April 2019 arXiv papers — page 82

Victor Fleurov, Anatoly Kuklov

Recent realization of Bose-Einstein condensation of light in 2D provides a new platform for studying novel phases and phase transitions. The combination of low effective mass of the confined light and the presence of the dye molecules with randomly oriented directions of the dipolar transition engages a competition between disorder and the tendency to formin

V. V. Belykh, D. R. Yakovlev, M. Bayer

We suggest a new pump-probe method for studying semiconductor spin dynamics based on pumping of carrier spins by a pulse of oscillating radiofrequency (rf) magnetic field and probing by measuring the Faraday rotation of a short laser pulse. We demonstrate this technique on $n$-GaAs and observe the onset and decay of coherent spin precession during and after

Amir Hossein Raffiee, Arezoo M. Ardekani, Sadegh Dabiri

Viscoelastic microfluidic devices are promising for various microscale procedures such as particle sorting and separation. In this study, we perform three dimensional computational investigation of a particle in a viscoelastic channel flow by considering combined inertial and elastic effects. We calculate equilibrium positions of the particle in the microcha

Yuta Nakahara, Toshiyasu Matsushima

A spatially "Mt. Fuji" coupled low-density parity check (LDPC) ensemble is a modified version of the original spatially coupled (SC) LDPC ensemble. Its desirable properties are first observed in experimentally. The decoding error probability in the error floor region over the binary erasure channel (BEC) is theoretically analyzed later. In this paper

Nina Schaaf, Marco F. Huber, Johannes Maucher

One obstacle that so far prevents the introduction of machine learning models primarily in critical areas is the lack of explainability. In this work, a practicable approach of gaining explainability of deep artificial neural networks (NN) using an interpretable surrogate model based on decision trees is presented. Simply fitting a decision tree to a trained

Serena Dipierro, Ovidiu Savin, Enrico Valdinoci

We prove that nonlocal minimal graphs in the plane exhibit generically stickiness effects and boundary discontinuities. More precisely, we show that if a nonlocal minimal graph in a slab is continuous up to the boundary, then arbitrarily small perturbations of the far-away data produce boundary discontinuities. Hence, either a nonlocal minimal graph is disco

Mohamed Akrout, Collin Wilson, Peter C. Humphreys, Timothy Lillicrap

Current algorithms for deep learning probably cannot run in the brain because they rely on weight transport, where forward-path neurons transmit their synaptic weights to a feedback path, in a way that is likely impossible biologically. An algorithm called feedback alignment achieves deep learning without weight transport by using random feedback weights, bu

Joshua Brakensiek, Aviad Rubinstein

We show that the edit distance between two strings of length $n$ can be computed within a factor of $f(ε)$ in $n^{1+ε}$ time as long as the edit distance is at least $n^{1-δ}$ for some $δ(ε) > 0$.

Paula Fraga-Lamas, Tiago M. Fernández-Caramés

The rise of ubiquitous deepfakes, misinformation, disinformation, propaganda and post-truth, often referred to as fake news, raises concerns over the role of Internet and social media in modern democratic societies. Due to its rapid and widespread diffusion, digital deception has not only an individual or societal cost (e.g., to hamper the integrity of elect

Adamantios Ntakaris, Giorgio Mirone, Juho Kanniainen, Moncef Gabbouj

Mid-price movement prediction based on limit order book (LOB) data is a challenging task due to the complexity and dynamics of the LOB. So far, there have been very limited attempts for extracting relevant features based on LOB data. In this paper, we address this problem by designing a new set of handcrafted features and performing an extensive experimental

Andrew Adams, Kay Avila, Jim Basney, Dana Brunson

This article describes experiences and lessons learned from the Trusted CI project, funded by the US National Science Foundation to serve the community as the NSF Cybersecurity Center of Excellence. Trusted CI is an effort to address cybersecurity for the open science community through a single organization that provides leadership, training, consulting, and

Qianfan Wu, Weishan Zhu, Longlong Feng

Probing the polarization of gravitational waves (GWs) would provide an evidence of graviton, indicating the quantization of gravity. Motivated by the next generation of gravitational wave detectors, we make an attempt to study the possible helicity coupling of structured lights to GWs. With the analogue between of gravitational fields and the generic electro

O. A. Malafeyev, I. I. Pavlov

Modelling all possible life cycles of a company in a highly competitive economic environment gives a significant advantage to the owner in his business investment activities. This article proposes and analyses a dynamic model of a company's life cycle with known action costs and transition probabilities, that can be affected by an outside influence. For

