December 2023 arXiv papers — page 20

Giulia Tucci

Unraveling the role of opinion leaders in the digital realm, this study investigates the influence of key actors on Telegram, a hybrid platform that combines messaging app features with social network dynamics, where channel administrators gain a unique authoritative role. This research aims to create a method to identify opinion leaders in a network of forw

Robert Schippa

We show new global well-posedness results for mass-critical nonlinear Schr\"odinger equations on tori in one and two dimensions. For the quintic nonlinear Schr\"odinger equation on the circle we show global well-posedness for initial data in $H^s(\mathbb{T})$ for $s>\frac{1}{3}$ and $\| u_0 \|_{L^2(\mathbb{T})} \ll 1$. In two dimensions we show global well-p

Jaume de Haro

Einstein presented the Hole Argument against General Covariance, understood as invariance with respect to a change of coordinates, as a consequence of his initial failure to obtain covariant equations that, in the weak static limit, contain Newton's law. Fortunately, about two years later, Einstein returned to General Covariance and found these famous equati

Georgios Argyris

Background: Imagine a paper with n nodes on it where each pair undergoes a coin toss experiment; if heads we connect the pair with an undirected link, while tails maintain the disconnection. This procedure yields a random graph. Now consider duplicating this network onto another paper with a slight bias-a fraction of its links (approximately 1/10) undergo re

Przemysław Pałka, Marco Lippi, Francesca Lagioia, Rūta Liepiņa

The paper reports the results of an experiment aimed at testing to what extent ChatGPT 3.5 and 4 is able to answer questions regarding privacy policies designed in the new format that we propose. In a world of human-only interpreters, there was a trade-off between comprehensiveness and comprehensibility of privacy policies, leading to the actual policies not

Alberto F. Boix, Danny A. J. Gómez-Ramírez

The goal of this paper is to study Goldbach's conjecture for rings of regular functions of affine algebraic varieties over a field. Among our main results, we define the notion of Goldbach condition for Newton polytopes, and we prove in a constructive way that any polynomial in at least two variables over a field can be expressed as sum of at most $2r$ absol

Elia Rizzetto, Silvio Peroni

This study describes the methodology and analyses the results of the process of mapping entities between two large open bibliographic metadata collections, OpenCitations Meta and OpenAlex. The primary objective of this mapping is to integrate OpenAlex internal identifiers into the existing metadata of bibliographic resources in OpenCitations Meta, thereby in

Victor Aldaya, Julio Guerrero, Francisco F. López-Ruiz

The momentum space associated with "tachyonic particles" proves to be rather intricate, departing very much from the ordinary dual to Minkowski space directly parametrized by space-time translations of the Poincar\'e group. In fact, although described by the constants of motion (Noether invariants) associated with space-time translations, they depend non-tri

A. Larosa, C. H. K Chen, J. R. McIntyre, V. K. Jagarlamudi

We investigate the relation between turbulence and magnetic field switchbacks in the inner heliosphere below 0.5 AU in a distance and scale dependent manner. The analysis is performed by studying the evolution of the magnetic field vector increments and the corresponding rotation distributions, which contain the switchbacks. We find that the rotation distrib

Fatemeh Hashemniya, Arvind Balachandran, Erik Frisk, Mattias Krysander

Safety, reliability, and durability are targets of all engineering systems, including Li-ion batteries in electric vehicles. This paper focuses on sensor setup exploration for a battery-integrated modular multilevel converter (BI-MMC) that can be part of a solution to sustainable electrification of vehicles. BI-MMC contains switches to convert DC to AC to dr

Tomer Garber, Tom Tirer

Training deep neural networks has become a common approach for addressing image restoration problems. An alternative for training a "task-specific" network for each observation model is to use pretrained deep denoisers for imposing only the signal's prior within iterative algorithms, without additional training. Recently, a sampling-based variant of this app

Vladimir S. Matveev, Yuri Nikolayevsky

Every Killing tensor field on the space of constant curvature and on the complex projective space can be decomposed into the sum of symmetric tensor products of Killing vector fields (equivalently, every polynomial in the velocities integral of the geodesic flow is a polynomial in the linear integrals). This fact led to the natural question on whether this p

Roberto Araujo

We show that the set of awesome homogeneous metrics on non-compact manifolds is Ricci flow invariant. Moreover, if the universal cover of such awesome homogeneous space is not contractible the Ricci flow has finite extinction time, confirming the Dynamical Alekseevskii Conjecture in this case. We also analyze the long-time limits of awesome homogeneous Ricci

