October 2020 arXiv papers — page 21

Jinfeng Zeng, Zipeng Wu, Chenfeng Cao, Chao Zhang

Variational quantum eigensolver (VQE) is promising to show quantum advantage on near-term noisy-intermediate-scale quantum (NISQ) computers. One central problem of VQE is the effect of noise, especially the physical noise on realistic quantum computers. We study systematically the effect of noise for the VQE algorithm, by performing numerical simulations wit

Yanhu Zhan, Emanuele Lago, Chiara Santillo, Antonio Esau Del Rio Castillo

Multifunctional polymer composites with anisotropic properties are attracting interests as they fulfil the growing demand of multitasking materials. In this work, anisotropic polymer composites are fabricated by combining the layer-by-layer (LBL) filtration method with the alternative assembling of carbon nanotubes (CNTs) and hexagonal boron nitride flakes (

Kai Han, Yunhe Wang, Qiulin Zhang, Wei Zhang

To obtain excellent deep neural architectures, a series of techniques are carefully designed in EfficientNets. The giant formula for simultaneously enlarging the resolution, depth and width provides us a Rubik's cube for neural networks. So that we can find networks with high efficiency and excellent performance by twisting the three dimensions. This paper a

Zengrun Wen, Kaile Wang, Baole Lu, Haowei Chen

Generally speaking, the self-sweeping effect relies on the dynamical grating formed in a gain fiber. Here, the normal self-sweeping was generated in a pump-free ytterbium-doped fiber which serves as a fiber saturable absorber and is introduced to the laser cavity by a circulator in this experiment. The sweeping rate and the sweeping range alter as usual, bot

Ben-Hao Sa, Dai-Mei Zhou, Yu-Liang Yan, Wen-Di Liu

In this work, we propose a method to show the correspondence between hadron and its quark component nuclear modification factors. A parton and hadron cascade model PACIAE based on the PYTHIA6.4 is employed to calculate the hadron and its quark component nuclear modification factors in the 0-5\% most central $Pb+Pb$ collisions at $\sqrt{s_{NN}}$=2.76 TeV. It

Jean Mercat

Following up on the linear transformer part of the article from Katharopoulos et al., that takes this idea from Shen et al., the trick that produces a linear complexity for the attention mechanism is re-used and extended to a second-order approximation of the softmax normalization.

Fei Ma, Ping Wang

As known, the commonly-utilized ways to determine mean first-passage time $\overline{\mathcal{F}}$ for random walk on networks are mainly based on Laplacian spectra. However, methods of this type can become prohibitively complicated and even fail to work when the Laplacian matrix of network under consideration is difficult to describe in the first place. In

Jan Dreier, Peter Rossmanith

Kuske and Schweikardt introduced the very expressive first-order counting logic FOC(P) to model database queries with counting operations. They showed that there is an efficient model-checking algorithm on graphs with bounded degree, while Grohe and Schweikardt showed that probably no such algorithm exists for trees of bounded depth. We analyze the fragment

Maxime W. Matthès, Yaron Bromberg, Julien de Rosny, Sébastien M. Popoff

Multimode optical fibers (MMFs) have gained renewed interest in the past decade, emerging as a way to boost optical communication data-rates in the context of an expected saturation of current single-mode fiber-based networks. They are also attractive for endoscopic applications, offering the possibility to achieve a similar information content as multicore

Steve Bryson, Michelle Kunimoto, Ravi K. Kopparapu, Jeffrey L. Coughlin

We present occurrence rates for rocky planets in the habitable zones (HZ) of main-sequence dwarf stars based on the Kepler DR25 planet candidate catalog and Gaia-based stellar properties. We provide the first analysis in terms of star-dependent instellation flux, which allows us to track HZ planets. We define $\eta_\oplus$ as the HZ occurrence of planets wit

Danilo Dessì, Francesco Osborne, Diego Reforgiato Recupero, Davide Buscaldi

The continuous growth of scientific literature brings innovations and, at the same time, raises new challenges. One of them is related to the fact that its analysis has become difficult due to the high volume of published papers for which manual effort for annotations and management is required. Novel technological infrastructures are needed to help research

Feng Li, Jin Wang, Jun Luo

While both outdoor and indoor localization methods are flourishing, how to properly marry them to offer pervasive localizability in urban areas remains open. Recently proposals on indoor-outdoor detection make the first step towards such an integration, yet complicated urban environments render such a binary classification incompetent. In this paper, we inte

