July 2022 arXiv papers — page 35

Ryutaro Tsuji, Natsuki Tsukamoto, Yasumichi Aoki, Ken-Ichi Ishikawa

We present results for the scalar and tensor isovector-couplings ($g_S$ and $g_T$) of the nucleon measured at the physical point ($M_{\pi}=135$ MeV) with a single lattice spacing of $0.085\ \mathrm{fm}$ in 2+1 flavor QCD. Our calculations are carried out with two ensembles of gauge configurations generated by the PACS Collaboration with nonperturbatively ${\

Gan Zhai, Yizhou Xin, Cameron J. Kopas, Ella Lachman

Contactless excitation and detection of high harmonic acoustic overtones in a thin insulator single crystal are described using radio frequency spectroscopy techniques. Single crystal [001] silicon wafer samples were investigated, one side covered with a Nb thin film, the common starting point for fabrication of quantum devices. The coupling between electrom

Qinghua Liu, Yuxiang Jiang

The increasing scale of model size and continuous improvement of performance herald the arrival of the Big Model era. In this report, we explore what and how the big model training works by diving into training objectives and training methodologies. Specifically,training objectives describe how to leverage web-scale data to develop extremely capable and incr

Bangbang Yang, Chong Bao, Junyi Zeng, Hujun Bao

Very recently neural implicit rendering techniques have been rapidly evolved and shown great advantages in novel view synthesis and 3D scene reconstruction. However, existing neural rendering methods for editing purposes offer limited functionality, e.g., rigid transformation, or not applicable for fine-grained editing for general objects from daily lives. I

Yi-Fu Cai, Xiao-Han Ma, Misao Sasaki, Dong-Gang Wang

For primordial perturbations, deviations from Gaussian statistics on the tail of the probability distribution can be associated with non-perturbative effects of inflation. In this paper, we present some particular examples in which the tail of the distribution becomes highly non-Gaussian although the statistics remains almost Gaussian in the perturbative reg

Yuzuru Yoshii, Hiroaki Sameshima, Takuji Tsujimoto, Toshikazu Shigeyama

The search for Population III (Pop III) stars has fascinated and eluded astrophysicists for decades. One promising place for capturing evidence of their presence must be high-redshift objects; signatures should be recorded in their characteristic chemical abundances. We deduce the Fe and Mg abundances of the broad-line region (BLR) from the intensities of ul

Yan Wang, Liangchi Zhang, Chuhan Wu

This paper experimentally investigated the effects of silicone oil on the tribological behaviour of AZ31B/86CrMoV7 contact pair under a pin-on-disk configuration. A commercial silicone oil was used as an oxidation inhibiter for the AZ31B at elevated temperatures to 300 oC. The wear mechanism of the contact pair was explored by SEM morphologies of worn surfac

Balendra Pratap Singh, Md Sabir Ali, Sushant~G. ~Ghosh

The presence of a photon region around the black hole is an essential feature in receiving the emitted spectrum from the vicinity of the black hole by the distant observer. In this paper, we investigate the optical properties of rotating regular anti-de Sitter (AdS) black holes, which characterized by its mass $(M)$, spin parameter $(a)$, deviation parameter

Chunxi Liu, Yuan Shangguan, Haichuan Yang, Yangyang Shi

There is growing interest in unifying the streaming and full-context automatic speech recognition (ASR) networks into a single end-to-end ASR model to simplify the model training and deployment for both use cases. While in real-world ASR applications, the streaming ASR models typically operate under more storage and computational constraints - e.g., on embed

Arnesh Sujanani, Renato D. C. Monteiro

This work presents an adaptive superfast proximal augmented Lagrangian (AS-PAL) method for solving linearly-constrained smooth nonconvex composite optimization problems. Each iteration of AS-PAL inexactly solves a possibly nonconvex proximal augmented Lagrangian (AL) subproblem obtained by an aggressive/adaptive choice of prox stepsize with the aim of substa

Paul Hamacher, Ziquan Yang, Xiaolei Zhao

We prove that the Tate conjecture for divisors is ''generically true'' for mod p reductions of complex projective varieties with $h^{2, 0} = 1$, under a mild assumption on moduli. By refining this general result, we establish a new case of the BSD conjecture over global function fields, and the Tate conjecture for a class of general type surfaces of geometri

Allen Liu, Ankur Moitra

In this work, we study the problem of community detection in the stochastic block model with adversarial node corruptions. Our main result is an efficient algorithm that can tolerate an $\epsilon$-fraction of corruptions and achieves error $O(\epsilon) + e^{-\frac{C}{2} (1 \pm o(1))}$ where $C = (\sqrt{a} - \sqrt{b})^2$ is the signal-to-noise ratio and $a/n$