Maghsood Salimi, Mohammad Loni, Sara Afshar, Antonio Cicchetti

The increasing demand for autonomous machines in construction environments necessitates the development of robust object detection algorithms that can perform effectively across various weather and environmental conditions. This paper introduces a new semantic segmentation dataset specifically tailored for construction sites, taking into account the diverse

Mathias Beiglböck, Gudmund Pammer, Alexander Posch

A basic and natural coupling between two probabilities on $\mathbb R^N$ is given by the Knothe-Rosenblatt coupling. It represents a multiperiod extension of the quantile coupling and is simple to calculate numerically. We consider the distance on $\mathcal P (\mathbb R^N)$ that is induced by considering the transport costs associated to the Knothe-Rosenblatt

Jingchun Li, J. Bao, Z. Lin, J. Q. Dong

The characteristics of ion temperature gradient (ITG) turbulence in the presence of a magnetic island are numerically investigated using a gyrokinetic model. We observe that in the absence of the usual ITG drive gradient, a solitary magnetic island alone can drive ITG instability. The magnetic island not only drives high-n modes of ITG instability but also i

Alessandro Palma, Marco Angelini

Attack Graph (AG) represents the best-suited solution to support cyber risk assessment for multi-step attacks on computer networks, although their generation suffers from poor scalability due to their combinatorial complexity. Current solutions propose to address the generation problem from the algorithmic perspective and postulate the analysis only after th

Stefan Volz, Martin Storath, Andreas Weinmann

Many popular piecewise regression models rely on minimizing a cost function on the model fit with a linear penalty on the number of segments. However, this penalty does not take into account varying complexities of the model functions on the segments potentially leading to overfitting when models with varying complexities, such as polynomials of different de

Baokui Li, Sen Zhang, Wangshu Zhang, Yicheng Chen

Supplying data augmentation to conversational question answering (CQA) can effectively improve model performance. However, there is less improvement from single-turn datasets in CQA due to the distribution gap between single-turn and multi-turn datasets. On the other hand, while numerous single-turn datasets are available, we have not utilized them effective

Sergey Feofilov, Dmitry Khapkin, Andrey Kozyr, Eduard Heiss

The article outlines the methodology of structural and parametric synthesis of neural network controllers for controlling objects with limiters under incomplete information about the controlled object. Artificial neural networks are used to create controllers that are sequentially integrated into a control system with control objects. Reinforcement learning

Subramanya Bhat K N, Amita Das, V Ravishankar, Bhooshan Paradkar

The dynamics of strongly interacting particles are governed by Yang-Mills (Y-M) theory, which is a natural generalization of Maxwell Electrodynamics (ED). Its quantized version is known as quantum chromodynamics (QCD) and has been very well studied. Classical Y-M theory is proving to be equally interesting because of the central role it plays in describing t

Simona Olmi, Lucia Valentina Gambuzza, Mattia Frasca

In this work, we propose a control scheme for power grids subject to large perturbations that cause the failure of a node of the grid. Under such circumstances, the system may lose synchrony and, in addition, a cascade of line failures can be triggered as an effect of the flow redistribution that activates the protection mechanisms equipped on each line of t

David Harel, Uwe Aßmann, Fabiana Fournier, Lior Limonad

Methodologies for development of complex systems and models include external reviews by domain and technology experts. Among others, such reviews can uncover undocumented built-in assumptions that may be critical for correct and safe operation or constrain applicability. Since such assumptions may still escape human-centered processes like reviews, agile dev

J. Smak

System parameters are re-determined: $M_1=0.86\pm0.18M\odot$, $M_2=0.103\pm0.022M\odot$, $A=1.508\pm 0.100\times 10^{10}$cm, and $i=69\pm3^{\circ}$. The secondary component is a semi-degenerate helium star loosing mass at a rate $\dot M=4.93\pm 1.65\times10^{-9}M\odot/yr$. The accretion disk is sufficiently hot to avoid thermal instability. The orbital light

Guillaume Gbikpi-Benissan, Qinmeng Zou, Frédéric Magoulès

A general asynchronous alternating iterative model is designed, for which convergence is theoretically ensured both under classical spectral radius bound and, then, for a classical class of matrix splittings for $\mathsf H$-matrices. The computational model can be thought of as a two-stage alternating iterative method, which well suits to the well-known Herm

Truong Hoang

We make use of the cotangent complex formalism developed by Lurie to formulate Quillen cohomology of algebras over an enriched operad. Additionally, we introduce a spectral Hochschild cohomology theory for enriched operads and algebras over them. We prove that both the Quillen and Hochschild cohomologies of algebras over an operad can be controlled by the co

