December 2020 arXiv papers — page 117

Tianyi Zhao, Kai Cao, Jiawen Yao, Isabella Nogues

The pancreatic disease taxonomy includes ten types of masses (tumors or cysts)[20,8]. Previous work focuses on developing segmentation or classification methods only for certain mass types. Differential diagnosis of all mass types is clinically highly desirable [20] but has not been investigated using an automated image understanding approach. We exploit the

Khuong Nguyen, Yoonsuck Choe

Tool use is an important milestone in the evolution of intelligence. In this paper, we investigate different modes of tool use that emerge in a reaching and dragging task. In this task, a jointed arm with a gripper must grab a tool (T, I, or L-shaped) and drag an object down to the target location (the bottom of the arena). The simulated environment had real

Daniel L. Felps, Amelia D. Schwickerath, Joyce D. Williams, Trung N. Vuong

Individuals are gaining more control of their personal data through recent data privacy laws such the General Data Protection Regulation and the California Consumer Privacy Act. One aspect of these laws is the ability to request a business to delete private information, the so called "right to be forgotten" or "right to erasure". These laws h

Zachary Stier

Parzanchevski and Sarnak recently adapted an algorithm of Ross and Selinger for factorization of PU(2)-diagonal elements to within distance $\varepsilon$ into an efficient probabilistic algorithm for any PU(2)-element, using at most $3\log_p\frac{1}{\varepsilon^3}$ factors from certain well-chosen sets. The Clifford+$T$ gates are one such set arising from $p

Yohsuke Matsuzawa

Assuming Vojta's conjecture, we give a sufficient condition for the limit \[ \lim_{n \to \infty} \frac{h_{Y}(f^{n}(x))}{h_{H}(f^{n}(x))} \] is equal to zero, where $f \colon X \longrightarrow X$ is a surjective self-morphism on a smooth projective variety $X$, $h_{H}$ is an ample height function on $X$, and $h_{Y}$ is a global height function associated

Amish Goel, Pierre Moulin

Deep learning image classifiers are known to be vulnerable to small adversarial perturbations of input images. In this paper, we derive the locally optimal generalized likelihood ratio test (LO-GLRT) based detector for detecting stochastic targeted universal adversarial perturbations (UAPs) of the classifier inputs. We also describe a supervised training met

Charuhas Shiveshwarkar, Drew Jamieson, Marilena Loverde

We investigate the gravitational effect of large-scale radiation perturbations on small-scale structure formation. In addition to making the growth of matter perturbations scale dependent, the free-streaming of radiation also affects the coupling between structure formation at small and large scales. We study this using Separate Universe N-body simulations t

Goran Banjac, Jianzhe Zhen, Dick den Hertog, John Lygeros

Various control schemes rely on a solution of a convex optimization problem involving a particular robust quadratic constraint, which can be reformulated as a linear matrix inequality using the well-known $\mathcal{S}$-lemma. However, the computational effort required to solve the resulting semidefinite program may be prohibitively large for real-time applic

Andrea Camposeo, Francesca D'Elia, Alberto Portone, Francesca Matino

Combined dry-wet transient materials and devices are introduced, which are based on water-dissolvable dye-doped polymers layered onto non-polar cyclic hydrocarbon sublimating substrates. Light-emitting heterostructures showing amplified spontaneous emission are used as illumination sources for speckle-free, full-field imaging, and transient optical labels ar

M. S. Hernandez, M. R. Schreiber, S. G. Parsons, B. T. Gansicke

Constraints from surveys of post common envelope binaries (PCEBs) consisting of a white dwarf plus an M-dwarf companion have led to significant progress in our understanding of the formation of close white dwarf binary stars with low-mass companions. The white dwarf binary pathways project aims at extending these previous surveys to larger secondary masses,

Aditya Mantha, Anirudha Sundaresan, Shashank Kedia, Yokila Arora

E-commerce platforms consistently aim to provide personalized recommendations to drive user engagement, enhance overall user experience, and improve business metrics. Most e-commerce platforms contain multiple carousels on their homepage, each attempting to capture different facets of the shopping experience. Given varied user preferences, optimizing the pla