Quan Kong, Wenpeng Wei, Ziwei Deng, Tomoaki Yoshinaga

We present Cycle-Contrastive Learning (CCL), a novel self-supervised method for learning video representation. Following a nature that there is a belong and inclusion relation of video and its frames, CCL is designed to find correspondences across frames and videos considering the contrastive representation in their domains respectively. It is different from

Xing Rong, Man Jiao, Maosen Guo, Diguang Wu

Searching for physics beyond the standard model is crucial for understanding the mystery of the universe, such as the dark matter. We utilized a single spin in a diamond as a sensor to explore the spin-dependent interactions mediated by the axion-like particles, which are well motivated by dark matter candidates. We recorded non-zero magnetic fields exerted

David Békollè, Jocelyn Gonessa, Benoît F. Sehba

Very recently, E. H. Lieb and J. P. Solovej stated a conjecture about the constant of embedding between two Bergman spaces of the upper-half plane. A question in relation with a Werhl-type entropy inequality for the affine $AX+B$ group. More precisely, that for any holomorphic function $F$ on the upper-half plane $\Pi^+$, $$\int_{\Pi^+}|F(x+iy)|^{2s}y^{2s-2}

Jun Ma, Yao Zhang, Song Gu, Cheng Zhu

With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved comparable results with inter-rater variability on many benchmark datasets. However, most of the existing abdominal datasets only contain single-center, single-phase, single-vendor

Jonathan Barés, Daniel Bonamy

We examine the effect of small, spatially localized, excitations applied periodically in different manners, on the crackling dynamics of a brittle crack driven slowly in a heterogeneous solid. When properly adjusted, these excitations are observed to radically modify avalanche statistics and considerably limit the magnitude of the largest events. Surprisingl

Liwei Wu, Xiao Pan, Zehui Lin, Yaoming Zhu

This paper describes our VolcTrans system on WMT20 shared news translation task. We participated in 8 translation directions. Our basic systems are based on Transformer, with several variants (wider or deeper Transformers, dynamic convolutions). The final system includes text pre-process, data selection, synthetic data generation, advanced model ensemble, an

Qiuqiang Kong, Keunwoo Choi, Yuxuan Wang

Music classification is a task to classify a music piece into labels such as genres or composers. We propose large-scale MIDI based composer classification systems using GiantMIDI-Piano, a transcription-based dataset. We propose to use piano rolls, onset rolls, and velocity rolls as input representations and use deep neural networks as classifiers. To our kn

Zhonghao Li, Benlai Tang, Xiang Yin, Yuan Wan

Singing voice conversion (SVC) aims to convert the voice of one singer to that of other singers while keeping the singing content and melody. On top of recent voice conversion works, we propose a novel model to steadily convert songs while keeping their naturalness and intonation. We build an end-to-end architecture, taking phonetic posteriorgrams (PPGs) as

Amir Weiss, Arie Yeredor

One-bit quantization has recently become an attractive option for data acquisition in cutting edge applications, due to the increasing demand for low power and higher sampling rates. Subsequently, the rejuvenated one-bit array processing field is now receiving more attention, as "classical" array processing techniques are adapted / modified accordingly. Howe

Zhitian Zhang, Jimin Rhim, Taher Ahmadi, Kefan Yang

This article describes a dataset collected in a set of experiments that involves human participants and a robot. The set of experiments was conducted in the computing science robotics lab in Simon Fraser University, Burnaby, BC, Canada, and its aim is to gather data containing common gestures, movements, and other behaviours that may indicate humans' navigat

Yuri Malykhin

In this paper we apply methods originated in Complexity theory to some problems of Approximation. We notice that the construction of Alman and Williams that disproves the rigidity of Walsh-Hadamard matrices, provides good $\ell_p$-approximation for $p<2$. It follows that the first $n$ functions of Walsh system can be approximated with an error $n^{-\delta}$

Lazhar Bougoffa, Smail Bougouffa

In this paper, we propose a reliable treatment for studying the two-wave (symbiotic) solitons of interactions in nonlinear quadratic media. We investigate Schauder's fixed point theorem for proving the existence theorem. Additionally, the uniqueness solution for this system is proved. Also, a highly accurate approximate solution is presented via an iteration

Amir Weiss, Arie Yeredor

Blind calibration of sensors arrays (without using calibration signals) is an important, yet challenging problem in array processing. While many methods have been proposed for "classical" array structures, such as uniform linear arrays, not as many are found in the context of the more "modern" sparse arrays. In this paper, we present a novel blind calibratio