W. H. Dai, H. Ma, Q. Yue, L. T. Yang

A model of the Li-diffused inactive layer in P-type high purity germanium detectors is built to describe the transportation of charge carriers and calculate the charge collection efficiency therein. The model is applied to calculate charge collection efficiency of a P-type point-contact germanium detector used in rare event physics experiments and validated

Wenqi Zhang, Kai Zhao, Peng Li, Xiao Zhu

Reliable navigation systems have a wide range of applications in robotics and autonomous driving. Current approaches employ an open-loop process that converts sensor inputs directly into actions. However, these open-loop schemes are challenging to handle complex and dynamic real-world scenarios due to their poor generalization. Imitating human navigation, we

Jiang Li, Xiaoping Wang, Guoqing Lv, Zhigang Zeng

Multimodal Emotion Recognition in Conversation (ERC) plays an influential role in the field of human-computer interaction and conversational robotics since it can motivate machines to provide empathetic services. Multimodal data modeling is an up-and-coming research area in recent years, which is inspired by human capability to integrate multiple senses. Sev

Ya-Juan Wu, Shao-Ming Fei, Zhi-Xi Wang, Ke Wu

Extracting work from quantum system is one of the important areas in quantum thermodynamics. As a significant thermodynamic quantity, the ergotropy gap characterizes the difference between the global and local maximum extractable works. We derive an analytical upper bound of the ergotropic gap with respect to $d\times d\times d$ tripartite separable states.

Junjie Li, Yichao Yan, Guanshuo Wang, Fufu Yu

Person search is a challenging task which aims to achieve joint pedestrian detection and person re-identification (ReID). Previous works have made significant advances under fully and weakly supervised settings. However, existing methods ignore the generalization ability of the person search models. In this paper, we take a further step and present Domain Ad

Tosin Ige, Sikiru Adewale

"Unless and until our society recognizes cyber bullying for what it is, the suffering of thousands of silent victims will continue." ~ Anna Maria Chavez. There had been series of research on cyber bullying which are unable to provide reliable solution to cyber bullying. In this research work, we were able to provide a permanent solution to this by developing

Zhenyu Xiao, Junyi Yang, Tianqi Mao, Chong Xu

With the rapid development of satellite communication technologies, the space-based access network has been envisioned as a promising complementary part of the future 6G network. Aside from terrestrial base stations, satellite nodes, especially the low-earth-orbit (LEO) satellites, can also serve as base stations for Internet access, and constitute the LEO-s

Yingjie Chen, Huasong Zhong, Chong Chen, Chen Shen

Face clustering is a promising way to scale up face recognition systems using large-scale unlabeled face images. It remains challenging to identify small or sparse face image clusters that we call hard clusters, which is caused by the heterogeneity, \ie, high variations in size and sparsity, of the clusters. Consequently, the conventional way of using a unif

Maaz Amjad, Grigori Sidorov, Alisa Zhila, Alexander Gelbukh

This paper gives the overview of the first shared task at FIRE 2020 on fake news detection in the Urdu language. This is a binary classification task in which the goal is to identify fake news using a dataset composed of 900 annotated news articles for training and 400 news articles for testing. The dataset contains news in five domains: (i) Health, (ii) Spo

Aupendu Kar, Suresh Nehra, Jayanta Mukhopadhyay, Prabir Kumar Biswas

With the availability of commercial Light Field (LF) cameras, LF imaging has emerged as an up and coming technology in computational photography. However, the spatial resolution is significantly constrained in commercial microlens based LF cameras because of the inherent multiplexing of spatial and angular information. Therefore, it becomes the main bottlene

Maaz Amjad, Grigori Sidorov, Alisa Zhila, Alexander Gelbukh

This overview paper describes the first shared task on fake news detection in Urdu language. The task was posed as a binary classification task, in which the goal is to differentiate between real and fake news. We provided a dataset divided into 900 annotated news articles for training and 400 news articles for testing. The dataset contained news in five dom

Kun He, Kewen Wu, Kuan Yang

Let $\Phi$ be a random $k$-CNF formula on $n$ variables and $m$ clauses, where each clause is a disjunction of $k$ literals chosen independently and uniformly. Our goal is to sample an approximately uniform solution of $\Phi$ (or equivalently, approximate the partition function of $\Phi$). Let $\alpha=m/n$ be the density. The previous best algorithm runs in