Felix Köster, Kazutaka Kanno, Jun Ohkubo, Atsushi Uchida

Photonic reservoir computing has been successfully utilized in time-series prediction as the need for hardware implementations has increased. Prediction of chaotic time series remains a significant challenge, an area where the conventional reservoir computing framework encounters limitations of prediction accuracy. We introduce an attention mechanism to the

Fangqing Chen

In this paper, a feature extraction approach for the deformable linear object is presented, which uses a Bezier curve to represent the original geometric shape. The proposed extraction strategy is combined with a parameterization technique, the goal is to compute the regression features from the visual-feedback RGB image, and finally obtain the efficient sha

Jinrui Chen, Mingfei Xiao, Zesheng Chen, Sibghah Khan

Reconfigurable memristors featuring neural and synaptic functions hold great potential for neuromorphic circuits by simplifying system architecture, cutting power consumption, and boosting computational efficiency. Their additive manufacturing on sustainable substrates offers unique advantages for future electronics, including low environmental impact. Here,

L Qin, C Lin, S Huang, S Yang

Surround-view system (SVS) is widely used in the Advanced Driver Assistance System (ADAS). SVS uses four fisheye lenses to monitor real-time scenes around the vehicle. However, accurate intrinsic and extrinsic parameter estimation is required for the proper functioning of the system. At present, the intrinsic calibration can be pipeline by utilizing checkerb

Xiao Fang, Xin Gao, Baofeng Li, Feng Zhai

Low-light image enhancement aims to improve the perception of images collected in dim environments and provide high-quality data support for image recognition tasks. When dealing with photos captured under non-uniform illumination, existing methods cannot adaptively extract the differentiated luminance information, which will easily cause over-exposure and u

Xin Yuan, Ning Li, kang Wei, Wenchao Xu

The edge intelligence (EI) has been widely applied recently. Spliting the model between device, edge server, and cloud can improve the performance of EI greatly. The model segmentation without user mobility has been investigated deeply by previous works. However, in most use cases of EI, the end devices are mobile. Only a few works have been carried out on t

Andrea Carotti, Cosimo Sguanci, Anastasios Sidiropoulos

The Bitcoin Lightning Network (LN) is designed to improve the scalability of blockchain systems by using off-chain payment paths to settle transactions in a faster, cheaper, and more private manner. This work aims to empirically study LN's fee revenue for network participants. Under realistic assumptions on payment amounts, routing algorithms and traffic dis

Axel Osses, Faouzi Triki

We establish a new spectral inequality for the quantified estimation of the $H^s$-norm, $s\ge 0$ of a finite linear combination of eigenfunctions in a domain in terms of its $H^s$-norm in a strictly open subset of the whole domain. The corresponding upper bound depends exponentially on the square root of the frequency number associated to the linear combinat

Yu. S. Tveryanovich, A. V. Povolotskiy, S. S. Lunkov

The plasma-chemical process of producing hydrogen from propane under the excitation by laser radiation has been studied. The study was carried out using femtosecond (35 fs) and nanosecond (7 ns) pulsed laser radiation sources. Experimental dependences of the volumetric hydrogen content in the gas mixture at the outlet of the reactor were measured depending o

Michele N. Notarnicola, Stefano Olivares

We address the problem of coherent state discrimination in the presence of phase diffusion. We investigate the role of the hybrid near-optimum receiver (HYNORE) we proposed in [J. Opt. Soc. Am. B 40, 705-714 (2023)] in the task of mitigating the noise impact. We prove the HYNORE to be a robust receiver, outperforming the displacement photon-number-resolving

Zhenguo Liang, Jiawen Luo, Zhiyan Zhao

For a class of reducible Hamiltonian partial differential equations (PDEs) with arbitrary spatial dimensions, quantified by a quadratic polynomial with time-dependent coefficients, we present a comprehensive classification of long-term solution behaviors within Sobolev space. This classification is achieved through the utilization of Metaplectic and Schr\"od

Salvador Moreno-Rodríguez, Antonio Alex-Amor, Pablo Padilla, Juan F. Valenzuela-Valdés

This paper details a class of metal-based space-time metasurfaces for application in wireless communications scenarios. Concretely, we describe space-time metasurfaces that periodically alternate their properties in time between three spatial states: "air", "conductor" and "grating". We analyze the physics of these metastructures via a computationally-effici