Daniel Moyer, Greg Ver Steeg, Chantal M. W. Tax, Paul M. Thompson

Purpose: In the present work we describe the correction of diffusion-weighted MRI for site and scanner biases using a novel method based on invariant representation. Theory and Methods: Pooled imaging data from multiple sources are subject to variation between the sources. Correcting for these biases has become very important as imaging studies increase in s

Yadav P. Kandel, Haifeng Qiao, Saeed Fallahi, Geoffrey C. Gardner

Quantum information science has the potential to revolutionize modern technology by providing resource-efficient approaches to computing, communication, and sensing. Although the physical qubits in a realistic quantum device will inevitably suffer errors, quantum error correction creates a path to fault-tolerant quantum information processing. Quantum error

Baptiste Louf

We obtain simple quadratic recurrence formulas counting bipartite maps on surfaces with prescribed degrees (in particular, $2k$-angulations), and constellations. These formulas are the fastest known way of computing these numbers. Our work is a natural extension of previous works on integrable hierarchies (2-Toda and KP), namely the Pandharipande recursion f

José G. Fernández-Trincado, Leonardo Chaves-Velasquez, Angeles Pérez-Villegas, Katherine Vieira

We have used the galaxy modeling algorithm \texttt{GravPot16}, to explore the more probable orbital elements of a sample of 64 selected N-rich stars across the Milky Way. Using the newly measured proper motions from \texttt{Gaia} DR2 with existing line-of-sight velocities from APOGEE-2 survey and spectrophotometric distance estimations from the \texttt{StarH

José G. Fernández-Trincado, Timothy C. Beers, Vinicius M. Placco, Edmundo Moreno

We report the discovery of a unique collection of metal-poor giant-stars, that exhibit anomalously high levels of $^{28}$Si, clearly above typical Galactic levels. Our sample spans a narrow range of metallicities, peaking at $-1.07\pm 0.06$, and exhibit abundance ratios of [Si,Al/Fe] that are as extreme as those observed in Galactic globular clusters (GCs),

Justin Kaidi

We revisit a correspondence between toroidal compactifications of M-theory and del Pezzo surfaces, in which rational curves on the del Pezzo are related to ${1\over 2}$-BPS branes of the corresponding compactification. We argue that curves of higher genus correspond to non-geometric backgrounds of the M-theory compactifications, which are related to exotic b

Peter L. Taylor, Thomas D. Kitching, Justin Alsing, Benjamin D. Wandelt

Density-estimation likelihood-free inference (DELFI) has recently been proposed as an efficient method for simulation-based cosmological parameter inference. Compared to the standard likelihood-based Markov Chain Monte Carlo (MCMC) approach, DELFI has several advantages: it is highly parallelizable, there is no need to assume a possibly incorrect functional

Vitor Cardoso, Paolo Pani

Very compact objects probe extreme gravitational fields and may be the key to understand outstanding puzzles in fundamental physics. These include the nature of dark matter, the fate of spacetime singularities, or the loss of unitarity in Hawking evaporation. The standard astrophysical description of collapsing objects tells us that massive, dark and compact

Christopher Couzens, Huibert het Lam, Kilian Mayer, Stefan Vandoren

We study the central charges and levels of 2d $\mathcal{N}=(0,4)$ superconformal field theories that are dual to four- and five-dimensional BPS black holes in compactifications of type IIB string theory on a K3 surface. They arise from wrapping a D3-brane on a curve $C$ inside K3 and have transverse space either an ALE or ALF space. These D3-branes have an A

Hao-Lin Li, Ling-Xiao Xu, Jiang-Hao Yu, Shou-Hua Zhu

Composite Higgs and neutral-naturalness models are popular scenarios in which the Higgs boson is a pseudo Nambu-Goldstone boson, and naturalness problem is addressed by composite top partners. Since the standard model effective field theory (SMEFT) with dimension-six operators cannot fully retain the information of Higgs nonlinearity due to its PNGB nature,

Masahito Yamazaki

Swampland conjectures are a set of proposed necessary conditions for a low-energy effective field theory to have a UV completion inside a theory of quantum gravity. Swampland conjectures have interesting phenomenological consequences, and conversely phenomenological considerations are useful guidelines in sharping our understanding of quantum gravity.