Lisa Wölfer, Stefano Facchini, Nicolas T. Kurtovic, Richard Teague

In the past years, high angular resolution observations have revealed that circumstellar discs appear in a variety of shapes with diverse substructures being ubiquitous. This has given rise to the question of whether these substructures are triggered by planet-disc interactions. Besides direct imaging, one of the most promising methods to distinguish between

Roberto Decarli, Fabrizio Arrigoni-Battaia, Joseph F. Hennawi, Fabian Walter

Enormous Ly$α$ nebulae, extending over 300-500\,kpc around quasars, represent the pinnacle of galaxy and cluster formation. Here we present IRAM Plateau de Bure Interferometer observations of the enormous Ly$α$ nebulae `Slug' ($z$=$2.282$) and `Jackpot' ($z$=$2.041$). Our data reveal bright, synchrotron emission associated with the two radio-loud AGN

Arnab Chakraborty, Abhirup Datta, Nirupam Roy, Somnath Bharadwaj

Measurement of fluctuations in diffuse HI 21 cm background radiation from the post-reionization epoch (z < 6) is a promising avenue to probe the large-scale structure of the Universe and understand the evolution of galaxies. We observe the European Large-Area ISO Survey-North 1 (ELAIS-N1) field at 300-500 MHz using the upgraded Giant Meterwave Radio Telescop

Daniel Sheinbaum

There is a lack of knowledge about the topological invariants of non-linear $d$-dimensional systems with a periodic potential. We study these systems through a classification of the linearized NLS/GP equation around their soliton solutions. Stability conditions under linearized (mode) adiabatic evolution can be interpreted topologically and we can use equiva

Michela Rigoselli, Sandro Mereghetti, Roberto Taverna, Roberto Turolla

The radio-quiet pulsar PSR J2021+4026 is mostly known because it is the only rotation-powered pulsar that shows variability in its γ-ray emission. Using XMM-Newton archival data, we first confirmed that its flux is steady in the X-ray band, and then we showed that both the spectral and timing X-ray properties, i.e. the narrow pulse profile, the high pulsed f

Benjamin D. Boizelle, Jonelle L. Walsh, Aaron J. Barth, David A. Buote

We present Atacama Large Millimeter/submillimeter Array (ALMA) Cycle 5 and Cycle 6 observations of CO(2$-$1) and CO(3$-$2) emission at 0.2&#39;&#39;$-$0.3&#39;&#39; resolution in two radio-bright, brightest group/cluster early-type galaxies, NGC 315 and NGC 4261. The data resolve CO emission that extends within their black hole (BH) spheres of influence ($r_

Christopher M. Carroll, Ryan C. Hickox, Alberto Masini, Lauranne Lanz

We present a large sample of infrared-luminous candidate active galactic nuclei (AGNs) that lack X-ray detections in Chandra, XMM-Newton, and NuSTAR fields. We selected all optically detected SDSS sources with redshift measurements, combined additional broadband photometry from WISE, UKIDSS, 2MASS, and GALEX, and modeled the spectral energy distributions (SE

Wei Gu, Jirui Guo, Yaoxiong Wen

We propose Picard-Fuchs equations for periods of nonabelian mirrors in this paper. The number of parameters in our Picard-Fuchs equations is the rank of the gauge group of the nonabelian GLSM, which is eventually reduced to the actual number of Kähler parameters. These Picard-Fuchs equations are concise and novel. We justify our proposal by reproducing exist

Derek S. Wang, Tomáš Neuman, Prineha Narang

Control over transition rates between spin states of emitters is crucial in a wide variety of fields ranging from quantum information science to the nanochemistry of free radicals. We present an approach to drive a both electric and magnetic dipole-forbidden transition of a spin emitter by placing it in a nanomagnonic cavity, requiring a description of both

Adrian Bittner, Adriana de Lorenzo-Cáceres, Dimitri A. Gadotti, Patricia Sánchez-Blázquez

Inner bars are frequent structures in the local Universe and thought to substantially influence the nuclear regions of disc galaxies. In this study we explore the structure and dynamics of inner bars by deriving maps and radial profiles of their mean stellar population content and comparing them to previous findings in the context of main bars. To this end,

George N. Wong, Benjamin R. Ryan, Charles F. Gammie

Electron-positron pair creation near sub-Eddington accretion rate black holes is believed to be dominated by the Breit-Wheeler process (photon-photon collisions). The interacting high energy photons are produced when unscreened electric fields accelerate leptons either in coherent, macroscopic gaps or in incoherent structures embedded in the turbulent plasma

