December 2020 arXiv papers — page 10

Pavel Exner, Takashi Ichinose

Given a nonnegative self-adjoint operator $H$ acting on a separable Hilbert space and an orthogonal projection $P$ such that $H_P := (H^{1/2}P)^*(H^{1/2}P)$ is densely defined, we prove that $\lim_{n\rightarrow \infty} (P\,\mathrm{e}^{-itH/n}P)^n = \mathrm{e}^{-itH_P}P$ holds in the strong operator topology. We also derive modifications of this product formu

G. A. Tsolias, Robert J. Decker, A. Demirkaya, T. J. Alexander

We consider the interaction of solitary waves in a model involving the well-known $\phi^4$ Klein-Gordon theory, but now bearing both Laplacian and biharmonic terms with different prefactors. As a result of the competition of the respective linear operators, we obtain three distinct cases as we vary the model parameters. In the first the biharmonic effect dom

Rakshitha Godahewa, Kasun Bandara, Geoffrey I. Webb, Slawek Smyl

With large quantities of data typically available nowadays, forecasting models that are trained across sets of time series, known as Global Forecasting Models (GFM), are regularly outperforming traditional univariate forecasting models that work on isolated series. As GFMs usually share the same set of parameters across all time series, they often have the p

Alexey Glazyrin

In this note, we give a short solution of the kissing number problem in dimension three.

Kai-Syun Jhan, Chin-Fei Lee

HH 211 is a highly collimated jet with a chain of knots and a wiggle structure on both sides of a young Class 0 protostar. We used two epochs of Atacama Large Millimeter/submillimeter Array (ALMA) data to study its inner jet in the CO(J=3-2), SiO(J=8-7), and SO(N_J=8_9-7_8) lines at $\sim$25 AU resolution. With these ALMA and previous 2008 Submillimeter Arra

Debarsho Sannyasi

We study weighted edge coloring of graphs, where we are given an undirected edge-weighted general multi-graph $G := (V, E)$ with weights $w : E \rightarrow [0, 1]$. The goal is to find a proper weighted coloring of the edges with as few colors as possible. An edge coloring is called a proper weighted coloring if the sum of the weights of the edges incident t

Hanan Aljubran, Maxim L. Yattselev

Let $ \{\varphi_i(z;\alpha)\}_{i=0}^\infty $, corresponding to $ \alpha\in(-1,1) $, be orthonormal Geronimus polynomials. We study asymptotic behavior of the expected number of real zeros, say $ \mathbb E_n(\alpha) $, of random polynomials \[ P_n(z) := \sum_{i=0}^n\eta_i\varphi_i(z;\alpha), \] where $ \eta_0,\dots,\eta_n $ are i.i.d. standard Gaussian random

Tasfia Shermin, Shyh Wei Teng, Ferdous Sohel, Manzur Murshed

Bidirectional mapping-based generalized zero-shot learning (GZSL) methods rely on the quality of synthesized features to recognize seen and unseen data. Therefore, learning a joint distribution of seen-unseen domains and preserving domain distinction is crucial for these methods. However, existing methods only learn the underlying distribution of seen data,

Saumyak Mukherjee, Sayantan Mondal, Biman Bagchi

Two factors that are often ignored but could play a crucial role in the progression of an infectious disease are the distributions of inherent susceptibility ($\sigma_{inh}$) and external infectivity ($\iota_{ext}$), in a given population. While the former is determined by the immunity of an individual towards a disease, the latter depends on the duration of

Zhangkai Ni, Wenhan Yang, Shiqi Wang, Lin Ma

In this work, we aim to learn an unpaired image enhancement model, which can enrich low-quality images with the characteristics of high-quality images provided by users. We propose a quality attention generative adversarial network (QAGAN) trained on unpaired data based on the bidirectional Generative Adversarial Network (GAN) embedded with a quality attenti

W. R. Arcus, J. -P. Macquart, M. W. Sammons, C. W. James

We compare the dispersion measure (DM) statistics of FRBs detected by the ASKAP and Parkes radio telescopes. We jointly model their DM distributions, exploiting the fact that the telescopes have different survey fluence limits but likely sample the same underlying population. After accounting for the effects of instrumental temporal and spectral resolution o

Gerardo Alvarez, Hai-Bo Yu

Self-interacting dark matter (SIDM) naturally gives rise to a cored isothermal density profile, which is favored in observations of many dwarf galaxies. The dark matter distribution in the presence of a central black hole in an isothermal halo develops a density spike with a power law of $r^{-7/4}$, which is shallower than $r^{-7/3}$ as expected for collisio

