April 2024 arXiv papers — page 136

Yaowen Hu, Di Zhu, Shengyuan Lu, Xinrui Zhu

Electro-optics serves as the crucial bridge between electronics and photonics, unlocking a wide array of applications ranging from communications and computing to sensing and quantum information. Integrated electro-optics approaches in particular enable essential electronic high-speed control for photonics while offering substantial photonic parallelism for

Che Hao Liu, Van Que Tran, Qiaoyi Wen, Fanrong Xu

We study the flavor-changing bottom quark radiative decay $b \to s \gamma$ induced at one-loop level within the minimal gauged two-Higgs-doublet model (G2HDM). Among the three new contributions to this rare process in G2HDM, we find that only the charged Higgs $\mathcal{H^\pm}$ contribution can be constrained by the current global fit data in $B$-physics. Ot

Shengding Hu, Yuge Tu, Xu Han, Chaoqun He

The burgeoning interest in developing Large Language Models (LLMs) with up to trillion parameters has been met with concerns regarding resource efficiency and practical expense, particularly given the immense cost of experimentation. This scenario underscores the importance of exploring the potential of Small Language Models (SLMs) as a resource-efficient al

Alonso Castillo-Ramirez, Eduardo Veliz-Quintero

For a group $G$ and a finite set $A$, a cellular automaton (CA) is a transformation $\tau : A^G \to A^G$ defined via a finite memory set $S \subseteq G$ and a local map $\mu : A^S \to A$. Although memory sets are not unique, every CA admits a unique minimal memory set, which consists on all the essential elements of $S$ that affect the behavior of the local

Xingwei Qu, Yuelin Bai, Yinghao Ma, Ziya Zhou

In this paper, we explore the application of Large Language Models (LLMs) to the pre-training of music. While the prevalent use of MIDI in music modeling is well-established, our findings suggest that LLMs are inherently more compatible with ABC Notation, which aligns more closely with their design and strengths, thereby enhancing the model's performance in

Mikel Zubillaga, Oscar Sainz, Ainara Estarrona, Oier Lopez de Lacalle

Cross-lingual transfer-learning is widely used in Event Extraction for low-resource languages and involves a Multilingual Language Model that is trained in a source language and applied to the target language. This paper studies whether the typological similarity between source and target languages impacts the performance of cross-lingual transfer, an under-

Zhanran Lin, Puheng Li, Lei Wu

One of the most intriguing findings in the structure of neural network landscape is the phenomenon of mode connectivity: For two typical global minima, there exists a path connecting them without barrier. This concept of mode connectivity has played a crucial role in understanding important phenomena in deep learning. In this paper, we conduct a fine-grained

Haotian Luo

Ensuring alignment with human preferences is a crucial characteristic of large language models (LLMs). Presently, the primary alignment methods, RLHF and DPO, require extensive human annotation, which is expensive despite their efficacy. The significant expenses associated with current alignment techniques motivate researchers to investigate the development

Afonso Oliveira, Nuno Fachada, João P. Matos-Carvalho

Raster Forge is a Python library and graphical user interface for raster data manipulation and analysis. The tool is focused on remote sensing applications, particularly in wildfire management. It allows users to import, visualize, and process raster layers for tasks such as image compositing or topographical analysis. For wildfire management, it generates f

Yi Wang

The limiting character, introduced by Tillmann, has been studied recently in the context of Culler-Shalen theory. We extend the methods of the author's previous work to show that certain families of essential twice-punctured tori are detected by an ideal point on the character variety and determine the limiting character at these ideal points. We then provid

Nancirose Piazza, Amirhossein Karimia, Behnia Soleymanib, Vahid Behzadan

Effective communication in Multi-Agent Reinforcement Learning (MARL) can significantly enhance coordination and collaborative performance in complex and partially observable environments. However, reliance on communication can also introduce vulnerabilities when agents are misaligned, potentially leading to adversarial interactions that exploit implicit assu

Giovanna Broccia, Maurice H. ter Beek, Alberto Lluch Lafuente, Paola Spoletini

Context and Motivation Attack-Defense Trees (ADTs) are a graphical notation used to model and assess security requirements. ADTs are widely popular, as they can facilitate communication between different stakeholders involved in system security evaluation, and they are formal enough to be verified, e.g., with model checkers. Question/Problem While the qualit

Rahul Chakraborty, Matheus Morato F. de Moraes, Katharina Boguslawski, Artur Nowak

The dipole moment is a crucial molecular property linked to a molecular system's bond polarity and overall electronic structure. To that end, the electronic dipole moment, which results from the electron density of a system, is often used to assess the accuracy and reliability of new electronic structure methods. This work analyses electronic dipole moments

