November 2020 arXiv papers — page 6

R. A. Kycia, P. Lebiedowicz, A. Szczurek

Recently, there is a need for a general-purpose event generator of decays of an elementary particle or a hadron to a state of higher multiplicity ($N > 2$) that is simple to use and universal. We present the structure of such a library to produce generators that generate kinematics of decay processes and can be used to integrate any matrix element squared ov

Antoni Rangachev

Let A and B be integral domains. Suppose A is Noetherian and B is a finitely generated A-algebra that contains A. Denote by A' the integral closure of A in B. We show that A' is determined by finitely many unique discrete valuation rings. Our result generalizes Rees' classical valuation theorem for ideals. We also obtain a variant of Zariski's main theorem.

Weicong Chen, Chao-Kai Wen, Xiao Li, Shi Jin

In frequency division duplexing systems, the base station (BS) acquires downlink channel state information (CSI) via channel feedback, which has not been adequately investigated in the presence of RIS. In this study, we examine the limited channel feedback scheme by proposing a novel cascaded codebook and an adaptive bit partitioning strategy. The RIS segmen

Masayo Y. Hirose, Shuhei Mano

A procedure for asymptotic bias reduction of maximum likelihood estimates of generic estimands is developed. The estimator is realized as a plug-in estimator, where the parameter maximizes the penalized likelihood with a penalty function that satisfies a quasi-linear partial differential equation of the first order. The integration of the partial differentia

I. O. Goriachuk, A. L. Kataev

Two renormalization group invariant quantities in quantum chromodinamics (QCD), defined in Euclidean space,namely, Adler D-function of electron-positron annihilation to hadrons and Bjorken polarized deep-inelastic scattering sum rule, are considered. It is shown, that the 5-th order corrections to them in $\overline{MS}$-like renormalization prescriptions, p

Jesse T. Palmerio, Frédéric Daigne

Long Gamma-Ray Bursts (LGRBs) have been shown to be powerful probes of the Universe, in particular to study the star formation rate up to very high redshift ($z \sim 9$). Since LGRBs are produced by only a small fraction of massive stars, it is paramount to have a good understanding of their underlying intrinsic population in order to use them as cosmologica

Yinyu Nie, Ji Hou, Xiaoguang Han, Matthias Nießner

Semantic scene understanding from point clouds is particularly challenging as the points reflect only a sparse set of the underlying 3D geometry. Previous works often convert point cloud into regular grids (e.g. voxels or bird-eye view images), and resort to grid-based convolutions for scene understanding. In this work, we introduce RfD-Net that jointly dete

Barbora Bruant Gulejova

The International Particle Physics Outreach Group (IPPOG) has been making concerted and systematic efforts to present and popularise particle physics across all audiences and age groups since 1997. Today the scientific community has in IPPOG a strategic pillar in fostering long-term, sustainable support for fundamental research around the world. One of the m

Sabri Bahrouni, Hichem Ounaies, Ariel Salort

In the present work we study existence of sequences of variational eigenvalues to non-local non-standard growth problems ruled by the fractional $g-$Laplacian operator with different boundary conditions (Dirichlet, Neumann and Robin). Due to the non-homogeneous nature of the operator several drawbacks must be overcome, leading to some results that contrast w

Xu Chen, Yuqian Wang, Zhiwei Guo, Xian Wu

The magnetic shield plays an important role in magnetic near-field control. However, the requirements of efficient, ultrathin, lightweight and cheap are still the challenges. Here, we firstly propose a composite metamaterial in which the mu-near-zero media is covered with a ferrite slab. We verify that this structure can enhance the shielding effectiveness i

Shun Watanabe

A minimax converse for the identification via channels is derived. By this converse, a general formula for the identification capacity, which coincides with the transmission capacity, is proved without the assumption of the strong converse property. Furthermore, the optimal second-order coding rate of the identification via channels is characterized when the

Massimo Pippi

We provide an equivalence between the dg category of coherent matrix factorizations and a certain dg category of absolute singularities. As an application, we compute the l-adic cohomology of the dg category of coherent matrix factorizations, as well as its Hochschild and periodic cyclic homologies (these last two only in the affine case).

Ákos G. Horváth

This paper contains a new concept to measure the width and thickness of a convex body in the hyperbolic plane. We compare the known concepts with the new one and prove some results on bodies of constant width, constant diameter and given thickness.