Rajeev Kumar Singh, Rohan Gorantla, Sai Giridhar Allada, Narra Pratap

Skin cancer is considered to be the most common human malignancy. Around 5 million new cases of skin cancer are recorded in the United States annually. Early identification and evaluation of skin lesions is of great clinical significance, but the disproportionate dermatologist-patient ratio poses significant problem in most developing nations. Therefore a de

Erik D. Kountz, Jiecheng Zhang, Joshua A. W. Straquadine, Anisha G. Singh

ErTe$_3$ is studied as a model system to explore thermal transport in a layered charge density wave (CDW) material. We present data from thermal diffusivity, resistivity, and specific heat measurements: There is a sharp decrease in thermal conductivity both parallel and perpendicular to the primary CDW at the CDW transition temperature. At the same time, the

Linfan Zhang, Arash A. Amini

We propose a goodness-of-fit test for degree-corrected stochastic block models (DCSBM). The test is based on an adjusted chi-square statistic for measuring equality of means among groups of $n$ multinomial distributions with $d_1,\dots,d_n$ observations. In the context of network models, the number of multinomials, $n$, grows much faster than the number of o

Nam Ho-Nguyen, Fatma Kılınç-Karzan

Prediction models are often employed in estimating parameters of optimization models. Despite the fact that in an end-to-end view, the real goal is to achieve good optimization performance, the prediction performance is measured on its own. While it is usually believed that good prediction performance in estimating the parameters will result in good subseque

Sheng Shen, Alexei Baevski, Ari S. Morcos, Kurt Keutzer

We demonstrate that transformers obtain impressive performance even when some of the layers are randomly initialized and never updated. Inspired by old and well-established ideas in machine learning, we explore a variety of non-linear "reservoir" layers interspersed with regular transformer layers, and show improvements in wall-clock compute time until conve

Chun-Fan Liu, Hsien Shang, Gregory J. Herczeg, Frederick M. Walter

Forbidden neon emission lines from small-scale microjets can probe high-energy processes in low-mass young stellar systems. We obtained spatially resolved [Ne III] spectra of the microjets from the classical T Tauri Star Sz 102 using the Hubble Space Telescope Imaging Spectrograph (HST/STIS) at a spatial resolution of ~0".1. The blueshifted and redshifted [N

Arabinda Bera, Soudamini Sahoo, Snigdha Thakur, Subir K. Das

We study dynamics of clustering in systems containing active particles that are immersed in an explicit solvent. For this purpose we have adopted a hybrid simulation method, consisting of molecular dynamics and multi-particle collision dynamics. In our model, overlap-avoiding passive interaction of an active particle with another active particle or a solvent

Song He, Zhenjie Li, Qinglin Yang, Chi Zhang

We study Feynman integrals and scattering amplitudes in ${\cal N}=4$ super-Yang-Mills by exploiting the duality with null polygonal Wilson loops. Certain Feynman integrals, including one-loop and two-loop chiral pentagons, are given by Feynman diagrams of a supersymmetric Wilson loop, where one can perform loop integrations and be left with simple integrals

Jaouhar Fattahi, Mohamed Mejri

Fingerprint recognition is often a game-changing step in establishing evidence against criminals. However, we are increasingly finding that criminals deliberately alter their fingerprints in a variety of ways to make it difficult for technicians and automatic sensors to recognize their fingerprints, making it tedious for investigators to establish strong evi

Mehwish Majeed, Adam Zaman Chaudhry

Repeated measurements in quantum mechanics can freeze (the quantum Zeno effect) or enhance (the quantum anti-Zeno effect) the time-evolution of a quantum system. In this paper, we present a general treatment of the quantum Zeno and anti-Zeno effects for arbitrary driven open quantum systems, assuming only that the system-environment coupling is weak. In part

Wen-Fei Wang

We study the resonance contributions for the kaon pair originating from the intermediate states $\rho(770,1450,1700)$ and $\omega(782,1420,1650)$ for the three-body hadronic decays $B\to K\bar K h$ in the perturbative QCD approach, where $h=(\pi, K)$. The branching fractions of the virtual contributions for $K\bar K$ from the Breit-Wigner formula tails of $\

Kenta Hashizume

We prove that the non-vanishing conjecture holds for generalized lc pairs with a polarization.

