April 2023 arXiv papers — page 78

Filippo Sarti, Alessio Savini

We introduce the notion of measurable bounded cohomology for measured groupoids, extending continuous bounded cohomology of locally compact groups. We show that the measurable bounded cohomology of the semidirect groupoid associated to a measure class preserving action of a locally compact group $G$ on a standard Borel space is isomorphic to the continuous b

Iraklis Giannakis, Anshuman Bhardwaj, Lydia Sam, Georgios Leontidis

Craters are amongst the most important morphological features in planetary exploration. To that extent, detecting, mapping and counting craters is a mainstream process in planetary science, done primarily manually, which is a very laborious and time-consuming process. Recently, machine learning (ML) and computer vision have been successfully applied for both

Xiuyuan Qin, Huanhuan Yuan, Pengpeng Zhao, Junhua Fang

Contrastive Learning (CL) performances as a rising approach to address the challenge of sparse and noisy recommendation data. Although having achieved promising results, most existing CL methods only perform either hand-crafted data or model augmentation for generating contrastive pairs to find a proper augmentation operation for different datasets, which ma

Linqi Yu, Mustafa Z. Yousif, Young-Woo Lee, Xiaojue Zhu

In this study, an efficient deep-learning model is developed to predict unavailable parameters, e.g., streamwise velocity, temperature, and pressure from available velocity components. This model, termed mapping generative adversarial network (M-GAN), consists of a label information generator (LIG) and an enhanced super-resolution generative adversarial netw

Anshuman Baruah, Ali Övgün, Atri Deshamukhya

The vacuum expectation value of the non-minimally coupled Kalb-Ramond (KR) field leads to spontaneous local Lorentz symmetry violation, and static spherically symmetric solutions exist. In this study, we study the quasinormal modes (QNMs) of modified black holes in non--minimally coupled KR gravity. We employ a higher-order Pad\'e averaged WKB method to comp

Congwen Liu, Heng Xu

This short note is motivated by an attempt to understand the distinction between the Laplace operator and the hyperbolic Laplacian on the unit ball of $\mathbb{R}^n$, regarding the Lipschitz continuity of the solutions to the corresponding Dirichlet problems. We investigate the Dirichlet problem \begin{equation*} \left\{\begin{array}{ll} \Delta_{\vartheta} u

Ciprian-Octavian Truică, Elena-Simona Apostol

Misinformation is considered a threat to our democratic values and principles. The spread of such content on social media polarizes society and undermines public discourse by distorting public perceptions and generating social unrest while lacking the rigor of traditional journalism. Transformers and transfer learning proved to be state-of-the-art methods fo

Yafeng Bi, Ping Zhou, Han Jia, Fan Lu

Tuning the mass density and bulk modulus independently is the key to manipulate the propagation of sound wave. Acoustic metamaterials provide a feasible method to realize various acoustic parameters. However, the relevant studies are mainly concentrated in air, and the huge impedance difference makes it difficult to directly extend these airborne structures

Mathias Van Den Bossche, Philippe Grangier

Within the framework of quantum contextuality, we discuss the ideas of extracontextuality and extravalence, that allow one to relate Kochen-Specker's and Gleason's theorems. We emphasize that whereas Kochen-Specker's is essentially a no-go theorem, Gleason's provides a mathematical justification of Born's rule. Our extracontextual approach requires however a

Xin Wang, Zhenrong Shen, Zhiyun Song, Sheng Wang

Magnetic resonance (MR) images collected in 2D scanning protocols typically have large inter-slice spacing, resulting in high in-plane resolution but reduced through-plane resolution. Super-resolution techniques can reduce the inter-slice spacing of 2D scanned MR images, facilitating the downstream visual experience and computer-aided diagnosis. However, mos

Huan Jia, Naihong Hu, Rongchuan Xiong, Yinhuo Zhang

Let $\mathbb{K}$ be a field. We study the free bialgebra $\mathcal{T}$ generated by the coalgebra $C=\mathbb{K} g \oplus \mathbb{K} h$ and its quotient bialgebras (or Hopf algebras) over $\mathbb{K}$. We show that the free noncommutative Fa\`a di Bruno bialgebra is a sub-bialgebra of $\mathcal{T}$, and the quotient bialgebra $\overline{\mathcal{T}}:=\mathcal

K. Shizuya

In equilibrium planer systems of Hall electrons, such as GaAs heterostructures and graphene, support two species of current counterflowing along the system edges, as observed recently in experiment using a nanoscale magnetometer. We examine distinct origins and distinctive features of these equilibrium currents, with the Coulombic many-body effects taken int