Tarik Faouzi, Emilio Procu, Igor Kondrashuk, Moreno Bevilacqua

The Mat\'ern and the Generalized Cauchy families of covariance functions have a prominent role in spatial statistics as well as in a wealth of statistical applications. The Mat\'ern family is crucial to index mean-square differentiability of the associated Gaussian random field; the Cauchy family is a decoupler of the fractal dimension and Hurst effect for G

Augustine Denteh, Désiré Kédagni

The difference-in-differences (DID) design is one of the most popular methods used in empirical economics research. However, there is almost no work examining what the DID method identifies in the presence of a misclassified treatment variable. This paper studies the identification of treatment effects in DID designs when the treatment is misclassified. Misc

Songlin Fan, Wei Gao, Ge Li

This paper researches the unexplored task-point cloud salient object detection (SOD). Differing from SOD for images, we find the attention shift of point clouds may provoke saliency conflict, i.e., an object paradoxically belongs to salient and non-salient categories. To eschew this issue, we present a novel view-dependent perspective of salient objects, rea

Zhifan Li, Yanhang Zhang, Jianxin Yin

In this paper, we focus on the high-dimensional double sparse structure, where the parameter of interest simultaneously encourages group-wise sparsity and element-wise sparsity in each group. By combining the Gilbert-Varshamov bound and its variants, we develop a novel lower bound technique for the metric entropy of the parameter space, specifically tailored

Jing Liu, Tongya Zheng, Qinfen Hao

Researchers have recently proposed plenty of heterogeneous graph neural networks (HGNNs) due to the ubiquity of heterogeneous graphs in both academic and industrial areas. Instead of pursuing a more powerful HGNN model, in this paper, we are interested in devising a versatile plug-and-play module, which accounts for distilling relational knowledge from pre-t

Jiawang Bai, Baoyuan Wu, Zhifeng Li, Shu-tao Xia

To explore the vulnerability of deep neural networks (DNNs), many attack paradigms have been well studied, such as the poisoning-based backdoor attack in the training stage and the adversarial attack in the inference stage. In this paper, we study a novel attack paradigm, which modifies model parameters in the deployment stage. Considering the effectiveness

Nicky Nirlipta Sahoo, Balamurali Murugesan, Ayantika Das, Srinivasa Karthik

Preterm babies in the Neonatal Intensive Care Unit (NICU) have to undergo continuous monitoring of their cardiac health. Conventional monitoring approaches are contact-based, making the neonates prone to various nosocomial infections. Video-based monitoring approaches have opened up potential avenues for contactless measurement. This work presents a pipeline

Tongyu Wang, Peng Yi

In this paper, we focus on solving a distributed convex aggregative optimization problem in a network, where each agent has its own cost function which depends not only on its own decision variables but also on the aggregated function of all agents' decision variables. The decision variable is constrained within a feasible set. In order to minimize the sum o

Mingzhou Xu, Kun Cheng, Wangke Yu

Let $\{Y_i,-\infty<i<\infty\}$ be a doubly infinite sequence of identically distributed, negatively dependent random variables under sub-linear expectations, $\{a_i,-\infty<i<\infty\}$ be an absolutely summable sequence of real numbers. In this article, we study complete convergence and Marcinkiewicz-Zygmund strog law of large numbers for the partial sums of

Zhenyu Xiao, Tianqi Mao, Zhu Han, Xiang-Gen Xia

Precipitated by the technological innovations of the near-space platform stations (NSPS), the near space communication (NS-COM) network has emerged as an indispensable part of the next-generation space-air-ground integrated network (SAGIN) that facilitates ubiquitous coverage and broadband data transfer. This paper aims to provide a comprehensive overview of

Tosin Ige, Sikiru Adewale

Ever since the era of internet had ushered in cloud computing, there had been increase in the demand for the unlimited data available through cloud computing for data analysis, pattern recognition and technology advancement. With this also bring the problem of scalability, efficiency and security threat. This research paper focuses on how data can be dynamic

Huaying Hao, Cong Xu, Dan Zhang, Qifeng Yan

Retinal Optical Coherence Tomography Angiography (OCTA) with high-resolution is important for the quantification and analysis of retinal vasculature. However, the resolution of OCTA images is inversely proportional to the field of view at the same sampling frequency, which is not conducive to clinicians for analyzing larger vascular areas. In this paper, we

Takashi Asawa, Haruki Oshio, Kazuki Tanaka

Mean radiant temperature (MRT) is the primary metric of radiant heat exchange between a human body and the environment, and it dominates human thermal comfort and heat stress. This study develops a new portable recording system for spherical thermography utilizing only commercial devices (an infrared thermal imaging camera and a portable rotation platform) a

