with each of its cycle lengths divides the length of its largest cycle. We describe completely the minimal polynomial of $\rho(g)$, showing that, in most cases, it equals $x^{o(g)} - 1 $, with a few

Runhong He, Ji Guan, Xin Hong, Guolong Cui

In this paper we present an architecture that enables the redesign of large-scale quantum circuits on quantum hardware based on the entangling quantum generative adversarial network (EQ-GAN). Specifically, by prepending a random quantum circuit module to the standard EQ-GAN framework, we extend its capability from quantum state learning to unitary transforma

Freddie Bickford Smith, Jannik Kossen, Eleanor Trollope, Mark van der Wilk

The ideas of aleatoric and epistemic uncertainty are widely used to reason about the probabilistic predictions of machine-learning models. We identify incoherence in existing discussions of these ideas and suggest this stems from the aleatoric-epistemic view being insufficiently expressive to capture all the distinct quantities that researchers are intereste

Howard Nuer

We prove that families of Calabi-Yau threefolds (CY3's) admit Bridgeland stability conditions when they are obtained via orbifolding from a family of CY3's admitting Bridgeland stability conditions. In particular, we prove that the quintic mirror admits Bridgeland stability conditions.

Xiaolin Hu, Xiang Cheng, Peiyu Liu, Wei Liu

Low-rank adaptation (LoRA) reduces the computational and memory demands of fine-tuning large language models (LLMs) by approximating updates with low-rank matrices. However, low-rank approximation in two-dimensional space fails to capture high-dimensional structures within the target matrix. Recently, tensor decomposition methods have been explored for fine-

Chengye Yu, Xiaolin Zhang, Sobhan Kazempour, Sichun Sun

Rotating superradiance in cylindrical geometries has recently been observed experimentally using acoustic waves, shedding light on the superradiant phenomenon in black holes. In this paper, we study superradiance in acoustic black holes made with solid material for the first time, using theoretical analysis and numerical simulations in COMSOL Multiphysics. W

Dinh-Nguyen Nguyen, Raymond Kai-Yu Tong, Ngoc-Duy Dinh

Applying Large language models (LLMs) within specific domains requires substantial adaptation to account for the unique terminologies, nuances, and context-specific challenges inherent to those areas. Here, we introduce DropMicroFluidAgents (DMFAs), an advanced language-driven framework leveraging state-of-the-art pre-trained LLMs. DMFAs employs LLM agents t

Meng-Meng Lu, Zheng-Chuan Wang

Weinvestigate the topological phase transition of Kitaev spin liquid in an external magnetic field by calculating the Berry curvature and the Fubini-Study metric. Employing Jordan-Wigner transformation and effective perturbative theory to transform the Hamiltonian into fermionic quadratic form, the Berry curvature is calculated by choosing the effective magn

Atharva Divekar, Atharva Sonawane

The AUTO-PCOS Classification Challenge seeks to advance the diagnostic capabilities of artificial intelligence (AI) in identifying Polycystic Ovary Syndrome (PCOS) through automated classification of healthy and unhealthy ultrasound frames. This report outlines our methodology for building a robust AI pipeline utilizing transfer learning with the InceptionV3

Liuzhenghao Lv, Hao Li, Yu Wang, Zhiyuan Yan

Chemical language models (CLMs) are prominent for their effectiveness in exploring chemical space and enabling molecular engineering. However, while exploring chemical-linguistic space, CLMs suffer from the gap between natural language and molecular representations. This challenge is primarily due to the inherent modeling differences between molecules and te

Wei Li, Hanbyul Kim, Xinbo Wang, Jianlin Luo

Coherent manipulation of lattice vibrations using ultrafast light pulses enables access to nonequilibrium 'hidden' phases with designed functionalities in quantum materials. However, expanding the understanding of nonlinear light-phonon interaction mechanisms remains crucial for developing new strategies. Here, we report re-entrant ultrafast phase transition

