December 2020 arXiv papers — page 114

Jyrki Jauhiainen, Mohammad Pour-Ghaz, Tuomo Valkonen, Aku Seppänen

Electrical resistance tomography (ERT) -based distributed surface sensing systems, or sensing skins, offer alternative sensing techniques for structural health monitoring, providing capabilities for distributed sensing of, for example, damage, strain and temperature. Currently, however, the computational techniques utilized for sensing skins are limited to p

Charles M. Elliott, Philip J. Herbert

We consider a model of a biomembrane with attached proteins. The membrane is represented by a near spherical continuous surface and attached proteins are described as discrete rigid structures which attach to the membrane at a finite number of points. The resulting surface minimises a quadratic elastic energy (obtained by a perturbation of the Canham-Helfric

Gautier Izacard, Edouard Grave

The task of information retrieval is an important component of many natural language processing systems, such as open domain question answering. While traditional methods were based on hand-crafted features, continuous representations based on neural networks recently obtained competitive results. A challenge of using such methods is to obtain supervised dat

Nikhil Kalyanapuram

The analytic structures of scattering amplitudes in gauge theory and gravity are examined on the celestial sphere. The celestial amplitudes in the two theories - computed by employing a regulated Mellin transform - can be compared at low multiplicity. It is established by direct computation that up to five external particles, the double copy relations of Kaw

R. Abbasi, M. Ackermann, J. Adams, J. A. Aguilar

In multi-messenger astronomy, rapid investigation of interesting transients is imperative. As an observatory with a 4$\pi$ steradian field of view and $\sim$99\% uptime, the IceCube Neutrino Observatory is a unique facility to follow up transients, and to provide valuable insight for other observatories and inform their observing decisions. Since 2016, IceCu

Dwight Nwaigwe, Marek Rychlik

We revisit the problem of the existence of the maximum likelihood estimate for multi-class logistic regression. We show that one method of ensuring its existence is by assigning positive probability to every class in the sample dataset. The notion of data separability is not needed, which is in contrast to the classical set up of multi-class logistic regress

Joseph Turian, Max Henry

Growing research demonstrates that synthetic failure modes imply poor generalization. We compare commonly used audio-to-audio losses on a synthetic benchmark, measuring the pitch distance between two stationary sinusoids. The results are surprising: many have poor sense of pitch direction. These shortcomings are exposed using simple rank assumptions. Our tas

Louis Esperet, Lyuben Lichev

A box is the cartesian product of real intervals, which are either bounded or equal to $\mathbb{R}$. A box is said to be $d$-local if at most $d$ of the intervals are bounded. In this paper, we investigate the recently introduced local boxicity of a graph $G$, which is the minimum $d$ such that $G$ can be represented as the intersection of $d$-local boxes in

Razvan V Marinescu, Daniel Moyer, Polina Golland

Machine learning models are commonly trained end-to-end and in a supervised setting, using paired (input, output) data. Examples include recent super-resolution methods that train on pairs of (low-resolution, high-resolution) images. However, these end-to-end approaches require re-training every time there is a distribution shift in the inputs (e.g., night i

Balázs Major, Omair Ghafur, Katalin Kovács, Katalin Varjú

High-intensity laser pulses covering the ultraviolet to terahertz spectral regions are nowadays routinely generated in a large number of laboratories. In contrast, intense extreme-ultraviolet (XUV) pulses have only been demonstrated using a small number of sources including free-electron laser facilities [1-3] and long high-harmonic generation (HHG) beamline

Elle Najt, Daryl DeFord, Justin Solomon

The space of connected graph partitions underlies statistical models used as evidence in court cases and reform efforts that analyze political districting plans. In response to the demands of redistricting applications, researchers have developed sampling methods that traverse this space, building on techniques developed for statistical physics. In this pape

Cornelis A. A. Franken, Albert van Rees, Lisa V. Winkler, Youwen Fan

Generating visible light with wide tunability and high coherence based on photonic integrated circuits is of high interest for applications in biophotonics, precision metrology and quantum technology. Here we present the first demonstration of a hybrid-integrated diode laser in the visible spectral range. Using an AlGaInP optical amplifier coupled to a low-l

Niklas Witt, Erik G. C. P. van Loon, Takuya Nomoto, Ryotaro Arita

Superconductivity arises mostly at energy and temperature scales that are much smaller than the typical bare electronic energies. Since the computational effort of diagrammatic many-body techniques increases with the number of required Matsubara frequencies and thus with the inverse temperature, phase transitions that occur at low temperatures are typically