Nitin Serwa

We explore new symmetries in two-component third-order Burgers' type systems in (1+1)-dimension using Wang's O-scheme. We also find a master symmetry for a (2+1)-dimensional Davey-Stewartson type system. These results shed light on the behavior of these equations and help us understand their integrability properties. Our approach offers a practical method fo

Loïc Gassmann

We describe the asymptotic behaviour of large degrees in random hyperbolic graphs, for all values of the curvature parameter $ \alpha$. We prove that, with high probability, the node degrees satisfy the following ordering property: the ranking of the nodes by decreasing degree coincides with the ranking of the nodes by increasing distance to the centre, at l

Tianchen Yuan, Petros A. Ioannou

Arterial traffic interacts with freeway traffic, yet the two are controlled independently. Arterial traffic signals do not take into account freeway traffic and how ramps control ingress traffic and have no control over egress traffic from the freeway. This often results in long queues in either direction that block ramps and spill over to arterial streets o

Ghassan Dibeh, Omar El Deeb

We examine a system of N=2 coupled non-linear delay-differential equations representing financial market dynamics. In such time delay systems, coupled oscillations have been derived. We linearize the system for small time delays and study its collective dynamics. Using analytical and numerical solutions, we obtain the bifurcation diagrams and analyze the cor

Pushpa Panday, Amaresh Jaiswal, Binoy Krishna Patra

In the present work, we derive a linearly stable and causal theory of relativistic third-order viscous hydrodynamics from the Boltzmann equation with relaxation-time approximation. We employ viscous correction to the distribution function obtained using a Chapman-Enskog like iterative solution of the Boltzmann equation. Our derivation highlights the necessit

Timothée Crin-Barat, Dragoş Manea

In this paper, we analyze the preservation of asymptotic properties of partially dissipative hyperbolic systems when switching to a discrete setting. We prove that one of the simplest consistent and unconditionally stable numerical methods - the central finite difference scheme - preserves both the asymptotic behaviour and the parabolic relaxation limit of o

Joel Brewster Lewis, Bridget Eileen Tenner

Previous work has shown that the disarray (or displacement) of an (affine) (signed) permutation is bounded in terms of its Coxeter length. Here, we characterize the permutations for which the bound is sharp in two ways: in terms of a natural property of their reduced words, and by ``globally'' avoiding the pattern 321.

Malachi Noel, Jason J. Wang, Bruce Macintosh, Katie Crotts

The Atmospheric Dispersion Corrector (ADC) of the Gemini Planet Imager (GPI) corrects the chromatic dispersion caused by differential atmospheric refraction (DAR), making it an important optic for exoplanet observation. Despite requiring less than 5 mas of residual DAR to avoid potentially affecting the coronagraph, the GPI ADC averages $\sim7$ and $\sim11$

Juliette Plouin, Bertrand Baudouy, Aurélien Four, Jean-Pierre Charrier

Superconducting RF cavities are used in particle accelerators to provide energy to the particle beam. Such cavities are mostly fabricated in niobium and often operated in superfluid helium. One of their limits of operation is the appearance of a local quench, initiated by a local field enhancement due to a defect, which leads to a normal conducting transitio

David Flores-Peñaloza, Mario A. Lopez, Nestaly Marín, David Orden

Let $P$ be a $k$-colored set of $n$ points in the plane, $4 \leq k \leq n$. We study the problem of deciding if $P$ contains a subset of four points of different colors such that its Rectilinear Convex Hull has positive area. We show this problem to be equivalent to deciding if there exists a point $c$ in the plane such that each of the open quadrants define

Alireza Rashnu, Armin Salimi-Badr

Efficient early diagnosis is paramount in addressing the complexities of Parkinson's disease because timely intervention can substantially mitigate symptom progression and improve patient outcomes. In this paper, we present a pioneering deep learning architecture tailored for the binary classification of subjects, utilizing gait cycle datasets to facilitate

Martin Bojowald, Erick I. Duque

A complete canonical formulation of general covariance makes it possible to construct new modified theories of gravity that are not of higher-curvature form, as shown here in a spherically symmetric setting. The usual uniqueness theorems are evaded by using a crucial and novel ingredient, allowing for fundamental fields of gravity distinct from an emergent s

Mark Walth, Amir Sajadi, Marc Carbone, Bri-Mathias Hodge

Achieving stable synchronized operation in an alternating current power network is critical to the continuity and reliability of energy delivery. In this paper, we study a dynamic model for synchronization in the proposed power network which the National Aeronautic and Space Agency plans to build on the lunar surface to support continuous human presence on t