Oleg Gutik, Maksym Shchypel

We study topologization of the semigroup $\mathscr{O\!\!I}\!_n(L)$ of finite partial order isomorphisms of a bounded rank of an infinite linear ordered set $(L,\leqslant)$. In particular we show that every $T_1$ left-topological (right-topological) semigroup $\mathscr{O\!\!I}\!_n(L)$ is a completely Hausdorff, Urysohn, totally separated, scattered space. We

Chenjie Xie, Li You, Zhenzhou Jin, Jinke Tang

Multi-band massive multiple-input multiple-output (MIMO) communication can promote the cooperation of licensed and unlicensed spectra, effectively enhancing spectrum efficiency for Wi-Fi and other wireless systems. As an enabler for multi-band transmission, channel fingerprints (CF), also known as the channel knowledge map or radio environment map, are used

P. Michael Kielstra, Michael Lindsey

Gaussian Process Regression (GPR) is widely used for inferring functions from noisy data. GPR crucially relies on the choice of a kernel, which might be specified in terms of a collection of hyperparameters that must be chosen or learned. Fully Bayesian GPR seeks to infer these kernel hyperparameters in a Bayesian sense, and the key computational challenge i

Vesa Saarinen, Robin Rajamäki, Visa Koivunen

This paper develops a generative deep learning model for the synthesis of multiple-input multiple-output (MIMO) active sensing waveforms with desired properties, including constant modulus and a user-defined beampattern. The proposed approach is capable synthesizing unique phase codes of on-the-fly, which has the potential to reduce interference between co-e

Yang Long, Haoran Xue, Baile Zhang

The integration of artificial intelligence (AI) into fundamental science has opened new possibilities to address long-standing scientific challenges rooted in mathematical limitations. For example, topological invariants are used to characterize topology, but there is no universally applicable one. This limitation explains why, in the past decades-long class

Fardin Ayar, Ehsan Javanmardi, Manabu Tsukada, Mahdi Javanmardi

Panoptic segmentation, which combines instance and semantic segmentation, has gained a lot of attention in autonomous vehicles, due to its comprehensive representation of the scene. This task can be applied for cameras and LiDAR sensors, but there has been a limited focus on combining both sensors to enhance image panoptic segmentation (PS). Although previou

P. Encarnación, A. Feijoo, V. Mantovani Sarti, A. Ramos

We study the femtoscopic correlation functions of meson-baryon pairs in the strangeness $S=-1$ sector, employing unitarized s-wave scattering amplitudes derived from the chiral Lagrangian up to next-to-leading order. For the first time, we deliver predictions on the $\pi^-\Lambda$ and $K^+\Xi^-$ correlation functions which are feasible to be measured at the

M. Bugatti, C. Lovis, F. Pepe, N. Blind

The upcoming Ristretto spectrograph is dedicated to the detection and analysis of exoplanetary atmospheres, with a primary focus on the temperate rocky world Proxima b. This scientific endeavor relies on the interplay of a high-contrast adaptive optics (AO) system and a high-resolution echelle spectrograph. In this work, I present a comprehensive simulation

Mohammad Abdulaziz, Kurt Mehlhorn

We present the first formal correctness proof of Edmonds' blossom shrinking algorithm for maximum cardinality matching in general graphs. We focus on formalising the mathematical structures and properties that allow the algorithm to run in worst-case polynomial running time. We formalise Berge's lemma, blossoms and their properties, and a mathematical model

Mark Edelman

The first step in investigating fractional difference maps, which do not have periodic points except fixed points, is to find asymptotically periodic points and bifurcation points and draw asymptotic bifurcation diagrams. Recently derived equations that allow calculations of asymptotically periodic and bifurcation points contain coefficients defined as slowl

Brian Kintu

In this first article of a multi-part series, we inspect a surprising relationship between the set of fixed points of a polynomial map $\varphi_{d, c}$ defined by $\varphi_{d, c}(z) = z^d + c$ for all $c, z \in \mathbb{Z}$ and the coefficient $c$, where $d > 2$ is an integer. Inspired greatly by the elegant counting problems along with the very striking resu