Chris Nixon, Jim Pringle

Be stars are rapidly rotating B stars with Balmer emission lines that indicate the presence of a Keplerian, rotationally supported, circumstellar gas disc. Current disc models, referred to as &#34;decretion discs&#34;, make use of the zero torque inner boundary condition typically applied to accretion discs, with the &#39;decretion&#39; modelled by adding ma

Kun Qian, Bjorn W. Schuller, Yoshiharu Yamamoto

Computer audition (CA) has been demonstrated to be efficient in healthcare domains for speech-affecting disorders (e.g., autism spectrum, depression, or Parkinson&#39;s disease) and body sound-affecting abnormalities (e. g., abnormal bowel sounds, heart murmurs, or snore sounds). Nevertheless, CA has been underestimated in the considered data-driven technolo

Alexander V. Lapinov, Svetlana A. Lapinova, Leonid Yu. Petrov, Daniel Ferrusca

Thanks to the first mm studies on the territory of the former USSR in the early 1960s and succeeding sub-mm measurements in the 1970s - early 1980s at wavelengths up to 0.34 mm, a completely unique astroclimate was revealed in the Eastern Pamirs, only slightly inferior to the available conditions on the Chajnantor plateau in Chile and Mauna Kea. Due to its h

Andrew Zic, Tara Murphy, Christene Lynch, George Heald

Studies of solar radio bursts play an important role in understanding the dynamics and acceleration processes behind solar space weather events, and the influence of solar magnetic activity on solar system planets. Similar low-frequency bursts detected from active M-dwarfs are expected to probe their space weather environments and therefore the habitability

Zhengyuan Yang, Yijuan Lu, Jianfeng Wang, Xi Yin

In this paper, we propose Text-Aware Pre-training (TAP) for Text-VQA and Text-Caption tasks. These two tasks aim at reading and understanding scene text in images for question answering and image caption generation, respectively. In contrast to the conventional vision-language pre-training that fails to capture scene text and its relationship with the visual

Abhijit Mahalunkar, John D. Kelleher

We present an approach to design the grid searches for hyper-parameter optimization for recurrent neural architectures. The basis for this approach is the use of mutual information to analyze long distance dependencies (LDDs) within a dataset. We also report a set of experiments that demonstrate how using this approach, we obtain state-of-the-art results for

Ramprasaath R. Selvaraju, Karan Desai, Justin Johnson, Nikhil Naik

Recent advances in self-supervised learning (SSL) have largely closed the gap with supervised ImageNet pretraining. Despite their success these methods have been primarily applied to unlabeled ImageNet images, and show marginal gains when trained on larger sets of uncurated images. We hypothesize that current SSL methods perform best on iconic images, and st

Áron Szabó Cedric Klinkert, Davide Campi, Christian Stieger, Nicola Marzari

Full-band atomistic quantum transport simulations based on first principles are employed to assess the potential of band-to-band tunneling FETs (TFETs) with a 2-D channel material as future electronic circuit components. We demonstrate that single-layer (SL) transition metal dichalcogenides are not well suited for TFET applications. There might, however, exi

Boubakr Nour, Hakima Khelifi, Rasheed Hussain, Spyridon Mastorakis

Information-Centric Networking (ICN) has recently emerged as a prominent candidate for the Future Internet Architecture (FIA) that addresses existing issues with the host-centric communication model of the current TCP/IP-based Internet. Named Data Networking (NDN) is one of the most recent and active ICN architectures that provides a clean slate approach for

Aleksandr Ivchenko, Pavel Kononyuk, Alexander Dvorkovich, Liubov Antiufrieva

Dynamic adaptive streaming over HTTP provides the work of most multimedia services, however, the nature of this technology further complicates the assessment of the QoE (Quality of Experience). In this paper, the influence of various objective factors on the subjective estimation of the QoE of streaming video is studied. The paper presents standard and handc

Nicolas Jouvin, Charles Bouveyron, Pierre Latouche

High-dimensional data clustering has become and remains a challenging task for modern statistics and machine learning, with a wide range of applications. We consider in this work the powerful discriminative latent mixture model, and we extend it to the Bayesian framework. Modeling data as a mixture of Gaussians in a low-dimensional discriminative subspace, a