Jindong Han, Hao Liu, Hengshu Zhu, Hui Xiong

Accurate and timely air quality and weather predictions are of great importance to urban governance and human livelihood. Though many efforts have been made for air quality or weather prediction, most of them simply employ one another as feature input, which ignores the inner-connection between two predictive tasks. On the one hand, the accurate prediction o

Victor Luo, Yazhen Wang, Glenn Fung

With the rise of big data analytics, multi-layer neural networks have surfaced as one of the most powerful machine learning methods. However, their theoretical mathematical properties are still not fully understood. Training a neural network requires optimizing a non-convex objective function, typically done using stochastic gradient descent (SGD). In this p

Minkyu Shin, Jin Kim, Minkyung Kim

Across a growing number of domains, human experts are expected to learn from and adapt to AI with superior decision making abilities. But how can we quantify such human adaptation to AI? We develop a simple measure of human adaptation to AI and test its usefulness in two case studies. In Study 1, we analyze 1.3 million move decisions made by professional Go

Yichong Zhou

The optimal calculation order of a computational graph can be represented by a set of algebraic expressions. Computational graph and algebraic expression both have close relations and significant differences, this paper looks into these relations and differences, making plain their interconvertibility. By revealing different types of multiplication relations

Mayura Balakrishnan, J. M. Miller, M. T. Reynolds, E. Kammoun

GRS 1915$+$105 is a stellar-mass black hole that is well known for exhibiting at least 12 distinct classes of X-ray variability and correlated multi-wavelength behavior. Despite such extraordinary variability, GRS 1915$+$105 remained one of the brightest sources in the X-ray sky. However, in early 2019, the source became much fainter, apparently entering a n

Zhiyuan Chen, Isa Dino, Nik Ahmad Akram

This paper aims at improving the classification accuracy of a Support Vector Machine (SVM) classifier with Sequential Minimal Optimization (SMO) training algorithm in order to properly classify failure and normal instances from oil and gas equipment data. Recent applications of failure analysis have made use of the SVM technique without implementing SMO trai

Reza M. Ziazi, James A. Liburdy

Pore-scale observation of vortical flow structures in porous media is a significant challenge in many natural and industrial systems. Vortical structure dynamics is believed to be the driving mechanism in the transition regime in porous media based on the pore Reynolds number, $Re_p$. To examine this assertion, a refractive-index matched randomly packed poro

Chen ZhiYuan, Olugbenro. O. Selere, Nicholas Lu Chee Seng

This paper aims at improving the classification accuracy of a Support Vector Machine (SVM) classifier with Sequential Minimal Optimization (SMO) training algorithm in order to properly classify failure and normal instances from oil and gas equipment data. Recent applications of failure analysis have made use of the SVM technique without implementing SMO trai

Ha Q. Nguyen, Khanh Lam, Linh T. Le, Hieu H. Pham

Most of the existing chest X-ray datasets include labels from a list of findings without specifying their locations on the radiographs. This limits the development of machine learning algorithms for the detection and localization of chest abnormalities. In this work, we describe a dataset of more than 100,000 chest X-ray scans that were retrospectively colle

Takeo Noda, Shin-ichi Yasutomi

In non-Euclidean geometry, there are several known correspondings to Chapple-Euler Theorem. This remark shows that those results yield expressions corredponding to the well-known formula $d=\sqrt{R(R-2r)}$.

Shen Cheng, Yuzhi Wang, Haibin Huang, Donghao Liu

In this paper, we introduce NBNet, a novel framework for image denoising. Unlike previous works, we propose to tackle this challenging problem from a new perspective: noise reduction by image-adaptive projection. Specifically, we propose to train a network that can separate signal and noise by learning a set of reconstruction basis in the feature space. Subs

Yuqing Zhu

Distributed hash table (DHT) is the foundation of many widely used storage systems, for its prominent features of high scalability and load balancing. Recently, DHT-based systems have been deployed for the Internet-of-Things (IoT) application scenarios. Unfortunately, such systems can experience a breakdown in the scale-out and load rebalancing process. This

Le Dinh Van Khoa, Zhiyuan Chen

The pipelines transmission system is one of the growing aspects, which has existed for a long time in the energy industry. The cost of in-pipe exploration for maintaining service always draws lots of attention in this industry. Normally exploration methods (e.g. Magnetic flux leakage and eddy current) will establish the sensors stationary for each pipe miles

Francesco Caravelli, Bin Yan, Luis Pedro Garcia-Pintos, Alioscia Hamma

We study the role of coherence in closed and open quantum batteries. We obtain upper bounds to the work performed or energy exchanged by both closed and open quantum batteries in terms of coherence. Specifically, we show that the energy storage can be bounded by the Hilbert-Schmidt coherence of the density matrix in the spectral basis of the unitary operator