Kaiyi Luo, Chao Zhang, Huaxiong Li, Xiuyi Jia

In recent years, Cross-Modal Hashing (CMH) has aroused much attention due to its fast query speed and efficient storage. Previous literatures have achieved promising results for Cross-Modal Retrieval (CMR) by discovering discriminative hash codes and modality-specific hash functions. Nonetheless, most existing CMR works are subjected to some restrictions: 1)

Tasnim Ibn Faiz, Chrysafis Vogiatzis, Md. Noor-E-Alam

Providing first aid and other supplies (e.g., epi-pens, medical supplies, dry food, water) during and after a disaster is always challenging. The complexity of these operations increases when the transportation, power, and communications networks fail, leaving people stranded and unable to communicate their locations and needs. The advent of emerging technol

Daniel Frolovsky, Sergei V. Ketov, Sultan Saburov

We propose and study the new (generalized) E-type $\alpha$-attractor models of inflation, in order to include formation of primordial black holes (PBHs). The inflaton potential has a near-inflection point where slow-roll conditions are violated, thus leading to large scalar perturbations collapsing to PBHs later. An ultra-slow roll (short) phase exists betwe

Christopher Kang, Kazuumi Fujioka, Rui Sun

In spite of the great success that all-atom molecular dynamics simulations have seen in revealing the nature of the lipid bilayer, the interplay between a membrane's curvature and dynamics remains elusive. This is largely due to the computational challenges involved in simulating a highly curved membrane, as the one found in a small vesicle. In the present w

Kohei Yamashita, Yuto Enyo, Shohei Nobuhara, Ko Nishino

We introduce a novel multi-view stereo (MVS) method that can simultaneously recover not just per-pixel depth but also surface normals, together with the reflectance of textureless, complex non-Lambertian surfaces captured under known but natural illumination. Our key idea is to formulate MVS as an end-to-end learnable network, which we refer to as nLMVS-Net,

Jingyuan Yang, Jie Li, Leida Li, Xiumei Wang

Visual Emotion Analysis (VEA), which aims to predict people's emotions towards different visual stimuli, has become an attractive research topic recently. Rather than a single label classification task, it is more rational to regard VEA as a Label Distribution Learning (LDL) problem by voting from different individuals. Existing methods often predict visual

Gregory R. Chambers

Suppose that $M$ is a hyperbolic surface of genus $g$ and with $n$ cusps. Then we can find a pants decomposition of $M$ composed of simple closed geodesics so that each curve is contained in a ball of diameter at most $C\sqrt{g + n}$, where $C$ is a universal constant.

Bill Basener

In this paper we investigate Deep Learning Models using topological dynamical systems, index theory, and computational homology. These mathematical machinery was invented initially by Henri Poincare around 1900 and developed over time to understand shapes and dynamical systems whose structure and behavior is too complicated to solve for analytically but can

Jeovanny de Jesus Muentes Acevedo, Sergio Romaña Ibarra, Raibel Arias Cantillo

Let $N$ be an $n$-dimensional compact riemannian manifold, with $n\geq 2$. In this paper, we prove that for any $\alpha\in [0,n]$, the set consisting of homeomorphisms on $N$ with lower and upper metric mean dimensions equal to $\alpha$ is dense in $\text{Hom}(N)$. More generally, given $\alpha,\beta\in [0,n]$, with $\alpha\leq \beta$, we show the set consis

Rashmi Agrawal, Leo de Castro, Guowei Yang, Chiraag Juvekar

FHE offers protection to private data on third-party cloud servers by allowing computations on the data in encrypted form. However, to support general-purpose encrypted computations, all existing FHE schemes require an expensive operation known as bootstrapping. Unfortunately, the computation cost and the memory bandwidth required for bootstrapping add signi

Fengbin Zhu, Wenqiang Lei, Fuli Feng, Chao Wang

Document Visual Question Answering (VQA) aims to understand visually-rich documents to answer questions in natural language, which is an emerging research topic for both Natural Language Processing and Computer Vision. In this work, we introduce a new Document VQA dataset, named TAT-DQA, which consists of 3,067 document pages comprising semi-structured table

Sungkyung Kang, JungHwan Park

We define a nontrivial mod 2 valued additive concordance invariant defined on the torsion subgroup of the knot concordance group using involutive knot Floer package. For knots not contained in its kernel, we prove that their iterated $(\text{odd},1)$-cables have infinite order in the concordance group and, among them, infinitely many are linearly independent

Hélio D. Perottoni, Guilherme Limberg, João A. S. Amarante, Silvia Rossi

In the first billion years after its formation, the Galaxy underwent several mergers with dwarf satellites of various masses. The debris of Gaia-Sausage/Enceladus (GSE), the galaxy responsible for the last significant merger of the Milky Way, dominates the inner halo and has been suggested to be the progenitor of both the Hercules-Aquila Cloud (HAC) and Virg