Meijuan Cheng, Xiaohong Shi, Shunqing Wu, Zi-Zhong Zhu

One-dimensional selenium and tellurium crystalize in helical chainlike structures and thus exhibit fascinating properties. By performing first-principles calculations, we have researched the linear and nonlinear optical (NLO) properties of 1D Se and Te, and find that both systems exhibit pronounced NLO responses. In particular, 1D Se is found to possess larg

Tobias Haug, Kishor Bharti

We provide a noisy intermediate-scale quantum framework for simulating the dynamics of open quantum systems, generalized time evolution, non-linear differential equations and Gibbs state preparation. Our algorithm does not require any classical-quantum feedback loop, bypass the barren plateau problem and does not necessitate any complicated measurements such

Vasiliki Evdoridou, Philip J. Rippon, Gwyneth M. Stallard

Although detailed descriptions of the possible types of behaviour inside periodic Fatou components have been known for over 100 years, a classification of wandering domains has only recently been given. Recently, simply connected wandering domains were classified into nine possible types and examples of escaping wandering domains of each of these types were

Roland Gerard Gera, Tim Friede

The increasing interest in subpopulation analysis has led to the development of various new trial designs and analysis methods in the fields of personalized medicine and targeted therapies. In this paper, subpopulations are defined in terms of an accumulation of disjoint population subsets and will therefore be called composite populations. The proposed tria

L. Coraggio, N. Itaco, G. De Gregorio, A. Gargano

Neutrinoless double beta decay searches are currently among the major foci of experimental physics. The observation of such a decay will have important implications in our understanding of the intrinsic nature of neutrinos and shed light on the limitations of the Standard Model. The rate of this process depends on both the unknown neutrino effective mass and

Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia

DRDr II is a hybrid of machine learning and deep learning worlds. It builds on the successes of its antecedent, namely, DRDr, that was trained to detect, locate, and create segmentation masks for two types of lesions (exudates and microaneurysms) that can be found in the eyes of the Diabetic Retinopathy (DR) patients; and uses the entire model as a solid fea

Maryam Songhorabadi, Morteza Rahimi, Amir Mahdi Moghaddam Farid, Mostafa Haghi Kashani

These days, the development of smart cities, specifically in location-aware, latency-sensitive, and security-crucial applications (such as emergency fire events, patient health monitoring, or real-time manufacturing) heavily depends on a more advance computing paradigms that can address these requirements. In this regard, fog computing, a robust cloud comput

Caglar Cakan, Cristiana Dimulescu, Liliia Khakimova, Daniela Obst

During slow-wave sleep, the brain is in a self-organized regime in which slow oscillations (SOs) between up- and down-states travel across the cortex. While an isolated piece of cortex can produce SOs, the brain-wide propagation of these oscillations are thought to be mediated by the long-range axonal connections. We address the mechanism of how SOs emerge a

Meijuan Cheng, Zi-Zhong Zhu, Guang-Yu Guo

Few-layer selenium and tellurium films have been recently prepared, and they provide a new platform to explore novel properties of two-dimensional (2D) elemental materials. In this work, we have performed a systematic first-principles study on the electronic, linear, and nonlinear optical (NLO) properties of atomically thin selenium and tellurium films withi

Zhengsu Chen, Jianwei Niu, Xuefeng Liu, Shaojie Tang

Convolutional neural networks (CNNs) have achieved remarkable success in image recognition. Although the internal patterns of the input images are effectively learned by the CNNs, these patterns only constitute a small proportion of useful patterns contained in the input images. This can be attributed to the fact that the CNNs will stop learning if the learn

Daniel Neuen

We give an isomorphism test that runs in time $n^{\operatorname{polylog}(h)}$ on all $n$-vertex graphs excluding some $h$-vertex vertex graph as a topological subgraph. Previous results state that isomorphism for such graphs can be tested in time $n^{\operatorname{polylog}(n)}$ (Babai, STOC 2016) and $n^{f(h)}$ for some function $f$ (Grohe and Marx, SIAM J.