Selim C. Hotinli, Marc Kamionkowski, Andrew H. Jaffe

Pulsar-timing arrays (PTAs) are seeking gravitational waves from supermassive-black-hole binaries, and there are prospects to complement these searches with stellar-astrometry measurements. Theorists still disagree, however, as to whether the local gravitational-wave background will be statistically isotropic, as arises if it is the summed contributions from

Ivan Levcovitz

The Roller boundary is a well-known compactification of a CAT(0) cube complex X. When X is locally finite, essential, irreducible, non-Euclidean and admits a cocompact action by a group G, Nevo-Sageev show that a subset, B(X), of the Roller boundary is the realization of the Poisson boundary and that the action of G on B(X) is minimal and strongly proximal.

Hyojoong Kim, Nakwoo Kim

Recently it was discovered that twisted superconformal index ${\mathcal{I}}$ can be used to understand the Bekenstein-Hawking entropy of magnetically charged black holes in AdS spacetime. In this paper we apply the so-called $\mathcal{I}$-extremization procedure to three-dimensional gauge field theories and their geometric dual, focusing in particular on the

Matthew Tancik, Ben Mildenhall, Ren Ng

Printed and digitally displayed photos have the ability to hide imperceptible digital data that can be accessed through internet-connected imaging systems. Another way to think about this is physical photographs that have unique QR codes invisibly embedded within them. This paper presents an architecture, algorithms, and a prototype implementation addressing

Jianqing Fan, Cong Ma, Yiqiao Zhong

Deep learning has arguably achieved tremendous success in recent years. In simple words, deep learning uses the composition of many nonlinear functions to model the complex dependency between input features and labels. While neural networks have a long history, recent advances have greatly improved their performance in computer vision, natural language proce

Kexin Huang, Jaan Altosaar, Rajesh Ranganath

Clinical notes contain information about patients that goes beyond structured data like lab values and medications. However, clinical notes have been underused relative to structured data, because notes are high-dimensional and sparse. This work develops and evaluates representations of clinical notes using bidirectional transformers (ClinicalBERT). Clinical

R. A. Konoplya, A. F. Zinhailo

The higher derivative gravity includes corrections of the second order in curvature and allows for both Schwarzschild and non-Schwarzschild asymptotically flat black-hole solutions. Here we find the grey-body factors and energy emission rates for Hawking radiation of test Dirac and electromagnetic fields in the vicinity of such a non-Schwarzschild black hole

Anudeep Kumar Arora, Svetlana Roudenko

We study the global behavior of solutions to the nonlinear generalized Hartree equation, where the nonlinearity is of the non-local type and is expressed as a convolution, $$ i u_t + Δu + (|x|^{-(N-γ)} \ast |u|^p)|u|^{p-2}u=0, \quad x \in \mathbb{R}^N, t\in \mathbb{R}. $$ Our main goal is to understand behavior of $H^1$ (finite energy) solutions of this equa

I. A. Ado, A. Qaiumzadeh, A. Brataas, M. Titov

We consider a contribution $w_{\text{ch}}$ to the micromagnetic energy density that is linear with respect to the first spatial derivatives of the local magnetization direction. For a generalized 2D Rashba ferromagnet, we present a microscopic analysis of this contribution and, in particular, demonstrate that it cannot be expressed through Lifshitz invariant

Wasim Raja Mondal, T. Berlijn, M. Jarrell, N. S. Vidhyadhiraja

We report the development and application of a new method for carrying out computational investigations of the effects of mass and force-constant (FC) disorder on phonon spectra. The method is based on the recently developed typical medium dynamical cluster approach (TMDCA), which is a Green's function approach. Excellent quantitative agreement with prev

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

We introduce two notions of convexity for an infinite regular tree. For these two notions we show that given a continuous boundary datum there exists a unique convex envelope on the tree and characterize the equation that this envelope satisfies. We also relate the equation with two versions of the Laplacian on the tree. Moreover, for a function defined on t

Andrea Mendizabal, Pablo Márquez-Neila, Stéphane Cotin

The finite element method (FEM) is among the most commonly used numerical methods for solving engineering problems. Due to its computational cost, various ideas have been introduced to reduce computation times, such as domain decomposition, parallel computing, adaptive meshing, and model order reduction. In this paper we present U-Mesh: a data-driven method

Shirshendu Ganguly, Sourav Sarkar

Stochastic point processes with Coulomb interactions arise in various natural examples of statistical mechanics, random matrices and optimization problems. Often such systems due to their natural repulsion exhibit remarkable hyperuniformity properties, that is, the number of points landing in any given region fluctuates at a much smaller scale compared to th