Wei Xiang Lim, Zhiyuan Chen, Amr Ahmed, Tissa Chandesa

Diabetes is a global epidemic and it is increasing at an alarming rate. The International Diabetes Federation (IDF) projected that the total number of people with diabetes globally may increase by 48%, from 425 million (year 2017) to 629 million (year 2045). Moreover, diabetes had caused millions of deaths and the number is increasing drastically. Therefore,

Chuxiong Sun, Jie Hu, Hongming Gu, Jinpeng Chen

Graph Neural Networks (GNNs) have received much attention in the graph deep learning domain. However, recent research empirically and theoretically shows that deep GNNs suffer from over-fitting and over-smoothing problems. The usual solutions either cannot solve extensive runtime of deep GNNs or restrict graph convolution in the same feature space. We propos

Priyankit Acharya, Aditya Ku. Pathak, Rakesh Ch. Balabantaray, Anil Ku. Singh

Language Identification is a very important part of several text processing pipelines. Extensive research has been done in this field. This paper proposes a procedure for automatic language identification of poems for poem analysis task, consisting of 10 Devanagari based languages of India i.e. Angika, Awadhi, Braj, Bhojpuri, Chhattisgarhi, Garhwali, Haryanv

Yujia Qin, Yankai Lin, Ryuichi Takanobu, Zhiyuan Liu

Pre-trained Language Models (PLMs) have shown superior performance on various downstream Natural Language Processing (NLP) tasks. However, conventional pre-training objectives do not explicitly model relational facts in text, which are crucial for textual understanding. To address this issue, we propose a novel contrastive learning framework ERICA to obtain

Ryan D. Hass, Aditya S. Ghate, Sanjiva K. Lele

With the continuing progress in large eddy simulations (LES), and ever increasing computational resources, it is currently possible to numerically solve the time-dependent and anisotropic large scales of turbulence in a large variety of flows. For some applications this large-scale resolution is satisfactory. However, a wide range of engineering problems inv

Zhangkai Ni, Wenhan Yang, Shiqi Wang, Lin Ma

Improving the aesthetic quality of images is challenging and eager for the public. To address this problem, most existing algorithms are based on supervised learning methods to learn an automatic photo enhancer for paired data, which consists of low-quality photos and corresponding expert-retouched versions. However, the style and characteristics of photos r

Chris Cundy, Rishi Desai, Stefano Ermon

As reinforcement learning techniques are increasingly applied to real-world decision problems, attention has turned to how these algorithms use potentially sensitive information. We consider the task of training a policy that maximizes reward while minimizing disclosure of certain sensitive state variables through the actions. We give examples of how this se

Ding Huang, Alex Abulnaga, Sacha Welinski, Mouktik Raha

Integrating atomic quantum memories based on color centers in diamond with on-chip photonic devices would enable entanglement distribution over long distances. However, efforts towards integration have been challenging because color centers can be highly sensitive to their environment, and their properties degrade in nanofabricated structures. Here, we descr

Kotaro Nishimura, Yuxi Fu, Akira Suda, Katsumi Midorikawa

In our recent study [Commun. Phys. 3, 92 (2020)], we have developed an approach for energy-scaling of high-order harmonic generation in water-window region under neutral-medium condition. More specifically, we obtained nanojoule-class water-window soft x-ray harmonic beam under phase match condition. It has been achieved by combining a newly developed terawa

Stephan Schmidt, Melanie Gräßer, Hans-Joachim Schmid

We present a second order numerical scheme to compute capillary bridges between arbitrary solids by minimizing the total energy of all interfaces. From a theoretical point of view, this approach can be interpreted as the computation of generalized minimal surfaces using a Newton-scheme utilizing the shape Hessian. In particular, we give an explicit represent

Yuxian Meng, Shuhe Wang, Qinghong Han, Xiaofei Sun

When humans converse, what a speaker will say next significantly depends on what he sees. Unfortunately, existing dialogue models generate dialogue utterances only based on preceding textual contexts, and visual contexts are rarely considered. This is due to a lack of a large-scale multi-module dialogue dataset with utterances paired with visual contexts. In

Garret Sobczyk

A nested coordinate system is a reassigning of independent variables to take advantage of geometric or symmetry properties of a particular application. Polar, cylindrical and spherical coordinate systems are primary examples of such a regrouping that have proved their importance in the separation of variables method for solving partial differential equations

Ruochuan Liu, Guozhen Wang

We introduce a new approach to determining the structure of topological cyclic homology by means of a descent spectral sequence. We carry out the computation for a p-adic local field with Fp-coefficients, including the case p=2 which was only covered by motivic methods except in the totally unramified case.