U. Kavak, A. Sanchez-Monge, A. Lopez-Sepulcre, R. Cesaroni

Recent theoretical and observational studies debate the similarities between the formation process of high-mass (>8 Msun) and low-mass stars. The formation of low-mass star formation is directly associated with the presence of disks and jets. According to this scenario, radio jets are expected to be common in high-mass star-forming regions. We aim to increas

Huaju Liang, Hongyang Bai, Tong Zhou

Our previous work has demonstrated that Rayleigh model, which is widely used in polarized skylight navigation to describe skylight polarization patterns, does not contain three-dimensional (3D) attitude information [1]. However, it is still necessary to further explore whether the skylight polarization patterns contain 3D attitude information. So, in this pa

A. I. Krivchikov, A. Jeżowski

Among the many physical properties, the amorphous state manifests itself in the most spectacular way in heat transport. Anomalously low thermal conductivity, its low-temperature dependence as a function of temperature, the presence of a plateau of thermal conductivity, all are definitely different when compared with the ordered state of crystals. For this re

Shuwen Sun, Wei Qin, Leiqiang Li, Zhenyu Zhang

Materials realization of chiral topological superconductivity is a crucial condition for observing and manipulating Majorana fermions in condensed matter physics. Here we develop a tight-binding description of Pb$_3$Bi/Ge(111), identified recently as an appealing candidate system for realizing chiral $p$-wave topological superconductivity [Nat. Phys. 15, 796

Michael Olesik, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner

This work discusses the numerical aspects of representing the diffusional (condensational) growth in particulate systems such as atmospheric clouds. It focuses on the Eulerian modeling approach, in which the evolution of the particle size spectrum is carried out using a fixed-bin discretization associated with inherent numerical diffusion. Focus is on the ap

I. L. Buchbinder, S. A. Fedoruk, A. P. Isaev, M. A. Podoinitsyn

We study the massless irreducible representations of the Poincar\'{e} group in the six-dimensional Minkowski space. The Casimir operators are constructed and their eigenvalues are found. It is shown that the finite spin (helicity) representation is defined by two integer or half-integer numbers while the infinite spin representation is defined by the real pa

Joan Bagaria, Claudio Ternullo

We address Steel's Programme to identify a 'preferred' universe of set theory and the best axioms extending ZFC by using his multiverse axioms MV and the 'core hypothesis'. In the first part, we examine the evidential framework for MV, in particular the use of large cardinals and of 'worlds' obtained through forcing to 'represent' alternative extensions of Z

Dvir Ginzburg, Dan Raviv

We provide a novel new approach for aligning geometric models using a dual graph structure where local features are mapping probabilities. Alignment of non-rigid structures is one of the most challenging computer vision tasks due to the high number of unknowns needed to model the correspondence. We have seen a leap forward using DNN models in template alignm

Shivam Garg, Kirankumar Shiragur, Deborah M. Gordon, Moses Charikar

Colonies of the arboreal turtle ant create networks of trails that link nests and food sources on the graph formed by branches and vines in the canopy of the tropical forest. Ants put down a volatile pheromone on edges as they traverse them. At each vertex, the next edge to traverse is chosen using a decision rule based on the current pheromone level. There

Verónica Álvarez, Santiago Mazuelas, José A. Lozano

Load forecasting is crucial for multiple energy management tasks such as scheduling generation capacity, planning supply and demand, and minimizing energy trade costs. Such relevance has increased even more in recent years due to the integration of renewable energies, electric cars, and microgrids. Conventional load forecasting techniques obtain single-value

Nikita Geldhauser, Andrei Lavrenov, Victor Petrov, Pavel Sechin

We compute the algebraic Morava K-theory ring of split special orthogonal and spin groups. In particular, we establish certain stabilization results for the Morava K-theory of special orthogonal and spin groups. Besides, we apply these results to study Morava motivic decompositions of orthogonal Grassmannians. For instance, we determine all indecomposable su

Julio Araujo, Alexandre Cezar, Carlos V. G. C. Lima, Vinicius F. dos Santos

An orientation $D$ of a graph $G=(V,E)$ is a digraph obtained from $G$ by replacing each edge by exactly one of the two possible arcs with the same end vertices. For each $v \in V(G)$, the indegree of $v$ in $D$, denoted by $d^-_D(v)$, is the number of arcs with head $v$ in $D$. An orientation $D$ of $G$ is proper if $d^-_D(u)\neq d^-_D(v)$, for all $uv\in E

Leandro M. Del Pezzo, Nicolás Frevenza, Julio D. Rossi

We study convex and quasiconvex functions on a metric graph. Given a set of points in the metric graph, we consider the largest convex function below the prescribed datum. We characterize this largest convex function as the unique largest viscosity subsolution to a simple differential equation, $u''=0$ on the edges, plus nonlinear transmission conditions at

N. Pathak, A. Zhidkov, T. Hosokai

Particle energy chirp is shown to be a useful instrument in the staging laser wake field acceleration directed to generation of high-quality dense electron beams. The chirp is a necessary tool to compensate non-uniformity of acceleration field in longitudinal direction and achieve essential reduction of energy dispersion. This is demonstrated via particle-in