Margaret Gregory, Paul Hockett, Albert Stolow, Varun Makhija

The application of a matrix-based reconstruction protocol for obtaining Molecular Frame (MF) photoelectron angular distributions (MFPADs) from laboratory frame (LF) measurements (LFPADs) is explored. Similarly to other recent works on the topic of MF reconstruction, this protocol makes use of time-resolved LF measurements, in which a rotational wavepacket is

Alaittin Kırtışoğlu, Lale Özkahya

The problem of finding the minimum number of colors to color a graph properly without containing any bicolored copy of a fixed family of subgraphs has been widely studied. Most well-known examples are star coloring and acyclic coloring of graphs (Gr\"unbaum, 1973) where bicolored copies of $P_4$ and cycles are not allowed, respectively. In this paper, we int

Ahmet Inci, Mehmet Meric Isgenc, Diana Marculescu

Non-volatile memory (NVM) technologies such as spin-transfer torque magnetic random access memory (STT-MRAM) and spin-orbit torque magnetic random access memory (SOT-MRAM) have significant advantages compared to conventional SRAM due to their non-volatility, higher cell density, and scalability features. While previous work has investigated several architect

Yuexin Wu, Tianyu Gao, Sihao Wang, Zhongmin Xiong

The review-based recommender systems are commonly utilized to measure users preferences towards different items. In this paper, we focus on addressing three main problems existing in the review-based methods. Firstly, these methods suffer from the class-imbalanced problem where rating levels with lower proportions will be ignored to some extent. Thus, their

H. B. Camara, R. G. Felipe, F. R. Joaquim

We study the phenomenology of the minimal $(2,2)$ inverse-seesaw model supplemented with Abelian flavour symmetries. To ensure maximal predictability, we establish the most restrictive flavour patterns which can be realised by those symmetries. This setup requires adding an extra scalar doublet and two complex scalar singlets to the Standard Model, paving th

Haining Pan, Sankar Das Sarma

Using a realistic band structure for twisted WSe$_2 $ materials, we develop a theory for the interaction-driven correlated insulators to conducting metals transitions through the tuning of the filling factor around commensurate fractional fillings of the moir\'e unit cell in the 2D honeycomb lattice, focusing on the dominant half-filled Mott insulating state

Chen Xie, Kaixiang Ni, Ke Han, Shaobo Wang

Double beta decay of $^{136}$Xe to excited states of $^{136}$Ba (DBD-ES) has not yet been discovered experimentally yet. The experimental signature of such decays, one or two gamma rays following the beta signals, can be identified more effectively in a gaseous detector with the help of topological signatures. We have investigated key parameters of particle

Ajinkya Kadu, Tristan van Leeuwen, K. Joost Batenburg

We introduce single-shot X-ray tomography that aims to estimate the target image from a single cone-beam projection measurement. This linear inverse problem is extremely under-determined since the measurements are far fewer than the number of unknowns. Moreover, it is more challenging than conventional tomography where a sufficiently large number of projecti

Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani

Consider a prediction setting with few in-distribution labeled examples and many unlabeled examples both in- and out-of-distribution (OOD). The goal is to learn a model which performs well both in-distribution and OOD. In these settings, auxiliary information is often cheaply available for every input. How should we best leverage this auxiliary information f

Behzad Golparvar, Petros Papadopoulos, Ahmed Aziz Ezzat, Ruo-Qian Wang

Power curve is widely used in the wind industry to estimate power output for planning and operational purposes. Existing methods for power curve estimation have three main limitations: (i) they mostly rely on wind speed as the sole input, thus ignoring the secondary, yet possibly significant effects of other environmental factors, (ii) they largely overlook

Javier Gómez-Serrano, Jaemin Park, Jia Shi, Yao Yao

In this paper, we show that the only solution of the vortex sheet equation, either stationary or uniformly rotating with negative angular velocity $\Omega$, such that it has positive vorticity and is concentrated in a finite disjoint union of smooth curves with finite length is the trivial one: constant vorticity amplitude supported on a union of nested, con

Angelo Ziletti, Christoph Berns, Oliver Treichel, Thomas Weber

Millions of unsolicited medical inquiries are received by pharmaceutical companies every year. It has been hypothesized that these inquiries represent a treasure trove of information, potentially giving insight into matters regarding medicinal products and the associated medical treatments. However, due to the large volume and specialized nature of the inqui

D. V. Bochek, K. B. Samusev, D. A. Yavsin, M. V. Zhukov

We experimentally demonstrate fabrication of tunable high contrast periodic fishnet metasurfaces with 3 um period on 200 nm thick Ge2Sb2Te5 films sputted onto glass and sapphire substrates using direct laser writing technique. We find that the use of sapphire substrate provides better accuracy of metasurface segments due to high thermal conductivity. The adv