S. Chakraborty Thakur, M. Paul, E. M. Hollmann, E. Lister

Radio Frequency (RF) driven helicon plasma sources are commonly used for their ability to produce high-density argon plasmas (n > 10^19/m^3) at relatively moderate powers (typical RF power < 2 kW). Typical electron temperatures are < 10 eV and typical ion temperatures are < 0.6 eV. A newly designed helicon antenna assembly (with concentric, double-layered, f

Rakesh Kumar Pandey

Entropic analysis of a scenario at a traffic intersection is attempted in detail. The model is utilized to define Conflict Entropy. It is shown that with the use of strategies (policies) like installing traffic lights and construction of flyovers the Entropy is reduced thereby making the traffic ordered. It is shown that these policies help in reducing the E

Kohei Motegi, Travis Scrimshaw

We construct a vertex model whose partition function is a refined dual Grothendieck polynomial, where the states are interpreted as nonintersecting lattice paths. Using this, we show refined dual Grothendieck polynomials are multi-Schur functions and give a number of identities, including a Littlewood and Cauchy(-Littlewood) identity. We then refine Yeliussi

Haishan Ye, Wei Xiong, Tong Zhang

This paper considers the decentralized composite optimization problem. We propose a novel decentralized variance-reduction proximal-gradient algorithmic framework, called PMGT-VR, which is based on a combination of several techniques including multi-consensus, gradient tracking, and variance reduction. The proposed framework relies on an imitation of central

Yun Zhou, Prabhakar R. Bandaru, Daniel F. Sievenpiper

Confining sound is of significant importance for the manipulation and routing acoustic waves. We propose a Helmholtz resonator (HR) based subwavelength sound channel formed at the interface of two metamaterials, for this purpose. The confinement is quantified through (i) a substantial reduction of the pressure, and (ii) an increase in a specific acoustic imp

KwangYik Jung, YeEun Kim, HyunJun Lim, Hyun Myung

The amount of texture can be rich or deficient depending on the objects and the structures of the building. The conventional mono visual-initial navigation system (VINS)-based localization techniques perform well in environments where stable features are guaranteed. However, their performance is not assured in a changing indoor environment. As a solution to

Kevin He, Jonathan Libgober

Toward explaining the persistence of biased inferences, we propose a framework to evaluate competing (mis)specifications in strategic settings. Agents with heterogeneous (mis)specifications coexist and draw Bayesian inferences about their environment through repeated play. The relative stability of (mis)specifications depends on their adherents' equilibrium

Shimiao Li, Amritanshu Pandey, Bryan Hooi, Christos Faloutsos

Given sensor readings over time from a power grid, how can we accurately detect when an anomaly occurs? A key part of achieving this goal is to use the network of power grid sensors to quickly detect, in real-time, when any unusual events, whether natural faults or malicious, occur on the power grid. Existing bad-data detectors in the industry lack the sophi

Yadong Zhou, Zhihao Ding, Xiaoming Liu, Chao Shen

User attributes, such as gender and education, face severe incompleteness in social networks. In order to make this kind of valuable data usable for downstream tasks like user profiling and personalized recommendation, attribute inference aims to infer users' missing attribute labels based on observed data. Recently, variational autoencoder (VAE), an end-to-

Yuuki Sugiyama, Kazuhiro Yamamoto, Tsutomu Kobayashi

We derive the solutions of gravitational waves in the future (F) expanding and the past (P) shrinking Kanser spacetimes as well as in the left (L) and right (R) Rindler wedges in the Regge-Wheeler gauge. The solutions for all metric components are obtained in an analytic form in each region. We identify the master variables, which are equivalent to massless

Zhijie Huang, Xiaopeng Guo, Mingyu Shang, Jie Gao

In this paper, a novel QP variable convolutional neural network based in-loop filter is proposed for VVC intra coding. To avoid training and deploying multiple networks, we develop an efficient QP attention module (QPAM) which can capture compression noise levels for different QPs and emphasize meaningful features along channel dimension. Then we embed QPAM

Spencer Compton, Slobodan Mitrović, Ronitt Rubinfeld

Interval scheduling is a basic problem in the theory of algorithms and a classical task in combinatorial optimization. We develop a set of techniques for partitioning and grouping jobs based on their starting and ending times, that enable us to view an instance of interval scheduling on many jobs as a union of multiple interval scheduling instances, each con