Davy Weissenbacher, Abeed Sarker, Ari Klein, Karen O'Connor

Objective: After years of research, Twitter posts are now recognized as an important source of patient-generated data, providing unique insights into population health. A fundamental step to incorporating Twitter data in pharmacoepidemiological research is to automatically recognize medication mentions in tweets. Given that lexical searches for medication na

Jozsef Balogh, Maksim Zhukovskii

We consider the binomial random graph $G(n,p)$, where $p$ is a constant, and answer the following two questions. First, given $e(k)=p{k\choose 2}+O(k)$, what is the maximum $k$ such that a.a.s.~the binomial random graph $G(n,p)$ has an induced subgraph with $k$ vertices and $e(k)$ edges? We prove that this maximum is not concentrated in any finite set (in co

Adán Cabello

Bell non-locality and Kochen-Specker (KS) contextuality are logically independent concepts, fuel different protocols with quantum vs classical advantage, and have distinct classical simulation costs. A natural question is what are the relations between these concepts, advantages, and costs. To address this question, it is useful to have a map that captures a

Albert Samoilenka, Filipp N. Rybakov, Egor Babaev

Cooper-pair formation in a system of imbalanced fermions leads to the well-studied Fulde-Ferrell or Larkin-Ovchinnikov superfluid state. In the former case the system forms spontaneous phase gradients while in the latter case it forms a stripelike or a crystal-like density gradient. We show that in multicomponent imbalanced mixtures, the superfluid states ca

Hao Chen, Yin Xia

Many statistical methodologies for high-dimensional data assume the population is normal. Although a few multivariate normality tests have been proposed, to the best of our knowledge, none of them can properly control the type I error when the dimension is larger than the number of observations. In this work, we propose a novel nonparametric test that utiliz

Micah Chrisman

Let $Σ_0,Σ_1$ be closed oriented surfaces. Two oriented knots $K_0 \subset Σ_0 \times [0,1]$ and $K_1 \subset Σ_1 \times [0,1]$ are said to be (virtually) concordant if there is a compact oriented $3$-manifold $W$ and a smoothly and properly embedded annulus $A$ in $W \times [0,1]$ such that $\partial W=Σ_1 \sqcup -Σ_0$ and $\partial A=K_1 \sqcup -K_0$. This

Steven B. Giddings

The impressive images from the Event Horizon Telescope sharpen the conflict between our observations of gravitational phenomena and the principles of quantum mechanics. Two related scenarios for reconciling quantum mechanics with the existence of black hole-like objects, with "minimal" departure from general relativity and local quantum field theory,

Alistair J. Brash, Jake Iles-Smith, Catherine L. Phillips, Dara P. S. McCutcheon

Coherent scattering of light by a single quantum emitter is a fundamental process at the heart of many proposed quantum technologies. Unlike atomic systems, solid-state emitters couple to their host lattice by phonons. Using a quantum dot in an optical nanocavity, we resolve these interactions in both time and frequency domains, going beyond the atomic pictu

Quentin Berger, Michele Salvi

We consider a one-dimensional random walk among biased i.i.d. conductances, in the case where the random walk is transient but sub-ballistic: this occurs when the conductances have a heavy-tail at $+\infty$ or at $0$. We prove that the scaling limit of the process is the inverse of an $α$-stable subordinator, which indicates an aging phenomenon, expressed in

Daochen Wang

In breakthrough work, Bravyi, Gosset, and K\"{o}nig (BGK) [Science, 2018] unconditionally proved that constant depth quantum circuits are more powerful than their classical counterparts. Their result is equivalent to saying that a particular family of constant depth quantum circuits takes classical circuits at least $\Omega(\log n)$ depth to "simulate", in a

Michael E. Tobar, Ben T. McAllister, Maxim Goryachev

The conversion of external energy into electricity is the foundation of power station and energy harvesting operation. The external source supplies an impressed force per unit charge to free or bound charge to produces AC electricity. We analyze the electrodynamics of ideal electricity generators through a time dependent permanent polarization without any ap

Jean-François Tremblay, Martin Béland, François Pomerleau, Richard Gagnon

Forestry is a major industry in many parts of the world. It relies on forest inventory, which consists of measuring tree attributes. We propose to use 3D mapping, based on the iterative closest point algorithm, to automatically measure tree diameters in forests from mobile robot observations. While previous studies showed the potential for such technology, t