Farid Ya. Khalili, Emil Zeuthen

State-of-the-art sensors of force, motion and magnetic fields have reached the sensitivity where the quantum noise of the meter is significant or even dominant. In particular, the sensitivity of the best optomechanical devices has reached the Standard Quantum Limit (SQL), which directly follows from the Heisenberg uncertainty relation and corresponds to bala

Pavlo Golub, Andrej Antalik, Libor Veis, Jiri Brabec

The active-space quantum chemical methods could provide very accurate description of strongly correlated electronic systems, which is of tremendous value for natural sciences. The proper choice of the active space is crucial, but a non-trivial task. In this article, we present the neural network (NN) based approach for automatic selection of active spaces, f

Chuang Yang, Mulin Chen, Zhitong Xiong, Yuan Yuan

Recently fast arbitrary-shaped text detection has become an attractive research topic. However, most existing methods are non-real-time, which may fall short in intelligent systems. Although a few real-time text methods are proposed, the detection accuracy is far behind non-real-time methods. To improve the detection accuracy and speed simultaneously, we pro

Wen-Qiang Liu, Hai-Rui Wei, Leong-Chuan Kwek

Effective quantum information processing is tantamount in part to the minimization the quantum resources needed by quantum logic gates. Here, we propose an optimization of an n-controlled-qubit Fredkin gate with a maximum of 2n+1 two-qubit gates and 2n single-qudit gates by exploiting auxiliary Hilbert spaces. The number of logic gates required improves on e

Monique Dauge, Michal Jex, Vladimir Lotoreichik

We obtain a trace Hardy inequality for the Euclidean space with a bounded cut $\Sigma\subset\mathbb R^d$, $d \ge 2$. In this novel geometric setting, the Hardy-type inequality non-typically holds also for $d = 2$. The respective Hardy weight is given in terms of the geodesic distance to the boundary of $\Sigma$. We provide its applications to the heat equati

Vishrut Jetly, Bhaskar Chaudhury

Electron-neutral scattering cross sections are fundamental quantities in simulations of low temperature plasmas used for many technological applications today. From these microscopic cross sections, several macro-scale quantities (called "swarm" parameters) can be calculated. However, measurements as well as theoretical calculations of cross sections are cha

Mikhail Z. Iofa

Near-horizon symmetries are studied for static black hole solutions to Einstein equations containing supertranslation field. We consider general diffeomorphisms which preserve the gauge and the near-horizon structure of the metric. Diffeomorphisms are generated by the vector fields and form a group of near-horizon symmetries. The densities of variation of th

James Y. S. Tan, Zengguang Cheng, Johannes Feldmann, Xuan Li

Over a century ago, Ivan P. Pavlov, in a classic experiment, demonstrated how dogs can learn to associate a ringing bell with food, thereby causing a ring to result in salivation. Today, it is rare to find the use of Pavlovian type associative learning for artificial intelligence (AI) applications even though other learning concepts, in particular backpropag

Felix Tim Bölle, August E. G. Mikkelsen, Kristian S. Thygesen, Tejs Vegge

One-dimensional inorganic nanotubes hold promise for technological applications due to their distinct physical/chemical properties, but so far advancements have been hampered by difficulties in producing single-wall nanotubes with a well-defined radius. In this work we investigate, based on Density Functional Theory (DFT), the formation mechanism of 135 diff

Jan N. Kirchhof, Kristina Weinel, Sebastian Heeg, Victor Deinhart

In the field of phononics, periodic patterning controls vibrations and thereby the flow of heat and sound in matter. Bandgaps arising in such phononic crystals realize low-dissipation vibrational modes and enable applications towards mechanical qubits, efficient waveguides, and state-of-the-art sensing. Here, we combine phononics and two-dimensional material

Mostafa Haghi Kashani, Ahmad Ahmadzadeh, Ebrahim Mahdipour

Recently, fog computing has been introduced as a modern distributed paradigm and complement to cloud computing to provide services. Fog system extends storing and computing to the edge of the network, which can solve the problem about service computing of the delay-sensitive applications remarkably besides enabling the location awareness and mobility support

Olivier Lai, Mark Chun, Ryan Dungee, Jessica Lu

Adaptive optics systems require a calibration procedure to operate, whether in closed loop or even more importantly in forward control. This calibration usually takes the form of an interaction matrix and is a measure of the response on the wavefront sensor to wavefront corrector stimulus. If this matrix is sufficiently well conditioned, it can be inverted t