Zhengjia Wang, Danding Wang, Qiang Sheng, Juan Cao

Understanding the intent behind information is crucial. However, news as a medium of public discourse still lacks a structured investigation of perceived news intent and its application. To advance this field, this paper reviews interdisciplinary studies on intentional action and introduces a conceptual deconstruction-based news intent understanding framewor

Masahiro Kato, Shinji Ito

This study investigates the problem of $K$-armed linear contextual bandits, an instance of the multi-armed bandit problem, under an adversarial corruption. At each round, a decision-maker observes an independent and identically distributed context and then selects an arm based on the context and past observations. After selecting an arm, the decision-maker i

Mohammed Ataaur Rahaman, Julia Ive

Source code clone detection is the task of finding code fragments that have the same or similar functionality, but may differ in syntax or structure. This task is important for software maintenance, reuse, and quality assurance (Roy et al. 2009). However, code clone detection is challenging, as source code can be written in different languages, domains, and

Gilles Dowek, Murdoch J. Gabbay

We define a model of predicate logic in which every term and predicate, open or closed, has an absolute denotation independently of a valuation of the variables. For each variable a, the domain of the model contains an element [[a]] which is the denotation of the term a (which is also a variable symbol). Similarly, the algebra interpreting predicates in the

Guansong Lu, Yuanfan Guo, Jianhua Han, Minzhe Niu

Current large-scale diffusion models represent a giant leap forward in conditional image synthesis, capable of interpreting diverse cues like text, human poses, and edges. However, their reliance on substantial computational resources and extensive data collection remains a bottleneck. On the other hand, the integration of existing diffusion models, each spe

Ercília Sousa, Cristina Tablino-Possio, Rolf Krause, Stefano Serra-Capizzano

Twenty years ago the anti-reflective numerical boundary conditions (BCs) were introduced in a context of signal processing and imaging, for increasing the quality of the reconstruction of a blurred signal/image contaminated by noise and for reducing the overall complexity to that of few fast sine transforms i.e. to $O(N\log N)$ real arithmetic operations, wh

He Zhang, Wei Zhong, Yanghao Meng, Bowen Tang

The trigonal ${\alpha}$-HgS has a 3-fold helical chain structure, and is in form of a noncentrosymmetric $P3_121$ phase, known as the cinnabar phase. However, under pressure, the helical chains gradually approach and connect with each other, finally reconstructing into a centrosymmetric NaCl structure at 21 GPa. Superconductivity emerges just after this heli

Juncai He, Tong Mao, Jinchao Xu

In this paper, we investigate the expressivity and approximation properties of deep neural networks employing the ReLU$^k$ activation function for $k \geq 2$. Although deep ReLU networks can approximate polynomials effectively, deep ReLU$^k$ networks have the capability to represent higher-degree polynomials precisely. Our initial contribution is a comprehen

Giao Ky Duong, Rupert L. Frank, Thi Minh Thao Le, Phan Thành Nam

We prove a Cwikel-Lieb-Rozenblum type inequality for the number of negative eigenvalues of the Hardy-Schr\"odinger operator $-\Delta - (d-2)^2/(4|x|^2) -W(x)$ on $L^2(\mathbb{R}^d)$. The bound is given in terms of a weighted $L^{d/2}-$norm of $W$ which is sharp in both large and small coupling regimes. We also obtain a similar bound for the fractional Laplac

Francesco D'Andrea

In this survey, we discuss the description of Vaksman-Soibelman quantum spheres using graph C*-algebras, following the seminal work of Hong and Szyma\'nski. We give a slightly different proof of the isomorphism with a graph C*-algebra, borrowing the idea of Mikkelsen and Kaad of using conditional expectations to prove the desired result.

Gilles Dowek, Murdoch J. Gabbay

Permissive-Nominal Logic (PNL) is an extension of first-order predicate logic in which term-formers can bind names in their arguments. This allows for direct axiomatisations with binders, such as of the lambda-binder of the lambda-calculus or the forall-binder of first-order logic. It also allows us to finitely axiomatise arithmetic, and similarly to axiomat

Prosenjit Paul

In this paper, we investigate quasinormal modes of scalar and electromagnetic fields in the background of Einstein--scalar--Gauss--Bonnet (EsGB) black holes. Using the scalar and electromagnetic field equations in the vicinity of the EsGB black hole, we study nature of the effective potentials. The dependence of real and imaginary parts of the fundamental qu

Zhuohang Dang, Minnan Luo, Chengyou Jia, Guang Dai

Cross-modal retrieval relies on well-matched large-scale datasets that are laborious in practice. Recently, to alleviate expensive data collection, co-occurring pairs from the Internet are automatically harvested for training. However, it inevitably includes mismatched pairs, \ie, noisy correspondences, undermining supervision reliability and degrading perfo