Yujie Zhang, Ryan Spiniolas, Kai Shinbrough, Bin Fang

We experimentally study the generation of photon pairs via spontaneous four-wave mixing with two distinct laser pulses. We find that the dual-pump technique enables new capabilities: 1) a new characterization methodology to measure noise contributions, source brightness and photon collection efficiencies directly from raw photon-count measurements; 2) an enh

Tadahiro Oh, Tristan Robert, Nikolay Tzvetkov

We study the Cauchy problem for the nonlinear wave equations (NLW) with random data and/or stochastic forcing on a two-dimensional compact Riemannian manifold without boundary. (i) We first study the defocusing stochastic damped NLW driven by additive space-time white-noise, and with initial data distributed according to the Gibbs measure. By introducing a s

Luca Ferialdi, Ashley Setter, Marko Toroš, Chris Timberlake

We consider feedback cooling in a cavityless levitated optomechanics setup, and we investigate the possibility to improve the feedback implementation. We apply optimal control theory to derive the optimal feedback signal both for quadratic (parametric) and linear (electric) feedback. We numerically compare optimal feedback against the typical feedback implem

Ju-chieh Chou, Cheng-chieh Yeh, Hung-yi Lee

Recently, voice conversion (VC) without parallel data has been successfully adapted to multi-target scenario in which a single model is trained to convert the input voice to many different speakers. However, such model suffers from the limitation that it can only convert the voice to the speakers in the training data, which narrows down the applicable scenar

Vida Dujmović, Louis Esperet, Gwenaël Joret, Bartosz Walczak

A colouring of a graph is "nonrepetitive" if for every path of even order, the sequence of colours on the first half of the path is different from the sequence of colours on the second half. We show that planar graphs have nonrepetitive colourings with a bounded number of colours, thus proving a conjecture of Alon, Grytczuk, Haluszczak and Riordan (2002). We

Iiris Sundin, Peter Schulam, Eero Siivola, Aki Vehtari

Machine learning can help personalized decision support by learning models to predict individual treatment effects (ITE). This work studies the reliability of prediction-based decision-making in a task of deciding which action $a$ to take for a target unit after observing its covariates $\tilde{x}$ and predicted outcomes $\hat{p}(\tilde{y} \mid \tilde{x}, a)

Bin Liu, Qian Guo, Shucai Li, Benchao Liu

The inverse problem of electrical resistivity surveys (ERSs) is difficult because of its nonlinear and ill-posed nature. For this task, traditional linear inversion methods still face challenges such as suboptimal approximation and initial model selection. Inspired by the remarkable nonlinear mapping ability of deep learning approaches, in this article, we p

Weinan E, Chao Ma, Qingcan Wang, Lei Wu

The behavior of the gradient descent (GD) algorithm is analyzed for a deep neural network model with skip-connections. It is proved that in the over-parametrized regime, for a suitable initialization, with high probability GD can find a global minimum exponentially fast. Generalization error estimates along the GD path are also established. As a consequence,

Davesh Maulik, Andrei Neguţ

The Beauville-Voisin conjecture for a hyperkähler manifold X states that the subring of the Chow ring A^*(X) generated by divisor classes and Chern characters of the tangent bundle injects into the cohomology ring of X. We prove a weak version of this conjecture when X is the Hilbert scheme of points on a K3 surface, for the subring generated by divisor clas

Massimo Blasone, Gaetano Lambiase, Giuseppe Gaetano Luciano, Luciano Petruzziello

We derive the Mandelstam-Tamm time-energy uncertainty relation for neutrino oscillations in a generic stationary curved spacetime. In particular, by resorting to Stodolsky covariant formula of the quantum mechanical phase, we estimate gravity effects on the neutrino energy uncertainty. Deviations from the standard Minkowski result are explicitly evaluated in

Shifeng Cui, F. Hébert, B. Grémaud, V. G. Rousseau

We study the ground state phase diagrams of two-photon Dicke, the one-dimensional Jaynes-Cummings-Hubbard (JCH), and Rabi-Hubbard (RH) models using mean field, perturbation, quantum Monte Carlo (QMC), and density matrix renormalization group (DMRG) methods. We first compare mean field predictions for the phase diagram of the Dicke model with exact QMC result

Victor Kulikov, Victor Lempitsky

We present a new instance segmentation approach tailored to biological images, where instances may correspond to individual cells, organisms or plant parts. Unlike instance segmentation for user photographs or road scenes, in biological data object instances may be particularly densely packed, the appearance variation may be particularly low, the processing