Darryl D. Holm, Ruiao Hu, Oliver D. Street

We derive new models of stochastic Hall magnetohydrodynamics (MHD) by using a symmetry-reduced stochastic Euler-Poincar\'e variational principle. The new stochastic Hall MHD theory has potential applications for uncertainty quantification and data assimilation in space plasma (space weather) and solar physics. The stochastic geometric mechanics approach we t

Elise Potters, Behzad Mosalla Nezhad, Viktor Huiskes, Erwin Hans

The significance of last-mile logistics in the healthcare supply chain is growing steadily, especially in pharmacies where the growing prevalence of medication delivery to patients' homes is remarkable. This paper proposes a novel mathematical model for the last-mile logistics of the pharmaceutical supply chain and optimizes a pharmacy's logistical financial

Hua Chen, Jiangtao Hu, Xiaochun Liu, Yawei Wei

In this paper, we study the cone degenerate p-Laplace equation. We provide the existence of the viscosity solutions by proving Alexandrov-Bakelman-Pucci and H\"older estimates. Further more, we give the comparison principle by an equivalent transformation. Finally, we obtain the existence of weak solutions by analyzing the relationship between weak solutions

Ana Clara das Neves Silva, Clebson Cruz

In this paper, we investigate the use of variational quantum algorithms for simulating the thermodynamic properties of dinuclear metal complexes. Our study highlights the potential of quantum computing to transform advanced simulations and provide insights into the physical behavior of quantum systems. The results demonstrate the effectiveness of variational

Alessio Ferrari, Sallam Abualhaija, Chetan Arora

Complementing natural language (NL) requirements with graphical models can improve stakeholders' communication and provide directions for system design. However, creating models from requirements involves manual effort. The advent of generative large language models (LLMs), ChatGPT being a notable example, offers promising avenues for automated assistance in

Valdecy Pereira, Marcio Pereira Basilio, Carlos Henrique Tarjano SantosCarlos Henrique Tarjano Santos

Purpose: Multicriteria decision analysis (MCDA) has become increasingly essential for decision-making in complex environments. In response to this need, the pyDecision library, implemented in Python and available at https://bit.ly/3tLFGtH, has been developed to provide a comprehensive and accessible collection of MCDA methods. Methods: The pyDecision offers

Yi Gui, Zhen Li, Yao Wan, Yemin Shi

Automatically generating webpage code from webpage designs can significantly reduce the workload of front-end developers, and recent Multimodal Large Language Models (MLLMs) have shown promising potential in this area. However, our investigation reveals that most existing MLLMs are constrained by the absence of high-quality, large-scale, real-world datasets,

Samuel Carolus, Jacob Laubacher, Sydney D. Vitalbo, Leah K. Widlarz

It is well known that the bar resolution can be replaced with any projective resolution of the corresponding algebra when computing the Hochschild (co)homology of that algebra. This is, in fact, a feature of its construction via derived functors. For generalizations and extensions of the Hochschild (co)homology, one uses a bar-like resolution in a simplicial

Fernando Gallego, Guillermo López-García, Luis Gasco-Sánchez, Martin Krallinger

Advances in natural language processing techniques, such as named entity recognition and normalization to widely used standardized terminologies like UMLS or SNOMED-CT, along with the digitalization of electronic health records, have significantly advanced clinical text analysis. This study presents ClinLinker, a novel approach employing a two-phase pipeline

Aurélien Drezet

In this note, we discuss a historical point regarding Schr\"odinger's discovery of the famous quantum wave equation in 1926 following de Broglie's fundamental works published in 1923-1925 regarding the introduction of matter waves. Drawing on the work of historians and personal analysis, we show that de Broglie was very close to the discovery of the Schr\"od

Songpan Wang, Xu Li, Tianxiang Jiang, Yuanlun Xie

Facial expression recognition (FER) is vital for human-computer interaction and emotion analysis, yet recognizing expressions in low-resolution images remains challenging. This paper introduces a practical method called Dynamic Resolution Guidance for Facial Expression Recognition (DRGFER) to effectively recognize facial expressions in images with varying re

Xintao Wang, Jiangjie Chen, Nianqi Li, Lida Chen

In the rapidly advancing research fields such as AI, managing and staying abreast of the latest scientific literature has become a significant challenge for researchers. Although previous efforts have leveraged AI to assist with literature searches, paper recommendations, and question-answering, a comprehensive support system that addresses the holistic need