Jianfei Xu

In this paper, we discuss the gravitational waves in the context of gauge theory gravity with a negative cosmological constant. The gauge theory gravity is a gravity theory under gauge formulation in the language of geometric algebra. In contrast to general relativity, the background spacetime in gauge theory gravity is flat, the gauge freedom comes from the

Michaël Defferrard, Martino Milani, Frédérick Gusset, Nathanaël Perraudin

Designing a convolution for a spherical neural network requires a delicate tradeoff between efficiency and rotation equivariance. DeepSphere, a method based on a graph representation of the sampled sphere, strikes a controllable balance between these two desiderata. This contribution is twofold. First, we study both theoretically and empirically how equivari

Jin Quan Zhou, Wen Jin He

The industrial life cycle theory has proved to be helpful for describing the evolution of industries from birth to maturity. This paper is to highlight the historical evolution stage of Atlantic City's gambling industry in a structural framework covered by industrial market, industrial organization, industrial policies and innovation. Data mining was employe

Xiaohu Yang, Haojie Xu, Min He, Yizhou Gu

We extend the halo-based group finder developed by \citet[][]{Yang2005a} to use data {\it simultaneously} with either photometric or spectroscopic redshifts. A mock galaxy redshift survey constructed from a high-resolution N-body simulation is used to evaluate the performance of this extended group finder. For galaxies with magnitude ${\rm z\le 21}$ and reds

Manushan Thenabadu, M. D. Reid

We consider tests of Leggett-Garg's macrorealism and of macroscopic local realism, where for spacelike separated measurements the assumption of macroscopic noninvasive measurability is justified by that of macroscopic locality. We give a mapping between the Bell and Leggett-Garg experiments for microscopic qubits based on spin $1/2$ eigenstates and gedanken

Taran Lynn, Dipak Ghosal

The choice of feedback mechanism between delay and packet loss has long been a point of contention in TCP congestion control. This has partly been resolved, as it has become increasingly evident that delay based methods are needed to facilitate modern interactive web applications. However, what has not been resolved is what control should be used, with the t

J. B. Habashi, S. Fleming, U. van Kolck

We discuss shallow resonances in the nonrelativistic scattering of two particles using an effective field theory (EFT) that includes an auxiliary field with the quantum numbers of the resonance. We construct the manifestly renormalized scattering amplitude up to next-to-leading order in a systematic expansion. For a narrow resonance, the amplitude is perturb

Takuma Aihara, Aaron Chan, Takahiro Honma

Motivated by the relation between Schur algebra and the group algebra of a symmetric group, along with other similar examples in algebraic Lie theory, Min Fang and Steffen Koenig addressed some behaviour of the endomorphism algebra of a generator over a symmetric algebra, which they called gendo-symmetric algebra. Continuing this line of works, we classify i

Robert G. Donnelly, Molly W. Dunkum, Murray L. Huber, Lee Knupp

We consider various properties and manifestations of some sign-alternating univariate polynomials borne of right-triangular integer arrays related to certain generalizations of the Fibonacci sequence. Using a theory of the root geometry of polynomial sequences developed by J. L. Gross, T. Mansour, T. W. Tucker, and D. G. L. Wang, we show that the roots of th

Ron Aharoni, Eli Berger, Maria Chudnovsky, Shira Zerbib

A conjecture of the first two authors is that $n$ matchings of size $n$ in any graph have a rainbow matching of size $n-1$. We prove a lower bound of $\frac{2}{3}n-1$, improving on the trivial $\frac{1}{2}n$, and an analogous result for hypergraphs. For $\{C_3,C_5\}$-free graphs and for disjoint matchings we obtain a lower bound of $\frac{3n}{4}-O(1)$. We al

Robert G. Donnelly, Molly W. Dunkum, Sasha V. Malone, Alexandra Nance

We present a family of rank symmetric diamond-colored distributive lattices that are naturally related to the Fibonacci sequence and certain of its generalizations. These lattices re-interpret and unify descriptions of some un- or differently-colored lattices found variously in the literature. We demonstrate that our symmetric Fibonaccian lattices naturally

Marcin Nowakowski

The equivalence principle, being one of the building blocks of general relativity, seems to be also crucial for analysis of quantum effects in gravity. In this paper we consider the question if the equivalence principle has to hold for consistency of performing quantum computation in gravitational field. We propose an analysis with a looped evolution consist