Shuai Zhang, Jiangyan Yi, Zhengkun Tian, Ye Bai

Despite the recent significant advances witnessed in end-to-end (E2E) ASR system for code-switching, hunger for audio-text paired data limits the further improvement of the models' performance. In this paper, we propose a decoupled transformer model to use monolingual paired data and unpaired text data to alleviate the problem of code-switching data shortage

Saksham Sharma, D. Ian Wilson

We present a fully analytical solution for the natural oscillation of an inviscid sessile drop of arbitrary contact angle on a horizontal plate for the case for the case of low Bond number, when surface tension dominates gravity. The governing equations are expressed in terms of the toroidal coordinate system which yields solutions involving hypergeometric f

Seok Hyung Lie, Seongjeon Choi, Hyunseok Jeong

We give an operational meaning to the min-entropy of a quantum state as a resource measure for various interconnected tasks. In particular, we show that the min-entropy without smoothing measures the amount of quantum information that can be hidden or encoded perfectly in the one-shot setting when the quantum state is used as a randomness/correlation source.

Seok Hyung Lie, Hyunseok Jeong

Randomness can help one to implement quantum maps that cannot be realized in a deterministic fashion. Recently, it was discovered that explicitly treating a randomness source as a quantum system could double the efficiency as a catalyst for some tasks. In this work, we first show that every quantum channel that can be implemented with a randomness source wit

Kun Zhou, Berrak Sisman, Rui Liu, Haizhou Li

Emotional voice conversion aims to transform emotional prosody in speech while preserving the linguistic content and speaker identity. Prior studies show that it is possible to disentangle emotional prosody using an encoder-decoder network conditioned on discrete representation, such as one-hot emotion labels. Such networks learn to remember a fixed set of e

Angira Sharma, Naeemullah Khan, Ganesh Sundaramoorthi, Philip Torr

In this paper we present a novel loss function, called class-agnostic segmentation (CAS) loss. With CAS loss the class descriptors are learned during training of the network. We don't require to define the label of a class a-priori, rather the CAS loss clusters regions with similar appearance together in a weakly-supervised manner. Furthermore, we show that

Arjun Anand, Buvanasri A K, Meenakshi R, Karthika S

This paper introduces the concept of Open Source Intelligence (OSINT) as an important application in intelligent profiling of individuals. With a variety of tools available, significant data shall be obtained on an individual as a consequence of analyzing his/her internet presence but all of this comes at the cost of low relevance. To increase the relevance

Zhengkun Tian, Jiangyan Yi, Ye Bai, Jianhua Tao

The RNN-Transducers and improved attention-based encoder-decoder models are widely applied to streaming speech recognition. Compared with these two end-to-end models, the CTC model is more efficient in training and inference. However, it cannot capture the linguistic dependencies between the output tokens. Inspired by the success of two-pass end-to-end model

Joachim König

We investigate unramified extensions of number fields with prescribed solvable Galois group and certain extra conditions. In particular, we are interested in the minimal degree of a number field $K$, Galois over $\mathbb{Q}$, such that $K$ possesses an unramified $G$-extension. We improve the best known bounds for the degree of such number fields $K$ for cer

Colin Klaus

In this work I show how a diffusion-advection equation in three space-dimensions may have its advection term weakly limited to a velocity field localized to a moving curve. This is rigorously accomplished through the technique of concentrated capacity, and the form of the concentrated capacity limit along with small time existence of solutions is determined.

Jin-Peng Li, Xuemei Gu, Jian Qin, Dian Wu

Heralded entangling quantum gates are an essential element for the implementation of large-scale optical quantum computation. Yet, the experimental demonstration of genuine heralded entangling gates with free-flying output photons in linear optical system, was hindered by the intrinsically probabilistic source and double-pair emission in parametric down-conv

Daniel Yaron, Daphna Keidar, Elisha Goldstein, Yair Shachar

Early detection of COVID-19 is key in containing the pandemic. Disease detection and evaluation based on imaging is fast and cheap and therefore plays an important role in COVID-19 handling. COVID-19 is easier to detect in chest CT, however, it is expensive, non-portable, and difficult to disinfect, making it unfit as a point-of-care (POC) modality. On the o

Di Xiao, Zi-Gao Dai

Very recently a fast radio burst (FRB) 200428 associated with a strong X-ray burst from the Galactic magnetar SGR 1935+2154 has been detected, which is direct evidence supporting the magnetar progenitor models of FRBs. Assuming the FRB radiation mechanism is synchrotron maser emission from magnetized shocks, we develop a specific scenario by introducing a de