Nathan Albin, Joan Lind, Anna Melikyan, Pietro Poggi-Corradini

In this paper, we study extremal values for the determinant of the weighted graph Laplacian under simple nondegeneracy conditions on the weights. We derive necessary and sufficient conditions for the determinant of the Laplacian to be bounded away from zero and for the existence of a minimizing set of weights. These conditions are given both in terms of prop

Sidra Aleem, Fangyijie Wang, Mayug Maniparambil, Eric Arazo

The Segment Anything Model (SAM) and CLIP are remarkable vision foundation models (VFMs). SAM, a prompt driven segmentation model, excels in segmentation tasks across diverse domains, while CLIP is renowned for its zero shot recognition capabilities. However, their unified potential has not yet been explored in medical image segmentation. To adapt SAM to med

Delia Kesner, Victor Arrial, Giulio Guerrieri

This paper studies the notion of meaningfulness for a unifying framework called dBang-calculus, which subsumes both call-by-name (dCbN) and call-by-value (dCbV). We first characterize meaningfulness in dBang by means of typability and inhabitation in an associated non-idempotent intersection type system previously proposed in the literature. We validate the

Ebode Atangana Pie Desire

This paper studies the circular coloring of signed graphs. A signed graph is a graph with a signature that assigns a sign to each edge, either positive or negative. This paper studies circular coloring and a circular chromatic number of Type 1 and Type Cartesian products. We shall prove the following results: The circular chromatic number of Cartesian produc

Bastian Kuth, Max Oberberger, Felix Kawala, Sander Reitter

We propose a codec specifically designed for meshlet compression, optimized for rapid data-parallel GPU decompression within a mesh shader. Our compression strategy orders triangles in optimal generalized triangle strips (GTSs), which we generate by formulating the creation as a mixed integer linear program (MILP). Our method achieves index buffer compressio

Pedro A. García-Sánchez, Laura González, Francesc Planas-Vilanova

Let $S$ be the numerical semigroup generated by three consecutive numbers $a,a+1,a+2$, where $a\in\mathbb{N}$, $a\geq 3$. We describe the elements of $S$ whose factorizations have all the same length, as well as the set of factorizations of each of these elements. We give natural partitions of this subset of $S$ in terms of the length and the denumerant. By

Hyewon Jang, Diego Frassinelli

We tested the robustness of sarcasm detection models by examining their behavior when fine-tuned on four sarcasm datasets containing varying characteristics of sarcasm: label source (authors vs. third-party), domain (social media/online vs. offline conversations/dialogues), style (aggressive vs. humorous mocking). We tested their prediction performance on th

Matthew Thomas Jackson, Michael Tryfan Matthews, Cong Lu, Benjamin Ellis

In many real-world settings, agents must learn from an offline dataset gathered by some prior behavior policy. Such a setting naturally leads to distribution shift between the behavior policy and the target policy being trained - requiring policy conservatism to avoid instability and overestimation bias. Autoregressive world models offer a different solution

Suman Jyoti De, Sumathi Rao, Ganpathy Murthy

We study magnon transmission across gate-controlled junctions in the $n=0$ manifold of Landau levels in monolayer graphene, in the presence of both spin and valley Zeeman fields. Specifically, we consider the $1|-1|1$ sandwich geometry. The nature of the interfaces between regions of different filling turns out to be crucial for magnon transmission. Using th

Agustín Moreno Cañadas, Pedro Fernando Fernández Espinosa, José Gregorio Rodríguez Nieto, Odette M. Mendez

Since their introduction, Brauer configuration algebras (BCAs) and their specialized messages have helped research in several fields of mathematics and sciences. This paper deals with a new perspective on using such algebras as a theoretical framework in classical cryptography and music theory. It is proved that some block cyphers define labeled Brauer confi

Subhojoy Gupta, Gobinda Sau

For any twisted ideal polygon in $\mathbb{H}^3$, we construct a harmonic map from $\mathbb{C}$ to $\mathbb{H}^3$ with a polynomial Hopf differential, that is asymptotic to the given polygon, and is a bounded distance from a pleated plane. Our proof uses the harmonic map heat flow. We also show that such a harmonic map is unique once we prescribe the principa

Mahmut S. Gokmen, Cody Bumgardner, Jie Zhang, Ge Wang

Consistency models possess high capabilities for image generation, advancing sampling steps to a single step through their advanced techniques. Current advancements move one step forward consistency training techniques and eliminates the limitation of distillation training. Even though the proposed curriculum and noise scheduling in improved training techniq

