December 2020 arXiv papers — page 109

Marianne Gauffriau

The present review of bibliometric counting methods investigates 1) the number of unique counting methods in the bibliometric research literature, 2) to what extent the counting methods can be categorized according to selected characteristics of the counting methods, 3) methods and elements to assess the internal validity of the counting methods, and 4) to w

S. D. Liles, F. Martins, D. S. Miserev, A. A. Kiselev

Single holes confined in semiconductor quantum dots are a promising platform for spin qubit technology, due to the electrical tunability of the $g$-factor of holes. However, the underlying mechanisms that enable electric spin control remain unclear due to the complexity of hole spin states. Here, we study the underlying hole spin physics of the first hole in

Eneko Osaba, Esther Villar-Rodriguez, Izaskun Oregi, Aitor Moreno-Fernandez-de-Leceta

Quantum Computing is considered as the next frontier in computing, and it is attracting a lot of attention from the current scientific community. This kind of computation provides to researchers with a revolutionary paradigm for addressing complex optimization problems, offering a significant speed advantage and an efficient search ability. Anyway, Quantum C

Hédi Ben-Younes, Éloi Zablocki, Patrick Pérez, Matthieu Cord

In this era of active development of autonomous vehicles, it becomes crucial to provide driving systems with the capacity to explain their decisions. In this work, we focus on generating high-level driving explanations as the vehicle drives. We present BEEF, for BEhavior Explanation with Fusion, a deep architecture which explains the behavior of a trajectory

Manisha Luthra, Sebastian Hennig, Kamran Razavi, Lin Wang

Complex Event Processing (CEP) is a powerful paradigm for scalable data management that is employed in many real-world scenarios such as detecting credit card fraud in banks. The so-called complex events are expressed using a specification language that is typically implemented and executed on a specific runtime system. While the tight coupling of these two

Jaume Jaume Bestard, Jiří Štěpán, Javier Trujillo Bueno

Accurate angular quadratures are crucial for the numerical solution of three-dimensional (3D) radiative transfer problems, especially when the spectral line polarisation produced by the scattering of anisotropic radiation is included. There are two requirements for obtaining an optimal quadrature and they are difficult to satisfy simultaneously: high accurac

Michael Amir, Noa Agmon, Alfred M. Bruckstein

We study the collective motion of autonomous mobile agents on a ringlike environment. The agents' dynamics is inspired by known laboratory experiments on the dynamics of locust swarms. In these experiments, locusts placed at arbitrary locations and initial orientations on a ring-shaped arena are observed to eventually all march in the same direction. In this

Uiara Celine de Moura, Ann Margareth Rosa Brusin, Andrea Carena, Darko Zibar

A machine learning framework predicting pump powers and noise figure profile for a target distributed Raman amplifier gain profile is experimentally demonstrated. We employ a single-layer neural network to learn the mapping from the gain profiles to the pump powers and noise figures. The obtained results show highly-accurate gain profile designs and noise fi

David Huber, Ralf Kissmann, Anita Reimer, Olaf Reimer

Context. Gamma-ray binaries are systems that radiate the dominant part of their non-thermal emission in the gamma-ray band. In a wind-driven scenario, these binaries are thought to consist of a pulsar orbiting a massive star, accelerating particles in the shock arising in the wind collision. Aims. We develop a comprehensive, numerical model for the non-therm

Caner Mercan, Maschenka Balkenhol, Roberto Salgado, Mark Sherman

Nuclear pleomorphism, defined herein as the extent of abnormalities in the overall appearance of tumor nuclei, is one of the components of the three-tiered breast cancer grading. Given that nuclear pleomorphism reflects a continuous spectrum of variation, we trained a deep neural network on a large variety of tumor regions from the collective knowledge of se

W. de Paula, E. Ydrefors, J. H. Alvarenga Nogueira, T. Frederico

A dynamical model is applied to the study of the pion valence light-front wave function, obtained from the actual solution of the Bethe-Salpeter equation in Minkowski space, resorting to the Nakanishi integral representation. The kernel is simplified to a ladder approximation containing constituent quarks, an effective massive gluon exchange, and the scale o

Robin Chan, Matthias Rottmann, Hanno Gottschalk

Deep neural networks (DNNs) for the semantic segmentation of images are usually trained to operate on a predefined closed set of object classes. This is in contrast to the "open world" setting where DNNs are envisioned to be deployed to. From a functional safety point of view, the ability to detect so-called "out-of-distribution" (OoD) samples, i.e., objects