Ritesh Patel, Vaibhav Pant, Priyanka Iyer, Dipankar Banerjee

Solar eruptions such as Coronal Mass Ejections (CMEs) observed in the inner solar corona (up to 4 R$_{\odot}$) show acceleration profiles which appear as parabolic ridges in height-time plots. Inspired by the white-light automated detection algorithms, Computer Aided CME Tracking System (CACTus) and Solar Eruptive Events Detection System (SEEDS), we employ t

Nathan Dahlin, Krishna Chaitanya Kalagarla, Nikhil Naik, Rahul Jain

In an ever expanding set of research and application areas, deep neural networks (DNNs) set the bar for algorithm performance. However, depending upon additional constraints such as processing power and execution time limits, or requirements such as verifiable safety guarantees, it may not be feasible to actually use such high-performing DNNs in practice. Ma

Qingli Man, Yuanhao Zhuo

In order to improve the accuracy performance of Chinese text classification models with low hardware requirements, an improved concatenation-based model is designed in this paper, which is a concatenation of 5 different sub-models, including TextCNN, LSTM, and Bi-LSTM. Compared with the existing ensemble learning method, for a text classification mission, th

Minsu Kim, Sungho Lee, Chanwon Park, Jemin Lee

Age of information (AoI) is a recently proposed metric for quantifying data freshness in real-time status monitoring systems where timeliness is of importance. In this paper, we explore the data freshness in the Hyperledger Fabric Blockchain-enabled monitoring network (HeMN) by leveraging the AoI metric. In HeMN, status updates from sources are transmitted t

Xin Ding, Qiong Zhang, William J. Welch

Modern methods often formulate the counting of cells from microscopic images as a regression problem and more or less rely on expensive, manually annotated training images (e.g., dot annotations indicating the centroids of cells or segmentation masks identifying the contours of cells). This work proposes a supervised learning framework based on classificatio

Elif Haytaoglu, Erdi Kaya, Suayb S. Arslan

The base station-mobile device communication traffic has dramatically increased recently due to mobile data, which in turn heavily overloaded the underlying infrastructure. To decrease Base Station (BS) interaction, intra-cell communication between local devices, known as Device-to-Device, is utilized for distributed data caching. Nevertheless, due to the co

Rui Xiong

In this article, the comodule structure of Chow rings of Flag manifolds $\operatorname{CH}(G/B)$ is described by Schubert cells. Its equivariant version gives rise to a Hopf structure of the equivariant cohomology of flag manifolds $H^*_B(G/B)$. We get two identities of generalized Schubert polynomials as explanations of the geometric facts.

Elyes Balti, Brian K. Johnson

In this work, we consider the performance analysis of the uplink cellular networks with free space optics (FSO) backhauling. The user equipment (UE) communicates with the nearest Base Station (BS) in first slot while in second slot, the BS converts the received radio frequency (RF) signal into FSO pulse and transmits to the data center. We adopt the Rayleigh

Yongan Zhang, Yonggan Fu, Weiwen Jiang, Chaojian Li

Powerful yet complex deep neural networks (DNNs) have fueled a booming demand for efficient DNN solutions to bring DNN-powered intelligence into numerous applications. Jointly optimizing the networks and their accelerators are promising in providing optimal performance. However, the great potential of such solutions have yet to be unleashed due to the challe

Itsaso Arrayago, Kim J. R. Rasmussen, Esther Real

Traditional member-based two-step design approaches included in current structural codes for steel structures, as well as more recent system-based direct-design alternatives, require building rigorous structural reliability frameworks for the calibration of partial coefficients (resistance factors) to achieve specified target reliability requirements. Key de

Shihao Ru, Yunlong Wang, Min An, Feiran Wang

Quantum controlled-logic gates, including controlled NOT gate and Toffoli gate, play critical roles in lots of quantum information processing schemes. We design and experimentally demonstrate deterministic Toffoli gate by utilizing orbital-angular-momentum and polarization degrees of freedom of a single photon. In addition, we generate Bell states by using t

Xavier Dahan

Let T(x) in k[x] be a monic non-constant polynomial and write R=k[x] / (T) the quotient ring. Consider two bivariate polynomials a(x, y), b(x, y) in R[y]. In a first part, T = p^e is assumed to be the power of an irreducible polynomial p. A new algorithm that computes a minimal lexicographic Groebner basis of the ideal ( a, b, p^e), is introduced. A second p

Md Osman Gani, Shravan Kethireddy, Marvi Bikak, Paul Griffin

Recent advances in causal inference techniques, more specifically, in the theory of structural causal models, provide the framework for identification of causal effects from observational data in the cases where the causal graph is identifiable, i.e., the data generating mechanism can be recovered from the joint distribution. However, no such studies have be