Pınar Uğurlu

We prove the conjugacy of Sylow $2$-subgroups in pseudofinite $\mathfrak{M}_c$ (in particular linear) groups under the assumption that there is at least one finite Sylow $2$-subgroup. We observe the importance of the pseudofiniteness assumption by analyzing an example of a linear group with non-conjugate finite Sylow $2$-subgroups which was constructed by Pl

Ondrej Bohdal, Timothy Hospedales, Philip H. S. Torr, Fazl Barez

Successful deployment of artificial intelligence (AI) in various settings has led to numerous positive outcomes for individuals and society. However, AI systems have also been shown to harm parts of the population due to biased predictions. AI fairness focuses on mitigating such biases to ensure AI decision making is not discriminatory towards certain groups

Pınar Uğurlu

We prove the conjugacy of Sylow $p$-subgroups of linear pseudofinite groups under the assumption of the existence of a finite Sylow $p$-subgroup. We also give an example of a linear pseudofinite group with non-conjugate Sylow $2$-subgroups.

A. Mitrašinović, M. Micic

Close galaxy flybys, interactions during which two galaxies inter-penetrate, are frequent and can significantly affect the evolution of individual galaxies. Equal-mass flybys are extremely rare and almost exclusively distant, while frequent flybys have mass ratios 0.1 or lower, with a secondary galaxy penetrating deep into the primary. This can result in com

Valerio Marsocci, Nicolas Gonthier, Anatol Garioud, Simone Scardapane

Land cover maps are a pivotal element in a wide range of Earth Observation (EO) applications. However, annotating large datasets to develop supervised systems for remote sensing (RS) semantic segmentation is costly and time-consuming. Unsupervised Domain Adaption (UDA) could tackle these issues by adapting a model trained on a source domain, where labels are

Santanu Tantubay, Priyanshu Chakraborty, Punita Batra

In this paper, we consider the twisted Hamiltonian extended affine Lie algebra (THEALA). We classify the irreducible integrable modules for these Lie algebras with finite-dimensional weight spaces when the finite-dimensional center acts non-trivially. This Lie algebra has a triangular decomposition, which is different from the natural triangular decompositio

Jierui Wang, Wentao Yu, Guoyang Cheng, Lin Chen

For the battery management system of electric vehicle, accurate estimation of the State of Charge of Lithium-ion battery can effectively avoid structural damage caused by overcharge or over discharge inside the battery. Considering that the lithium-ion battery is a time-varying nonlinear system, which needs real-time State of Charge estimation, a joint algor

Fuxiang Huang, Lei Zhang

Interactive Image Retrieval (IIR) aims to retrieve images that are generally similar to the reference image but under the requested text modification. The existing methods usually concatenate or sum the features of image and text simply and roughly, which, however, is difficult to precisely change the local semantics of the image that the text intends to mod

Dung Xuan Nguyen, Jake Arkinstall, Henning Schomerus

Half-integer quantized flux vortices appear in honeycomb lattices when the signs of an odd number of couplings around a plaquette are inverted. We show that states trapped at these vortices can be isolated by applying inhomogeneous strain to the system. A vortex then results in localized mid-gap states lying between the strain-induced pseudo-Landau levels, w

Laurent Kloeker, Chenghua Liu, Chao Wei, Lutz Eckstein

The use of smart roadside infrastructure sensors is highly relevant for future applications of connected and automated vehicles. External sensor technology in the form of intelligent transportation system stations (ITS-Ss) can provide safety-critical real-time information about road users in the form of a digital twin. The choice of sensor setups has a major

Natalia Valderrama, Ioannis Pitsiorlas, Luisa Vargas, Pablo Arbeláez

We propose the first joint-task learning framework for brain and vessel segmentation (JoB-VS) from Time-of-Flight Magnetic Resonance images. Unlike state-of-the-art vessel segmentation methods, our approach avoids the pre-processing step of implementing a model to extract the brain from the volumetric input data. Skipping this additional step makes our metho

Deborah Levy, Amit Peleg, Naama Pearl, Dan Rosenbaum

Research on neural radiance fields (NeRFs) for novel view generation is exploding with new models and extensions. However, a question that remains unanswered is what happens in underwater or foggy scenes where the medium strongly influences the appearance of objects. Thus far, NeRF and its variants have ignored these cases. However, since the NeRF framework

Bin Li, Wancheng Xie, Yinghui Ye, Lei Liu

Integrating unmanned aerial vehicles (UAVs) into vehicular networks have shown high potentials in affording intensive computing tasks. In this paper, we study the digital twin driven vehicular edge computing networks for adaptively computing resource management where an unmanned aerial vehicle (UAV) named FlexEdge acts as a flying server. In particular, we f