Qi Wang, Andrii V. Chumak, Philipp Pirro

The field of magnonics offers a new type of low-power information processing, in which magnons, the quanta of spin waves, carry and process data instead of electrons. Many magnonic devices were demonstrated recently, but the development of each of them requires specialized investigations and, usually, one device design is suitable for one function only. Here

Parisa Karimi, Mark Butala, Zhizhen Zhao, Farzad Kamalabadi

The computation required for a switching Kalman Filter (SKF) increases exponentially with the number of system operation modes. In this paper, a computationally tractable graph representation is proposed for a switching linear dynamic system (SLDS) along with the solution of a minimum-sum optimization problem for clustering to reduce the switching mode cardi

Parisa Karimi, Zhizhen Zhao, Mark Butala, Farzad Kamalabadi

Switching Kalman Filters (SKF) are well known for their ability to solve the piecewise linear dynamic system estimation problem using the standard Kalman Filter (KF). Practical SKFs are heuristic, approximate filters that are not guaranteed to have optimal performance and require more computational resources than a single mode KF. On the other hand, applying

Matyas Barczy, Gyula Pap

We establish multidimensional analogues of one-dimensional stable limit theorems due to H\"ausler and Luschgy (2015) for so called explosive processes. As special cases we present multidimensional stable limit theorems involving multidimensional normal-, Cauchy- and stable distributions as well.

Ioanna Miliou, Xinyue Xiong, Salvatore Rinzivillo, Qian Zhang

Increased availability of epidemiological data, novel digital data streams, and the rise of powerful machine learning approaches have generated a surge of research activity on real-time epidemic forecast systems. In this paper, we propose the use of a novel data source, namely retail market data to improve seasonal influenza forecasting. Specifically, we con

Andrea Gagna, Yonatan Harpaz, Edoardo Lanari

We study four types of (co)cartesian fibrations of $\infty$-bicategories over a given base $\mathcal{B}$, and prove that they encode the four variance flavors of $\mathcal{B}$-indexed diagrams of $\infty$-categories. We then use this machinery to set up a general theory of 2-(co)limits for diagrams valued in an $\infty$-bicategory, capable of expressing lax,

Seyed Mostafa Moniri, Heshmatollah Yavari, Elnaz Darsheshdar

The $p$-wave superfluid state is a promising spin-triplet and non $s$-wave pairing state in an ultracold Fermi gas. In this work we study the low-temperature shear viscosity of a one-component $p$-wave superfluid Fermi gas, by means of Kubo formalism. Our study is done in the strong-coupling limit where Fermi superfluid reduces into a system of composite bos

Patrick J. Fox, Shangqing Huang, Joshua Isaacson, Xiangyang Ju

Tracking is one of the most time consuming aspects of event reconstruction at the Large Hadron Collider (LHC) and its high-luminosity upgrade (HL-LHC). Innovative detector technologies extend tracking to four-dimensions by including timing in the pattern recognition and parameter estimation. However, present and future hardware already have additional inform

Eve M. Vavagiakis, Zeeshan Ahmed, Aamir Ali, Kam Arnold

The Simons Observatory (SO) will be a cosmic microwave background (CMB) survey experiment with three small-aperture telescopes and one large-aperture telescope, which will observe from the Atacama Desert in Chile. In total, SO will field $\sim$70,000 transition-edge sensor (TES) bolometers in six spectral bands centered between 27 and 280 GHz in order to ach

Petter Brändén

We prove that projective spaces of Lorentzian and real stable polynomials are homeomorphic to closed Euclidean balls. This solves a conjecture of June Huh and the author. The proof utilizes and refines a connection between the symmetric exclusion process in Interacting Particle Systems and the geometry of polynomials.

Lingbo Liu, Jiaqi Chen, Hefeng Wu, Guanbin Li

Crowd counting is a fundamental yet challenging task, which desires rich information to generate pixel-wise crowd density maps. However, most previous methods only used the limited information of RGB images and cannot well discover potential pedestrians in unconstrained scenarios. In this work, we find that incorporating optical and thermal information can g

Gaspard Junot, Eric Clément, Harold Auradou, Reinaldo García-García

We develop a maximum likelihood method to infer relevant physical properties of elongated active particles. Using individual trajectories of advected swimmers as input, we are able to accurately determine their rotational diffusion coefficients and an effective measure of their aspect ratio, also providing reliable estimators for the uncertainties of such qu