Arijit Manna, Sabyasachi Pal

In the Jovian atmosphere, the trace species are detected for the first time after the collision of comet Shoemaker-Levy 9 near 44$^\circ$S in July 1994. Most of these trace species are detected with spectroscopic millimeter/submillimeter observation. In the atmosphere of Jupiter, trace gases play an important role in atmospheric chemistry with heterogeneous

Luis A. La Rocca, Julia Frank, Heidi Beate Bentzen, Jean-Tori Pantel

Despite increasing data from population-wide sequencing studies, the risk for recessive disorders in consanguineous partnerships is still heavily debated. An important aspect that has not sufficiently been investigated theoretically, is the influence of inbreeding on mutation load and incidence rates when the population sizes change. We therefore developed a

Margarita Kovaleva, Leonid Manevitch

In our report we consider two weakly coupled Schr\"odinger equations as a model of the interchain energy transport in the DNA double-helix. We use the reduction of the Yakushevich-type model considering the torsional dynamics of the DNA. In the previous works only small amplitude excitations and stationary dynamics were investigated, while we focus on the no

el Houcein el Abdalaoui

We establish a generalization of Bourgain double recurrence theorem and ergodic Bourgain-Sarnak's theorem by proving that for any aperiodic $1$-bounded multiplicative function $\boldsymbol{\nu}$, for any map $T$ acting on a probability space $(X,\mathcal{A},\mu)$, for any integers $a,b$, for any $f,g \in L^2(X)$, and for almost all $x \in X$, we have \[\frac

Eric Knauss

Context: Software engineering researchers and practitioners rely on empirical evidence from the field. Thus, education of software engineers must include strong and applied education in empirical research methods. For most students, the master's thesis is the last, but also most applied form of this education in their studies. Problem: Especially thesis work

Asbjørn Engmark Espe, Thomas S. Haugan, Geir Mathisen

Magnetic field energy harvesting (MFEH) is a method by which a system can harness an ambient, alternating magnetic field in order to scavenge energy. Presented in this article is a novel application of the concept aimed at the magnetic fields surrounding the rail current in electrified railway. Due to its non-invasive nature, the approach has the potential t

Peter F. Faul, Graham Manuell, José Siqueira

Artin glueings of frames correspond to adjoint split extensions in the category of frames and finite-meet-preserving maps. We extend these ideas to the setting of toposes and show that Artin glueings of toposes correspond to a 2-categorical notion of adjoint split extensions in the 2-category of toposes, finite-limit-preserving functors and natural transform

Kaustav Chakraborty, Debajyoti Dutta, Srubabati Goswami, Dipyaman Pramanik

We study the physics potential of the long-baseline experiments T2HK, T2HKK and ESS$\nu$SB in the context of invisible neutrino decay. We consider normal mass ordering and assume that the state $\nu_{3}$ as unstable, decaying into sterile states during the flight and obtain constraints on the neutrino decay lifetime ($\tau_3$). We find that T2HK, T2HKK and E

Botond Szabo, Lasse Vuursteen, Harry van Zanten

In this paper we study the problem of signal detection in Gaussian noise in a distributed setting where the local machines in the star topology can communicate a single bit of information. We derive a lower bound on the Euclidian norm that the signal needs to have in order to be detectable. Moreover, we exhibit optimal distributed testing strategies that att

Marco Leonetti, Lorenzo Pattelli, Simone De Panfilis, Diederik S. Wiersma

Speckle is maybe the most fundamental interference effect of light in disordered media, giving rise to fascinating physical phenomena and enabling applications in imaging, spectroscopy or cryptography, to name a few. While speckle formed outside a sample is easily measured and analysed, true bulk speckle, as formed inside random media, is difficult to invest

Walter Tarantino, Carsten A. Ullrich

The Kohn-Sham approach to time-dependent density-functional theory (TDDFT) can be formulated, in principle exactly, by invoking the force-balance equation for the density, which leads to an explicit expression for the exchange-correlation potential as an implicit density functional. It is shown that this suggests a reformulation of TDDFT in terms of the seco

Thomas Gaudelet, Ben Day, Arian R. Jamasb, Jyothish Soman

Graph Machine Learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships between them, and integrate multi-omic datasets - amongst other data types. Herein, we present a multidisciplinary academic-industrial review of the topic within the c

Yuenan Li, Xin Tian, Qiang Zhu, Min Wu

This paper presents a computational solution that enables continuous cardiac monitoring through cross-modality inference of electrocardiogram (ECG). While some smartwatches now allow users to obtain a 30-second ECG test by tapping a built-in bio-sensor, these short-term ECG tests often miss intermittent and asymptomatic abnormalities of cardiac functions. It