Aijaz H. Lone, Xuecui Zou, Debasis Das, Xuanyao Fong

Topologically protected spin textures, such as magnetic skyrmions, have the potential for dense data storage as well as energy-efficient computing due to their small size and a low driving current. The evaluation of the writing and reading of the skyrmion's magnetic and electrical characteristics is a key step toward the implementation of these devices. In t

Chenggang Zhao, Genghan Zhang, Ao Shen, Mingyu Gao

The demands for higher performance and accuracy in neural networks (NNs) never end. Existing tensor compilation and Neural Architecture Search (NAS) techniques orthogonally optimize the two goals but actually share many similarities in their concrete strategies. We exploit such opportunities by combining the two into one and make a case for Kernel Architectu

Yaping Qi, Esther Xinyi Chen, Dan Hu, Ying Yang

Raman spectroscopy provides spectral information related to the specific molecular structures of substances and has been well established as a powerful tool for studying biological tissues and diagnosing diseases. This article reviews recent advances in Raman spectroscopy and its applications in diagnosing various critical diseases, including cancers, infect

Zijian Zhang, Xiangyu Zhao, Hao Miao, Chunxu Zhang

Spatio-Temporal prediction plays a critical role in smart city construction. Jointly modeling multiple spatio-temporal tasks can further promote an intelligent city life by integrating their inseparable relationship. However, existing studies fail to address this joint learning problem well, which generally solve tasks individually or a fixed task combinatio

Alexander Komech, Elena Kopylova

We develop the theory of momentum map for the Maxwell-Lorentz equations with spinning extended charged particle. This theory is indispensable for the study of long-time behaviour and radiation of the solitons of this system. The development relies on the Hamilton-Poisson structure of the system. As an example, we apply the theory to the rotation group of sym

Luca Cocconi, Henry Alston, Thibault Bertrand

Static nonreciprocal forces between particles generically drive persistent motion reminiscent of self-propulsion. Here, we demonstrate that reciprocity-breaking fluctuations about a reciprocal mean coupling strength are sufficient to generate this behavior in a minimal two-particle model, with the velocity of the ensuing \textit{active} bound state being mod

Kalle Koivisto, Toni Taipalus

Knowledge is considered an essential resource for organizations. For organizations to benefit from their possessed knowledge, knowledge needs to be managed effectively. Despite knowledge sharing and management being viewed as important by practitioners, organizations fail to benefit from their knowledge, leading to issues in cooperation and the loss of valua

Yves Brihaye, Betti Hartmann

We study charged and rotating boson stars in 5-dimensional Einstein-Maxwell(-Chern-Simons) theory assuming the two angular momenta associated to the two orthogonal planes of rotation to be equal. Next to the angular momenta, the boson stars carry electric charge and magnetic moment. Interestingly, we find new branches of Einstein-Maxwell-Chern-Simons solutio

Hengyuan Xu, Liyao Xiang, Hangyu Ye, Dixi Yao

Revolutionizing the field of deep learning, Transformer-based models have achieved remarkable performance in many tasks. Recent research has recognized these models are robust to shuffling but are limited to inter-token permutation in the forward propagation. In this work, we propose our definition of permutation equivariance, a broader concept covering both

K. Aditya

We investigate the stability of nearby disc galaxies and galaxies at redshift ($z$) equal to 4.5. We explore the connection between the stability parameter $(Q_{RW})$, star formation rate ($SFR$), gas fraction $(f^{Gas})$, and the time scale for growth of gravitational instabilities $(\tau)$. We find that, despite differences in morphology $91$ $\%$ of the n

Guglielmo Macrelli

A criterium is derived to understand the relevance of thermal effects resulting from high rate mechanical actions on glass surface. The criterium is based on the concept of characteristic contact time of the load to the glass surface. This criterium is of particular relevance to impact phenomena. A general discussion about dissipative aspects of indentation

Diego Pallara, Sergio Polidoro

We prove mean value formulas for classical solutions to second order linear differential equations in the form $$ \partial_t u = \sum_{i,j=1}^m X_i (a_{ij} X_j u) + X_0 u + f, $$ where $A = (a_{ij})_{i,j=1, \dots,m}$ is a bounded, symmetric and uniformly positive matrix with $C^1$ coefficients under the assumption that the operator $\sum_{j=1}^m X_j^2 + X_0