Fernando Cruz-Roldán, Wallace A. Martins, Fausto García G., Marc Moonen

A new unified formulation for seven different orthogonal frequency-division multiplexing (OFDM) systems is presented. The proposed formulation relies on six parameters and encompasses conventional OFDM systems, with windowing in the transmitter and/or in the receiver, and also with a cyclic prefix (CP) or both a CP and cyclic suffix (CS). A new equivalent ch

Antoine Maillard, Florent Krzakala, Yue M. Lu, Lenka Zdeborová

We consider the phase retrieval problem, in which the observer wishes to recover a $n$-dimensional real or complex signal $\mathbf{X}^\star$ from the (possibly noisy) observation of $|\mathbf{\Phi} \mathbf{X}^\star|$, in which $\mathbf{\Phi}$ is a matrix of size $m \times n$. We consider a \emph{high-dimensional} setting where $n,m \to \infty$ with $m/n = \m

Jiarui Gan, Bo Li, Yingkai Li

We study a fair resource sharing problem, where a set of resources are to be shared among a group of agents. Each agent demands one resource and each resource can serve a limited number of agents. An agent cares about what resource they get as well as the externalities imposed by their mates, who share the same resource with them. Clearly, the strong notion

Nicole Bäuerle, Alexander Glauner

We study the minimization of a spectral risk measure of the total discounted cost generated by a Markov Decision Process (MDP) over a finite or infinite planning horizon. The MDP is assumed to have Borel state and action spaces and the cost function may be unbounded above. The optimization problem is split into two minimization problems using an infimum repr

Katherine Baker, Lehel Banjai

We study a wave equation with a nonlocal time fractional damping term that models the effects of acoustic attenuation characterized by a frequency dependence power law. First we prove existence of a unique solution to this equation with particular attention paid to the handling of the fractional derivative. Then we derive an explicit time stepping scheme bas

Guillaume Chapuy, Theo Douvropoulos

We prove universal (case-free) formulas for the weighted enumeration of factorizations of Coxeter elements into products of reflections valid in any well-generated reflection group $W$, in terms of the spectrum of an associated operator, the $W$-Laplacian. This covers in particular all finite Coxeter groups. The results of this paper include generalizations

Ekaterina Kotliarova, Alexander Gasnikov, Evgenia Gasnikova, Demyan Yarmoshik

Authors describe a two-stage traffic assignment model. It contains of two blocks. The first block consists of model for calculating correspondence (demand) matrix, whereas the second block is a traffic assignment model. The first model calculates a matrix of correspondences using a matrix of transport costs. It characterizes the required volumes of movement

Omer Dahary, Matan Jacoby, Alex M. Bronstein

Mechanical image stabilization using actuated gimbals enables capturing long-exposure shots without suffering from blur due to camera motion. These devices, however, are often physically cumbersome and expensive, limiting their widespread use. In this work, we propose to digitally emulate a mechanically stabilized system from the input of a fast unstabilized

Radu Horaud, Matti Niskanen, Guillaume Dewaele, Edmond Boyer

We address the problem of human motion tracking by registering a surface to 3-D data. We propose a method that iteratively computes two things: Maximum likelihood estimates for both the kinematic and free-motion parameters of a kinematic human-body representation, as well as probabilities that the data are assigned either to a body part, or to an outlier clu

Franca Manghi

We study the effects of e-e interaction in a 3D Crystalline Topological Insulator by adding on-site repulsion to the single-particle Hamiltonian and solving the many-body problem within Cluster Perturbation Theory. The goal is to clarify how many body effects modify the topological phase that stems from the crystal symmetries. Tuning the strength of the on-s

Yiqing Liang, Boyuan Chen, Shuran Song

This paper focuses on visual semantic navigation, the task of producing actions for an active agent to navigate to a specified target object category in an unknown environment. To complete this task, the algorithm should simultaneously locate and navigate to an instance of the category. In comparison to the traditional point goal navigation, this task requir

Maitreyee Wairagkar, Maria R Lima, Daniel Bazo, Richard Craig

We introduce the conceptual formulation, design, fabrication, control and commercial translation with IoT connection of a hybrid-face social robot and validation of human emotional response to its affective interactions. The hybrid-face robot integrates a 3D printed faceplate and a digital display to simplify conveyance of complex facial movements while prov

Tatsuro Kawamoto, Takaaki Aoki, Michiko Ueda

The COVID-19 pandemic is an unprecedented public health crisis with broad social and economic consequences. We conducted four surveys between April and August 2020 using the graph-based open-ended survey (GOS) framework, and investigated the most pressing concerns and issues for the general public in Japan. The GOS framework is a hybrid of the two traditiona

Doan The Hieu, Nguyen Thi My Duyen

In this paper, we generalize some halfspace type theorems for self-shrinkers of codimension 1 to the case of arbitrary codimension.