Jeffrey A. Mudrock

List packing is a notion that was introduced in 2021 (by Cambie et al.). The list packing number of a graph $G$, denoted $\chi_{\ell}^*(G)$, is the least $k$ such that for any list assignment $L$ that assigns $k$ colors to each vertex of $G$, there is a set of $k$ proper $L$-colorings of $G$, $\{f_1, \ldots, f_k \}$, with the property $f_i(v) \neq f_j(v)$ wh

A. J. Schwartz

The parameter $y_{CP}$ is used to characterize mixing in the $D^0$-$\bar{D}{}^0$ meson system. To determine $y_{CP}$, one measures the effective decay width of a $D^0$ or $\bar{D}{}^0$ decaying to a $CP$ eigenstate, relative to the effective width for a decay to a Cabibbo-favored, flavor-specific final state. When using $y_{CP}$ to extract information about

Nageswari Shanmugalingam

In this note we deconstruct and explore the components of a theorem of Carrasco Piaggio, which relates Ahlfors regular conformal gauge of a compact doubling metric space to weights on Gromov-hyperbolic fillings of the metric space. We consider a construction of hyperbolic filling that is simpler than the one considered by Carrasco Piaggio, and we determine t

MengKe Feng, Jun Yoneda, Wister Huang, Yue Su

One of the key pathways towards scalability of spin-based quantum computing systems lies in achieving long-range interactions between electrons and increasing their inter-connectivity. Coherent spin transport is one of the most promising strategies to achieve this architectural advantage. Experimental results have previously demonstrated high fidelity transp

Robert L. Obenchain

My first paper exclusively about ridge regression was published in Technometrics and chosen for invited presentation at the 1975 Joint Statistical Meetings in Atlanta. Unfortunately, that paper contained a wide range of assorted details and results. Luckily, Gary McDonald's published discussion of that paper focused primarily on my use of Maximum Likelihood

Miantao Liu, Gongxiang Liu, Kun Zhou

Let $H$ be the Hopf algebra $H_{c: \sigma_{0}}$ of Kashina [J. Algebra, 232(2000),pp.617-663]. We give all simple Yetter-Drinfel'd modules $V$ over $H$, then classify all finite-dimensional Nichols algebras of $V$. The finite dimensional Nichols algebras of diagonal type are either $A_{1}, A_{2}$ or quantum planes, and non-diagonal type ones are $8$ or $16$

Di Jin, Sijia Liu, Yang Liu, Dilek Hakkani-Tur

Though chatbots based on large neural models can often produce fluent responses in open domain conversations, one salient error type is contradiction or inconsistency with the preceding conversation turns. Previous work has treated contradiction detection in bot responses as a task similar to natural language inference, e.g., detect the contradiction between

Markus Reineke, Brendon Rhoades, Vasu Tewari

We apply the method of orbit harmonics to the set of break divisors and orientable divisors on graphs to obtain the central and external zonotopal algebras respectively. We then relate a construction of Efimov in the context of cohomological Hall algebras to the central zonotopal algebra of a graph $G_{Q,\gamma}$ constructed from a symmetric quiver $Q$ with

Jiaming Zhang, Kailun Yang, Hao Shi, Simon Reiß

In this paper, we address panoramic semantic segmentation which is under-explored due to two critical challenges: (1) image distortions and object deformations on panoramas; (2) lack of semantic annotations in the 360{\deg} imagery. To tackle these problems, first, we propose the upgraded Transformer for Panoramic Semantic Segmentation, i.e., Trans4PASS+, eq

Mohammed Rashid, Jeffrey A. Nanzer

Distributed phased arrays are comprised of separate, smaller antenna systems that coordinate with each other to support coherent beamforming towards a destination. However, due to the frequency drift and phase jitter of the oscillators, as well as the frequency and phase estimation errors induced at the nodes, there exists decoherence that degrades the beamf

Jae Woo Lee, Kyeongsoo Hong, Hye-Young Kim, Jang-Ho Park

For the EL CVn candidate 1SWASPJ181417.43+481117.0 (WASP 1814+48), we secured the first spectroscopic observations between 2015 April and 2021 March. Using the echelle spectra, the radial velocities (RVs) of the primary star were measured with its atmospheric parameters of $T_{\rm eff,1}=7770\pm130$ K and $v_1$$\sin$$i=47\pm6$ km s$^{-1}$. We fitted our sing