John W. Noonan, Walter M. Harris, Steven Bromley, Davide Farnocchia

Far ultraviolet observations of comets yield information about the energetic processes that dissociate the sublimated gases from their primitive surfaces. Understanding which emission processes are dominant, their effects on the observed cometary spectrum, and how to properly invert the spectrum back to composition of the presumably pristine surface ices of

J. -F. Coupechoux, A. Arbey

The nature of dark matter and of dark energy which constitute more than $95\%$ of the energy in the Universe remains a great and unresolved question in cosmology. Cold dark matter can be made of an ultralight scalar field dominated by its mass term which interacts only gravitationally. The cosmological constant introduced to explain the recent acceleration o

Félix Musil, Michele Ceriotti

Statistical learning algorithms are finding more and more applications in science and technology. Atomic-scale modeling is no exception, with machine learning becoming commonplace as a tool to predict energy, forces and properties of molecules and condensed-phase systems. This short review summarizes recent progress in the field, focusing in particular on th

Joao Chakrian, Antonio de Padua Santos

Black holes have been a subject of investigation over years not only because they have interesting physical properties, but also because they seem to be the appropriate tool for studying gravity in quantum scale. Although a lot of effort has been made to understand the aspects of spacetime on the quantum scale, the approach which includes noncommutativity of

Christophe Kervazo, Nicolas Gillis, Nicolas Dobigeon

In this work, we tackle the problem of hyperspectral (HS) unmixing by departing from the usual linear model and focusing on a Linear-Quadratic (LQ) one. The proposed algorithm, referred to as Successive Nonnegative Projection Algorithm for Linear Quadratic mixtures (SNPALQ), extends the Successive Nonnegative Projection Algorithm (SNPA), designed to address

Susarla Raghuram, Anil Bhardwaj, Damien Hutsemékers, Cyrielle Opitom

The recent observations show that comet C/2016 R2 (Pan-Starrs) has a unique and peculiar composition when compared with several other comets observed at 2.8 au heliocentric distance. Assuming solar resonance fluorescence is the only excitation source, the observed ionic emission intensity ratios are used to constrain the corresponding neutral abundances in t

Faramarz Rahmani, Mehdi Golshani

In this study, we use the concept of Bohmian trajectories to present a dynamical and deterministic interpretation for the gravity induced wave function reduction. We shall classify all possible regimes for the motion of a particle, based on the behavior of trajectories in the ensemble and under the influence of quantum and gravitational forces. In the usual

Masfiqur Rahaman, MD. Nazmul Hasan Sakib, Nafisa Islam, Saiful Islam Salim

Using low-cost piezoelectric sensors to sense structural vibration exhibits great potential in augmenting structural engineering, which is yet to be explored in the literature to the best of our knowledge. Examples of such unexplored augmentation include classifying diverse structures (such as building, flyover, foot over-bridge, etc.), and relating the exte

Bernardo S. Mendoza, Lucila Juarez-Reyes, Benjamin M. Fregoso

We compute the spectrum of pure spin current injection in ferroelectric single-layer SnS, SnSe, GeS, and GeSe. The formalism takes into account the coherent spin dynamics of optically excited conduction states split in energy by spin orbit coupling. The velocity of spins is calculated as a function of incoming photon energy and angle of linearly polarized li

Mohammad Babaeizadeh, Mohammad Taghi Saffar, Danijar Hafner, Harini Kannan

Model-based reinforcement learning (MBRL) methods have shown strong sample efficiency and performance across a variety of tasks, including when faced with high-dimensional visual observations. These methods learn to predict the environment dynamics and expected reward from interaction and use this predictive model to plan and perform the task. However, MBRL

Lorenzo Rossi

The first law of black hole mechanics has been the main motivation for investigating thermodynamic properties of black holes. The first version of this law was proved in \cite{Bardeen:1973gs} by considering perturbations of an asymptotically flat, stationary black hole spacetime to other stationary black hole spacetimes. This result was then extended to full

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

Dirk Johannßen, Chris Biemann

The COVID-19 pandemic has caused international social tension and unrest. Besides the crisis itself, there are growing signs of rising conflict potential of societies around the world. Indicators of global mood changes are hard to detect and direct questionnaires suffer from social desirability biases. However, so-called implicit methods can reveal humans in