Li Zhong, Zhen Fang, Feng Liu, Jie Lu

Unsupervised domain adaptation (UDA) aims to train a target classifier with labeled samples from the source domain and unlabeled samples from the target domain. Classical UDA learning bounds show that target risk is upper bounded by three terms: source risk, distribution discrepancy, and combined risk. Based on the assumption that the combined risk is a smal

Huiquan Li, Jiancheng Wang

We show that energy should be dissipated or extracted in the current sheet (CS) of a split magnetosphere deviating from the Michel split monopole, with the CS heating up or cooling down. But the electromagnetic energy remains unchanged everywhere. Based on the de-centered monopole solution generated by symmetry in flat spacetime, we construct two generalized

Joseph Samuel

Einstein's genius and penetrating physical intuition led to the general theory of relativity, which incorporates gravity into the geometry of spacetime. However, the theory of general relativity leads to perspectives which go far beyond the vision of its creator. Many of these insights came to light only after Einstein's death in 1955. These developments wer

C. Yao, H. Mei, Y. Xiao, A. Shahsafi

We found that temperature-dependent infrared spectroscopy measurements (i.e., reflectance or transmittance) using a Fourier-transform spectrometer can have substantial errors, especially for elevated sample temperatures and collection using an objective lens (e.g., using an infrared microscope). These errors arise as a result of partial detector saturation d

Robert G. Donnelly, Molly W. Dunkum

We generalize the famous weight basis constructions of the finite-dimensional irreducible representations of $\mathfrak{sl}(n,\mathbb{C})$ obtained by Gelfand and Tsetlin in 1950. Using combinatorial methods, we construct one such basis for each finite-dimensional representation of $\mathfrak{sl}(n,\mathbb{C})$ associated to a given skew Schur function. Our

Yan Yan, Tiange Bi, Nisha Geng, Xiaoyu Wang

Evolutionary searches predicted a number of ternary phases that could be synthesized at pressures of 100-300~GPa. $P6_3/mmc$ CaSH$_2$, $Pnma$ CaSH$_2$, $Cmc2_1$ CaSH$_6$, and $I\bar{4}$ CaSH$_{20}$ were composed of a Ca-S lattice along with H$_2$ molecules coordinated in a ``side-on'' fashion to Ca. The H-H bond lengths in these semiconducting phases were el

Maryam Akbari-Moghaddam, Douglas G. Down

For a single server system, Shortest Remaining Processing Time (SRPT) is an optimal size-based policy. In this paper, we discuss scheduling a single-server system when exact information about the jobs' processing times is not available. When the SRPT policy uses estimated processing times, the underestimation of large jobs can significantly degrade performan

Manuel Hohmann

We present a package for the computer algebra system Mathematica, which implements the parametrized post-Newtonian (PPN) formalism. This package, named xPPN, is built upon the widely used tensor algebra package suite xAct, and in particular the package xTensor therein. The main feature of xPPN is to provide functions to perform a proper $3+1$ decomposition o

Sabrina J. Mielke, Arthur Szlam, Emily Dinan, Y-Lan Boureau

While improving neural dialogue agents' factual accuracy is the object of much research, another important aspect of communication, less studied in the setting of neural dialogue, is transparency about ignorance. In this work, we analyze to what extent state-of-the-art chit-chat models are linguistically calibrated in the sense that their verbalized expressi

Shaode Yu, Haobo Chen, Hang Yu, Zhicheng Zhang

Feature selection is important in data representation and intelligent diagnosis. Elastic net is one of the most widely used feature selectors. However, the features selected are dependant on the training data, and their weights dedicated for regularized regression are irrelevant to their importance if used for feature ranking, that degrades the model interpr

Satyabrata Datta, Ambar Ghosal, Rome Samanta

Ultralight primordial black holes (PBHs)($\lesssim10^9$g) completely evaporate via Hawking radiation (HR) and produce all the particles in a given theory regardless of their other interactions. If the right handed (RH) neutrinos are produced from PBH evaporation, successful baryogenesis via leptogenesis predicts mass scale of RH neutrinos as well as black ho

Elijah S. Lee, Daigo Shishika, Vijay Kumar

We study a variant of pursuit-evasion game in the context of perimeter defense. In this problem, the intruder aims to reach the base plane of a hemisphere without being captured by the defender, while the defender tries to capture the intruder. The perimeter-defense game was previously studied under the assumption that the defender moves on a circle. We exte