Fakhar Zaman, Hyundong Shin, Moe Z. Win

Distributed computing is a fastest growing field -- enabling virtual computing, parallel computing, and distributed storage. By exploiting the counterfactual techniques, we devise a distributed blind quantum computation protocol to perform a universal two-qubit controlled unitary operation for any input state without using preshared entanglement and without

Martijn van der Klis, Jos Tellings

This paper reports on the state-of-the-art in application of multidimensional scaling (MDS) techniques to create semantic maps in linguistic research. MDS refers to a statistical technique that represents objects (lexical items, linguistic contexts, languages, etc.) as points in a space so that close similarity between the objects corresponds to close distan

Jagdev Singh, Muthu Priyal, B. Ravindra

In the earlier analysis of Ca-K spectroheliograms obtained at Kodaikanal Observatory, the "Good" images were used to investigate variations in the chromosphere. Still, the contrast of the images varied on a day-to-day basis. We developed a new methodology to generate images to form a uniform time series. We adjusted each image's contrast until the FWHM of th

Christian Bick, Tobias Böhle, Christian Kuehn

The classical Kuramoto model consists of finitely many pairwise coupled oscillators on the circle. In many applications a simple pairwise coupling is not sufficient to describe real-world phenomena as higher-order (or group) interactions take place. Hence, we replace the classical coupling law with a very general coupling function involving higher-order term

Ginés López-Pérez, Rubén Medina

We study Banach spaces with a weak stable unit ball, that is Banach spaces where every convex combination of relatively weakly open subsets in its unit ball is again a relatively weakly open subset in its unit ball. It is proved that the class of $L_1$ preduals with a weak stable unit ball agree with those $L_1$ preduals which are purely atomic, that is pred

D. P. Watts, J. Bordes, J. R. Brown, A. Cherlin

Positron Emission Tomography (PET) is a widely-used imaging modality for medical research and clinical diagnosis. Here we demonstrate, through detailed experiments and simulations, an exploration of the benefits of exploiting the quantum entanglement of linear polarisation between the two positron annihilation photons utilised in PET. A new simulation, which

Ilane Schroetter, Nicolas F. Bouché, Johannes Zabl, Hadi Rahmani

Using the MEGAFLOW survey, which consists of a combination of MUSE and UVES observations of 22 quasar fields selected to contain strong MgII absorbers, we measure covering fractions of CIV and MgII as a function of impact parameter $b$ using a novel Bayesian logistic regression method on unbinned data, appropriate for small samples. We also analyse how the C

G. G. L. Nashed, S. Nojiri

Recent observation shows that general relativity (GR) is not valid in the strong regime. $\mathit{f(R)}$ gravity where $\mathit{R}$ is the Ricci scalar, is regarded to be one of good candidates able to cure the anomalies appeared in the conventional general relativity. In this realm, we apply the equation of motions of $\mathit{f(R)}$ gravity to a sphericall

Zhiwei Jia, Bodi Yuan, Kangkang Wang, Hong Wu

Many applications of unpaired image-to-image translation require the input contents to be preserved semantically during translations. Unaware of the inherently unmatched semantics distributions between source and target domains, existing distribution matching methods (i.e., GAN-based) can give undesired solutions. In particular, although producing visually r

Abuduwaili. Abudukelimu, Tursunay. Yibibulla, Muhammad Ikram, Ziyan Zhang

Circular dichroism (CD) is absorption difference of right-hand and left-hand circularly polarized light by components. CD spectroscopy technique is an important tool for detecting molecular chirality, but the molecular circular dichroism (MCD) is weak and always appears in the ultraviolet (UV) region that is more noisy than visual range (VR). Induced circula

Pramod Padmanabhan, Jintae Kim, Jung Hoon Han

It is commonly believed that models defined on a closed one-dimensional manifold cannot give rise to topological order. Here we construct frustration-free Hamiltonians which possess both symmetry protected topological order (SPT) on the open chain {\it and} multiple ground state degeneracy (GSD) that is unrelated to global symmetry breaking on the closed cha

B. Hernandez, P. Sarriguren, O. Moreno, E. Moya de Guerra

Backward elastic electron scattering from odd-A nuclear targets is characterized by magnetic form factors containing precise information on the nuclear structure. We study the sensitivity of the magnetic form factors to structural effects related to the evolution and shape transitions in both isotopic and isotonic chains. Calculations of magnetic form factor

Jun Wan, Zhihui Lai, Jing Li, Jie Zhou

Recently, heatmap regression has been widely explored in facial landmark detection and obtained remarkable performance. However, most of the existing heatmap regression-based facial landmark detection methods neglect to explore the high-order feature correlations, which is very important to learn more representative features and enhance shape constraints. Mo