Eustasio del Barrio, Hristo Inouzhe, Jean-Michel Loubes

We consider the problem of diversity enhancing clustering, i.e, developing clustering methods which produce clusters that favour diversity with respect to a set of protected attributes such as race, sex, age, etc. In the context of fair clustering, diversity plays a major role when fairness is understood as demographic parity. To promote diversity, we introd

Jing Luo, Gia-Wei Chern

We present extensive large-scale dynamical simulations of phase-separated states in the double exchange model. These inhomogeneous electronic states that play a crucial role in the colossal magnetoresistance phenomenon are composed of ferromagnetic metallic clusters embedded in an antiferromagnetic insulating matrix. We compute the dynamical structure factor

Alfredo Braunstein, Anna Paola Muntoni, Andrea Pagnani, Mirko Pieropan

Many interesting problems in fields ranging from telecommunications to computational biology can be formalized in terms of large underdetermined systems of linear equations with additional constraints or regularizers. One of the most studied ones, the Compressed Sensing problem (CS), consists in finding the solution with the smallest number of non-zero compo

Alexander Migdal

We study properties of the minimal surface in the Area Law Solution \cite{M93}, \cite{M19a}, \cite{M19b}. We find out that Area Law holds exactly for 2D turbulence as well as for arbitrary planar loop in higher dimensions. This relies on our previous result $α= \frac{1}{2}$ in which case the second moment of circulation can be proven to reduce to the area in

Xiao Liu, Yuanwei Liu, Yue Chen

A novel framework is proposed for quality of experience (QoE)-driven deployment and dynamic movement of multiple unmanned aerial vehicles (UAVs). The problem of joint non-convex three-dimensional (3D) deployment and dynamic movement of the UAVs is formulated for maximizing the sum mean opinion score (MOS) of ground users, which is proved to be NP-hard. In th

Kamran Kowsari, Rasoul Sali, Marium N. Khan, William Adorno

Celiac Disease (CD) and Environmental Enteropathy (EE) are common causes of malnutrition and adversely impact normal childhood development. CD is an autoimmune disorder that is prevalent worldwide and is caused by an increased sensitivity to gluten. Gluten exposure destructs the small intestinal epithelial barrier, resulting in nutrient mal-absorption and ch

Rima Alaifari, Xiuyuan Cheng, Lillian B. Pierce, Stefan Steinerberger

Given two symmetric and positive semidefinite square matrices $A, B$, is it true that any matrix given as the product of $m$ copies of $A$ and $n$ copies of $B$ in a particular sequence must be dominated in the spectral norm by the ordered matrix product $A^m B^n$? For example, is $$ \| AABAABABB \| \leq \| AAAAABBBB \|\ ? $$ Drury has characterized precisel

CMS Collaboration

Normalised multi-differential cross sections for top quark pair ($\mathrm{t\overline{t}}$) production are measured in proton-proton collisions at a centre-of-mass energy of 13 TeV using events containing two oppositely charged leptons. The analysed data were recorded with the CMS detector in 2016 and correspond to an integrated luminosity of 35.9 fb$^{-1}$.

Hoel Kervadec, Jose Dolz, Eric Granger, Ismail Ben Ayed

This study investigates a curriculum-style strategy for semi-supervised CNN segmentation, which devises a regression network to learn image-level information such as the size of a target region. These regressions are used to effectively regularize the segmentation network, constraining softmax predictions of the unlabeled images to match the inferred label d

Peter Humphries, Rizwanur Khan

We prove two results on arithmetic quantum chaos for dihedral Maass forms, both of which are manifestations of Berry's random wave conjecture: Planck scale mass equidistribution and an asymptotic formula for the fourth moment. For level $1$ forms, these results were previously known for Eisenstein series and conditionally on the generalised Lindelof hypo

Dennis Kristensen, Patrick K. Mogensen, Jong Myun Moon, Bertel Schjerning

We propose to combine smoothing, simulations and sieve approximations to solve for either the integrated or expected value function in a general class of dynamic discrete choice (DDC) models. We use importance sampling to approximate the Bellman operators defining the two functions. The random Bellman operators, and therefore also the corresponding solutions

Bruno Escoffier, Hugo Gilbert, Adèle Pass-Lanneau

Liquid democracy is a collective decision making paradigm which lies between direct and representative democracy. One of its main features is that voters can delegate their votes in a transitive manner such that: A delegates to B and B delegates to C leads to A indirectly delegates to C. These delegations can be effectively empowered by implementing liquid d

Thomas G. Mertens, Gustavo J. Turiaci

We classify and study defects in 2d Jackiw-Teitelboim gravity. We show these are holographically described by a deformation of the Schwarzian theory where the reparametrization mode is integrated over different coadjoint orbits of the Virasoro group. We show that the quantization of each coadjoint orbit is connected to 2d Liouville CFT between branes with in

Yisheng Tian

We establish arithmetic duality theorems for short complexes associated to reductive groups over $p$-adic function fields. Using dualities, we deduce obstructions to weak approximation for certain reductive groups (especially quasi-split ones) and relate this obstruction to an unramified Galois cohomology group.