S. H. Shekh, M. Muzammil, R. V. Mapari, G. U. Khapekar

The current analysis uses the non-static plane symmetric space-time to dynamically examine the holographic dark energy model as a candidates of IR cut-offs (specifically Hubble's and Granda-Oliveros cut-off). Using the Markov Chain Monte Carlo (MCMC) method, we estimate the best fit values for the model parameters imposed from the combined datasets of $CC+SC

Meysam Miralaei, Ali Mohammadian, Behruz Tayfeh-Rezaie, Maksim Zhukovskii

For a given graph $F$, the $F$-saturation number of a graph $G$, denoted by $ {sat}(G, F)$, is the minimum number of edges in an edge-maximal $F$-free subgraph of $G$. In 2017, Kor\'andi and Sudakov determined $ {sat}({G}(n, p), K_r)$ asymptotically, where ${G}(n, p) $ denotes the Erd\H{o}s-R\'enyi random graph and $ K_r$ is the complete graph on $r$ vertice

Somsubhra Ghosh, Diptiman Sen, K. Sengupta

We study the prethermal Floquet phases of a two-dimensional (2D) Rydberg atom array on a rectangular lattice in the presence of a periodic drive with large drive amplitude. We derive an analytic, albeit perturbative, Floquet Hamiltonian using Floquet perturbation theory (FPT) which charts out these phases and shows that the transition between them can be acc

Leyuan Sun, Guanqun Ding, Yue Qiu, Yusuke Yoshiyasu

Multi-modal fusion of sensors is a commonly used approach to enhance the performance of odometry estimation, which is also a fundamental module for mobile robots. However, the question of \textit{how to perform fusion among different modalities in a supervised sensor fusion odometry estimation task?} is still one of challenging issues remains. Some simple op

Rémi Abgrall, Fatemeh Nassajian Mojarrad

We present a class of arbitrarily high order fully explicit kinetic numerical methods in compressible fluid dynamics, both in time and space, which include the relaxation schemes by S. Jin and Z. Xin. These methods can use CFL number larger or equal to unity on regular Cartesian meshes for multi-dimensional case. These kinetic models depend on a small parame

Shonosuke Sugasawa, Kosaku Takanashi, Kenichiro McAlinn, Edoardo M. Airoldi

The estimation of heterogeneous treatment effects in the potential outcome setting is biased when there exists model misspecification or unobserved confounding. As these biases are unobservable, what model to use when remains a critical open question. In this paper, we propose a novel Bayesian methodology to mitigate misspecification and improve estimation v

Sang-Ho Kim, Jung Keun Ahn, Shin Hyung Kim, Seung-il Nam

We investigate double-strangeness exchange reactions, $K^-p\to K^+\Xi^-$ and $K^-p\to K^0\Xi^0$, using an effective Lagrangian approach based on a hybrid Regge-plus-resonance model involving rescattering diagrams. We consider the background processes that include $\Lambda$, $\Sigma$, and $\Sigma(1385)$ Regge trajectories in the $u$ channel and the $s$-channe

Fatemeh Rezaei, Pouriya Khaliliyan, Mohsen Rezaei, Parvin Karimi

Recurrent Neural Networks are classes of Artificial Neural Networks that establish connections between different nodes form a directed or undirected graph for temporal dynamical analysis. In this research, the laser induced breakdown spectroscopy (LIBS) technique is used for quantitative analysis of aluminum alloys by different Recurrent Neural Network (RNN)

Zhifeng Ma, Hao Zhang, Jie Liu

The drastic variation of motion in spatial and temporal dimensions makes the video prediction task extremely challenging. Existing RNN models obtain higher performance by deepening or widening the model. They obtain the multi-scale features of the video only by stacking layers, which is inefficient and brings unbearable training costs (such as memory, FLOPs,

Yihua Bai, Qing Zhang, Tan Zhang, Haoran Lv

Controlling light at the nanoscale by exploiting ultra-confined polaritons - hybrid light and matter waves - in various van der Waals (vdW) materials empowers unique opportunities for many nanophotonic on-chip technologies. So far, mainstream approaches have relied interfacial techniques (e.g., refractive optics, meta-optics and moire engineering) to manipul

Sara Saeidian, Giulia Cervia, Tobias J. Oechtering, Mikael Skoglund

Pointwise maximal leakage (PML) is an operationally meaningful privacy measure that quantifies the amount of information leaking about a secret $X$ to a single outcome of a related random variable $Y$. In this paper, we extend the notion of PML to random variables on arbitrary probability spaces. We develop two new definitions: First, we extend PML to counta