M. N. Chernodub

We discuss the effects of rotation on confining properties of gauge theories focusing on compact electrodynamics in two spatial dimensions as an analytically tractable model. We show that at finite temperature, the rotation leads to a deconfining transition starting from a certain distance from the rotation axis. A uniformly rotating confining system possess

Menghan Xia, Yi Wang, Chu Han, Tien-Tsin Wong

As a generic modeling tool, Convolutional Neural Networks (CNNs) have been widely employed in image generation and translation tasks. However, when fed with a flat input, current CNN models may fail to generate vivid results due to the spatially shared convolution kernels. We call it the flatness degradation of CNNs. Unfortunately, such degradation is the gr

Wenzhe Liu, Wei Liu, Lei Shi, Yuri Kivshar

Polarization singularities of vectorial electromagnetic fields locate at the positions (such as points, lines, or surfaces) where properties of polarization ellipses are not defined. They are manifested as circular and linear polarization, for which respectively the semi-major axes and normal vectors of polarization ellipses become indefinite. First observed

George Georgescu, Leonard Kwuida, Claudia Mureşan

We investigate from an algebraic and topological point of view the minimal prime spectrum of a universal algebra, considering the prime congruences w.r.t. the term condition commutator. Then we use the topological structure of the minimal prime spectrum to study extensions of universal algebras that generalize certain types of ring extensions. Our results ho

Chengchao Shen, Xinchao Wang, Youtan Yin, Jie Song

Knowledge distillation has demonstrated encouraging performances in deep model compression. Most existing approaches, however, require massive labeled data to accomplish the knowledge transfer, making the model compression a cumbersome and costly process. In this paper, we investigate the practical few-shot knowledge distillation scenario, where we assume on

K. Szałowski, T. Balcerzak

The paper contains the discussion of the magnetocaloric and electrocaloric effect in a model dimer (pair cluster). The system of interest is modelled with a Hubbard Hamiltonian including the external electric and magnetic field. The thermodynamics of such pair is described exactly, on the grounds of the grand canonical ensemble, focusing on the half-filling

Jarah Evslin, Hengyuan Guo

At one loop, quantum kinks are described by a sum of quantum harmonic oscillator Hamiltonians, and the ground state is just the product of the oscillator ground states. Two-loop kink masses are only known in integrable and supersymmetric cases and two-loop states have never been found. We find the two-loop kink mass and explicitly construct the two-loop kink

Fabio Valerio Massoli, Fabrizio Falchi, Alperen Kantarci, Şeymanur Akti

Anomalies are ubiquitous in all scientific fields and can express an unexpected event due to incomplete knowledge about the data distribution or an unknown process that suddenly comes into play and distorts observations. Due to such events' rarity, to train deep learning models on the Anomaly Detection (AD) task, scientists only rely on "normal" data, i.e.,

Jean-Luc Lehners, Jerome Quintin

We study the quantum circuit complexity of cosmological perturbations in different models of the early universe. A natural measure for the complexity of cosmological perturbations is based on the symplectic group, allowing us to identify complexity with geodesics in the hyperbolic plane. We investigate the complexity of both the mode functions and the physic

Yuuki Aoike, Tatsuya Gima, Tesshu Hanaka, Masashi Kiyomi

A cactus is a connected graph that does not contain $K_4 - e$ as a minor. Given a graph $G = (V, E)$ and integer $k \ge 0$, Cactus Vertex Deletion (also known as Diamond Hitting Set) is the problem of deciding whether $G$ has a vertex set of size at most $k$ whose removal leaves a forest of cacti. The current best deterministic parameterized algorithm for th

Toshimitsu Takaesu

In this paper, we investigate the $\phi^4$ model with cutoffs. By introducing a spatial cutoff and a momentum cutoff, the total Hamiltonian is a self-adjoint operator on a boson Fock space. Under regularity conditions of the momentum cutoff, we obtain the first order expansion of a non-degenerate ground state energy of the total Hamiltonian.