Jianming Huang, Hiroyuki Kasai

For graph classification tasks, many traditional kernel methods focus on measuring the similarity between graphs. These methods have achieved great success on resolving graph isomorphism problems. However, in some classification problems, the graph class depends on not only the topological similarity of the whole graph, but also constituent subgraph patterns

Naoki Sato

In ideal fluids, Clebsch potentials occur as paired canonical variables associated with the Hamiltonian description of the Euler equations. This paper explores the properties of the incompressible Navier-Stokes equations when the velocity field is expressed through a complete set of paired Clebsch potentials. First, it is shown that the incompressible Navier

Andreas Dechant, Shin-ichi Sasa

We introduce a continuous time-reversal operation which connects the time-forward and time-reversed trajectories in the steady state of an irreversible Markovian dynamics via a continuous family of stochastic dynamics. This continuous time-reversal allows us to derive a tighter version of the thermodynamic uncertainty relation (TUR) involving observables eva

Jiwen Zeng, Jiping Zhang

The aim of this paper is to apply character properties of Frobenius group to a local block form of an group algebra. We start by establishing a block form of Brauer permutation Lemma by using block participation of conjugate classes of a group $G$. Then we can define a pair of Frobenius corresponding blocks between a group $G$ and its normal subgroup $N$. A

Jinho Choi, Jihong Park, Shiva Pokhrel

Improving the data rate of machine-type communication (MTC) is essential in supporting emerging Internet of things (IoT) applications ranging from real-time surveillance to edge machine learning. To this end, in this paper we propose a resource allocation approach for uplink transmissions within a random access procedure in MTC by exploiting multichannel sel

Weinan Lin

We make a conjecture about the whole $E_2$ page of the May spectral sequence in terms of generators and relations and we prove it in a subalgebra which covers a large range of dimensions. We show that the $E_2$ page plays a universal role in the study of Massey products in commutative DGAs. We conjecture that the $E_2$ page is nilpotent free and also prove i

Adway Kumar Das, Anandamohan Ghosh

We introduce a two-parameter ensemble of generalized $2\times 2$ real symmetric random matrices called the $\beta$-Rosenzweig-Porter ensemble (\brpe), parameterized by $\beta$, a fictitious inverse temperature of the analogous Coulomb gas model, and $\gamma$, controlling the relative strength of disorder. \brpe\ encompasses RPE from all of the Dyson's threef

Mandy Xie, Karl Van Wyk, Anqi Li, Muhammad Asif Rana

This paper describes the pragmatic design and construction of geometric fabrics for shaping a robot's task-independent nominal behavior, capturing behavioral components such as obstacle avoidance, joint limit avoidance, redundancy resolution, global navigation heuristics, etc. Geometric fabrics constitute the most concrete incarnation of a new mathematical f

Cameron C. Hopkins, Simon J. Haward, Amy Q. Shen

Viscoelastic flows through microscale porous arrays exhibit complex path-selection and switching phenomena. However, understanding this process is limited by a lack of studies linking between a single object and large arrays. Here, we report experiments on viscoelastic flow past side-by-side microcylinders with variable intercylinder gap. With increasing flo

Martin Hentschinski

In this contribution we briefly review some aspects of Lipatov's gauge invariant QCD high energy effective action. The high energy effective provides a field theory framework to systematically factorize QCD scattering amplitudes and related theories in the limit of high center of mass energies. After a short review of the underlying concepts, we address the

Nathan D. Ratliff, Karl Van Wyk, Mandy Xie, Anqi Li

A common approach to the provably stable design of reactive behavior, exemplified by operational space control, is to reduce the problem to the design of virtual classical mechanical systems (energy shaping). This framework is widely used, and through it we gain stability, but at the price of expressivity. This work presents a comprehensive theoretical frame

Donghyun Yu, Ruei-Hau Hsu, Jemin Lee

In-vehicle communications are not designed for message exchange between the vehicles and outside systems originally. Thus, the security design of message protection is insufficient. Moreover, the internal devices do not have enough resources to process the additional security operations. Nonetheless, due to the characteristic of the in-vehicle network in whi

Parth Shisode

Democrats and Republicans have seemed to grow apart in the past three decades. Since the United States as we know it today is undeniably bipartisan, this phenomenon would not appear as a surprise to most. However, there are triggers which can cause spikes in disagreements between Democrats and Republicans at a higher rate than how the two parties have been g