Stylianos D. Assimonis, M. Ali Babar Abbasi, Vincent F. Fusco

This paper summarizes an investigation around millimeter-wave (mmWave) multimode circular antenna array based beamformer capable of specially encoded data transmission in a wide coverage area. The circular antenna array is capable of an entire 360 deg. azimuth sector coverage where broadcast, uni-cast and multi-cast radio transmissions are possible. Orbital

Michael C. Brennan, Mark Embree, Serkan Gugercin

Contour integral methods for nonlinear eigenvalue problems seek to compute a subset of the spectrum in a bounded region of the complex plane. We briefly survey this class of algorithms, establishing a relationship to system realization techniques in control theory. This connection motivates a new general framework for contour integral methods (for linear and

Jiaxin Huang, Chunyuan Li, Krishan Subudhi, Damien Jose

This paper presents a comprehensive study to efficiently build named entity recognition (NER) systems when a small number of in-domain labeled data is available. Based upon recent Transformer-based self-supervised pre-trained language models (PLMs), we investigate three orthogonal schemes to improve the model generalization ability for few-shot settings: (1)

Jorge Lasave, Sergio Koval, Alessandro Laio, Erio Tosatti

Ordinary ice has a proton-disordered phase which is kinetically metastable, unable to reach, spontaneously, the ferroelectric (FE) ground state at low temperature where a residual Pauling entropy persists. Upon light doping with KOH at low temperature, the transition to FE ice takes place, but its microscopic mechanism still needs clarification. We introduce

Peter Eisenberger

A Renewable Energy and Materials Economy (REME) is proposed as the solution to the climate change threat. REME mimics nature to produce carbon neutral liquid fuels and chemicals as well as carbon negative materials by using water, CO$_2$ from the atmosphere and renewable energy as inputs. By being in harmony with nature REME has a positive feedback between e

Jianping Pan, Joseph Pappe, Wencin Poh, Anne Schilling

Whereas set-valued tableaux are the combinatorial objects associated to stable Grothendieck polynomials, hook-valued tableaux are associated to stable canonical Grothendieck polynomials. In this paper, we define a novel uncrowding algorithm for hook-valued tableaux. The algorithm "uncrowds" the entries in the arm of the hooks and yields a set-valued tableau

Susan S. Sorensen, Daniel A. Thrasher, Thad G. Walker

Inertial navigation systems generally consist of timing, acceleration, and orientation measurement units. Although much progress has been made towards developing primary timing sources such as atomic clocks, acceleration and orientation measurement units often require calibration. Nuclear Magnetic Resonance (NMR) gyroscopes, which rely on continuous measurem

Carl Corcoran, Alan Hastings

Network-based models of epidemic spread have become increasingly popular in recent decades. Despite a rich foundation of such models, few low-dimensional systems for modeling SIS-type diseases have been proposed that manage to capture the complex dynamics induced by the network structure. We analyze one recently introduced model and derive important epidemio

Ana M. Montero, Filipe S. M. Guimarães, Samir Lounis

Molecular spintronics hinges on the detailed understanding of electronic and magnetic properties of molecules interfaced with various materials. Here we demonstrate with ab-initio simulations that the prototypical Co-phthalocyanine (CoPc) molecule can surprisingly develop multi-spin states once deposited on the two-dimensional 2H-NbSe$_2$ layer. Conventional

Susan Martonosi, Banafsheh Behzad, Kayla Cummings

According to the World Health Organization, development of the COVID-19 vaccine is occurring in record time. Administration of the vaccine has started the same year as the declaration of the COVID-19 pandemic. The United Nations emphasized the importance of providing COVID-19 vaccines as "a global public good", which is accessible and affordable world-wide.

Zheng Chen, Erik G. Larsson

Average consensus algorithms have wide applications in distributed computing systems where all the nodes agree on the average value of their initial states by only exchanging information with their local neighbors. In this letter, we look into link-based network metrics which are polynomial functions of pair-wise node attributes defined over the links in a n

Fahad Islam, Chris Paxton, Clemens Eppner, Bryan Peele

In many applications, including logistics and manufacturing, robot manipulators operate in semi-structured environments alongside humans or other robots. These environments are largely static, but they may contain some movable obstacles that the robot must avoid. Manipulation tasks in these applications are often highly repetitive, but require fast and relia

H. Idzuchi, F. Pientka, K. -F. Huang, K. Harada

When two superconductors are connected across a ferromagnet, the spin configuration of the transferred Cooper pairs can be modulated due to magnetic exchange interaction. The resulting supercurrent can reverse its sign across the Josephson junction (JJ) [1-4]. Here we demonstrate Josephson phase modulation in van der Waals heterostructures when Cooper pairs