Lixiang Xu, Qingzhe Cui, Richang Hong, Wei Xu

In recent years, the results of view-based 3D shape recognition methods have saturated, and models with excellent performance cannot be deployed on memory-limited devices due to their huge size of parameters. To address this problem, we introduce a compression method based on knowledge distillation for this field, which largely reduces the number of paramete

Ximing Xing, Haitao Zhou, Chuang Wang, Jing Zhang

Text-guided scalable vector graphics (SVG) synthesis has broad applications in icon and sketch generation. However, existing text-to-SVG methods often suffer from limited editability, suboptimal visual quality, and low sample diversity. To address these challenges, we propose \textbf{SVGDreamer}, a novel framework for text-guided vector graphics synthesis. O

Xin Yang, Hao Yu, Xin Gao, Hao Wang

Data privacy and silos are nontrivial and greatly challenging in many real-world applications. Federated learning is a decentralized approach to training models across multiple local clients without the exchange of raw data from client devices to global servers. However, existing works focus on a static data environment and ignore continual learning from str

Eric Marberg

We provide a construction for the kromatic symmetric function $\overline{X}_G$ of a graph introduced by Crew, Pechenik, and Spirkl using combinatorial (linearly compact) Hopf algebras. As an application, we show that $\overline{X}_G$ has a positive expansion into multifundamental quasisymmetric functions. We also study two related quasisymmetric $q$-analogue

Hengrui Zhang, Jie Chen, James M. Rondinelli, Wei Chen

Recent advances in machine learning (ML) have expedited materials discovery and design. One significant challenge faced in ML for materials is the expansive combinatorial space of potential materials formed by diverse constituents and their flexible configurations. This complexity is particularly evident in molecular mixtures, a frequently explored space for

G. Beretta, G. Chiarot, A. E. Cinà, M. Pelillo

One of the fundamental problems of information theory, since its foundation by Shannon in 1948, has been the computation of the capacity of a discrete memoryless channel, a quantity expressing the maximum rate at which information can travel through the channel. In the literature, several algorithms were proposed to approximately compute the capacity of a di

Ankush Maity, Roshan Pious, Sourabh Kumar Lenka, Vishal Choudhary

This compilation of various research paper highlights provides a comprehensive overview of recent developments in super-resolution image and video using deep learning algorithms such as Generative Adversarial Networks. The studies covered in these summaries provide fresh techniques to addressing the issues of improving image and video quality, such as recurs

Jingqi Niu, Qinji Yu, Shiwen Dong, Zilong Wang

Detecting anomalies in fundus images through unsupervised methods is a challenging task due to the similarity between normal and abnormal tissues, as well as their indistinct boundaries. The current methods have limitations in accurately detecting subtle anomalies while avoiding false positives. To address these challenges, we propose the ReSynthDetect netwo

Volker W. Elling

We show that the shock polars of compressible full potential flow are strictly convex if the enthalpy per mass is a convex function of volume per mass, in particular when the sound speed is a nondecreasing function of density. Counterexamples are given for some cases that violate the enthalpy condition. For the full Euler equations with convex equation of st

Wenbin An, Feng Tian, Wenkai Shi, Yan Chen

Generalized Category Discovery is a crucial real-world task. Despite the improved performance on known categories, current methods perform poorly on novel categories. We attribute the poor performance to two reasons: biased knowledge transfer between labeled and unlabeled data and noisy representation learning on the unlabeled data. To mitigate these two iss

Dionisis Stefanatos, Foteini Avouri, Emmanuel Paspalakis

In this article, we use spatially modulated control fields to increase the four-wave mixing efficiency in a four-subband semiconductor asymmetric double quantum well, motivated by similar works in atomic systems. Using a simplified version of the propagation equations, we show analytically that for control fields with constant amplitude and linearly varying

Quentin Rouxel, Serena Ivaldi, Jean-Baptiste Mouret

Many humanoid and multi-legged robots are controlled in positions rather than in torques, which prevents direct control of contact forces, and hampers their ability to create multiple contacts to enhance their balance, such as placing a hand on a wall or a handrail. This letter introduces the SEIKO (Sequential Equilibrium Inverse Kinematic Optimization) pipe

Pierre Gosselin

This paper introduces a comprehensive formalism for decomposing the state space of a quantum field into several entangled subobjects, i.e., fields generating a subspace of states. Projecting some of the subobjects onto degenerate background states reduces the system to an effective field theory depending on parameters representing the degeneracies. Notably,