Soroush Javadipour, Ali Shokuhfar, Zeinab Heidary, Mohammad Amin Amiri Roshkhar

The thermal conductivity and stability of nanofluids have posed the biggest challenges to their adoption as coolants in thermal applications in industries such as electronic equipment, heat exchangers, and solar technologies. In this paper, the thermal conductivity coefficient of an Al$_{12}$Mg$_{17}$ nanofluid is measured by a novel beam displacement method

Prathistith Raj Medi, Ghanta Sai Krishna, Praneeth Nemani, Satyanarayana Vollala

Person re-identification is vital for monitoring and tracking crowd movement to enhance public security. However, re-identification in the presence of occlusion substantially reduces the performance of existing systems and is a challenging area. In this work, we propose a plausible solution to this problem by developing effective occlusion detection and reco

A. Hourihane, P. Francois, C. C. Worley, L. Magrini

The Gaia-ESO Survey is a public spectroscopic survey that has targeted $\gtrsim10^5$ stars covering all major components of the Milky Way from the end of 2011 to 2018, delivering its public final release in May 2022. Unlike other spectroscopic surveys, Gaia-ESO is the only survey that observed stars across all spectral types with dedicated, specialised analy

Tanmoy Mondal, Stefano Moretti, Shoaib Munir, Prasenjit Sanyal

Extending the Higgs sector of the Standard Model (SM) by just one additional Higgs doublet field leads to the two-Higgs-doublet model (2HDM). In the Type-I $Z_2$-symmetric limit of the 2HDM, all the five new physical Higgs states can be fairly light, $\mathcal{O}(100)$\,GeV or less, without being in conflict with current data from the direct Higgs boson sear

Yongchan Kwon, James Zou

Data valuation is a powerful framework for providing statistical insights into which data are beneficial or detrimental to model training. Many Shapley-based data valuation methods have shown promising results in various downstream tasks, however, they are well known to be computationally challenging as it requires training a large number of models. As a res

Shinzo Bannai, Hiro-o Tokunaga, Emiko Yorisaki

We define ramified and split models of elliptic surfaces and study the relation between the two models. We focus on certain rational elliptic surfaces from these points of views and as an application, we give an observation on bitantgent lines of an irreducible quartic with at most nodes.

Moustapha Diaby, Mark Karwan, Lei Sun

In view of the extended formulations (EFs) developments (e.g. "Fiorini, S., S. Massar, S. Pokutta, H.R. Tiwary, and R. de Wolf [2015]. Exponential Lower Bounds for Polytopes in Combinatorial Optimization. Journal of the ACM 62:2"), we focus in this paper on the question of whether it is possible to model an NP-Complete problem as a polynomial-sized linear pr

Ruofan Jiang

Let $A$ be a non-isotrivial almost ordinary abelian surface with possibly bad reductions over a global function field of odd characteristic $p$. Suppose $\Delta$ is an infinite set of positive integers, such that $\left(\frac{m}{p}\right)=1$ for $\forall m\in \Delta$. If $A$ does not admit any global real multiplication, we prove the existence of infinitely

Xun-Jiang Luo, Fengcheng Wu

The Benalcazar-Bernevig-Hughes (BBH) model [Science 357, 61 (2017)], featuring bulk quadrupole moment, edge dipole moments, and corner states, is a paradigm of both higher-order topological insulators and topological multipole insulators. In this work, we generalize the BBH model to arbitrary dimensions by utilizing the Clifford algebra. For the generalized

Stefano Longhi

Anderson localization is ubiquitous in wavy systems with strong static and uncorrelated disorder. The delicate destructive interference underlying Anderson localization is usually washed out in the presence of temporal fluctuations or aperiodic drives in the Hamiltonian, leading to delocalization and restoring transport. However, in one-dimensional lattices

Yaolong Zhang, Bin Jiang

Machine learned interatomic interaction potentials have enabled efficient and accurate molecular simulations of closed systems. However, external fields, which can greatly change the chemical structure and/or reactivity, have been seldom included in current machine learning models. This work proposes a universal field-induced recursively embedded atom neural

Wendong Zhang, Qingjie Chai, Quanqi Zhang, Chengwei Wu

Recurrent Neural Network, Long Short-Term Memory, and Transformer have made great progress in predicting the trajectories of moving objects. Although the trajectory element with the surrounding scene features has been merged to improve performance, there still exist some problems to be solved. One is that the time series processing models will increase the i

Stefano Longhi

Anderson localization predicts that wave spreading in disordered lattices can come to a complete halt, providing a universal mechanism for {dynamical localization}. In the one-dimensional Hermitian Anderson model with uncorrelated diagonal disorder, there is a one-to-one correspondence between dynamical localization and spectral localization, i.e. the expone