Stepan Zakharov, Omri Hadar, Tovit Hakak, Dina Grossman

Online discourse is often perceived as polarized and unproductive. While some conversational discourse parsing frameworks are available, they do not naturally lend themselves to the analysis of contentious and polarizing discussions. Inspired by the Bakhtinian theory of Dialogism, we propose a novel theoretical and computational framework, better suited for

M. -H. Chou, É. Dumur, Y. P. Zhong, G. A. Peairs

Phonon modes at microwave frequencies can be cooled to their quantum ground state using conventional cryogenic refrigeration, providing a convenient way to study and manipulate quantum states at the single phonon level. Phonons are of particular interest because mechanical deformations can mediate interactions with a wide range of different quantum systems,

Dmitry S. Shalymov, Oleg N. Granichin, Zeev Volkovich, Gerhard-Wilhelm Weber

This paper proposes a novel method for prevention of the increasing oscillation of an aircraft wing under the flexural torsion flutter. The paper introduces the novel multi-agent method for control of an aircraft wing, assuming that the wing surface consists of controlled &#39;feathers&#39; (agents). Theoretical evaluation of the approach demonstrates its hi

James Jordon, Alan Wilson, Mihaela van der Schaar

Many ground-breaking advancements in machine learning can be attributed to the availability of a large volume of rich data. Unfortunately, many large-scale datasets are highly sensitive, such as healthcare data, and are not widely available to the machine learning community. Generating synthetic data with privacy guarantees provides one such solution, allowi

Parichehr Behjati, Pau Rodriguez, Armin Mehri, Isabelle Hupont

Convolutional neural networks are the most successful models in single image super-resolution. Deeper networks, residual connections, and attention mechanisms have further improved their performance. However, these strategies often improve the reconstruction performance at the expense of considerably increasing the computational cost. This paper introduces a

Judit Acs, Andras Kornai

We examine the role of character patterns in three tasks: morphological analysis, lemmatization and copy. We use a modified version of the standard sequence-to-sequence model, where the encoder is a pattern matching network. Each pattern scores all possible N character long subwords (substrings) on the source side, and the highest scoring subword&#39;s score

Raul Corrêa, Pablo L. Saldanha

We perform a detailed study of the connection between hidden momentum and the Abraham-Minkowski debate about the electromagnetic momentum density in material media. The results of a previous work on the subject [P. L. Saldanha and J. S. Oliveira Filho, Phys. Rev. A 95, 043804 (2017)] are extended to the continuous medium limit, where some subtleties arise. W

Shuoyang Wang, Guanqun Cao, Zuofeng Shang

In this work, we propose a deep neural network method to perform nonparametric regression for functional data. The proposed estimators are based on sparsely connected deep neural networks with ReLU activation function. By properly choosing network architecture, our estimator achieves the optimal nonparametric convergence rate in empirical norm. Under certain

Matti Estola

During its history, the ultimate goal of economics has been to develop similar frameworks for modeling economic behavior as invented in physics. This has not been successful, however, and current state of the process is the neoclassical framework that bases on static optimization. By using a static framework, however, we cannot model and forecast the time pa

Adel Daoud, Devdatt Dubhashi

Two decades ago, Leo Breiman identified two cultures for statistical modeling. The data modeling culture (DMC) refers to practices aiming to conduct statistical inference on one or several quantities of interest. The algorithmic modeling culture (AMC) refers to practices defining a machine-learning (ML) procedure that generates accurate predictions about an

Chirag Srivastava, Ujjwal Sen

Dynamics of a system exhibits non-adiabaticity even for slow quenches near critical points. We analyze the response to disorder in quenches on a non-adiabaticity quantifier for the quantum Rabi model, which possesses a phase transition between normal and superradiant phases. We consider a disordered version of a quench in the Rabi model, in which the system

Jordi Zomer, Nikola Bešinović, Mathijs M. de Weerdt, Rob M. P. Goverde

Due to increasing railway use, the capacity at railway yards and maintenance locations is becoming limiting to accommodate existing rolling stock. To reduce capacity issues at maintenance locations during nighttime, railway undertakings consider performing more daytime maintenance, but the choice at which locations personnel needs to be stationed for daytime