Anzor Beridze

In the paper [Ba-Be-Mdz], using the Alexander-Spanier cochains based on the normal coverings, the exact homology theory $\bar{H}^N_*(-,-;G)$, the so called Alexander-Spanier homology theory, is defined. In the paper we will use the method of construction of the strong homology theory to show that the homology theory $\bar{H}^N_*(-,-;G)$ is a strong shape inv

Zheng-Quan Cui, Yu Guo, Rong-Xin Miao

Cone holography is a codimension-$n$ doubly holographic model, which can be interpreted as the holographic dual of edge modes on defects. The initial model of cone holography is based on mixed boundary conditions. This paper formulates cone holography with Neumann boundary conditions, where the brane-localized gauge fields play an essential role. Firstly, we

Kai Jiang, Shifeng Li, Juan Zhang

Numerical solving the Schr\"odinger equation with incommensurate potentials presents a great challenge since its solutions could be space-filling quasiperiodic structures without translational symmetry nor decay. In this paper, we propose two high-accuracy numerical methods to solve the time-dependent quasiperiodic Schr\"odinger equation. Concretely, we disc

Qing-Yue Li, Pin-Tian Lyu, Bin Kang, Hong-Yuan Chen

Deciphering ion channel activity and signaling interactions within cells is one of the key tasks of neuroscience. Currently, measuring this electrophysiological activity is done using patch-clamp1-4 or voltage-sensitive imaging5-8. Unfortunately, these techniques are unable to balance between single-channel sensitivity and highthroughput detection. Here we i

Keren Censor-Hillel, Yuka Machino, Pedro Soto

Fault tolerance is a major concern in distributed computational settings. In the classic master-worker setting, a server (the master) needs to perform some heavy computation which it may distribute to $m$ other machines (workers) in order to speed up the time complexity. In this setting, it is crucial that the computation is made robust to failed workers, in

Jianming Yang, Kui Ji

Let $\mathrm{L}^2_a(\mathbb{D})$ be the classical Bergman space and denote $M_h$ for the multiplication operator by a function $h$. Let $B$ be a finite Blaschke product with order $n$.An open question proposed by R. G. Douglas is whether the operators $M_B$ on $\mathrm{L}^2_a(\mathbb{D})$ similar to $\oplus_1^n M_z$ on $\oplus_1^n \mathrm{L}^2_a(\mathbb{D})$

Clay Adams, Konrad Aguilar, Esteban Ayala, Evelyne Knight

We provide convergence in the quantum Gromov-Hausdorff propinquity of Latr\'emoli\`ere of some sequences of infinite-dimensional Leibniz compact quantum metric spaces of Rieffel given by AF algebras and Christensen-Ivan spectral spaces. The main examples are convergence of Effros-Shen algebras and UHF algebras.

Kaiwen Song, Xiaoyi Zeng, Chenqu Ren, Juyong Zhang

Existing neural radiance field-based methods can achieve real-time rendering of small scenes on the web platform. However, extending these methods to large-scale scenes still poses significant challenges due to limited resources in computation, memory, and bandwidth. In this paper, we propose City-on-Web, the first method for real-time rendering of large-sca

Guojian Wang, Faguo Wu, Xiao Zhang, Ning Guo

Deep reinforcement learning (DRL) faces significant challenges in addressing the hard-exploration problems in tasks with sparse or deceptive rewards and large state spaces. These challenges severely limit the practical application of DRL. Most previous exploration methods relied on complex architectures to estimate state novelty or introduced sensitive hyper

Yongsong Huang, Tomo Miyazaki, Xiaofeng Liu, Kaiyuan Jiang

Background and objective: High-resolution radiographic images play a pivotal role in the early diagnosis and treatment of skeletal muscle-related diseases. It is promising to enhance image quality by introducing single-image super-resolution (SISR) model into the radiology image field. However, the conventional image pipeline, which can learn a mixed mapping

Jose A. Magpantay

The effective dynamics of a system interacting with a bath or environment is presented in two ways, (1) the (LGKS) replacement of the von Neuman equation for the density matrix and (2) the Feynman-Vernon path-integral derivation, by integrating out the bath degree of freedom, to arrive at a system's density matrix. In this paper, I connect the two methods by