Ludovico Pinzari

This dissertation is based on a project co-founded by the Health Market Quality Program (now Rozetta Institute) and the Australian Institute of Health and Welfare. The overall objective of this work is to provide a framework and a tool for classification and clustering of homogeneous geographic areas based on aggregated population data. Thus, to enable the p

Kabeer Gulati, Zuhaib Ahmad, Abhishek Raj

Any complex dynamic system's ability to function successfully depends in significant part on the accuracy of the sensor data; hence sensor data validation is crucial. Because sensor data is utilized for monitoring and oversight, erroneous sensor data would result in overall poor process output. In this study, the data confidence of the sensor data is ascerta

Ke Song, Quan Xia, Guoqiang Liang, Zhaojie Chen

Non-exemplar class-incremental learning refers to classifying new and old classes without storing samples of old classes. Since only new class samples are available for optimization, it often occurs catastrophic forgetting of old knowledge. To alleviate this problem, many new methods are proposed such as model distillation, class augmentation. In this paper,

Stefano Longhi

We investigate the energy spectral phase transitions arising in one-dimensional superlattices under an imaginary gauge field and possessing M sites in each unit cell in the large M limit. It is shown that in models displaying nearly flat bands a smooth phase transition, from quasi entirely real to complex energies, can be observed as the imaginary gauge fiel

Yu Zhang, Huaming Chen, Wei Bao, Zhongzheng Lai

With the rapid development of deep learning, object detection and tracking play a vital role in today's society. Being able to identify and track all the pedestrians in the dense crowd scene with computer vision approaches is a typical challenge in this field, also known as the Multiple Object Tracking (MOT) challenge. Modern trackers are required to operate

Bingyu Shen

Access control mechanisms have been adopted in many real-world systems to control resource sharing for the principals in the system. An error in the access control policy (misconfiguration) can easily cause severe data leakage and system exploitation. Researchers have developed several methodologies to detect the access control misconfigurations through data

Alessandra Faggionato

We show that the symmetric simple exclusion process (SSEP) on a countable set is well defined by the stirring graphical construction as soon as the dynamics of a single particle is. The resulting process is Feller, its Markov generator is derived on local functions, duality at the level of the empirical density field holds. We also provide a general criterio

Yanbo Wang, Muhan Zhang

Research on the theoretical expressiveness of Graph Neural Networks (GNNs) has developed rapidly, and many methods have been proposed to enhance the expressiveness. However, most methods do not have a uniform expressiveness measure except for a few that strictly follow the $k$-dimensional Weisfeiler-Lehman ($k$-WL) test hierarchy, leading to difficulties in

Calford Odhiambo Otieno

In this paper, Second-order NLO properties of ZnO and AZO thin films from experimental results are discussed. Measurements were a single wavelength of 1.064 micrometers using the standard rotational Maker fringes technique in a transmission scheme. Further broadband dispersion of $\chi^{(2)}$ as characterized by harmonic generation over a broadband wavelengt

Yang Xu, Haibin Kan, Guangyue Han

In this paper, using some conditions that arise naturally in Alon's combinatorial Nullstellensatz as well as its various extensions and generalizations, we characterize Gr\"{o}bner bases consisting of monic polynomials, which helps us to establish a Nullstellensatz from a Gr\"{o}bner basis perspective. As corollaries of this general Nullstellensatz, we estab

Hao Wu, Zhong-Can Ou-Yang, Rudolf Podgornik

A mobile Coulomb gas permeating a fixed background crystalline lattice of charged colloidal crystals is subject to an electrostatic-elastic coupling, which we study on the continuum level by introducing a minimal coupling between electrostatic and displacement fields. We derive linearized, Debye-H\"uckel-like mean-field equations that can be analytically sol

Hanlei Zhang, Hua Xu, Xin Wang, Fei Long

New intent discovery is of great value to natural language processing, allowing for a better understanding of user needs and providing friendly services. However, most existing methods struggle to capture the complicated semantics of discrete text representations when limited or no prior knowledge of labeled data is available. To tackle this problem, we prop

Zhen-Xing Zhao, Fu-Wei Zhang, Xiao-Hui Hu, Yu-Ji Shi

In this work, a three-quark picture is constructed using a bottom-up approach for baryons in light-front quark model. The shape parameters, which characterize the momentum distribution inside a baryon, are determined with the help of the pole residue of the baryon. The relation between the three-quark picture and the diquark picture is clarified. When buildi

Robert M. Kerr

Six sets of Navier-Stokes trefoil vortex knots in $(2\pi)^3$ domains show how the shape of the initialprofile influences the evolution of the enstrophy $Z$, helicity ${\cal H}$ and dissipation-scale. Significant differences develop even when all have the same three-fold symmetric trajectory, the same initial circulation and the same range of the viscosities