William Giarè, Eleonora Di Valentino, Alessandro Melchiorri, Olga Mena

Axions, if realized in nature, can be copiously produced in the early universe via thermal processes, contributing to the mass-energy density of thermal hot relics. In light of the most recent cosmological observations, we analyze two different thermal processes within a realistic mixed hot-dark-matter scenario which includes also massive neutrinos. Consider

Arpita Chatterjee, Kishore Thapliyal, Anirban Pathak

The significance of photon addition in engineering the single- and two-mode (bipartite correlations) nonclassical properties of a quantum state is investigated. Specifically, we analyzed the behavior of the Wigner function of two quasi-Werner states theoretically constructed by superposing two normalized bipartite $m$-photon added coherent states. This allow

Isaac Nape, Nikiwe Mashaba, Nokwazi Mphuthi, Sruthy Jayakumar

Vector beams are inhomogeneously polarized optical fields with nonseparable, quantum-like correlations between their polarisation and spatial components, and hold tremendous promise for classical and quantum communication across various channels, e.g. the atmosphere, underwater, and in optical fibre. Here we show that by exploiting their quantum-like feature

Tobias Schwaiger, Thomas Gastine, Julien Aubert

In fluid dynamics, the scaling behaviour of flow length scales is commonly used to infer the governing force balance of a system. The key to a successful approach is to measure length scales that are representative of the energy contained in the solution (energetically relevant) and indicative of the established force balance (dynamically relevant). In numer

Dat Thanh Nguyen, Maurice Quach, Giuseppe Valenzise, Pierre Duhamel

This paper presents a learning-based, lossless compression method for static point cloud geometry, based on context-adaptive arithmetic coding. Unlike most existing methods working in the octree domain, our encoder operates in a hybrid mode, mixing octree and voxel-based coding. We adaptively partition the point cloud into multi-resolution voxel blocks accor

Andrea Cianchi, Vladimir Maz'ya

First and second-order inequalities of Friedrichs type for Sobolev functions in arbitrary domains are offered. The relevant inequalities involve optimal norms and constants that are independent of the geometry of the domain. Parallel inequalities for symmetric gradient Sobolev spaces of vector-valued functions are also presented. The results are derived via

Pranay Seshadri, Andrew Duncan, George Thorne, Geoffrey Parks

Aeroengine performance is determined by temperature and pressure profiles along various axial stations within an engine. Given limited sensor measurements both along and between axial stations, we require a statistically principled approach to inferring these profiles. In this paper we detail a Bayesian methodology for interpolating the spatial temperature o

R. Hagala, A. De Felice, D. F. Mota, S. Mukohyama

We investigate cosmological signatures of the minimal theory of massive gravity (MTMG). To this aim, we simulate the normal branch of the MTMG by employing the \textsc{Ramses} \mbox{$N$-body} code and extending it with an effective gravitational constant $G_{\rm eff}$. We implement an environment-dependent $G_{\rm eff}$ as a function of the graviton mass and

Akshay L Chandra, Sai Vikas Desai, Chaitanya Devaguptapu, Vineeth N Balasubramanian

Active Learning (AL) techniques aim to minimize the training data required to train a model for a given task. Pool-based AL techniques start with a small initial labeled pool and then iteratively pick batches of the most informative samples for labeling. Generally, the initial pool is sampled randomly and labeled to seed the AL iterations. While recent studi

Risheng Huang, Li Shen, Xuan Wang, Cheng Lin

This paper proposes an adaptive compact attention model for few-shot video-to-video translation. Existing works in this domain only use features from pixel-wise attention without considering the correlations among multiple reference images, which leads to heavy computation but limited performance. Therefore, we introduce a novel adaptive compact attention me

Omair Ali, Muhammad Saif-ur-Rehman, Susanne Dyck, Tobias Glasmachers

Brain-computer interfaces (BCIs) enable communication between humans and machines by translating brain activity into control commands. Electroencephalography (EEG) signals are one of the most used brain signals in non-invasive BCI applications but are often contaminated with noise. Therefore, it is possible that meaningful patterns for classifying EEG signal

Yutong Jiang, Gang Wu, Long Jiang

The Kaczmarz method is a popular iterative scheme for solving large-scale linear systems. The randomized Kaczmarz method (RK) greatly improves the convergence rate of the Kaczmarz method, by using the rows of the coefficient matrix in random order rather than in their given order. An obvious disadvantage of the randomized Kaczmarz method is its probability c