Chaoqin Huang, Fei Ye, Peisen Zhao, Ya Zhang

This paper explores semi-supervised anomaly detection, a more practical setting for anomaly detection where a small additional set of labeled samples are provided. We propose a new KL-divergence based objective function for semi-supervised anomaly detection, and show that two factors: the mutual information between the data and latent representations, and th

Shigeaki Kuzuoka

The problem of guessing subject to distortion is considered, and the performance of randomized guessing strategies is investigated. A one-shot achievability bound on the guessing moment (i.e., moment of the number of required queries) is given. Applying this result to i.i.d.~sources, it is shown that randomized strategies can asymptotically attain the optima

Huili Yi, Junfeng Wang, Xinwen Shu, Giuseppina Fabbiano

We present Chandra imaging and spectral observations of Seyfert 2 galaxy NGC 4388. Three extended X-ray structures around the nucleus on kpc scale are well imaged, allowing an in-depth spatially resolved study. Both the extended hard continuum and the Fe K$\alpha$ line show similar morphology, consistent with a scenario where the ionizing emission from nucle

Francois Jamet, Cedric Weber, Swagata Acharya, Dimitar Pashov

Optimally doped YBCO (YBa$_{2}$Cu$_{3}$O$_{7}$) has a high critical temperature, at 92 K. It is largely believed that Cooper pairs form in YBCO and other cuprates because of spin fluctuations, the issue and the detailed mechanism is far from settled. In the present work, we employ a state-of-the-art \emph{ab initio} ability to compute both the low and high e

Yuchi Wu, Kemi Ding, Yuzhe Li, Ling Shi

In this paper, we consider optimal linear sensor fusion for obtaining a remote state estimate of a linear process based on the sensor data transmitted over lossy channels. There is no local observability guarantee for any of the sensors. It is assumed that the state of the linear process is collectively observable. We transform the problem of finding the opt

T. Noguchi, S. Mima, C. Otani

It is shown that there are a significant number of quasiparticles present in the superconductor even at the temperature far below the transition temperature and that those quasiparticles seriously contribute to the characteristics of superconducting thin-film resonators.

Takafumi Suzuki, Takuto Yamada, Sei-ichiro Suga

In this paper, we investigate the ground-state phase diagram of the $S=1/2$ Heisenberg-$\Gamma$ model on a honeycomb lattice by dimer series expansion and exact diagonalization. We focus on the effects of the anisotropy of the interactions; by tuning the coupling constants, the system changes between the isolated dimer and the spin-chain models. We find that

Chia-Yu Hsu, Yu-Sheng Wang, Jia-Mou Chen, Fu-Chen Huang

We utilized the all-copropagating scheme, which maintains the phase-match condition, in the spontaneous four-wave mixing (SFWM) process to generate biphotons from a hot atomic vapor. The scheme enables our biphotons not only to surpass those in the previous works of hot-atom SFWM, but also to compete with the biphotons that are generated by either the cold-a

A. M. Kordbacheh, A. M. Martin

The focusing of a rubidium Bose-Einstein condensate via an optical lattice potential is numerically investigated. The results are compared with a classical trajectory model which under-estimates the full width half maximum of the focused beam. Via the inclusion of the effects of interactions, in the Bose-Einstein condensate, into the classical trajectory mod

Dan Qiu, Hai-Jun Tian, Xi-Dong Wang, Jia-Lu Nie

We analyze 4\,050 wide binary star systems involving a white dwarf (WD) and usually a main sequence (MS) star, drawn from the large sample assembled by \citet[][hereafter, T20]{Tian_2020}. Using the modeling code BASE-9, we determine the system's ages, the WD progenitors' ZAMS masses, the extinction values ($A_V$), and the distance moduli. Discarding the cas

Nicolas Macris, Raffaele Marino

Non-linear partial differential Kolmogorov equations are successfully used to describe a wide range of time dependent phenomena, in natural sciences, engineering or even finance. For example, in physical systems, the Allen-Cahn equation describes pattern formation associated to phase transitions. In finance, instead, the Black-Scholes equation describes the

Kohei Kurahara, Hiroyuki Nakanishi, Yuki Kudoh

We analyzed the data of Stokes $I$, $Q$, and $U$ in C- and X-bands and investigated the large-scale magnetic field structure of NGC 3627. The polarization intensity and angle in each band were derived using Stokes $Q$ and $U$ maps. The rotation measure was calculated using the polarization-angle maps. Moreover, the magnetic field strength was calculated by a

Jing Liu, Jiaxiang Wang, Weikang Wang, Yuting Su

As moving objects always draw more attention of human eyes, the temporal motive information is always exploited complementarily with spatial information to detect salient objects in videos. Although efficient tools such as optical flow have been proposed to extract temporal motive information, it often encounters difficulties when used for saliency detection

Shanshan Wang, Cheng Li, Rongpin Wang, Zaiyi Liu

Automatic medical image segmentation plays a critical role in scientific research and medical care. Existing high-performance deep learning methods typically rely on large training datasets with high-quality manual annotations, which are difficult to obtain in many clinical applications. Here, we introduce Annotation-effIcient Deep lEarning (AIDE), an open-s