Yunseong Cho, Jinseok Choi, Brian L. Evans

In this paper, we propose a learning-based detection framework for uplink massive multiple-input and multiple-output (MIMO) systems with one-bit analog-to-digital converters. The learning-based detection only requires counting the occurrences of the quantized outputs of -1 and +1 for estimating a likelihood probability at each antenna. Accordingly, the key a

Taichi Kato, Hiroshi Itoh, Tonny Vanmunster, Seiichiro Kiyota

We analyzed Asteroid Terrestrial-impact Last Alert System (ATLAS), Zwicky Transient Facility (ZTF) and All-Sky Automated Survey for Supernovae (ASAS-SN) data of MASTER OT J055845.55+391533.4 and found that this object repeats superoutburst with a dip in the middle of the outburst followed by long and sometimes oscillating rebrightening, just like a WZ Sge-ty

Gil Bor, Luis Hernández Lamoneda

A pair of planar polygons is "dancing" if one is inscribed in the other and they satisfy a certain cross-ratio relation at each vertex of the circumscribing polygon. Non-degenerate dancing pairs of closed $n$-gons exist for all $n\geq 6$. Dancing pairs correspond to trajectories of a non-holonomic mechanical system, consisting of a ball rolling, without slip

Jingxuan Kang, Tudor Jianu, Baoru Huang, Binod Bhattarai

Endovascular intervention training is increasingly being conducted in virtual simulators. However, transferring the experience from endovascular simulators to the real world remains an open problem. The key challenge is the virtual environments are usually not realistically simulated, especially the simulation images. In this paper, we propose a new method t

Amartya Goswami

We study the topology of a class of proper submodules and some of its distinguished subclasses and call them structure spaces. We give several criteria for the quasi-compactness of these structure spaces. We study $T_0$ and $T_1$ separation properties and characterize structure spaces in which nonempty irreducible closed subsets have unique generic points. W

Shen Yan, Yu Liu, Long Wang, Zehong Shen

Despite the remarkable advances in image matching and pose estimation, image-based localization of a camera in a temporally-varying outdoor environment is still a challenging problem due to huge appearance disparity between query and reference images caused by illumination, seasonal and structural changes. In this work, we propose to leverage additional sens

Muhammad Iqbal Rochman, Vanlin Sathya, Bill Payne, Mehmet Yavuz

The 3.7 - 3.98 GHz frequency band (also known as C-band) was recently allocated in the US for the deployment of 5G cellular services. Prior to this, the lower adjacent band, 3.55 - 3.7 GHz, had been allocated to Citizens Broadband Radio Service (CBRS), where the entire 150 MHz can be used for free by Tier 3 General Authorized Access (GAA) users, but access t

Zhiyuan Li, Ziru Liu, Anna Zou, Anca L. Ralescu

Deep metric learning techniques have been used for visual representation in various supervised and unsupervised learning tasks through learning embeddings of samples with deep networks. However, classic approaches, which employ a fixed distance metric as a similarity function between two embeddings, may lead to suboptimal performance for capturing the comple

Joy He-Yueya, Gabriel Poesia, Rose E. Wang, Noah D. Goodman

Automatically generating high-quality step-by-step solutions to math word problems has many applications in education. Recently, combining large language models (LLMs) with external tools to perform complex reasoning and calculation has emerged as a promising direction for solving math word problems, but prior approaches such as Program-Aided Language model

Zeinab Alizadeh, Afrooz Jalilzadeh, Farzad Yousefian

In this paper, we consider stochastic monotone Nash games where each player's strategy set is characterized by possibly a large number of explicit convex constraint inequalities. Notably, the functional constraints of each player may depend on the strategies of other players, allowing for capturing a subclass of generalized Nash equilibrium problems (GNEP).