Tomasz Mańdziuk

We study the closure of the locus of radical ideals in the multigraded Hilbert scheme associated with a standard graded polynomial ring and the Hilbert function of a homogeneous coordinate ring of points in general position in projective space. In the case of projective plane, we give a sufficient condition for an ideal to be in the closure of the locus of r

Het Shah, Avishree Khare, Neelay Shah, Khizir Siddiqui

In recent years, the growing size of neural networks has led to a vast amount of research concerning compression techniques to mitigate the drawbacks of such large sizes. Most of these research works can be categorized into three broad families : Knowledge Distillation, Pruning, and Quantization. While there has been steady research in this domain, adoption

Andrey O. Matveev

For a symmetric 2t-cycle in the tope graph of a simple oriented matroid M on the ground set {1,...,t}, where t is even, we describe decompositions of topes and subtopes of M with respect to the subtopes corresponding to the edges of the symmetric cycle.

Yongmin Yoon, Gu Lim

Previous studies suggest that compact young early-type galaxies (ETGs) were formed by recent mergers. However, it has not yet been revealed whether tidal features that are direct evidence of recent mergers are detected frequently around compact young ETGs. Here, we investigate how the fraction of ETGs having tidal features ($f_{T}$) depends on age and intern

Yassine Himeur, Abdullah Alsalemi, Faycal Bensaali, Abbes Amira

In spite of the substantial advance in developing energy-efficient buildings, power demand in the building sector is still remarkably growing due to teleworking and e-learning triggered by the COVID-19 movement restrictions. This is highlighted by the inefficiency of energy saving measures that have recently been set owing to the the marketability failure an

Guido Montúfar, Nina Otter, Yuguang Wang

Topological data analysis uses tools from topology -- the mathematical area that studies shapes -- to create representations of data. In particular, in persistent homology, one studies one-parameter families of spaces associated with data, and persistence diagrams describe the lifetime of topological invariants, such as connected components or holes, across

Masami Matsumoto, Gota Tanaka, Asato Tsuchiya

We study the relationship between the renormalization group and the diffusion equation. We consider the exact renormalization group equation for a scalar field that includes an arbitrary cutoff function and an arbitrary quadratic seed action. As a generalization of the result obtained by Sonoda and Suzuki, we find that the correlation functions of diffused f

Ujan Gangopadhyay

We consider a model of first passage percolation (FPP) where the nearest-neighbor edges of the standard two-dimensional Euclidean lattice are equipped with random variables. These variables are i.i.d.\, nonnegative, continuous, and have a finite moment generating function in a neighborhood of $0$. We derive consequences about transverse increments of passage

A. Leitao

We investigate an iterative mean value method for the inverse (and highly ill-posed) problem of solving the heat equation backwards in time. Semi-group theory is used to rewrite the solution of the inverse problem as the solution of a fixed point equation for an affine operator, with linear part satisfying special functional analytical properties. We give a

Simone Angarano, Vittorio Mazzia, Francesco Salvetti, Giovanni Fantin

Ultra-wideband (UWB) is the state-of-the-art and most popular technology for wireless localization. Nevertheless, precise ranging and localization in non-line-of-sight (NLoS) conditions is still an open research topic. Indeed, multipath effects, reflections, refractions, and complexity of the indoor radio environment can easily introduce a positive bias in t

M. Ratajczak, R. K. Pawłaszek, K. G. Hełminiak, M. Konacki

We present the results of a spectroscopic campaign on eclipsing binaries with long orbital period (P = 20 - 75 d) carried out with the CHIRON spectrograph. Physical and orbital solutions for seven systems were derived from the V-band, and I-band ASAS, WASP, and TESS photometry, while radial velocities were calculated from high quality optical spectra using a

R. Dale, D. Sáez

There is a viable vector-tensor gravity (VTG) theory, whose vector field produces repulsive forces leading to important effects. In the background universe, the effect of these forces is an accelerated expansion identical to that produced by vacuum energy (cosmological constant). Here, we prove that another of these effects arises for great enough collapsing

Ondřej Pražák, Pavel Přibáň, Stephen Taylor, Jakub Sido

In this paper, we describe our method for the detection of lexical semantic change, i.e., word sense changes over time. We examine semantic differences between specific words in two corpora, chosen from different time periods, for English, German, Latin, and Swedish. Our method was created for the SemEval 2020 Task 1: \textit{Unsupervised Lexical Semantic Ch

A. Leitao

We investigate the iterative methods proposed by Maz'ya and Kozlov (see [3], [4]) for solving ill-posed reconstruction problems modeled by PDE's. We consider linear time dependent problems of elliptic, hyperbolic and parabolic types. Each iteration of the analyzed methods consists on the solution of a well posed boundary (or initial) value problem. The itera