Amr Mahmoud, Youmna Ismaeil, Mohamed Zohdy

The introduction of unexpected system disturbances and new system dynamics does not allow guaranteed continuous system stability. In this research we present a novel approach for detecting early failure indicators of non-linear highly chaotic system and accordingly predict the best parameter calibrations to offset such instability using deep machine learning

Nathan D. Ratliff, Karl Van Wyk, Mandy Xie, Anqi Li

Robotics research has found numerous important applications of Riemannian geometry. Despite that, the concept remain challenging to many roboticists because the background material is complex and strikingly foreign. Beyond {\em Riemannian} geometry, there are many natural generalizations in the mathematical literature -- areas such as Finsler geometry and sp

Boyu Zhang, Anis Zaman, Rupam Acharyya, Ehsan Hoque

Depressive disorder is one of the most prevalent mental illnesses among the global population. However, traditional screening methods require exacting in-person interviews and may fail to provide immediate interventions. In this work, we leverage ubiquitous personal longitudinal Google Search and YouTube engagement logs to detect individuals with depressive

Zheshen Zhang, Quntao Zhuang

A plethora of applications hinge on a network or an array of sensors to undertake measurement tasks. A rule of thumb for sensing is that a collective measurement taken by $M$ independent sensors can improve the sensitivity by $1/\sqrt{M}$, known as the standard quantum limit (SQL). Quantum resources such as entanglement and squeezed light can be harnessed to

Sarah J. Morrison, Rebekah I. Dawson, Mariah G. MacDonald

Exoplanet systems with multiple planets in mean motion resonances have often been hailed as a signpost of disk driven migration. Resonant chains like Kepler-223 and Kepler-80 consist of a trio of planets with the three-body resonant angle librating and/or with a two-body resonant angle librating for each pair. Here we investigate whether close-in super-Earth

Hochul Hwang, Cheongjae Jang, Geonwoo Park, Junghyun Cho

To train deep learning models for vision-based action recognition of elders' daily activities, we need large-scale activity datasets acquired under various daily living environments and conditions. However, most public datasets used in human action recognition either differ from or have limited coverage of elders' activities in many aspects, making it challe

Xiao-Li Huang, En-Wei Liang

High energy photon radiations of gamma-ray bursts (GRBs) and active galactic nuclei (AGNs) are dominated by their jet radiations. We examine wether the synchrotron radiations of jets in BL Lacs, flat spectrum radio quasars (FSRQs), and Narrow Line Seyfert 1 galaxies (NLS1s) follow the relation between the prompt gamma-ray emission and the initial Lorentz fac

C. S. Kubrusly, B. P. Duggal

Every new inner product in a Hilbert space is obtained from the original one by means of a unique positive operator$.$ The first part of the paper is a survey on applications of such a technique, including a characterization of similarity to isometries$.$ The second part focuses on Banach limits for dealing with power bounded operators. It is shown that if a

Hongqin Liu

The well-known Maxwell construction[1] (the equal-area rule, EAR) was devised for vapor liquid equilibrium (VLE) calculation with the van der Waals (vdW) equation of state (EoS)[2]. The EAR generates an intermediate volume between the saturated liquid and vapor volumes. The trajectory of the intermediate volume over the coexistence region is defined here as

Dongsu Bak, Jae-Weon Lee, Sangnam Park

We numerically study the movement of two colliding fuzzy dark matter solitons without explicit self-interaction and find the effective cross section of dissipative change in velocity. The cross section turns out to be inversely proportional to the velocity cubed, and we present its analytic interpretation. Using the result we roughly estimate spatial offsets

Zongnan Li, Zhiyuan Li, Matthew W. L. Smith, Yu Gao

The circumnuclear region of M31, consisting of multiphase interstellar medium, provides a close-up view of the interaction of the central supermassive black hole and surrounding materials. Far-infrared (FIR) line structure lines and their flux ratios can be used as diagnostics of physical properties of the neutral gas in this region. Here we present the firs

Norihiro Hanihara

We give a structure theorem for Calabi-Yau triangulated category with a hereditary cluster tilting object. We prove that an algebraic $d$-Calabi-Yau triangulated category with a $d$-cluster tilting object $T$ such that its shifted sum $T\oplus\cdots\oplus T[-(d-2)]$ has hereditary endomorphism algebra $H$ is triangle equivalent to the orbit category $\mathsc

F. Rezazadeh, A. Mani

We investigate the problem of communicating three parameters in the absence of shared reference frame. We explore two methods in which the relative angles of spins are used to encode the parameters. In the first method we use three spins that carry the information in their relative angles while in the second method we use three disjoint spin-pairs and the in