Vitalii Soldatov

We study linear boundary-value problems for systems of first-order ordinary differential equations with the most general boundary conditions in the normed spaces of continuously differentiable functions on a finite closed interval. The boundary conditions are allowed to be overdetermined or underdetermined with respect to the differential system and may cont

Advait Gadhikar, Souptik Kumar Majumdar, Niclas Popp, Piyapat Saranrittichai

Advancements in deep learning are driven by training models with increasingly larger numbers of parameters, which in turn heightens the computational demands. To address this issue, Mixture-of-Depths (MoD) models have been proposed to dynamically assign computations only to the most relevant parts of the inputs, thereby enabling the deployment of large-param

Deping Song, Xuding Zhu

Assume $G$ is a bridgeless graph. A cycle cover of $G$ is a collection of cycles of $G$ such that each edge of $G$ is contained in at least one of the cycles. The length of a cycle cover of $G$ is the sum of the lengths of the cycles in the cover. The minimum length of a cycle cover of $G$ is denoted by $cc(G)$. It was proved independently by Alon and Tarsi

Marlo Paßler, Adrien Doerig

Neurophenomenal structuralism posits that conscious experiences are defined relationally and that their phenomenal structures are mirrored by neural structures. While this approach offers a promising framework for identifying neural correlates of contents of consciousness (NCCCs), we argue that merely establishing structural correspondences between neural an

Langyu Wang, Bingke Zhu, Yingying Chen, Jinqiao Wang

Audio-visual video parsing focuses on classifying videos through weak labels while identifying events as either visible, audible, or both, alongside their respective temporal boundaries. Many methods ignore that different modalities often lack alignment, thereby introducing extra noise during modal interaction. In this work, we introduce a Learning Interacti

Davide Martinenghi

Data integrity is crucial for ensuring data correctness and quality, maintained through integrity constraints that must be continuously checked, especially in data-intensive systems like OLTP. While DBMSs handle common constraints well, complex constraints often require ad-hoc solutions. Research since the 1980s has focused on automatic and simplified integr

Chengjie Wang, Xi Jiang, Bin-Bin Gao, Zhenye Gan

Although mainstream unsupervised anomaly detection (AD) (including image-level classification and pixel-level segmentation)algorithms perform well in academic datasets, their performance is limited in practical application due to the ideal experimental setting of clean training data. Training with noisy data is an inevitable problem in real-world anomaly det

Akhilesh Balaji, Dhruv Ramu

This paper presents a framework for developing a live vision-correcting display (VCD) to address refractive visual aberrations without the need for traditional vision correction devices like glasses or contact lenses, particularly in scenarios where wearing them may be inconvenient. We achieve this correction through deconvolution of the displayed image usin

Bernhard Reinke, Kexin Wang

The Euler characteristic of a very affine variety encodes the number of critical points of the likelihood equation on this variety. In this paper, we study the Euler characteristic of the complement of a hypersurface arrangement with generic hypersurfaces added. For hyperplane arrangements, it depends on the characteristic polynomial coefficients and generic

Tuğçe Gökdemir, Jakub Rydzewski

Understanding the long-time dynamics of complex physical processes depends on our ability to recognize patterns. To simplify the description of these processes, we often introduce a set of reaction coordinates, customarily referred to as collective variables (CVs). The quality of these CVs heavily impacts our comprehension of the dynamics, often influencing

Jonathan Külz, Michael Terzer, Marco Magri, Andrea Giusti

In situ robotic automation in construction is challenging due to constantly changing environments, a shortage of robotic experts, and a lack of standardized frameworks bridging robotics and construction practices. This work proposes a holistic framework for construction task specification, optimization of robot morphology, and mission execution using a mobil

Fatou Ndiaye Mbodji, Vinny Adjibi, Moustapha Awwalou Diouf, Gervais Mendy

Due to the inherent immutability of blockchain technology, smart contract updates require their deployment at new addresses rather than modifying existing ones, thus fragmenting version histories and creating critical blind spots for analyses. Indeed, for example, this fragmentation severely hinders security researchers ability to track vulnerability lifecyc