Senthil Yogamani, David Unger, Venkatraman Narayanan, Varun Ravi Kumar

Semantic segmentation is an effective way to perform scene understanding. Recently, segmentation in 3D Bird's Eye View (BEV) space has become popular as its directly used by drive policy. However, there is limited work on BEV segmentation for surround-view fisheye cameras, commonly used in commercial vehicles. As this task has no real-world public dataset an

Xiaolong Tang, Meina Kan, Shiguang Shan, Zhilong Ji

Predicting the trajectories of road agents is essential for autonomous driving systems. The recent mainstream methods follow a static paradigm, which predicts the future trajectory by using a fixed duration of historical frames. These methods make the predictions independently even at adjacent time steps, which leads to potential instability and temporal inc

Mingdeng Cao, Sidi Yang, Yujiu Yang, Yinqiang Zheng

This paper proposes to correct the rolling shutter (RS) distorted images by estimating the distortion flow from the global shutter (GS) to RS directly. Existing methods usually perform correction using the undistortion flow from the RS to GS. They initially predict the flow from consecutive RS frames, subsequently rescaling it as the displacement fields from

Yu Zhou, Xingyu Wu, Jibin Wu, Liang Feng

The ability to understand causality significantly impacts the competence of large language models (LLMs) in output explanation and counterfactual reasoning, as causality reveals the underlying data distribution. However, the lack of a comprehensive benchmark currently limits the evaluation of LLMs' causal learning capabilities. To fill this gap, this pap

Jeremy Karam, Alison Sills

We perform high resolution simulations of forming star clusters as they merge inside giant molecular clouds (GMCs) using hydrodynamics coupled to N-body dynamics to simultaneously model both the gas and stars. We zoom in to previously run GMC simulations and resolve clusters into their stellar and gas components while including the surrounding GMC environmen

Henan Wang, Hanxin Zhu, Tianyu He, Runsen Feng

3D Gaussian Splatting (3DGS) has become an emerging technique with remarkable potential in 3D representation and image rendering. However, the substantial storage overhead of 3DGS significantly impedes its practical applications. In this work, we formulate the compact 3D Gaussian learning as an end-to-end Rate-Distortion Optimization (RDO) problem and propos

Chenghao Xiao, G Thomas Hudson, Noura Al Moubayed

Semantic textual similartiy (STS) and information retrieval tasks (IR) tasks have been the two major avenues to record the progress of embedding models in the past few years. Under the emerging Retrieval-augmented Generation (RAG) paradigm, we envision the need to evaluate next-level language understanding abilities of embedding models, and take a conscious

Jiacheng Wei, Zhonghao Xia, Yi Xia, Jiangang He

Lattice thermal conductivity ($\kappa_{\rm L}$) is a crucial characteristic of crystalline solids with significant implications for practical applications. While the higher order of anharmonicity of phonon gas model is commonly used for explaining extraordinary heat transfer behaviors in crystals, the impact of exchange-correlation (XC) functionals in DFT on

Senkang Hu, Zhengru Fang, Zihan Fang, Yiqin Deng

Connected and autonomous driving is developing rapidly in recent years. However, current autonomous driving systems, which are primarily based on data-driven approaches, exhibit deficiencies in interpretability, generalization, and continuing learning capabilities. In addition, the single-vehicle autonomous driving systems lack of the ability of collaboratio

Tyler Hennen, Leon Brackmann, Tobias Ziegler, Sebastian Siegel

We present a fast generative modeling approach for resistive memories that reproduces the complex statistical properties of real-world devices. To enable efficient modeling of analog circuits, the model is implemented in Verilog-A. By training on extensive measurement data of integrated 1T1R arrays (6,000 cycles of 512 devices), an autoregressive stochastic

Nafiseh Ghasemi, Jon Alvarez Justo, Marco Celesti, Laurent Despoisse

Recent advancements in deep learning techniques have spurred considerable interest in their application to hyperspectral imagery processing. This paper provides a comprehensive review of the latest developments in this field, focusing on methodologies, challenges, and emerging trends. Deep learning architectures such as Convolutional Neural Networks (CNNs),

Zinovy Malkin

Recently, it has been suggested in the literature that the difference between universal and coordinated time UT1-UTC could reach a large positive value in the coming years (Agnew 2024). This would make it necessary to introduce a negative leap second into UTC for the first time in history, which in turn will cause serious problems in time keeping and synchro

Damiana Lazzaro, Serena Morigi, Luca Ratti

Sparse recovery principles play an important role in solving many nonlinear ill-posed inverse problems. We investigate a variational framework with support Oracle for compressed sensing sparse reconstructions, where the available measurements are nonlinear and possibly corrupted by noise. A graph neural network, named Oracle-Net, is proposed to predict the s