Derek Beaton

The generalized singular value decomposition (GSVD, a.k.a. "SVD triplet", "duality diagram" approach) provides a unified strategy and basis to perform nearly all of the most common multivariate analyses (e.g., principal components, correspondence analysis, multidimensional scaling, canonical correlation, partial least squares). Though the GSVD is ubiquitous,

Victor Emeli, Akansel Cosgun

This paper explores the Navigation Among Movable Obstacles (NAMO) problem and proposes joint path and push planning: which path to take and in what direction the obstacles should be pushed at, given a start and goal position. We present a planning algorithm for selecting a path and the obstacles to be pushed, where a Rapidly-exploring Random Tree (RRT)-based

Renjie Wang, Wen-Hong Ruan, Qing Yang, Zong-Kuan Guo

The Hubble parameter is one of the central parameters in modern cosmology, which describes the present expansion rate of the universe. Their values inferred from the late-time observations are systematically higher than those from the early-time measurements by about $10\%$. To come to a robust conclusion, independent probes with accuracy at percent levels a

Ayaan Haque, Abdullah-Al-Zubaer Imran, Adam Wang, Demetri Terzopoulos

Semi-supervised learning via learning from limited quantities of labeled data has been investigated as an alternative to supervised counterparts. Maximizing knowledge gains from copious unlabeled data benefit semi-supervised learning settings. Moreover, learning multiple tasks within the same model further improves model generalizability. We propose a novel

Xiaoyu Kou, Yankai Lin, Yuntao Li, Jiahao Xu

Knowledge graph embedding (KGE), aiming to embed entities and relations into low-dimensional vectors, has attracted wide attention recently. However, the existing research is mainly based on the black-box neural models, which makes it difficult to interpret the learned representation. In this paper, we introduce DisenE, an end-to-end framework to learn disen

Jia Wang, Xia-Ji Liu, Hui Hu

We theoretically investigate the finite-temperature structure and collective excitations of a self-bound ultradilute Bose droplet in a flat space realized in a binary Bose mixture with attractive inter-species interactions on the verge of mean-field collapse. As the droplet formation relies critically on the repulsive force provided by Lee-Huang-Yang quantum

German Malfatti

This thesis work focuses on studying the possible existence of phase transitions in the immediate compact remnants of core collapse supernova, neutron stars, and the theoretical models that describe the interior of dense matter. Specifically, we are interested in analyzing the feasibility of a transition from hadronic matter to quark matter in the cores of t

Jing Xu, Changchun Zhong, Xu Han, Dafei Jin

Hybrid magnonics has recently attracted intensive attentions as a promising platform for coherent information processing. In spite of its rapid development, on-demand control over the interaction of magnons with other information carriers, in particular microwave photons in electromagnonic systems, has been long missing, significantly limiting the broad appl

Kairan Liu

In this paper, for any given polynomial, by analyzing the limiting behavior of ergodic averages along polynomials of several variables and prime numbers, we prove that for a topology dynamical system, positive entropy implies mean Li-Yoke chaos along non-constant polynomials of several variables and prime numbers.

Wei Yan, Yimin Zhang, Yongsheng Li, Jinqiao Duan

We consider the Cauchy problem for the rotation-modified Kadomtsev-Petviashvili (RMKP) equation \begin{align*} \partial_{x}\left(u_{t}-\beta\partial_{x}^{3}u +\partial_{x}(u^{2})\right)+\partial_{y}^{2}u-\gamma u=0 \end{align*} in the anisotropic Sobolev spaces $H^{s_{1},\>s_{2}}(\mathbb{R}^{2})$. When $\beta <0$ and $\gamma >0,$ we prove that the Cauchy pro

Gnana Praveen R, Eric Granger, Patrick Cardinal

Automatic estimation of pain intensity from facial expressions in videos has an immense potential in health care applications. However, domain adaptation (DA) is needed to alleviate the problem of domain shifts that typically occurs between video data captured in source and target do-mains. Given the laborious task of collecting and annotating videos, and th

Ruchao Fan, Wei Chu, Peng Chang, Jing Xiao

We propose a CTC alignment-based single step non-autoregressive transformer (CASS-NAT) for speech recognition. Specifically, the CTC alignment contains the information of (a) the number of tokens for decoder input, and (b) the time span of acoustics for each token. The information are used to extract acoustic representation for each token in parallel, referr