Kasra Jamshidi, Keval Vora

Graph mining applications analyze the structural properties of large graphs, and they do so by finding subgraph isomorphisms, which makes them computationally intensive. Existing graph mining techniques including both custom graph mining applications and general-purpose graph mining systems, develop efficient execution plans to speed up the exploration of th

Alexander I. Zhdanok

General Markov chains in an arbitrary phase space are considered in the framework of the operator treatment. Markov operators continue from the space of countably additive measures to the space of finitely additive measures. Cycles of measures generated by the corresponding operator are constructed, and algebraic operations on them are introduced. One of the

M. M. Kupilas, C. J. Wareing, J. M. Pittard, S. A. E. G. Falle

Using the adaptive mesh refinement code MG, we perform hydrodynamic simulations of the interaction of a shock with a molecular cloud evolving due to thermal instability and gravity. To explore the relative importance of these processes, three case studies are presented. The first follows the formation of a molecular cloud out of an initially quiescent atomic

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

Abigail J. Lee, Wendy L. Freedman, Barry F. Madore, Kayla A. Owens

The local determination of the Hubble Constant sits at a crossroad. Current estimates of the local expansion rate of the Universe differ by about 1.7-sigma, derived from the Cepheid and TRGB based calibrations, applied to type Ia supernovae. To help elucidate possible sources of systematic error causing the tension, we show in this study the recently develop

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

Jan Kirchhof, Sebastian Semper, Christoph W. Wagner, Eduardo Pérez

In ultrasound nondestructive testing, a widespread approach is to take synthetic aperture measurements from the surface of a specimen to detect and locate defects within it. Based on these measurements, imaging is usually performed using the Synthetic Aperture Focusing Technique (SAFT). However, SAFT is sub-optimal in terms of resolution and requires oversam

A. B. Németh

Two retractions Q and R on closed convex cones M and respectively N of a Banach space are called mutually polar if Q+R=I and QR=RQ=0. This note investigates the existence of a pair of mutually polar retractions for given cones M and N. It is shown that if dim N=1 (or dim M=1) then the retractions are subadditive with respect to the order relation their cone

Masoumeh Izadparast, S. Habib Mazharimousavi

In this study, we introduce a two dimensional complex harmonic oscillator potential with space and time reflection symmetries. The corresponding time independent Schrödinger equation yields real eigenvalues with complex eigenfunctions. We also construct the coherent state of the system by using a superposition of 12 eigenfunctions. Using the complex correspo

Yuri Feigin, Hedva Spitzer, Raja Giryes

While GAN is a powerful model for generating images, its inability to infer a latent space directly limits its use in applications requiring an encoder. Our paper presents a simple architectural setup that combines the generative capabilities of GAN with an encoder. We accomplish this by combining the encoder with the discriminator using shared weights, then

Jia-Yu Chen, Chen Wang

For any $n\in\mathbb{N}=\{0,1,2,\ldots\}$ and $b,c\in\mathbb{Z}$, the generalized central trinomial coefficient $T_n(b,c)$ denotes the coefficient of $x^n$ in the expansion of $(x^2+bx+c)^n$. Let $p$ be an odd prime. In this paper, we determine the summation $\sum_{k=0}^{p-1}T_k(b,c)^2/m^k$ modulo $p^2$ for integers $m$ with certain restrictions. As applicat

Hadi Hosseini, Fatima Umar, Rohit Vaish

The deferred acceptance algorithm is an elegant solution to the stable matching problem that guarantees optimality and truthfulness for one side of the market. Despite these desirable guarantees, it is susceptible to strategic misreporting of preferences by the agents on the other side. We study a novel model of strategic behavior under the deferred acceptan

Tom Goodman, Karoline van Gemst, Peter Tino

This paper presents a geometric approach to pitch estimation (PE)-an important problem in Music Information Retrieval (MIR), and a precursor to a variety of other problems in the field. Though there exist a number of highly-accurate methods, both mono-pitch estimation and multi-pitch estimation (particularly with unspecified polyphonic timbre) prove computat

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

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

Victor Olkhov

We suggest use continuous numerical risk grades [0,1] of R for a single risk or the unit cube in Rn for n risks as the economic domain. We consider risk ratings of economic agents as their coordinates in the economic domain. Economic activity of agents, economic or other factors change agents risk ratings and that cause motion of agents in the economic domai

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

Razieh Ahmadian

The problem of toroidalization is to construct a toroidal lifting of a dominant morphism $φ:X\to Y$ of algebraic varieties by blowing up in the target and domain. This paper contains a solution to this problem when $φ$ is locally toroidal.