Tal Horesh, Yakov Karasik

We count primitive lattices of rank $d$ inside $\mathbb{Z}^{n}$ as their covolume tends to infinity, with respect to certain parameters of such lattices. These parameters include, for example, the subsapce that a lattice spans, namely its projection to the Grassmannian; its homothety class; and its equivalence class modulo rescaling and rotation, often refer

Renata Ferrero, Roberto Percacci

We construct a general effective dynamics for diffeomorphisms of spacetime, in a fixed external metric. Though related to familiar models of scalar fields as coordinates, our models have subtly different properties, both at kinematical and dynamical level. The energy-momentum tensor consists of two independently conserved parts. The background solution is th

Nicholas Syring, Ryan Martin

Bayesian posterior distributions are widely used for inference, but their dependence on a statistical model creates some challenges. In particular, there may be lots of nuisance parameters that require prior distributions and posterior computations, plus a potentially serious risk of model misspecification bias. Gibbs posterior distributions, on the other ha

Michele Maris, Erik Romelli, Maurizio Tomasi, Anna Gregorio

We present new estimates of the brightness temperatures of Jupiter, Saturn, Uranus, and Neptune based on the measurements carried in 2009--2013 by PLANCK/LFI at 30, 44, and 70 GHz and released to the public in 2018. This work extends the results presented in the 2013 and 2015 PLANCK/LFI Calibration Papers, based on the data acquired in 2009--2011. PLANCK obs

Zejian Li, Ariane Soret, Cristiano Ciuti

We propose a photonic quantum simulator for anti-ferromagnetic spin systems based on reservoir engineering. We consider a scheme where quadratically driven dissipative Kerr cavities are indirectly coupled via lossy ancillary cavities. We show that the ancillary cavities can produce an effective dissipative and Hamiltonian anti-ferromagnetic-like coupling bet

Silvana Pesenti, Sebastian Jaimungal

We study the problem of active portfolio management where an investor aims to outperform a benchmark strategy's risk profile while not deviating too far from it. Specifically, an investor considers alternative strategies whose terminal wealth lie within a Wasserstein ball surrounding a benchmark's -- being distributionally close -- and that have a specified

Eleftherios Moschandreou, Brian J. Rollick, Bing Qi, George Siopsis

In free-space Quantum Key Distribution in turbulent conditions, scattering and beam wandering cause intensity fluctuations which increase the detected signal-to-noise ratio. This effect can be mitigated by rejecting received bits when the channel's transmittance is below a threshold. Thus, the overall error rate is reduced and the secure key rate increases d

Qi Yao

Let $G$ be a simply-connected semisimple compact Lie group, $X$ a compact K\"ahler manifold homogeneous under $G$, and $L$ a negative $G$-equivariant holomorphic line bundle over $X$. We prove that all $G$-invariant K\"ahler metrics on the total space of $L$ arise from the Calabi ansatz. Using this, we then show that there exists a unique $G$-invariant scala

Shoukang Hu, Xurong Xie, Shansong Liu, Jianwei Yu

Discriminative training techniques define state-of-the-art performance for automatic speech recognition systems. However, they are inherently prone to overfitting, leading to poor generalization performance when using limited training data. In order to address this issue, this paper presents a full Bayesian framework to account for model uncertainty in seque

Peitao Liu, Carla Verdi, Ferenc Karsai, Georg Kresse

The accurate prediction of solid-solid structural phase transitions at finite temperature is a challenging task, since the dynamics is so slow that direct simulations of the phase transitions by first-principles (FP) methods are typically not possible. Here, we study the $\alpha$-$\beta$ phase transition of Zr at ambient pressure by means of on-the-fly machi

Sandeep Silwal

We give a concentration inequality for a stochastic version of the facility location problem. We show the objective $C_n = \min_{F \subseteq [0,1]^2}|F|+\sum_{x\in X}\min_{f\in F}\|x-f\|$ is concentrated in an interval of length $O(n^{1/6})$ and $\E[C_n]=\Theta(n^{2/3})$ if the input $X$ consists of i.i.d. uniform points in the unit square. Our main tool is

Maximiliano Isi, Will M. Farr, Matthew Giesler, Mark A. Scheel

We present observational confirmation of Hawking's black-hole area theorem based on data from GW150914, finding agreement with the prediction with 97% (95%) probability when we model the ringdown including (excluding) overtones of the quadrupolar mode. We obtain this result from a new time-domain analysis of the pre- and postmerger data. We also confirm that