Sharareh Alipour, Ehsan Futuhi, Shayan Karimi

In this paper, we propose a distributed algorithm for the minimum dominating set problem. For some especial networks, we prove theoretically that the achieved answer by our proposed algorithm is a constant approximation factor of the exact answer. This problem arises naturally in social networks, for example in news spreading, avoiding rumor spreading and re

Yunlong Liang, Fandong Meng, Ying Zhang, Jinan Xu

The successful emotional conversation system depends on sufficient perception and appropriate expression of emotions. In a real-life conversation, humans firstly instinctively perceive emotions from multi-source information, including the emotion flow hidden in dialogue history, facial expressions, audio, and personalities of speakers. Then, they convey suit

Andrew Fowlie

We consider the Jeffreys-Lindley paradox from an objective Bayesian perspective by attempting to find priors representing complete indifference to sample size in the problem. This means that we ensure that the prior for the unknown mean and the prior predictive for the $t$-statistic are independent of the sample size. If successful, this would lead to Bayesi

Aninda Sinha, Ahmadullah Zahed

For 2-2 scattering in quantum field theories, the usual fixed $t$ dispersion relation exhibits only two-channel symmetry. This paper considers a crossing symmetric dispersion relation, reviving certain old ideas in the 1970s. Rather than the fixed $t$ dispersion relation, this needs a dispersion relation in a different variable $z$, which is related to the M

Kevin C. Zhou, Ruobing Qian, Al-Hafeez Dhalla, Sina Farsiu

We present a general theory of optical coherence tomography (OCT), which synthesizes the fundamental concepts and implementations of OCT under a common 3D k-space framework. At the heart of this analysis is the Fourier diffraction theorem, which relates the coherent interaction between a sample and plane wave to the Ewald sphere in the 3D k-space representat

Junyao Hou, Xiang Yin, Shaoyuan Li

Opacity is an important information-flow security property that characterizes the plausible deniability of a dynamic system for its "secret" against eavesdropping attacks. As an information-flow property, the underlying observation model is the key in the modeling and analysis of opacity. In this paper, we investigate the verification of current-state opacit

Jinzheng Cai, Youbao Tang, Ke Yan, Adam P. Harrison

Monitoring treatment response in longitudinal studies plays an important role in clinical practice. Accurately identifying lesions across serial imaging follow-up is the core to the monitoring procedure. Typically this incorporates both image and anatomical considerations. However, matching lesions manually is labor-intensive and time-consuming. In this work

J. Maurice Rojas

Suppose $A=\{a_1,\ldots,a_{n+2}\}\subset\mathbb{Z}^n$ has cardinality $n+2$, with all the coordinates of the $a_j$ having absolute value at most $d$, and the $a_j$ do not all lie in the same affine hyperplane. Suppose $F=(f_1,\ldots,f_n)$ is an $n\times n$ polynomial system with generic integer coefficients at most $H$ in absolute value, and $A$ the union of

Huan Qing, Jingli Wang

Community detection has been well studied recent years, but the more realistic case of mixed membership community detection remains a challenge. Here, we develop an efficient spectral algorithm Mixed-ISC based on applying more than K eigenvectors for clustering given K communities for estimating the community memberships under the degree-corrected mixed memb

Dena Firoozi

Mean field game (MFG) systems consisting of a major agent and a large number of minor agents were introduced in (Huang, 2010) in an LQG setup. The Nash certainty equivalence was used to obtain a Markovian closed-loop Nash equilibrium for the limiting system when the number of minor agents tends to infinity. In the past years several approaches to major--mino

Vee-Liem Saw, Luca Vismara, Lock Yue Chew

Urban mobility involves many interacting components: buses, cars, commuters, pedestrians, trains etc., making it a very complex system to study. Even a bus system responsible for delivering commuters from their origins to their destinations in a loop service already exhibits very complicated dynamics. Here, we investigate the dynamics of a simplified version

Qi Zhou, Haipeng Chen, Yitao Zheng, Zhen Wang

As one of the most powerful topic models, Latent Dirichlet Allocation (LDA) has been used in a vast range of tasks, including document understanding, information retrieval and peer-reviewer assignment. Despite its tremendous popularity, the security of LDA has rarely been studied. This poses severe risks to security-critical tasks such as sentiment analysis

Pengtao Xie, Xuefeng Du, Hao Ban

Humans, as the most powerful learners on the planet, have accumulated a lot of learning skills, such as learning through tests, interleaving learning, self-explanation, active recalling, to name a few. These learning skills and methodologies enable humans to learn new topics more effectively and efficiently. We are interested in investigating whether humans'