M. Izadparast, S. Habib Mazharimousavi

In the present study, the concept of a quantum particle with step momentum is introduced. The energy eigenvalues and eigenfunctions of such particles are obtained in the context of the generalized momentum operator, proposed recently in [13, 14]. While, the number of bound states with real energy for the particles with Hermitian step momentum inside a square

Ana B. Ruescas, Gonzalo Mateo-Garcia, Gustau Camps-Valls, Martin Hieronymi

Water quality parameters are derived applying several machine learning regression methods on the Case2eXtreme dataset (C2X). The used data are based on Hydrolight in-water radiative transfer simulations at Sentinel-3 OLCI wavebands, and the application is done exclusively for absorbing waters with high concentrations of coloured dissolved organic matter (CDO

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

Yifat Piekner, Hen Dotan, Anton Tsyganok, Kirtiman Deo Malviya

Strong interference in ultrathin film semiconductor absorbers on metallic back reflectors has been shown to enhance the light harvesting efficiency of solar cell materials. However, metallic back reflectors are not suitable for tandem cell configurations because photons cannot be transmitted through the device. Here, we introduce a method to implement strong

Gavin A. Buxton, Marcel C. Minutolo

The efficacy of face masks, neck gaiters and face shields are predicted and contrasted. In particular, a Lattice Spring Model of a neck gaiter serves as the input to a Lattice Boltzmann simulation. The Lattice Boltzmann method is used to capture the fluid dynamics both through and around various face coverings. The evaporation and transport of respiratory dr

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

Suhas Lohit, Shubhendu Trivedi

Omnidirectional images and spherical representations of $3D$ shapes cannot be processed with conventional 2D convolutional neural networks (CNNs) as the unwrapping leads to large distortion. Using fast implementations of spherical and $SO(3)$ convolutions, researchers have recently developed deep learning methods better suited for classifying spherical image

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 ($σ$) and, for core-Sérsic galaxies, the size of the depleted core ($R_{\rm b}$). Our sample of 144 galaxies with dynamically determined $M_{\rm BH}$ encompasses 24 core-Sérsic galaxies, thought to be products of gas-poor merg

Julia Kwok, Kristen Pudenz

We develop a heuristic graph coloring approximation algorithm that uses the D-Wave 2X as an independent set sampler and evaluate its performance against a fully classical implementation. A randomly generated set of small but hard graph instances serves as our test set. Our performance analysis suggests limited quantum advantage in the hybrid quantum-classica

Philip Klement, Daniel Anders, Lukas Gümbel, Michele Bastianello

Area-selective atomic layer deposition is a key technology for modern microelectronics as it eliminates alignment errors inherent to conventional approaches by enabling material deposition only in specific areas. Typically, the selectivity originates from surface modifications of the substrate that allow or block precursor adsorption. The control of the depo

Mikihiro Fujii, Izumi Okada, Eiji Yanagida

We consider solutions of the linear heat equation in $\mathbb{R}^N$ with isolated singularities. It is assumed that the position of a singular point depends on time and is Hölder continuous with the exponent $α\in (0,1)$. We show that any isolated singularity is removable if it is weaker than a certain order depending on $α$. We also show the optimality of t

Kairui Feng, Ouyang Min, Ning Lin

Hurricanes have caused power outages and blackouts, affecting millions of customers and inducing severe social and economic impacts. The impacts of hurricane-caused blackouts may worsen due to increased heat extremes and possibly increased hurricanes under climate change. We apply hurricane and heatwave projections with power outage and recovery process anal

D. Choudhuri, K. Saoudi

We prove the existence of ground state solution to the following problem. \begin{align*} (-Δ)^{s}u+u&=λ|u|^{-γ-1}u+P(x)|u|^{p-1}u,~\text{in}~\mathbb{R}^N\setminusΩ\\ N_su(x)&=0,~\text{in}~Ω\end{align*} where $N\geq2$, $λ>0$, $0<s,γ<1$, $p\in(1,2_s^*-1)$ with $2_s^*=\frac{2N}{N-2s}$. % $0<s^-=\underset{(x,y)\inΩ\timesΩ}{\inf}\{s(x,y)\}\leq s(x,y)\leq s^+=\und