Jing-Cheng Liu, Ying Zhang, Zhi-Yong Wang, Ming-Liang Chen

For an expanding integer matrix $M\in M_2(\mathbb{Z})$ and an integer digit set $D=\{(0,0)^t,(\alpha_1,\alpha_2)^t,(\beta_1,\beta_2)^t\}$ with $\alpha_1\beta_2-\alpha_2\beta_1\neq0$, let $\mu_{M,D}$ be the Sierpinski-type self-affine measure defined by $\mu_{M,D}(\cdot)=\frac{1}{3}\sum_{d\in D}\mu_{M,D}(M(\cdot)-d)$. In [5.36], the authors separately investi

Jorge Nochebuena, Sehr Naseem-Khan, G. Andrés Cisneros

Quantum Mechanics/Molecular Mechanics (QM/MM) simulations are a popular approach to study various features of large systems. A common application of QM/MM calculations is in the investigation of reaction mechanisms in condensed-phase and biological systems. The combination of QM and MM methods to represent a system gives rise to several challenges that need

Norihisa Ikoma, Yasuhito Miyamoto

In this paper, we consider the following minimizing problem with two constraints: \[ \inf \left\{ E(u) | u=(u_1,u_2), \ \| u_1 \|_{L^2}^2 = \alpha_1, \ \| u_2 \|_{L^2}^2 = \alpha_2 \right\}, \] where $\alpha_1,\alpha_2 > 0$ and $E(u)$ is defined by \[ E(u) := \int_{\mathbf{R}^N} \left\{\frac{1}{2} \sum_{i=1}^2 \left( |\nabla u_1|^2 + V_i (x) |u_i|^2 \right)

Suprajo Das

The theory of mixed multiplicities of (not necessarily Noetherian) filtrations of $m_R$-primary ideals in a Noetherian local ring $R$, has been developed by Cutkosky, Sarkar and Srinivasan. The objective of this article is to generalise a Minkowski type inequality given in their paper. We also recover a result of Cutkosky, Srinivasan and Verma as a simple co

Songlin Yang, Yong Jiang, Wenjuan Han, Kewei Tu

Most of the unsupervised dependency parsers are based on first-order probabilistic generative models that only consider local parent-child information. Inspired by second-order supervised dependency parsing, we proposed a second-order extension of unsupervised neural dependency models that incorporate grandparent-child or sibling information. We also propose

Dou Dou, Dongmei Zheng, Xiaomin Zhou

Packing topological entropy is a dynamical analogy of the packing dimension, which can be viewed as a counterpart of Bowen topological entropy. In the present paper, we will give a systematically study to the packing topological entropy for a continuous $G$-action dynamical system $(X,G)$, where $X$ is a compact metric space and $G$ is a countable discrete a

Curtis Bechtel, Shaddin Dughmi

Delegation covers a broad class of problems in which a principal doesn't have the resources or expertise necessary to complete a task by themselves, so they delegate the task to an agent whose interests may not be aligned with their own. Stochastic probing describes problems in which we are tasked with maximizing expected utility by "probing" known distribut

Samuel H. C. Cabot, Rachael M. Roettenbacher, Gregory W. Henry, Lily Zhao

By controlling instrumental errors to below 10 cm/s, the EXtreme PREcision Spectrograph (EXPRES) allows for a more insightful study of photospheric velocities that can mask weak Keplerian signals. Gaussian Processes (GP) have become a standard tool for modeling correlated noise in radial velocity datasets. While GPs are constrained and motivated by physical

Min Yang, Norihiko Kamikubota, Yuto Tajima, Kenichi C. Sato

Since 2006, there have been unexpected trigger-failure events during the operation of the Japan Proton Accelerator Research Complex (J-PARC) timing system. However, among the many suspected modules, it has been difficult to find the one with the fault. To find such a faulty module more easily, the triggered scaler module, which was designed as a PLC-type I/O

Jinqi Shen, Stilian Stoev, Tailen Hsing

This paper studies the local structure of continuous random fields on $\mathbb R^d$ taking values in a complete separable linear metric space ${\mathbb V}$. Extending seminal work of Falconer, we show that the generalized $(1+k)$-th order increment tangent fields are self-similar and almost everywhere intrinsically stationary in the sense of Matheron. These

Yu Zhao, Chung-Kuei Lee

In this paper, we propose the differentiable channel sparsity search (DCSS) for convolutional neural networks. Unlike traditional channel pruning algorithms which require users to manually set prune ratios for each convolutional layer, DCSS automatically searches the optimal combination of sparsities. Inspired by the differentiable architecture search (DARTS