Giovanni Pizzi, Silvia Milana, Andrea C. Ferrari, Nicola Marzari

Layered materials (LMs), such as graphite, hexagonal boron nitride, and transition-metal dichalcogenides, are at the centre of an ever increasing research effort, due to their scientific and technological relevance. Raman and infrared spectroscopies are accurate, non-destructive, approaches to determine a wide range of properties, including the number of lay

Giuseppe Castagnoli

We consider the reversible processes between two one-to-one correlated measurement outcomes which underly both problem-solving and quantum nonlocality. In the former case the two outcomes are the setting and the solution of the problem, in the latter those of measuring a pair of maximally entangled observables whose subsystems are space separate. We argue th

Bastian Wandt, Marco Rudolph, Petrissa Zell, Helge Rhodin

Human pose estimation from single images is a challenging problem in computer vision that requires large amounts of labeled training data to be solved accurately. Unfortunately, for many human activities (\eg outdoor sports) such training data does not exist and is hard or even impossible to acquire with traditional motion capture systems. We propose a self-

Ondřej Pražák, Pavel Přibáň, Stephen Taylor

In this paper, we describe our method for detection of lexical semantic change (i.e., word sense changes over time) for the DIACR-Ita shared task, where we ranked $1^{st}$. We examine semantic differences between specific words in two Italian corpora, chosen from different time periods. Our method is fully unsupervised and language independent. It consists o

Yao Chen, Weihua Deng

L\'{e}vy walk is a popular and more `physical' model to describe the phenomena of superdiffusion, because of its finite velocity. The movements of particles are under the influences of external potentials almost at anytime and anywhere. In this paper, we establish a Langevin system coupled with a subordinator to describe the L\'{e}vy walk in the time-depende

Leonid Zelenko

This work is a continuation of our previos paper, where for the Schr\"odinger operator $H=-\Delta+ V(\e)\cdot$ $(V(\e)\ge 0)$, acting in the space $L_2(\R^d)\,(d\ge 3)$, some sufficient conditions for discreteness of its spectrum have been obtained on the base of well known Mazya -Shubin criterion and an optimization problem for a set function, which is an i

Mickaël Véril, Anthony Scemama, Michel Caffarel, Filippo Lipparini

We describe our efforts of the past few years to create a large set of more than 500 highly-accurate vertical excitation energies of various natures ($\pi \to \pi^*$, $n \to \pi^*$, double excitation, Rydberg, singlet, doublet, triplet, etc) in small- and medium-sized molecules. These values have been obtained using an incremental strategy which consists in

Ashita Victor, Abhay Shankar Jha, Janamejaya Channegowda, Sumukh Surya

Hybrid energy storage systems (HESS) have carved a niche in the industry. HESS improve the system efficiency, reduce the overall cost and increase the lifespan of the system. The proton exchange membrane (PEM) fuel cell is hybridized with Li-ion batteries (LIB) for vehicular applications, robotic applications etc. In applications which have geometrical space

Chiaro G., Kovacevic M., La Mura G

Since 2008 August the Fermi Large Area Telescope (LAT) has provided continuous coverage of the gamma-ray sky yielding more than 5000 gamma-ray sources, but 54% of the detected sources remain with no certain or unknown association with a low energy counterpart. Rigorous determination of class type for a gamma-ray source requires the optical spectrum of the co

Jiefeng Li, Chao Xu, Zhicun Chen, Siyuan Bian

Model-based 3D pose and shape estimation methods reconstruct a full 3D mesh for the human body by estimating several parameters. However, learning the abstract parameters is a highly non-linear process and suffers from image-model misalignment, leading to mediocre model performance. In contrast, 3D keypoint estimation methods combine deep CNN network with th

Fredrik Johansson

We consider the problem of efficiently computing isolated coefficients $c_n$ in the Fourier series of the elliptic modular function $j(\tau)$. We show that a hybrid numerical-modular method with complexity $n^{1+o(1)}$ is efficient in practice. As an application, we locate the first few values of $c_n$ that are prime, the first occurring at $n = 457871$.