Nikita Fominykh, Vladimir Stegailov

In this work, we apply the DFT+U approach for a detailed ab initio study of the refined structure of the low-temperature phase of magnetite [M. S. Senn et al., Nature 481, 173 (2012)]. We compare the electronic properties of this structure and several alternatives with respect to the presence of trimeron ordering and the bandgap properties. The connection of

Sergio Bermejo

This work proposes a novel approach to enhancing annotated bibliography generation through Large Language Model (LLM) ensembles. In particular, multiple LLMs in different roles -- controllable text generation, evaluation, and summarization -- are introduced and validated using a systematic methodology to enhance model performance in scholarly tasks. Output d

William Graham, Scott Joseph Larson

We study the torus-equivariant cohomology of weighted flag varieties, and prove a positivity property in the equivariant cohomology and Chow groups of weighted flag varieties, analogous to the non-weighted positivity proved in [Graham 2001]. Our result strengthens and generalizes the positivity proved for weighted Grassmannians by [Abe-Matsumura 2015]. The p

Hayato Shimabukuro

In this paper, we propose a novel method to recover the 21cm global signal from the 21cm power spectrum using artificial neural networks (ANNs). The 21cm global signal is crucial for understanding cosmic evolution from the Dark Ages through the Epoch of Reionization (EoR). While interferometers like LOFAR, MWA, HERA, and SKA focus on detecting the 21cm power

Ivan Limonchenko, Aleš Vavpetič

We describe all the Bier spheres of dimension $d$ with chromatic number equal to $d+1$ and prove that all other $d$-dimensional Bier spheres have chromatic number equal to $d+2$, for any integer $d\geq 0$. Then we prove a general formula for complex and mod $p$ Buchstaber numbers of a Bier sphere $\mathrm{Bier}(K)$, for each prime $p\in\mathbb{N}$ in terms o

Suman Raj, Radhika Mittal, Harshil Gupta, Yogesh Simmhan

Drone fleets with onboard cameras coupled with computer vision and DNN inferencing models can support diverse applications. One such novel domain is for one or more buddy drones to assist Visually Impaired People (VIPs) lead an active lifestyle. Video inferencing tasks from such drones can help both navigate the drone and provide situation awareness to the V

V. D. Stasenko, Yu. N. Eroshenko

The influence of a dark matter halo around pair of primordial black holes on their orbit evolution and the black hole merger rate is considered. Because of the nonspherical (nonradial) contraction of DM shells, each shell upon the first contraction passes through the halo center in the direction of the radius vector corresponding to zero angular momentum. Si

Leheng Cai, Qirui Hu

We develop a novel methodology for detecting abrupt break points in mean functions of functional time series, adaptable to arbitrary sampling schemes. By employing B-spline smoothing, we introduce $\mathcal L_{\infty}$ and $\mathcal L_2$ test statistics statistics based on a smoothed cumulative summation (CUMSUM) process, and derive the corresponding asympto

Teodor Bulboacă, Milutin Obradović, Nikola Tuneski

In this paper we give simple proofs for the main results concerning generalized Fekete-Szeg\H{o} functional of type $\left|a_{3}(f)-\lambda a_{2}(f)^{2}\right|-\mu|a_{2}(f)|$, where $\lambda\in\mathbb{C}$, $\mu>0$ and $a_{n}(f)$ is $n$-th coefficient of the power series expansion of $f\in\mathcal{S}$. In addition, we studied this functional separately for th

R. Chan, M. F. A. da Silva, V. H. Satheeshkumar

We present all possible analytical solutions of the Friedmann-Lema\^itre-Robertson-Walker metric in Einstein-aether theory for all values of the cosmological constant and spatial curvature with many reasonable values of the equation-of-state parameter. We analyze the dynamics of each model analytically and also graphically by plotting the geometric radius, H

Xin Yang, Xingrun Li, Heng Chang, Jinze Yang

The cold start problem is a challenging problem faced by most modern recommender systems. By leveraging knowledge from other domains, cross-domain recommendation can be an effective method to alleviate the cold start problem. However, the modelling distortion for long-tail data, which is widely present in recommender systems, is often overlooked in cross-dom