Meixia Lin, Defeng Sun, Kim-Chuan Toh

Shape-constrained convex regression problem deals with fitting a convex function to the observed data, where additional constraints are imposed, such as component-wise monotonicity and uniform Lipschitz continuity. This paper provides a unified framework for computing the least squares estimator of a multivariate shape-constrained convex regression function

Pedro Enrique Iturria Rivera, Shahram Mollahasani, Melike Erol-Kantarci

Starting from the Cloud Radio Access Network (C-RAN), continuing with the virtual Radio Access Network (vRAN) and most recently with Open RAN (O-RAN) initiative, Radio Access Network (RAN) architectures have significantly evolved in the past decade. In the last few years, the wireless industry has witnessed a strong trend towards disaggregated, virtualized a

Tetsuhiro S. Hatakeyama, Kunihiko Kaneko

In physics of living systems, a search for relationships of a few macroscopic variables that emerge from many microscopic elements is a central issue. We evolved gene regulatory networks so that the expression of target genes (partial system) is insensitive to environmental changes. Then, we found the expression levels of the remaining genes autonomously inc

Sina Alemohammad, Randall Balestriero, Zichao Wang, Richard Baraniuk

Kernels derived from deep neural networks (DNNs) in the infinite-width regime provide not only high performance in a range of machine learning tasks but also new theoretical insights into DNN training dynamics and generalization. In this paper, we extend the family of kernels associated with recurrent neural networks (RNNs), which were previously derived onl

Soumya Chatterjee, Pradeep Shenoy

In decision making tasks under uncertainty, humans display characteristic biases in seeking, integrating, and acting upon information relevant to the task. Here, we reexamine data from previous carefully designed experiments, collected at scale, that measured and catalogued these biases in aggregate form. We design deep learning models that replicate these b

Kewei Zhang

In this article we introduce a family of valuative invariants defined in terms of the $p$-th moment of the expected vanishing order. These invariants lie between $\alpha$ and $\delta$-invariants. They vary continuously in the big cone and semi-continuously in families. Most importantly, they can detect the K-stability of Fano varieties, which generalizes the

Tianyu Wang, Bo Lin, Baxi Chong, Julian Whitman

Snake robots composed of alternating single-axis pitch and yaw joints have many internal degrees of freedom, which make them capable of versatile three-dimensional locomotion. In motion planning process, snake robot motions are often designed kinematically by a chronological sequence of continuous backbone curves that capture desired macroscopic shapes of th

David Schwickert, Marco Ruberti, Přemys Kolorenč, Sergey Usenko

Quantum coherence between electronic states of a photoionized molecule and the resulting process of ultrafast electron-hole migration have been put forward as a possible quantum mechanism of charge-directed reactivity governing the photoionization-induced molecular decomposition. Attosecond experiments based on the indirect (fragment ion-based) characterizat

Kai-Min Chung, Yi Lee, Han-Hsuan Lin, Xiaodi Wu

In a recent breakthrough, Mahadev constructed a classical verification of quantum computation (CVQC) protocol for a classical client to delegate decision problems in BQP to an untrusted quantum prover under computational assumptions. In this work, we explore further the feasibility of CVQC with the more general sampling problems in BQP and with the desirable

Brendan P. Bowler, William D. Cochran, Michael Endl, Kyle Franson

We present the discovery of a white dwarf companion to the G1 V star 12 Psc found as part of a Keck adaptive optics imaging survey of long-term accelerating stars from the McDonald Observatory Planet Search Program. Twenty years of precise radial-velocity monitoring of 12 Psc with the Tull Spectrograph at the Harlan J. Smith telescope reveals a moderate radi

Erhan Bayraktar, Alekos Cecchin, Asaf Cohen, François Delarue

Forcing finite state mean field games by a relevant form of common noise is a subtle issue, which has been addressed only recently. Among others, one possible way is to subject the simplex valued dynamics of an equilibrium by a so-called Wright-Fisher noise, very much in the spirit of stochastic models in population genetics. A key feature is that such a ran

Shuhan Tan, Yujun Shen, Bolei Zhou

Generative Adversarial Networks (GANs) advance face synthesis through learning the underlying distribution of observed data. Despite the high-quality generated faces, some minority groups can be rarely generated from the trained models due to a biased image generation process. To study the issue, we first conduct an empirical study on a pre-trained face synt