Adil Z. Babar, Ozgur B. Akan

Agriculture faces critical challenges from population growth, resource scarcity, and climate change, driving a shift toward advanced, technology-integrated farming. Mechanization has transformed agriculture, enhancing sustainability and crop productivity. Now, technologies like artificial intelligence (AI), robotics, biotechnology, blockchain, and the Intern

Jennifer Yeom, Roshan Balu T M B, Guanrui Li, Giuseppe Loianno

Quadrotors have gained popularity over the last decade, aiding humans in complex tasks such as search and rescue, mapping and exploration. Despite their mechanical simplicity and versatility compared to other types of aerial vehicles, they remain vulnerable to rotor failures. In this paper, we propose an algorithmic and mechanical approach to addressing the

Mathivanan Periasamy, Rohith Mahadevan, Bagiya Lakshmi S, Raja CSP Raman

Sentiment analysis, a vital component in natural language processing, plays a crucial role in understanding the underlying emotions and opinions expressed in textual data. In this paper, we propose an innovative ensemble approach for sentiment analysis for finding fake reviews that amalgamate the predictive capabilities of Support Vector Machine (SVM), K-Nea

Erik Kuitunen, Matthew T. Moores, Teemu Härkönen

We propose a statistical approach for estimating the mean line width in spectra comprising Lorentzian, Gaussian, or Voigt line shapes. Our approach uses Gaussian processes in two stages to jointly model a spectrum and its Fourier transform. We generate statistical samples for the mean line width by drawing realizations for the Fourier transform and its deriv

Axel Barroso-Laguna, Sowmya Munukutla, Victor Adrian Prisacariu, Eric Brachmann

Given two images, we can estimate the relative camera pose between them by establishing image-to-image correspondences. Usually, correspondences are 2D-to-2D and the pose we estimate is defined only up to scale. Some applications, aiming at instant augmented reality anywhere, require scale-metric pose estimates, and hence, they rely on external depth estimat

Yuchen Zhu, Tianrong Chen, Evangelos A. Theodorou, Xie Chen

This article considers the generative modeling of the (mixed) states of quantum systems, and an approach based on denoising diffusion model is proposed. The key contribution is an algorithmic innovation that respects the physical nature of quantum states. More precisely, the commonly used density matrix representation of mixed-state has to be complex-valued

ATLAS Collaboration

The ATLAS experiment has developed extensive software and distributed computing systems for Run 3 of the LHC. These systems are described in detail, including software infrastructure and workflows, distributed data and workload management, database infrastructure, and validation. The use of these systems to prepare the data for physics analysis and assess it

Sarveshkumar Purohit, Shantanu Desai

In order to test the efficacy of Gamma-ray Bursts (GRB) as cosmological probes, we characterize the scatter in the correlations between six pairs of GRB observables, which have previously also been studied in arXiv:2011.14040. However, some of these observables depend on the luminosity distance, for which one needs to assume an underlying cosmological model.

Theo Johnson-Freyd, Mayuko Yamashita

We are aimed at giving a differential geometric, and accordingly physical, explanation of the 576-periodicity of TMF. In this paper, we settle the problem of giving the lower bound 576. We formulate the problem as follows: we assume a spectrum $\mathrm{SQFT}$ with some conditions, suggest from physical considerations about the classifying spectrum for two-di

Barbara Lopez-Doriga, Eric Ballouz, H. Jane Bae, Scott T. M. Dawson

Resolvent analysis provides a framework to predict coherent spatio-temporal structures of largest linear energy amplification, through a singular value decomposition (SVD) of the resolvent operator, obtained by linearizing the Navier-Stokes equations about a known turbulent mean velocity profile. Resolvent analysis utilizes a Fourier decomposition in time, w

Yanjie Li, Weijun Li, Lina Yu, Min Wu

The mathematical formula is the human language to describe nature and is the essence of scientific research. Finding mathematical formulas from observational data is a major demand of scientific research and a major challenge of artificial intelligence. This area is called symbolic regression. Originally symbolic regression was often formulated as a combinat

Felipe M. Dias, Diego A. C. Cardenas, Marcelo A. F. Toledo, Filipe A. C. Oliveira

Hypertension, a leading contributor to cardiovascular morbidity, underscores the need for accurate and continuous blood pressure (BP) monitoring. Photoplethysmography (PPG) presents a promising approach to this end. However, the precision of BP estimates derived from PPG signals has been the subject of ongoing debate, necessitating a comprehensive evaluation