Haoning Chen, Miaomiao Dong, Marc Henry, Ivan Sidorov

We propose a model of labor market sector self-selection that combines comparative advantage, as in the Roy model, and sector composition preference. Two groups choose between two sectors based on heterogeneous potential incomes and group compositions in each sector. Potential incomes incorporate group specific human capital accumulation and wage discriminat

Minquan Cheng, Kai Wan, Dequan Liang, Mingming Zhang

This paper considers the multiaccess coded caching systems formulated by Hachem et al., including a central server containing $N$ files connected to $K$ cache-less users through an error-free shared link, and $K$ cache-nodes, each equipped with a cache memory size of $M$ files. Each user has access to $L$ neighbouring cache-nodes with a cyclic wrap-around to

I. Krichever, A. Zabrodin

A characterization of the Kadomtsev-Petviashvili hierarchy of type C (CKP) in terms of the KP tau-function is given. Namely, we prove that the CKP hierarchy can be identified with the restriction of odd times flows of the KP hierarchy on the locus of turning points of the second flow. The notion of CKP tau-function is clarified and connected with the KP tau

Andrei Militaru, Max Innerbichler, Martin Frimmer, Felix Tebbenjohanns

Rare transitions between long-lived metastable states underlie a great variety of physical, chemical and biological processes. Our quantitative understanding of reactive mechanisms has been driven forward by the insights of transition state theory. In particular, the dynamic framework developed by Kramers marks an outstanding milestone for the field. Its pre

Mariia Seleznova, Gitta Kutyniok

Neural Tangent Kernel (NTK) theory is widely used to study the dynamics of infinitely-wide deep neural networks (DNNs) under gradient descent. But do the results for infinitely-wide networks give us hints about the behavior of real finite-width ones? In this paper, we study empirically when NTK theory is valid in practice for fully-connected ReLU and sigmoid

Isaiah Hull, Or Sattath, Eleni Diamanti, Göran Wendin

Research on quantum technology spans multiple disciplines: physics, computer science, engineering, and mathematics. The objective of this manuscript is to provide an accessible introduction to this emerging field for economists that is centered around quantum computing and quantum money. We proceed in three steps. First, we discuss basic concepts in quantum

Bililign T. Dullo, Armando Gil de Paz, Johan H. Knapen

[Abridged] We investigate the nature of the relations between black hole (BH) mass ($M_{\rm BH}$) and the central velocity dispersion ($\sigma$) and, for core-S\'ersic galaxies, the size of the depleted core ($R_{\rm b}$). Our sample of 144 galaxies with dynamically determined $M_{\rm BH}$ encompasses 24 core-S\'ersic galaxies, thought to be products of gas-

Osmel Martínez Rosabal, Onel L. Alcaraz López, Hirley Alves, Samuel Montejo-Sánchez

Wireless energy transfer (WET) is emerging as an enabling green technology for Internet of Things (IoT) networks. WET allows the IoT devices to wirelessly recharge their batteries with energy from external sources such as dedicated radio frequency transmitters called power beacons (PBs). In this paper, we investigate the optimal deployment of PBs that guaran

Absos Ali Shaikh, Antonio W. Cunha, Prosenjit Mandal

In this article we have showed that a gradient $\rho$-Einstein soliton with a vector field of bounded norm and satisfying some other conditions is isometric to the Euclidean sphere. Later, we have proved that a non-trivial complete gradient $\rho$-Einstein soliton with finite weighted Dirichlet integral and certain restriction on Ricci curvature must be of c

Suzanne Thornton, Minge Xie

Bayesian, frequentist and fiducial (BFF) inferences are much more congruous than they have been perceived historically in the scientific community (cf., Reid and Cox 2015; Kass 2011; Efron 1998). Most practitioners are probably more familiar with the two dominant statistical inferential paradigms, Bayesian inference and frequentist inference. The third, less

Bo-Cheng Yang, Liang Tang, Cong-Feng Qiao

Very recently, the LHCb Collaboration observed distinct structures with the $cc\bar{c}\bar{c}$ in the $J/\Psi$-pair mass spectrum. In this work, we construct four scalar ($J^{PC} = 0^{++}$) $[8_c]_{Q\bar{Q^\prime}}\otimes [8_c]_{Q^\prime \bar{Q}}$ type currents to investigate the fully-heavy tetraquark state $Q Q^\prime \bar{Q} \bar{Q^\prime}$ in the framewo

Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor

Deep neural networks trained with standard cross-entropy loss memorize noisy labels, which degrades their performance. Most research to mitigate this memorization proposes new robust classification loss functions. Conversely, we propose a Multi-Objective Interpolation Training (MOIT) approach that jointly exploits contrastive learning and classification to m

Jiongzhi Zheng, Kun He, Jianrong Zhou, Yan Jin

We address the Traveling Salesman Problem (TSP), a famous NP-hard combinatorial optimization problem. And we propose a variable strategy reinforced approach, denoted as VSR-LKH, which combines three reinforcement learning methods (Q-learning, Sarsa and Monte Carlo) with the well-known TSP algorithm, called Lin-Kernighan-Helsgaun (LKH). VSR-LKH replaces the i

A. Asensio Ramos, E. Pallé

Finding potential life harboring exo-Earths is one of the aims of exoplanetary science. Detecting signatures of life in exoplanets will likely first be accomplished by determining the bulk composition of the planetary atmosphere via reflected/transmitted spectroscopy. However, a complete understanding of the habitability conditions will surely require mappin

Magdalena Grzeszczyk, Katarzyna Olkowska-Pucko, Kenji Watanabe, Takashi Taniguchi

Atomically thin materials, like semiconducting transition metal dichalcogenides, are highly sensitive to the environment. This opens up an opportunity to externally control their properties by changing their surroundings. In this work, high-quality van der Waals heterostructures assembled from hBN-encapsulated monolayer MoS$_2$ are studied with the aid of ph

Yingfan Wang, Haiyang Huang, Cynthia Rudin, Yaron Shaposhnik

Dimension reduction (DR) techniques such as t-SNE, UMAP, and TriMAP have demonstrated impressive visualization performance on many real world datasets. One tension that has always faced these methods is the trade-off between preservation of global structure and preservation of local structure: these methods can either handle one or the other, but not both. I

Paul-Gauthier Noé, Mohammad Mohammadamini, Driss Matrouf, Titouan Parcollet

In speech technologies, speaker's voice representation is used in many applications such as speech recognition, voice conversion, speech synthesis and, obviously, user authentication. Modern vocal representations of the speaker are based on neural embeddings. In addition to the targeted information, these representations usually contain sensitive information

Stefano D'Alesio

In this paper we propose a procedure for a noncommutative derived Poisson reduction, in the spirit of the Kontsevich-Rosenberg principle: "a noncommutative structure of some kind on $A$ should give an analogous commutative structure on all schemes ${\mathrm{Rep}}_n(A)$". We use double Poisson structures as noncommutative Poisson structures and noncommutative

Emel Altas, Bayram Tekin

We construct analytical initial data for a slowly moving and rotating black hole for generic orientations of the linear momentum and the spin. We solve the Hamiltonian constraint approximately and work out the properties of the apparent horizon and show the dependence of its shape on the angle between the spin and the linear momentum. In particular a dimple,

Antonio Agresti, Mark Veraar

This paper is a continuation of Part I of this project, where we developed a new local well-posedness theory for nonlinear stochastic PDEs with Gaussian noise. In the current Part II we consider blow-up criteria and regularization phenomena. As in Part I we can allow nonlinearities with polynomial growth, and rough initial values from critical spaces. In the

Amit Saha, Ritajit Majumdar, Debasri Saha, Amlan Chakrabarti

The progress in building quantum computers to execute quantum algorithms has recently been remarkable. Grover's search algorithm in a binary quantum system provides considerable speed-up over classical paradigm. Further, Grover's algorithm can be extended to a $d$-ary (qudit) quantum system for utilizing the advantage of larger state space, which helps to re

Loris Arnold, Christian Le Merdy

We introduce a new Banach algebra ${\mathcal A}({\mathbb C}_+)$ of bounded analytic functions on ${\mathbb C}_+=\{z\in{\mathbb C}\, :\, {\rm Re}(z)>0\}$ which is an analytic version of the Figa-Talamenca-Herz algebras on ${\mathbb R}$. Then we prove that the negative generator $A$ of any bounded $C_0$-semigroup on Hilbert space $H$ admits a bounded (natural)

Xinhai Liu, Xinchen Liu, Yu-Shen Liu, Zhizhong Han

The task of point cloud upsampling aims to acquire dense and uniform point sets from sparse and irregular point sets. Although significant progress has been made with deep learning models, state-of-the-art methods require ground-truth dense point sets as the supervision, which makes them limited to be trained under synthetic paired training data and not suit

Yi Liu, Ruihui Zhao, Jiawen Kang, Abdulsalam Yassine

Federated Edge Learning (FEL) allows edge nodes to train a global deep learning model collaboratively for edge computing in the Industrial Internet of Things (IIoT), which significantly promotes the development of Industrial 4.0. However, FEL faces two critical challenges: communication overhead and data privacy. FEL suffers from expensive communication over