Seokeon Choi, Taekyung Kim, Minki Jeong, Hyoungseob Park

Although supervised person re-identification (Re-ID) methods have shown impressive performance, they suffer from a poor generalization capability on unseen domains. Therefore, generalizable Re-ID has recently attracted growing attention. Many existing methods have employed an instance normalization technique to reduce style variations, but the loss of discri

Yiming Wang, Alessio Del Bue

In this work we address the problem of autonomous 3D exploration of an unknown indoor environment using a depth camera. We cast the problem as the estimation of the Next Best View (NBV) that maximises the coverage of the unknown area. We do this by re-formulating NBV estimation as a classification problem and we propose a novel learning-based metric that enc

Ashutosh Kumar Alok, Suman Kumbhakar, Jyoti Saini, S Uma Sankar

The lepton universality violating flavor ratios $R_K/R_{K^*}$ indicate new physics either in $b \to s \mu^+ \mu^-$ or in $b \to s e^+ e^-$ or in both. If the new physics is only $b \to s e^+ e^-$ transition, the corresponding new physics operators, in principle, can have any Lorentz structure. In this work, we perform a model independent analysis of new phys

Seth Troisi

A new Combined Sieve algorithm is presented with cost proportional to the number of enumerated factors over a series of intervals. This algorithm achieves a significant speedup, over a traditional sieve, when handling many ([10^4, 10^7]) intervals concurrently. The speedup comes from a space-time tradeoff and a novel solution to a modular equation. In real w

Connor Paul Wilson

We show the following bounds on the prime counting function $\pi(x)$ using principles from analytic number theory, giving an estimate: $$2 \log 2 \geq \limsup_{x \rightarrow \infty} \frac{\pi(x)}{x / \log x} \geq \liminf_{x \rightarrow \infty} \frac{\pi(x)}{x / \log x} \geq \log 2$$ for all $x$ sufficiently large. We also conjecture about the bounding of $\p

Longyao Liu, Bo Ma, Yulin Zhang, Xin Yi

Few-shot object detection (FSOD) aims at learning a detector that can fast adapt to previously unseen objects with scarce annotated examples, which is challenging and demanding. Existing methods solve this problem by performing subtasks of classification and localization utilizing a shared component (e.g., RoI head) in the detector, yet few of them take the

Atsushi Nishimura, Akio Ohama, Kimihiro Kimura, Daichi Tsutsumi

We report the current status of the NASCO (NAnten2 Super CO survey as legacy) project which aims to provide all-sky CO data cube of southern hemisphere using the NANTEN2 4-m submillimeter telescope installed at the Atacama Desert through developing a new multi-beam receiver and a new telescope control system. The receiver consists of 5 beams. The four beams,

Isma Hadji, Richard P. Wildes

It has been repeatedly observed that convolutional architectures when applied to image understanding tasks learn oriented bandpass filters. A standard explanation of this result is that these filters reflect the structure of the images that they have been exposed to during training: Natural images typically are locally composed of oriented contours at variou

Aernout van Enter, Arnaud Le Ny, Frédéric Paccaut

In this review-type paper written at the occasion of the Oberwolfach workshop {\em One-sided vs. Two-sided stochastic processes} (february 22-29, 2020), we discuss and compare Markov properties and generalisations thereof in more directions, as well as weaker forms of conditional dependence, again either in one or more directions. In particular, we discuss i

Han-Jia Ye, Lu Han, De-Chuan Zhan

Meta-learning has become a practical approach towards few-shot image classification, where "a strategy to learn a classifier" is meta-learned on labeled base classes and can be applied to tasks with novel classes. We remove the requirement of base class labels and learn generalizable embeddings via Unsupervised Meta-Learning (UML). Specifically, episodes of

Ashwini Karmarkar, Saarthak Gupta, Isaac Boxx, Santosh Hemchandra

Global instabilities in swirling flows can significantly alter the flame and flow dynamics of swirl-stabilized flames, such as those in modern power generation gas turbine engines. In this study, we characterize the interaction between the precessing vortex core (PVC), which is the consequence of a global hydrodynamic instability, and thermoacoustic instabil

Seira Hidano, Takao Murakami, Yusuke Kawamoto

Transfer learning has been widely studied and gained increasing popularity to improve the accuracy of machine learning models by transferring some knowledge acquired in different training. However, no prior work has pointed out that transfer learning can strengthen privacy attacks on machine learning models. In this paper, we propose TransMIA (Transfer learn

Shuai Zhao, Liguang Zhou, Wenxiao Wang, Deng Cai

The width of a neural network matters since increasing the width will necessarily increase the model capacity. However, the performance of a network does not improve linearly with the width and soon gets saturated. In this case, we argue that increasing the number of networks (ensemble) can achieve better accuracy-efficiency trade-offs than purely increasing