Devdeep Ray, Connor Smith, Teng Wei, David Chu

This paper presents the design and evaluation of SQP, a congestion control algorithm (CCA) for interactive video streaming applications that need to stream high-bitrate compressed video with very low end-to-end frame delay (eg. AR streaming, cloud gaming). SQP uses frame-coupled, paced packet trains to sample the network bandwidth, and uses an adaptive one-w

Stephon Alexander, Tatsuya Daniel, Marcell Howard, Morgane Konig

The Chern-Simons-Kodama (CSK) state is an exact, non-perturbative wave function in the Ashtekar formulation of classical General Relativity. In this work, we find a generalized fermionic CSK state by solving the extended gravitational and fermionic Hamiltonian constraints of the Wheeler-DeWitt equation exactly. We show that this new state reduces to the orig

Lucas D. Venturato, Mariela B. Cirelli, Domingo A. Tarzia

Similarity solutions for the two-phase Rubinstein binary-alloy solidification problem in a semi-infinite material are developed. These new explicit solutions are obtained by considering two cases: a heat flux or a convective boundary conditions at the fixed face, and the necessary and sufficient conditions on data are also given in order to have an instantan

Quan Chen, Roberto Hernández Palomares, Corey Jones

We introduce a K-theoretic invariant for actions of unitary fusion categories on unital C*-algebras. We show that for inductive limits of finite dimensional actions of fusion categories on unital AF-algebras, this is a complete invariant. In particular, this gives a complete invariant for inductive limit actions of finite groups on AF-algebras. We apply our

Yinbang Lin

Over a smooth complex projective curve, we study an algebraic versal deformation space with fixed determinant of a coherent sheaf. The algebraic versal deformation space decomposes into a disjoint union of Shatz strata, namely locally closed subschemes which parametrize coherent sheaves with common Harder-Narasimhan types. We study the geometry and local top

Xiongping Dai

We define recurrence for a compactly generated para-topological group $G$ acting continuously on a locally compact Hausdorff space $X$ with $\dim X=0$, and then, show that if $\overline{Gx}$ is compact for all $x\in X$, the conditions (i) this dynamics is pointwise recurrent, (ii) $X$ is a union of $G$-minimal sets, (iii) the $G$-orbit closure relation is cl

A. Ramzy

In this paper, we provide a generalization of Proth&#39;s theorem for integers of the form $Kp^n+1$. In particular, a primality test that requires only one modular exponentiation similar to that of Fermat&#39;s test without the computation of any GCD&#39;s. We also provide two tests to increase the chances of proving the primality of $Kp^n+1$ numbers (if the

John T. Griesmer

We say that $S\subset\mathbb Z$ is a set of $k$-recurrence if for every measure preserving transformation $T$ of a probability measure space $(X,\mu)$ and every $A\subseteq X$ with $\mu(A)>0$, there is an $n\in S$ such that $\mu(A\cap T^{-n} A\cap T^{-2n}\cap \dots \cap T^{-kn}A)>0$. A set of $1$-recurrence is called a set of measurable recurrence. Answering

Yudong Han, Liqiang Nie, Jianhua Yin, Jianlong Wu

Several studies have recently pointed that existing Visual Question Answering (VQA) models heavily suffer from the language prior problem, which refers to capturing superficial statistical correlations between the question type and the answer whereas ignoring the image contents. Numerous efforts have been dedicated to strengthen the image dependency by creat

M. E. Raikh

A remarkable feature of the Landau-Zener transition is insensitivity of the survival probability to the decay rate, of the excited state. Namely, the probability for a particle, which is initially in the ground state, to remain in the same state is insensitive to decay, which is due to e.g. coupling to continuum [V. M. Akulin and W. P. Schleich, Phys. Rev. A

Youka Kaku, Shin'ya Maeda, Yasusada Nambu, Yuki Osawa

This study investigates the quantumness of gravity under the setup of the atomic interferometry from the viewpoint of mass-energy equivalence. We evaluated interference visibility considering a particle with internal energy levels in a harmonic trapping potential. As per the result, for a spatially superposed gravitational source mass, interference visibilit

Gary Guth

A result of Baykur-Sunukjian states that homologous surfaces in a 4-manifold become isotopic after a finite number of internal stabilizations, i.e. attaching tubes to the surfaces. A natural question is how many stabilizations are needed before the surfaces become isotopic. In particular, given an exotic pair of surfaces, is a single stabilization always eno

Taha Ceritli, Andrew P. Creagh, David A. Clifton

A particular challenge for disease progression modeling is the heterogeneity of a disease and its manifestations in the patients. Existing approaches often assume the presence of a single disease progression characteristics which is unlikely for neurodegenerative disorders such as Parkinson's disease. In this paper, we propose a hierarchical time-series mode