Jia Guo, Chen Zhu, Yilun Zhao, Heda Wang

Multi-modal representation learning by pretraining has become an increasing interest due to its easy-to-use and potential benefit for various Visual-and-Language~(V-L) tasks. However its requirement of large volume and high-quality vision-language pairs highly hinders its values in practice. In this paper, we proposed a novel label-augmented V-L pretraining

Ayush Chauhan, Aditya Anand, Shaddy Garg, Sunny Dhamnani

Often, data contains only composite events composed of multiple events, some observed and some unobserved. For example, search ad click is observed by a brand, whereas which customers were shown a search ad - an actionable variable - is often not observed. In such cases, inference is not possible on unobserved event. This occurs when a marketing action is ta

Stefanos Angelidis, Reinald Kim Amplayo, Yoshihiko Suhara, Xiaolan Wang

We present the Quantized Transformer (QT), an unsupervised system for extractive opinion summarization. QT is inspired by Vector-Quantized Variational Autoencoders, which we repurpose for popularity-driven summarization. It uses a clustering interpretation of the quantized space and a novel extraction algorithm to discover popular opinions among hundreds of

Michael Neumann, Sebastian Koralewski, Michael Beetz

Anticipating what might happen as a result of an action is an essential ability humans have in order to perform tasks effectively. On the other hand, robots capabilities in this regard are quite lacking. While machine learning is used to increase the ability of prospection it is still limiting for novel situations. A possibility to improve the prospection ab

Avigail Landman, Hen Dotan, Gennady E. Shter, Michael Wullenkord

Solar water splitting provides a promising path for sustainable hydrogen production and solar energy storage. One of the greatest challenges towards large-scale utilization of this technology is reducing the hydrogen production cost. The conventional electrolyzer architecture, where hydrogen and oxygen are co-produced in the same cell, gives rise to critical

Meijian Li

We investigate the scattering of a quark jet on a high-energy heavy nucleus using the time-dependent light-front Hamiltonian approach. We simulate a real-time evolution of the quark in a strong classical color field of the relativistic nucleus, described as the Color Glass Condensate. We study the sub-eikonal effect by letting the quark jet carry realistic f

Mikhail Mamaev, Oleg Golosov, Ilya Selyuzhenkov

Centrality dependence of the directed flow of protons in Au+Au collisions at the beam energy of 1.23A GeV collected by the HADES experiment at GSI is presented. Measurements are performed with respect to the spectators plane estimated using the Forward Wall hodoscope. Biases due to non-flow correlations and correlated detector effects are evaluated. The corr

Yutong Xie, Gaoxiang Chen, Quanzheng Li

The expressiveness of deep neural network (DNN) is a perspective to understandthe surprising performance of DNN. The number of linear regions, i.e. pieces thata piece-wise-linear function represented by a DNN, is generally used to measurethe expressiveness. And the upper bound of regions number partitioned by a rec-tifier network, instead of the number itsel

Juze Zhang, Zijian Gao, Xiaopeng Yu, Peng Ge

Deep-tissue optical imaging is a longstanding challenge limited by scattering. Both optical imaging and treatment can benefit from focusing light in deep tissue beyond one transport mean free path. Wavefront shaping based on time-reversed ultrasonically encoded (TRUE) optical focusing utilizes ultrasound focus, which is much less scattered than light in biol

Harrie Oosterhuis, Maarten de Rijke

Optimizing ranking systems based on user interactions is a well-studied problem. State-of-the-art methods for optimizing ranking systems based on user interactions are divided into online approaches - that learn by directly interacting with users - and counterfactual approaches - that learn from historical interactions. Existing online methods are hindered w

Andrii Neronov, Dmitry Semikoz

We explore possible physical origin of correlation between radio wave and very-high-energy neutrino emission in active galactic nuclei (AGN), suggested by recently reported evidence for correlation between neutrino arrival directions and positions of brightest radio-loud AGN. We show that such correlation is expected if both synchrotron emitting electrons an