Yijing Huang, Peihao Sun, Samuel W. Teitelbaum, Haoyuan Li

We demonstrate that the absorption of femtosecond x-ray pulses can excite quasi-spherical high-wavevector coherent acoustic phonon wavepackets using an all x-ray pump and probe scattering experiment. The time- and momentum-resolved diffuse scattering signal is consistent with strain pulses induced by the rapid electron cascade dynamics following photoionizat

Uihyeon Jeong

We study the blow-up dynamics for the energy-critical 1-corotational wave maps problem with 2-sphere target. In arXiv:0911.0692, Rapha\"el and Rodnianski exhibited a stable finite time blow-up dynamics arising from smooth initial data. In this paper, we exhibit a sequence of new finite-time blow-up rates (quantized rates), which can still arise from well-loc

Ingyun Lee, Wooju Lee, Hyun Myung

Deep neural networks have shown remarkable performance in image classification. However, their performance significantly deteriorates with corrupted input data. Domain generalization methods have been proposed to train robust models against out-of-distribution data. Data augmentation in the frequency domain is one of such approaches that enable a model to le

Weijun Chen, Heyuan Wang, Ye Tian, Shijie Guan

Multivariate time-series (MTS) forecasting is a challenging task in many real-world non-stationary dynamic scenarios. In addition to intra-series temporal signals, the inter-series dependency also plays a crucial role in shaping future trends. How to enable the model's awareness of dependency information has raised substantial research attention. Previous ap

Atsuo Hiroe

This study introduces an online target sound extraction (TSE) process using the similarity-and-independence-aware beamformer (SIBF) derived from an iterative batch algorithm. The study aimed to reduce latency while maintaining extraction accuracy. The SIBF, which is a linear method, provides more accurate estimates of the target than an approximate magnitude

Erdinc Akyildirim, Matteo Gambara, Josef Teichmann, Syang Zhou

We present convincing empirical results on the application of Randomized Signature Methods for non-linear, non-parametric drift estimation for a multi-variate financial market. Even though drift estimation is notoriously ill defined due to small signal to noise ratio, one can still try to learn optimal non-linear maps from data to future returns for the purp

Bobo Hua, Alexander Mednykh, Ilya Mednykh, Lili Wang

In this paper, we investigate the complexity of an infinite family of Cayley graphs $\mathcal{D}_{n}=Cay(\mathbb{D}_{n}, b^{\pm\beta_1},b^{\pm\beta_2},\ldots,b^{\pm\beta_s}, a b^{\gamma_1}, a b^{\gamma_2},\ldots, a b^{\gamma_t} )$ on the dihedral group $\mathbb{D}_{n}=\langle a,b| a^2=1, b^n=1,(a\,b)^2=1\rangle$ of order $2n.$ We obtain a closed formula for

Oleg Kiselyov

Variable environment is the time-honored way of making sense of free variables, used in programming language theory as well when writing interpreters and some compilers. Algebraic effects give another way, as was pointed already at HOPE 2017. Although a theoretical curiosity, it may have surprising practical benefits: a new way of writing compilers, with the

Xiaoyu Luo, Mingming Xu, Chuanhou Gao

The use of Lagrangian cuts proves effective in enhancing the lower bound of the master problem within the execution of benders-type algorithms, particularly in the context of two-stage stochastic programs. However, even the process of generating a single Lagrangian cut is notably time-intensive. In light of this challenge, we present a novel framework that i

M. Rossi, H. Lu, K. Lee, B. H. Goodge

We conducted a comparative study of the rare-earth infinite-layer nickelates films, RNiO2 (R = La, Pr, and Nd) using resonant inelastic X-ray scattering (RIXS). We found that the gross features of the orbital configurations are essentially the same, with minor variations in the detailed hybridization. For low-energy excitations, we unambiguously confirm the

Jaehyeok Choi, Sunjin Choi, Seok Kim, Jehyun Lee

We study new cohomologies for the BPS operators of the $\mathcal{N}=4$ Yang-Mills theory with $SU(3)$ and $SU(4)$ gauge groups, to better understand the black hole microstates. We first study the index of these black hole operators and identify their apparent threshold levels. For $SU(3)$, we find many towers of states and partial no-hair behaviors. We expli

Ryan Kellermann, Alessandro Barone, Shoji Hashimoto, Andreas Jüttner

We report on the calculation of the inclusive semileptonic decay of the $D_s$ meson on the lattice. We simulate the $D_s \rightarrow X_s\ell\nu_\ell$ process with M\"obius domain-wall charm and strange quarks, whose masses were approximately tuned to the physical values. We cover the whole kinematical region. The focus of this work is on the systematic error