Jiro Kitagawa, Kazuhisa Hoshi, Yuta Kawasaki, Rikuo Koga

We have found that body-centered cubic (bcc) HfMoNbTiZr is a type-II BCS high-entropy alloy (HEA) superconductor with a superconducting critical temperature of $T_\mathrm{c}$=4.1 K. By employing a Debye temperature $\theta_\mathrm{D}$ of 263 K and $T_\mathrm{c}$, the electron-phonon coupling constant $\lambda_\mathrm{e-p}$ is calculated to be 0.63. The elect

Nobutaka Boumuki

This paper shows an example of a connected open neighborhood of a compact connected complex submanifold in a complex flag manifold.

Min Zhang, Zhihong Pan, Xin Zhou, C. -C. Jay Kuo

Normalizing flow models have been used successfully for generative image super-resolution (SR) by approximating complex distribution of natural images to simple tractable distribution in latent space through Invertible Neural Networks (INN). These models can generate multiple realistic SR images from one low-resolution (LR) input using randomly sampled point

Marco Zank

We present quadrature schemes to calculate matrices, where the so-called modified Hilbert transformation is involved. These matrices occur as temporal parts of Galerkin finite element discretizations of parabolic or hyperbolic problems when the modified Hilbert transformation is used for the variational setting. This work provides the calculation of these ma

G. I. Drakoulas, T. V. Gortsas, G. C. Bourantas, V. N. Burganos

Digital twins have emerged as a key technology for optimizing the performance of engineering products and systems. High-fidelity numerical simulations constitute the backbone of engineering design, providing an accurate insight into the performance of complex systems. However, large-scale, dynamic, non-linear models require significant computational resource

Gombojav O. Ariunbold

Intriguing collective spontaneous cascade emissions have recently been realized. In despite of much success, a depth understanding of the complexity is still lacking. With this motivation, a new simple cascade superradiance model is developed in this work. The existing model of identical two-level atoms is reexamined with a new insight. Temporal evolutions o

Andrei Shubin

We show that the M\"{o}bius function is orthogonal to the Thue-Morse sequence $t(n)$ taken along the Piatetski-Shapiro numbers $\lfloor n^c \rfloor$ for any $1 < c < 2$. Previously this property was established for the subsequence along the squares $t(n^2)$. These are both examples of M\"{o}bius orthogonal sequences with maximum entropy.

Ahmad Mustapha, Wael Khreich, Wasim Masr

Deep Learning has demonstrated a significant improvement against traditional machine learning approaches in different domains such as image and speech recognition. Their success on benchmark datasets is transferred to the real-world through pretrained models by practitioners. Pretraining visual models using supervised learning requires a significant amount o

Ansh Mittal, Shuvam Ghosal, Rishibha Bansal

Detecting suspicious activities in surveillance videos is a longstanding problem in real-time surveillance that leads to difficulties in detecting crimes. Hence, we propose a novel approach for detecting and summarizing suspicious activities in surveillance videos. We have also created ground truth summaries for the UCF-Crime video dataset. We modify a pre-e

Ahmad Mustapha, Wael Khreich, Wes Masri

Since early machine learning models, metrics such as accuracy and precision have been the de facto way to evaluate and compare trained models. However, a single metric number doesn't fully capture the similarities and differences between models, especially in the computer vision domain. A model with high accuracy on a certain dataset might provide a lower ac

Haoran Yang, Xiangyu Zhao, Muyang Li, Hongxu Chen

Currently, graph learning models are indispensable tools to help researchers explore graph-structured data. In academia, using sufficient training data to optimize a graph model on a single device is a typical approach for training a capable graph learning model. Due to privacy concerns, however, it is infeasible to do so in real-world scenarios. Federated l

Kshitij Kulkarni, Theo Diamandis, Tarun Chitra

Maximal Extractable Value (MEV) refers to excess value captured by miners (or validators) from users in a cryptocurrency network. This excess value often comes from reordering users' transactions to maximize fees or from inserting new transactions that front-run users' transactions. One of the most common types of MEV involves a `sandwich attack' against a u

Mafoya Landry Dassoundo

We define and derive basic properties of the notion of Rota-Baxter operator on anti-flexible algebra. Starting from a Rota-Baxter operator on an anti-flexible algebra, we construct pre-anti-flexible algebra structure and associated left(right)-symmetric algebra as well. The notion of O-operator on anti-flexible algebra is recalled and used to build left(righ