Peter Mørch Groth, Mads Herbert Kerrn, Lars Olsen, Jesper Salomon

Reliable prediction of protein variant effects is crucial for both protein optimization and for advancing biological understanding. For practical use in protein engineering, it is important that we can also provide reliable uncertainty estimates for our predictions, and while prediction accuracy has seen much progress in recent years, uncertainty metrics are

M. K. Volkov, A. A. Pivovarov, K. Nurlan

In the framework of the $U(3) \times U(3)$ extended Nambu-Jona-Lasinio model, the processes $e^+e^- \to K^+K^-\pi^0$ and $e^+e^- \to K^+K^-\eta$ are described taking into account both ground and first radially excited intermediate meson states. It is shown that channels with radially excited $\phi(1680)$ meson are dominant in both processes. The influence on

Christine Foss Sjulstad, Danielle Monteiro, Bjarne Grimstad

In petroleum production systems, continuous multiphase flow rates are essential for efficient operation. They provide situational awareness, enable production optimization, improve reservoir management and planning, and form the basis for allocation. Furthermore, they can be crucial to ensure a fair revenue split between stakeholders for complex production s

Sanjeev Khanna, Aaron L. Putterman, Madhu Sudan

CSP sparsification, introduced by Kogan and Krauthgamer (ITCS 2015), considers the following question: how much can an instance of a constraint satisfaction problem be sparsified (by retaining a reweighted subset of the constraints) while still roughly capturing the weight of constraints satisfied by {\em every} assignment. CSP sparsification captures as a s

Tom Hanika, Tobias Hille

Dimensionality is an important aspect for analyzing and understanding (high-dimensional) data. In their 2006 ICDM paper Tatti et al. answered the question for a (interpretable) dimension of binary data tables by introducing a normalized correlation dimension. In the present work we revisit their results and contrast them with a concept based notion of intrin

Ruoxi Li, Dana Nau, Mark Roberts, Morgan Fine-Morris

Hierarchical Task Network (HTN) planning usually requires a domain engineer to provide manual input about how to decompose a planning problem. Even HTN-MAKER, a well-known method-learning algorithm, requires a domain engineer to annotate the tasks with information about what to learn. We introduce CURRICULAMA, an HTN method learning algorithm that completely

Payam Abdisarabshali, Kwang Taik Kim, Michael Langberg, Weifeng Su

Existing studies on federated learning (FL) are mostly focused on system orchestration for static snapshots of the network and making static control decisions (e.g., spectrum allocation). However, real-world wireless networks are susceptible to temporal variations of wireless channel capacity and users' datasets. In this paper, we incorporate multi-granular

A. C. Semposki, C. Drischler, R. J. Furnstahl, J. A. Melendez

Constraining the equation of state (EOS) of strongly interacting, dense matter is the focus of intense experimental, observational, and theoretical effort. Chiral effective field theory ($\chi$EFT) can describe the EOS between the typical densities of nuclei and those in the outer cores of neutron stars while perturbative QCD (pQCD) can be applied to propert

Jean Farago, Manon Jouanlanne, Antoine Egelé, Aurélie Hourlier-Fargette

Taking advantage of the competition between elasticity and capillarity has proven to be an efficient way to design structures by folding, bending, or assembling elastic objects in contact with liquid interfaces. Elastocapillary effects often occur at scales where gravity does not play an important role, such as in microfabrication processes. However, the inf

Erica S. Dinkins, Kailash C. Misra

Let $\mathfrak{g}$ be an affine Lie algebra with index set $I = \{0, 1, 2, \cdots , n\}$ and $\mathfrak{g}^L$ be its Langlands dual. It is conjectured that for each Dynkin node $i \in I \setminus \{0\}$ the affine Lie algebra $\mathfrak{g}$ has a positive geometric crystal whose ultra-discretization is isomorphic to the limit of a certain coherent family of

Portia Anderson

We generalize classical triangular Schubert puzzles to puzzles with convex polygonal boundary. We give these puzzles a geometric Schubert calculus interpretation and derive novel combinatorial commutativity statements, using purely geometric arguments, for puzzles with four, five, and six sides, having various types of symmetry in their boundary conditions.