Hongliang Luo, Feifei Gao, Fan Liu, Shi Jin

In this paper, we propose a novel scheme for sixdimensional (6D) radar sensing and tracking of dynamic target based on multiple input and multiple output (MIMO) array for monostatic integrated sensing and communications (ISAC) system. Unlike most existing ISAC studies believing that only the radial velocity of far-field dynamic target can be measured based o

Mukesh Singh, Alok Shukla, Brahmananda Chakraborty

In this work, we investigate the hydrogen-storage properties of Zr-decorated $\gamma$-graphyne monolayer employing Density Functional Theory (DFT) for green energy storage. We predict that each Zr atom decorated on graphyne sheet (2D) can adsorb up to seven H$_2$ molecules with an average adsorption energy of -0.44 eV/H$_2$, leading to a hydrogen gravimetric

Fan Shi

In this research, we introduce RefineNet, a novel architecture designed to address resolution limitations in text-to-image conversion systems. We explore the challenges of generating high-resolution images from textual descriptions, focusing on the trade-offs between detail accuracy and computational efficiency. RefineNet leverages a hierarchical Transformer

Zikun Qin, Bikram Karmakar

In a general set-up that allows unmeasured confounding, we show that the conditional average treatment effect on the treated can be identified as one of two possible values. Unlike existing causal inference methods, we do not require an exogenous source of variability in the treatment, e.g., an instrument or another outcome unaffected by the treatment. Inste

André Yuji Yasutomi, Hideyuki Ichiwara, Hiroshi Ito, Hiroki Mori

Anchor-bolt insertion is a peg-in-hole task performed in the construction field for holes in concrete. Efforts have been made to automate this task, but the variable lighting and hole surface conditions, as well as the requirements for short setup and task execution time make the automation challenging. In this study, we introduce a vision and proprioceptive

L. Wang, S. Zhang, B. B. Wang, B. X. Gao

The magnetic Weyl semimetal Co$_3$Sn$_2$S$_2$ is extensively investigated due to its giant anomalous Hall effect (AHE).Recent studies demonstrate that the AHE can be effectively tuned by multi-electron Ni doping.To reveal the underlying mechanism of this significant manipulation,it is crucial to explore the band structure modification caused by Ni doping. He

Jingwei Cai, Zuotong Wu, Sen Peng, Yuchen Wei

Chiplet technology enables the integration of an increasing number of transistors on a single accelerator with higher yield in the post-Moore era, addressing the immense computational demands arising from rapid AI advancements. However, it also introduces more expensive packaging costs and costly Die-to-Die (D2D) interfaces, which require more area, consume

Rong-Zhen Guo, Yang Jiang, Qing-Guo Huang

Ultralight bosons are attractive dark-matter candidates and appear in various scenarios beyond standard model. They can induce superradiant instabilities around spinning black holes (BHs), extracting the energy and angular momentum from BHs, and then dissipated through monochromatic gravitational radiation, which become promising sources of gravitational wav

Xuanji Hou, Li Zhang

We construct 1-dim difference Schr\"odinger operators with a class of Gevrey potentials such that Cantor spectrum occurs together with the estimations of open spectral gaps . The proof is based on KAM and Moser-P\"oschel argument .

Yuki Takeuchi

There are two types of universality in measurement-based quantum computation (MBQC): ${\it strict}$ and ${\it computational}$. It is well known that the former is stronger than the latter. We present a method of transforming from a certain type of computationally universal MBQC to a strictly universal one. Our method simply replaces a single qubit in a resou

Hikaru Wakaura, Andriyan Bayu Suksmono

Recently there are more promising qubit technology such as Majorana fermions Rydberg atoms and Silicon quantum dot have yet to be developed for realizing a quantum computer than Superconductivity and Ion trap into the world The simulation of the quantum hardware of these qubits can only be done numerically However a classical numerical simulation is limited

Nobutaka Nakazono

Recently, a birational representation of an extended affine Weyl group of $(A_{2N}\rtimes A_1)^{(1)}$-type, which gives a higher-order generalization of an $A_4^{(1)}$-surface type $q$-Painlev\'e equation, was obtained. In this paper, we extend it to a birational representation of an extended affine Weyl group of $(A_{2N}\rtimes A_1)^{(1)}\times A_1^{(1)}$-t

Zaifan Jiang, Xing Huang, Chao Wei

Preference learning is a key technology for aligning language models with human values. Reinforcement Learning from Human Feedback (RLHF) is a model-based algorithm to optimize preference learning, which first fits a reward model for preference scores and then optimizes the generating policy with an on-policy PPO algorithm to maximize the reward. The process