Rui Fan, Christopher Bowd, Nicole Brye, Mark Christopher

Convolutional neural networks (CNNs) are a promising technique for automated glaucoma diagnosis from images of the fundus, and these images are routinely acquired as part of an ophthalmic exam. Nevertheless, CNNs typically require a large amount of well-labeled data for training, which may not be available in many biomedical image classification applications

Pengxiang Wu, Songzhu Zheng, Mayank Goswami, Dimitris Metaxas

Noisy labels can impair the performance of deep neural networks. To tackle this problem, in this paper, we propose a new method for filtering label noise. Unlike most existing methods relying on the posterior probability of a noisy classifier, we focus on the much richer spatial behavior of data in the latent representational space. By leveraging the high-or

Aaron J. Mowitz

Geometric stress focusing, e.g. in a crumpled sheet, creates point-like vertices that terminate in a characteristic local crescent shape. The observed scaling of the size of this crescent is an open question in the stress focusing of elastic thin sheets. According to experiments and simulations, this size depends on the outer dimension of the sheet, but intu

Yang Xue, Fan Wang, Hao Tian, Min Zhao

Proactive human-robot interaction (HRI) allows the receptionist robots to actively greet people and offer services based on vision, which has been found to improve acceptability and customer satisfaction. Existing approaches are either based on multi-stage decision processes or based on end-to-end decision models. However, the rule-based approaches require s

Corwin Zigler, Vera Liu, Fabrizia Mealli, Laura Forastiere

Evaluating air quality interventions is confronted with the challenge of interference since interventions at a particular pollution source likely impact air quality and health at distant locations and air quality and health at any given location are likely impacted by interventions at many sources. The structure of interference in this context is dictated by

Xiaoqing Zhang, Yan Hu, Zunjie Xiao, Jiansheng Fang

Cataracts are the leading cause of visual impairment and blindness globally. Over the years, researchers have achieved significant progress in developing state-of-the-art machine learning techniques for automatic cataract classification and grading, aiming to prevent cataracts early and improve clinicians' diagnosis efficiency. This survey provides a compreh

Hassan Yazdani, Azadeh Vosoughi

We consider an opportunistic cognitive radio network, consisting of Nu secondary users (SUs) and an access point (AP), that can access a spectrum band licensed to a primary user. Each SU is capable of harvesting energy, and is equipped with a finite size battery, for energy storage. The SUs operate under a time-slotted scheme, where each time slot consists o

Cheng Cheng, Helen Zhou, Jeremy C. Weiss, Zachary C. Lipton

Since the COVID-19 pandemic first reached the United States, the case fatality rate has fallen precipitously. Several possible explanations have been floated, including greater detection of mild cases due to expanded testing, shifts in age distribution among the infected, lags between confirmed cases and reported deaths, improvements in treatment, mutations

Lu-Hao Su, Shu-Min Zhao, Xing-Xing Dong, Dan-Dan Cui

The MSSM is extended to the $U(1)_X$SSM, whose local gauge group is $SU(3)_C \times SU(2)_L \times U(1)_Y \times U(1)_X$. To obtain the $U(1)_X$SSM, we add the new superfields to the MSSM, namely: three Higgs singlets $\hat{\eta},~\hat{\bar{\eta}},~\hat{S}$ and right-handed neutrinos $\hat{\nu}_i$. It can give light neutrino tiny mass at the tree level throu

Marcus H. Wong, Peter Jordan, Igor A. Maia, André V. G. Cavalieri

We present a two-point model to investigate the underlying source mechanisms for broadband shock-associated noise (BBSAN) in shock-containing supersonic jets. In the model presented, the generation of BBSAN is assumed to arise from the non-linear interaction between downstream-propagating coherent structures with the quasi-periodic shock cells in the jet plu

Meng Ji, Yaping Mao

W. Mader [J. Graph Theory 65 (2010), 61--69] conjectured that for any tree $T$ of order $m$, every $k$-connected graph $G$ with $\delta(G)\geq\lfloor\frac{3k}{2}\rfloor+m-1$ contains a tree $T'\cong T$ such that $G-V(T')$ remains $k$-connected. In 2010, Mader confirmed the conjecture for the $k$-connected graph if $T$ is a path; very recently, Liu et al. con

N. U. Duronea, S. Cichowolski, L. Bronfman, E. Mendoza

With the aim of studying the properties of Galactic IR bubbles and their impact in massive star formation, we present a study of the IR bubble S169, associated with the massive star forming region IRAS12326-6245. We used CO(2-1),$^{13}$CO(2-1), C$^{18}$O(2-1), HCN(3-2), and HCO+(3-2) line data obtained with the APEX telescope to study the properties of the m