Víctor Valls, Shiqiang Wang, Yuang Jiang, Leandros Tassiulas

This paper presents a sufficient condition for stochastic gradients not to slow down the convergence of Nesterov's accelerated gradient method. The new condition has the strong-growth condition by Schmidt \& Roux as a special case, and it also allows us to (i) model problems with constraints and (ii) design new types of oracles (e.g., oracles for finite-sum

Greg Bodwin, Gary Hoppenworth

For an input graph $G$, an additive spanner is a sparse subgraph $H$ whose shortest paths match those of $G$ up to small additive error. We prove two new lower bounds in the area of additive spanners: 1) We construct $n$-node graphs $G$ for which any spanner on $O(n)$ edges must increase a pairwise distance by $+\Omega(n^{1/7})$. This improves on a recent lo

Binh Thanh Nguyen, Sergiu Ruta, Ondrej Hovorka, Richard. F. L. Evans

We employ an atomistic model using a nearest-neighbor Heisenberg Hamiltonian exchange to study computationally the dependence of the Curie temperature of L10-FePt on finite-size and surface effects in Heat-assisted Magnetic Recording (HAMR) media. We demonstrate the existence of a size threshold at 3.5nm below which the impact of finite-size effects start to

Geshuo Wang, Zhenning Cai

The small matrix path integral (SMatPI) method is an efficient numerical approach to simulate the evolution of a quantum system coupled to a harmonic bath. The method relies on a sequence of kernel matrices that defines the non-Markovian dynamics of the quantum system. In the original SMatPI method, these kernels are computed indirectly through the QuAPI met

Ruslan Prozorov, Mehdi Zarea, James A. Sauls

Niobium is one of the most researched superconductors, both theoretically and experimentally. It is enormously significant in all branches of superconducting applications, from powerful magnets to quantum computing. It is, therefore, imperative to understand its fundamental properties in great detail. Here we use the results of recent microscopic calculation

Connor Allen, Albert P. Bartók

Machine learning interatomic potentials (MLIPs) are routinely used atomic simulations, but generating databases of atomic configurations used in fitting these models is a laborious process, requiring significant computational and human effort. A computationally efficient method is presented to generate databases of atomic configurations that contain optimal

Rafael Garcia, Edgar Salazar, Eduardo Rozo, Susmita Adhikari

Dark matter haloes have long been recognized as one of the fundamental building blocks of large scale structure formation models. Despite their importance -- or perhaps because of it! -- halo definitions continue to evolve towards more physically motivated criteria. Here, we propose a new definition that is physically motivated, and effectively unique and pa

Thomas P. Fay, David T. Limmer

We describe a method for simulating exciton dynamics in protein-pigment complexes, including effects from charge transfer as well as fluorescence. The method combines the hierarchical equations of motion, which are used to describe quantum dynamics of excitons, and the Nakajima-Zwanzig quantum master equation, which is used to describe slower charge transfer

Matteo Bonvini, Edward H. Kennedy

We consider the problem of estimating a dose-response curve. Continuous treatments arise often in practice, e.g. in the form of time spent on an operation, distance traveled to a location or dosage of a drug. Letting $A$ denote a continuous treatment variable, the target of inference is the expected outcome if everyone in the population takes treatment level

Michael A. Bender, Seth Gilbert, Fabian Kuhn, John Kuszmaul

Randomized backoff protocols, such as exponential backoff, are a powerful tool for managing access to a shared resource, often a wireless communication channel (e.g., [1]). For a wireless device to transmit successfully, it uses a backoff protocol to ensure exclusive access to the channel. Modern radios, however, do not need exclusive access to the channel t

Tiger Lu, Gregory Laughlin

Uranus' startlingly large obliquity of 98 degrees has yet to admit a satisfactory explanation. The most widely accepted hypothesis involving a giant impactor that tipped Uranus onto its side encounters several difficulties with regards to the Uranus' spin rate and its prograde satellite system. An obliquity increase that was driven by capture of Uranus into

Sadaf Sarafan, Hoang Vuong, Daniel Jilani, Samir Malhotra

Monitoring of electrocardiogram (ECG) provides vital information as well as any cardiovascular anomalies. Recent advances in the technology of wearable electronics have enabled compact devices to acquire personal physiological signals in the home setting; however, signals are usually contaminated with high level noise. Thus, an efficient ECG filtering scheme

Dongning Ma, Xun Jiao

Hyperdimensional Computing (HDC) has obtained abundant attention as an emerging non von Neumann computing paradigm. Inspired by the way human brain functions, HDC leverages high dimensional patterns to perform learning tasks. Compared to neural networks, HDC has shown advantages such as energy efficiency and smaller model size, but sub-par learning capabilit