Dmitri Burago, Sergei Ivanov, Matti Lassas, Jinpeng Lu

In Gel'fand's inverse problem, one aims to determine the topology, differential structure and Riemannian metric of a compact manifold $M$ with boundary from the knowledge of the boundary $\partial M,$ the Neumann eigenvalues $\lambda_j$ and the boundary values of the eigenfunctions $\varphi_j|_{\partial M}$. We show that this problem has a stable solution wi

Linbin Huang, Jianzhe Zhen, John Lygeros, Florian Dörfler

Data-driven control that circumvents the process of system identification by providing optimal control inputs directly from system data has attracted renewed attention in recent years. In this paper, we focus on understanding the effects of the regularization on the data-enabled predictive control (DeePC) algorithm. We provide theoretical motivation and inte

Yi Liu, Xingliang Yuan, Ruihui Zhao, Cong Wang

Semi-supervised Federated Learning (SSFL) has recently drawn much attention due to its practical consideration, i.e., the clients may only have unlabeled data. In practice, these SSFL systems implement semi-supervised training by assigning a "guessed" label to the unlabeled data near the labeled data to convert the unsupervised problem into a fully supervise

Vincent Caudrelier, Matteo Stoppato, Benoit Vicedo

We derive the $2$d Zakharov-Mikhailov action from $4$d Chern-Simons theory. This $2$d action is known to produce as equations of motion the flatness condition of a large class of Lax connections of Zakharov-Shabat type, which includes an ultralocal variant of the principal chiral model as a special case. At the $2$d level, we determine for the first time the

Tsz-Kiu Aaron Chow

In this paper, we study the Ricci flow on manifolds with boundary. In the first part of the paper, we prove short-time existence and uniqueness of the solution, in which the boundary becomes instantaneously umbilic for positive time. In the second part of the paper, we prove that the flow we constructed in the first part preserves natural boundary conditions

Kenji Kubo, Yuya O. Nakagawa, Suguru Endo, Shota Nagayama

Stochastic differential equations (SDEs), which models uncertain phenomena as the time evolution of random variables, are exploited in various fields of natural and social sciences such as finance. Since SDEs rarely admit analytical solutions and must usually be solved numerically with huge classical-computational resources in practical applications, there i

Opeoluwa Owoyele, Pinaki Pal

A novel design optimization approach (ActivO) that employs an ensemble of machine learning algorithms is presented. The proposed approach is a surrogate-based scheme, where the predictions of a weak leaner and a strong learner are utilized within an active learning loop. The weak learner is used to identify promising regions within the design space to explor

Dimitris Bertsimas, Stefan ten Eikelder, Dick den Hertog, Nikolaos Trichakis

We formalize the concept of Pareto Adaptive Robust Optimality (PARO) for linear Adaptive Robust Optimization (ARO) problems. A worst-case optimal solution pair of here-and-now decisions and wait-and-see decisions is PARO if it cannot be Pareto dominated by another solution, i.e., there does not exist another such pair that performs at least as good in all sc

Lu Zhang, Xian-Wei Kang, Xin-Heng Guo, Ling-Yun Dai

The semileptonic decay of heavy flavor mesons offers a clean environment for extraction of the Cabibbo-Kobayashi-Maskawa (CKM) matrix elements, which describes the CP-violating and flavor changing process in the Standard Model. The involved form factors where the dynamical information is encoded play an essential role in achieving any conclusive statement. T

Michael Hallam

We derive the geodesic equation for relatively K\"ahler metrics on fibrations and prove that any two such metrics with fibrewise constant scalar curvature are joined by a unique smooth geodesic. We then show convexity of the log-norm functional for this setting along geodesics, which yields simple proofs of Dervan and Sektnan's uniqueness result for optimal

Yalong Cao, Feng Qu

We prove a conjectural correspondence of Cao-Maulik-Toda which relates Gopakumar-Vafa invariants of fiber classes on a smooth projective Calabi-Yau 4-fold fibered over a curve to the Gopakumar-Vafa invariants of a smooth fiber under an orientation compatibility assumption on the moduli spaces.

T. Mariz, R. Martinez, J. R. Nascimento, A. Yu. Petrov

In this paper, we apply the functional integral methodology to induce the Carroll-Field-Jackiw (CFJ) term in Horava-Lifshitz $z=3$ CPT-violating QED, where Lorentz and CPT breaking for fermion and photon sectors is introduced, and show that the CFJ term is finite but undetermined.