Sam van der Poel, Dakotah Lambert, Kalina Kostyszyn, Tiantian Gao

Synthetic datasets constructed from formal languages allow fine-grained examination of the learning and generalization capabilities of machine learning systems for sequence classification. This article presents a new benchmark for machine learning systems on sequence classification called MLRegTest, which contains training, development, and test sets from 1,

Jianzhang Zheng, Hao Shen, Jian Yang, Xuan Tang

Autoencoders have achieved great success in various computer vision applications. The autoencoder learns appropriate low dimensional image representations through the self-supervised paradigm, i.e., reconstruction. Existing studies mainly focus on the minimizing the reconstruction error on pixel level of image, while ignoring the preservation of Intrinsic Di

Serdar Yüksel

In deterministic and stochastic control theory, relaxed or randomized control policies allow for versatile mathematical analysis (on continuity, compactness, convexity and approximations) to be applicable with no artificial restrictions on the classes of control policies considered, leading to very general existence results on optimal measurable policies und

Huihui Zheng, Li Guo, Tianshui Ma, Liangyun Zhang

This paper studies the relationship of Rota-Baxter operators on cocommutative Hopf algebras with Hopf braces and the Yang-Baxter equation, with emphasis on the embedding of cocommutative Hopf braces into Rota-Baxter Hopf algebras. Through Hopf braces, we establish a connection between relative Rota-Baxter operators on cocommutative Hopf algebras and bijectiv

Emilio Ferrara

The significant advancements in applying Artificial Intelligence (AI) to healthcare decision-making, medical diagnosis, and other domains have simultaneously raised concerns about the fairness and bias of AI systems. This is particularly critical in areas like healthcare, employment, criminal justice, credit scoring, and increasingly, in generative AI models

Xiao-Yun Wang, Chen Dong, Xiang Liu

In this work, we investigate the nature of the strong coupling constant and related physics. Through the analysis of accumulated experimental data from around the world, we employ the ability of machine learning to unravel its physical laws. The result of our efforts is a formula that captures the expansive panorama of the distribution of the strong coupling

Shadi Shajari, Nitin Agarwal, Mustafa Alassad

YouTube is the second most visited website in the world and receives comments from millions of commenters daily. The comments section acts as a space for discussions among commenters, but it could also be a breeding ground for problematic behavior. In particular, the presence of suspicious commenters who engage in activities that deviate from the norms of co

Zhigang Yao, Jiaji Su, Bingjie Li, Shing-Tung Yau

While classical data analysis has addressed observations that are real numbers or elements of a real vector space, at present many statistical problems of high interest in the sciences address the analysis of data that consist of more complex objects, taking values in spaces that are naturally not (Euclidean) vector spaces but which still feature some geomet

Navid Seidi, Ardhendu Tripathy, Sajal K. Das

Time elapsed till an event of interest is often modeled using the survival analysis methodology, which estimates a survival score based on the input features. There is a resurgence of interest in developing more accurate prediction models for time-to-event prediction in personalized healthcare using modern tools such as neural networks. Higher quality featur

Guixian Xu, Huihui Wang, Qingping Zhou

Electrical Impedance Tomography (EIT) is widely applied in medical diagnosis, industrial inspection, and environmental monitoring. Combining the physical principles of the imaging system with the advantages of data-driven deep learning networks, physics-embedded deep unrolling networks have recently emerged as a promising solution in computational imaging. H

Dai Aoki, Ilya Sheikin, Alix McCollam, Jun Ishizuka

We performed de Haas-van Alphen (dHvA) experiments in the spin-triplet superconductor UTe2 for magnetic field along the c-axis above 15T. Three fundamental dHvA frequencies, named alpha1, alpha2 and beta corresponding to the cross sections of cylindrical Fermi surfaces (FSs) with large cyclotron effective masses (33-43 m0) were detected. No other fundamental

Richard K Bowles, Peter Harrowell

It has been established empirically that the rate of addition of molecules to the crystal during crystal growth from the melt is proportional to exp(-|{\Delta}S_fus|/R) where {\Delta}S_fus is the entropy of fusion. Here we show that this entropic slowdown arises directly from the separation of the entropy loss and energy loss processes associated with the fr

Nazar Waheed, Fazlullah Khan, Spyridon Mastorakis, Mian Ahmad Jan

The rapid expansion of Internet of Things (IoT) devices in smart homes has significantly improved the quality of life, offering enhanced convenience, automation, and energy efficiency. However, this proliferation of connected devices raises critical concerns regarding security and privacy of the user data. In this paper, we propose a differential privacy-bas

Jielin Qiu, Peide Huang, Makiya Nakashima, Jaehyun Lee

Self-supervised learning is crucial for clinical imaging applications, given the lack of explicit labels in healthcare. However, conventional approaches that rely on precise vision-language alignment are not always feasible in complex clinical imaging modalities, such as cardiac magnetic resonance (CMR). CMR provides a comprehensive visualization of cardiac

Nathan Klein, Neil Olver

In the laminar-constrained spanning tree problem, the goal is to find a minimum-cost spanning tree which respects upper bounds on the number of times each cut in a given laminar family is crossed. This generalizes the well-studied degree-bounded spanning tree problem, as well as a previously studied setting where a chain of cuts is given. We give the first c