Aaron Dant, Philip Feldman, Wayne Lutters

Tabletop fantasy role-playing games (TFRPGs) have existed in offline and online contexts for many decades, yet are rarely featured in scientific literature. This paper presents a case study where TFRPGs were used to generate and collect data for maps of belief environments using fiction co-created by multiple small groups of online tabletop gamers. The affor

Nicolas Marque

In this paper we prove a convergence result for sequences of Willmore immersions with simple minimal bubbles. To this end we replace the total curvature control in T. Rivi\`ere's proof of the $\varepsilon$-regularity for Willmore immersions by a control of the local Willmore energy.

Dennis Kristensen, Young Jun Lee

We develop a novel asymptotic theory for local polynomial extremum estimators of time-varying parameters in a broad class of nonlinear time series models. We show the proposed estimators are consistent and follow normal distributions in large samples under weak conditions. We also provide a precise characterisation of the leading bias term due to smoothing,

Rima Kriauzienė, Andrej Bugajev, Raimondas Čiegis

We consider a three-level parallelisation scheme. The second and third levels define a classical two-level parallelisation scheme and some load balancing algorithm is used to distribute tasks among processes. It is well-known that for many applications the efficiency of parallel algorithms of the second and third level starts to drop down after some critical

Luca Dell'Anna

We derive some entanglement properties of the ground states of two classes of quantum spin chains described by the Fredkin model, for half-integer spins, and the Motzkin model, for integer ones. Since the ground states of the two models are known analytically, we can calculate the entanglement entropy, the negativity and the quantum mutual information exactl

Hongwei Song, Jiqing Han, Shiwen Deng, Zhihao Du

In this paper, we propose a new strategy for acoustic scene classification (ASC) , namely recognizing acoustic scenes through identifying distinct sound events. This differs from existing strategies, which focus on characterizing global acoustical distributions of audio or the temporal evolution of short-term audio features, without analysis down to the leve

Maciej Blaszak

We show how to deform separable Henon-Heiles system with isospectral Lax representation, related with the stationary flow of the $5th$-order KdV, to respective non-autonomous systems of Painleve type with isomonodromic Lax representation.

Sergei M. Kuzenko

As an extension of the recent construction of generalised Fayet-Iliopoulos terms in ${\cal N}=1$ supergravity given in [1], we present self-interactions for a vector multiplet coupled to conformal supergravity. They are used to construct new models for spontaneously broken local supersymmetry.

Pere Ara, Joan Bosa, Enrique Pardo, Aidan Sims

Given an adaptable separated graph, we construct an associated groupoid and explore its type semigroup. Specifically, we first attach to each adaptable separated graph a corresponding semigroup, which we prove is an $E^*$-unitary inverse semigroup. As a consequence, the tight groupoid of this semigroup is a Hausdorff étale groupoid. We show that this groupoi

Beatrice Demiray, Julia Rackerseder, Stevica Bozhinoski, Nassir Navab

Although the segmentation of brain structures in ultrasound helps initialize image based registration, assist brain shift compensation, and provides interventional decision support, the task of segmenting grey and white matter in cranial ultrasound is very challenging and has not been addressed yet. We train a multi-scale fully convolutional neural network s

Jon Johnsen

This paper focuses on parabolic final value problems, and well-posedness is proved for a large class of these. The clarification is obtained from Hilbert spaces that characterise data that give existence, uniqueness and stability of the solutions. The data space is the graph normed domain of an unbounded operator that maps final states to the corresponding i

Yizhuang Liu, Maciej A. Nowak, Ismail Zahed

We provide a holographic description of non-strange multiquark exotics as compact topological molecules by binding heavy-light mesons to a tunneling configuration in D8-D$\bar 8$ that is homotopic to the vacuum state with fixed Chern-Simons number. In the tunneling process, the heavy-light mesons transmute to fermions. Their binding is generic and arises fro