Milan Hladík, Hossein Moosaei, Fakhrodin Hashemi, Saeed Ketabchi

This paper provides a thorough exploration of the absolute value equations $Ax-|x|=b$, a seemingly straightforward concept that has gained heightened attention in recent years. It is an NP-hard and nondifferentiable problem and equivalent with the standard linear complementarity problem. Offering a comprehensive review of existing literature, the study delve

Lalit Kumar, Arushi Sharma, Anil Khachi, Ayushi Awasthi

Background: The phase-shift analysis for proton-proton scattering has been studied by various research groups using the realistic potentials to be comprised of various internal interactions based on an exchange of pions and mesons, involving a large number of parameters. Purpose: The goal of the research is to construct inverse potentials for various l-chann

Haritha T, Chithra A

The central graph $C(G)$ of a graph $G$ is the graph obtained by inserting a new vertex into each edge of $G$ exactly once and joining all the non-adjacent vertices in $G$. Let $G_1$ and $G_2$ be two vertex disjoint graphs. The central vertex join of $G_1$ and $G_2$ is the graph $ G_1\dot{\vee} G_2$, is obtained from $C(G_1)$ and $G_2$ by joining each vertex

J. Lillo-Box, M. Morales-Calderón, D. Barrado, O. Balsalobre-Ruza

Chance-aligned sources or blended companions can cause false positives in planetary transit detections or simply bias the determination of the candidate properties. In the era of high-precision space-based photometers, the need for high-spatial resolution images has demonstrated to be critical for validating and confirming transit signals. This already appli

Yiwen Ding

Let $K$ be a finite extension of $\mathbb{Q}_p$. We study the locally $\mathbb{Q}_p$-analytic representations $\pi$ of $\mathrm{GL}_n(K)$ of integral weights that appear in spaces of $p$-adic automorphic representations. We conjecture that the translation of $\pi$ to the singular block has an internal structure which is compatible with certain algebraic repr

Nico Meyer, Christian Ufrecht, Maniraman Periyasamy, Axel Plinge

Quantum computer simulation software is an integral tool for the research efforts in the quantum computing community. An important aspect is the efficiency of respective frameworks, especially for training variational quantum algorithms. Focusing on the widely used Qiskit software environment, we develop the qiskit-torch-module. It improves runtime performan

Amir Hagai, Yair Weiss

The ability to fool deep learning classifiers with tiny perturbations of the input has lead to the development of adversarial training in which the loss with respect to adversarial examples is minimized in addition to the training examples. While adversarial training improves the robustness of the learned classifiers, the procedure is computationally expensi

W. H. Li, A. C. Bartnik, A. Fukasawa, M. Kaemingk

Achieving maximum electron beam brightness in photoinjectors requires detailed control of the 3D bunch shape and precise tuning of the beam focusing. Even in state-of-the-art designs, slice emittance growth due to nonlinear space charge forces and partial nonlaminarity often remains non-negligible. In this work we introduce a new means to linearize the trans

Shen Gao, Yifan Wang, Jiabao Fang, Lisi Chen

Recommendation systems play a crucial role in various domains, suggesting items based on user behavior.However, the lack of transparency in presenting recommendations can lead to user confusion. In this paper, we introduce Data-level Recommendation Explanation (DRE), a non-intrusive explanation framework for black-box recommendation models.Different from exi

Xiaoma Wang, Gan Gu, Xiaoyong Mu, Shuo Yuan

We extract key information of dark energy from current observations of BAO, OHD and $H_0$, and find hints of dynamical behaviour of dark energy. In particular, a dynamical dark energy model whose equation of state crosses $-1$ is favoured by observations. We also find that the Universe has started accelerating at a lower redshift than expected.

David Kurzendörfer, Otniel-Bogdan Mercea, A. Sophia Koepke, Zeynep Akata

Audio-visual zero-shot learning methods commonly build on features extracted from pre-trained models, e.g. video or audio classification models. However, existing benchmarks predate the popularization of large multi-modal models, such as CLIP and CLAP. In this work, we explore such large pre-trained models to obtain features, i.e. CLIP for visual features, a

Costantino Delizia, Michele Gaeta, Carmine Monetta

The study of verbal subgroups within a group is well-known for being an effective tool to obtain structural information about a group. Therefore, conditions that allow the classification of words in a free group are of paramount importance. One of the most studied problems is to establish which words are concise, where a word $w$ is said to be concise if the

Hung P. Tong-Viet

Let $G$ be a finite group and let $H$ be a subgroup of $G$. We say that $H$ is extremely closed in $G$ if $\langle H,H^g\rangle\cap N_G(H)=H$ for all $g\in G.$ In this paper, we determine the structure of finite groups with an extremely closed abelian $p$-subgroup for some prime $p$. In particular, we show that if $G$ contains such a subgroup $H$, then $G=N_

Dasheng Liu

The Riemann Hypothesis is a conjecture that all non-trivial zeros of Riemann Zeta function are located on the critical line in the complex plane. Hundreds of propositions in function theory and analytic number theory rely on this hypothesis. However, the problem has been unresolved for over a century. Here we show that at least one set of quadruplet-zeros ex