Sergey N. Galyamin, Viktor V. Vorobev, Andrey V. Tyukhtin

A theoretical investigation of radiation field produced by a charge moving through the dielectric concentrator for Cherenkov radiation is performed for the general case where a charge trajectory is shifted with respect to the target axis. The idea of dielectric target with specific profile of the outer surface was presented and investigated in our previous p

Tamara Fernandez, Nicolas Rivera

Weighted log-rank tests are arguably the most widely used tests by practitioners for the two-sample problem in the context of right-censored data. Many approaches have been considered to make weighted log-rank tests more robust against a broader family of alternatives, among them, considering linear combinations of weighted log-rank tests, and taking the max

Naoto Shiraishi

We elucidate the deep connection between the PXP model, which is a standard model of quantum many-body scars, and the AKLT Hamiltonian. Using the framework of embedded Hamiltonians, we establish the connection between the PXP Hamiltonian and the AKLT Hamiltonian, which clarifies the reason why the PXP Hamiltonian has nonthermal energy eigenstates similar to

Linxi Jiang, Xingjun Ma, Shaoxiang Chen, James Bailey

Deep neural networks (DNNs) are known for their vulnerability to adversarial examples. These are examples that have undergone small, carefully crafted perturbations, and which can easily fool a DNN into making misclassifications at test time. Thus far, the field of adversarial research has mainly focused on image models, under either a white-box setting, whe

C. Deng, S. Wu, Q. Zhang

In this paper, we consider a scalar-help-vector source coding problem for $L+1$ correlated Gaussian memoryless sources. We deal with the case where $L$ encoders observe noisy linear combinations of $K$ correlated Gaussian scalar sources which work as partial side information at the decoder, while the remaining one encoder observes a vector Gaussian source wh

Mostafa Mirzaie, Behshid Behkamal, Samad Paydar

One of the most significant problems of Big Data is to extract knowledge through the huge amount of data. The usefulness of the extracted information depends strongly on data quality. In addition to the importance, data quality has recently been taken into consideration by the big data community and there is not any comprehensive review conducted in this are

Stanislaw Ambroszkiewicz

A generic method for combinatorial constructions of intrinsic geometrical spaces is presented. It is based on the well known inverse sequences of finite graphs that determine (in the limit) topological spaces. If a pattern of the construction is sufficiently regular and uniform, then the notions of metric, geodesic and curvature can be defined in the space a

Nikolai E. Khokhlov, Petr I. Gerevenkov, Leonid A. Shelukhin, Andrei V. Azovtsev

Using a time-resolved optically-pumped scanning optical microscopy technique we demonstrate the laser-driven excitation and propagation of spin waves in a 20-nm film of a ferromagnetic metallic alloy Galfenol epitaxially grown on a GaAs substrate. In contrast to previous all-optical studies of spin waves we employ laser-induced thermal changes of magnetocrys

Stephen Bonner, Flavian Vasile

Recommendations are commonly used to modify user's natural behavior, for example, increasing product sales or the time spent on a website. This results in a gap between the ultimate business objective and the classical setup where recommendations are optimized to be coherent with past user behavior. To bridge this gap, we propose a new learning setup for

Ziwei Liu, Zhongqi Miao, Xiaohang Zhan, Jiayun Wang

Real world data often have a long-tailed and open-ended distribution. A practical recognition system must classify among majority and minority classes, generalize from a few known instances, and acknowledge novelty upon a never seen instance. We define Open Long-Tailed Recognition (OLTR) as learning from such naturally distributed data and optimizing the cla

Amal Attouchi, Hannes Luiro, Mikko Parviainen

We define a random step size tug-of-war game, and show that the gradient of a value function exists almost everywhere. We also prove that the gradients of value functions are uniformly bounded and converge weakly to the gradient of the corresponding $p$-harmonic function. Moreover, we establish an improved Lipschitz estimate when boundary values are close to

Itay Kaplan, Tomasz Rzepecki, Daoud Siniora

We show that the countable universal homogeneous meet-tree has a generic automorphism, but it does not have a generic pair of automorphisms.

Moumin Rudra, H. S. Tripathi, Alo Dutta, T. P. Sinha

X-ray diffraction pattern and Raman spectrum authenticate the monoclinic P21/n structure of polycrystalline Pr$_2$ZnMnO$_6$ (PZM) synthesized by the solid-state reaction technique. The X-ray photoemission spectrum suggests the existence of oxygen vacancy in PZM, which plays a crucial role in electrical conduction as well as in electrochemical behavior. The e