February 2019 arXiv papers — page 70

Antoine Durand, Elyes Ben-Hamida, David Leporini, Gérard Memmi

In the light of the recent fame of Blockchain technologies, numerous proposals and projects aiming at better practical viability have emerged. However, formally assessing their particularities and benefits has proven to be a difficult task. The aim of this work is to compare the fundamental differences of such protocols to understand how they lead to differe

Ryohei Seto, Abhinendra Singh, Bulbul Chakraborty, Morton M. Denn

The phenomenon of shear-induced jamming is a factor in the complex rheological behavior of dense suspensions. Such shear-jammed states are fragile, i.e., they are not stable against applied stresses that are incompatible with the stress imposed to create them. This peculiar flow-history dependence of the stress response is due to flow-induced microstructures

E. Rozas, M. D. Martín, C. Tejedor, L. Viña

We investigate the thermal robustness of traveling polariton condensates. We create remote condensates that have never been in contact, and study their interference in momentum space, when they travel with the same velocity, by means of time-resolved photoluminescence. We determine the condensed to thermal, uncondensed polariton fraction, which shows a gradu

Mohammad Kamalzare, Reza Kahani, Alireza Talebpour, Ahmad Mahmoudi-Aznaveh

Image semantic segmentation is parsing image into several partitions in such a way that each region of which involves a semantic concept. In a weakly supervised manner, since only image-level labels are available, discriminating objects from the background is challenging, and in some cases, much more difficult. More specifically, some objects which are commo

Leonardo S. G. Leite, R. L. Doretto

We calculate the bipartite von Neumann and second Rényi entanglement entropies of the ground states of spin-1/2 dimerized Heisenberg antiferromagnets on a square lattice. Two distinct dimerization patterns are considered: columnar and staggered. In both cases, we concentrate on the valence bond solid (VBS) phase and describe such a phase with the bond-operat

J. Meibohm, B. Mehlig

We study a one-dimensional model for heavy particles in a compressible fluid. The fluid-velocity field is modelled by a persistent Gaussian random function, and the particles are assumed to be weakly inertial. Since one-dimensional fluid-velocity fields are always compressible, the model exhibits spatial trapping regions where particles tend to accumulate. W

Scott Robertson, Charles Ciret, Serge Massar, Simon-Pierre Gorza

We study in detail the scattering of light on a soliton propagating in a waveguide which has been proposed as an experimental system in which one could observe the analogue Hawking effect. When not applying the rotating wave approximation, we show that the linearized wave equation governing perturbations has the same structure as that governing phonon propag

Gregor Dumphart, Marc Kuhn, Armin Wittneben, Florian Trösch

We study the estimation of distance d between two wireless nodes by means of their wideband channels to a third node, called observer. The motivating principle is that the channel impulse responses are similar for small d and drift apart when d increases. Following this idea we propose specific distance estimators based on the differences of path delays of t

Sirio Legramanti, Daniele Durante, David B. Dunson

There is a wide variety of models in which the dimension of the parameter space is unknown. For example, in factor analysis the number of latent factors is typically not known and has to be inferred from the observed data. Although classical shrinkage priors are useful in these contexts, increasing shrinkage priors can provide a more effective option, which

Emil Løvbak, Giovanni Samaey, Stefan Vandewalle

We propose a multilevel Monte Carlo method for a particle-based asymptotic-preserving scheme for kinetic equations. Kinetic equations model transport and collision of particles in a position-velocity phase-space. With a diffusive scaling, the kinetic equation converges to an advection-diffusion equation in the limit of zero mean free path. Classical particle

Kai Olav Ellefsen, Joost Huizinga, Jim Torresen

The structure and performance of neural networks are intimately connected, and by use of evolutionary algorithms, neural network structures optimally adapted to a given task can be explored. Guiding such neuroevolution with additional objectives related to network structure has been shown to improve performance in some cases, especially when modular neural n

Marija Vranic, Thomas Grismayer, Sebastian Meuren, Ricardo A. Fonseca

Scattering relativistic electrons with optical lasers can result in a significant frequency upshift for the photons, potentially producing $γ$-rays. This is what linear Compton scattering taught us. Ultra-intense lasers offer nowadays a new paradigm where multi-photon absorption effects come into play. These effects can result in higher harmonics, higher yie

Mathias Bürki, Lukas Schaupp, Marcin Dymczyk, Renaud Dubé

Changes in appearance is one of the main sources of failure in visual localization systems in outdoor environments. To address this challenge, we present VIZARD, a visual localization system for urban outdoor environments. By combining a local localization algorithm with the use of multi-session maps, a high localization recall can be achieved across vastly

Can Firtina, Jeremie S. Kim, Mohammed Alser, Damla Senol Cali

Long reads produced by third-generation sequencing technologies are used to construct an assembly (i.e., the subject's genome), which is further used in downstream genome analysis. Unfortunately, long reads have high sequencing error rates and a large proportion of bps in these long reads are incorrectly identified. These errors propagate to the assembly and

Étienne André, Didier Lime, Mathias Ramparison, Mariëlle Stoelinga

Risk assessment of cyber-physical systems, such as power plants, connected devices and IT-infrastructures has always been challenging: safety (i.e. absence of unintentional failures) and security (i.e. no disruptions due to attackers) are conditions that must be guaranteed. One of the traditional tools used to help considering these problems is attack trees,

Ryota Suzuki, Ryusuke Takahama, Shun Onoda

Obtaining continuous representations of structural data such as directed acyclic graphs (DAGs) has gained attention in machine learning and artificial intelligence. However, embedding complex DAGs in which both ancestors and descendants of nodes are exponentially increasing is difficult. Tackling in this problem, we develop Disk Embeddings, which is a framew

Yue Tan, Kan Zheng, Lei Lei

In order to maximize detection precision rate as well as the recall rate, this paper proposes an in-vehicle multi-source fusion scheme in Keyword Spotting (KWS) System for vehicle applications. Vehicle information, as a new source for the original system, is collected by an in-vehicle data acquisition platform while the user is driving. A Deep Neural Network

Winfried Auzinger, Harald Hofstätter, Othmar Koch, Karolina Kropielnicka

Time dependent Schrödinger equations with conservative force field U commonly constitute a major challenge in the numerical approximation, especially when they are analysed in the semiclassical regime. Extremely high oscillations originate from the semiclassical parameter, and call for appropriate methods. We propose to employ a combination of asymptotic Zas

Stephen Farry, Olli Lupton, Martina Pili, Mika Vesterinen

Precision electroweak tests are a powerful probe of physics beyond the Standard Model, but the sensitivity is limited by the precision with which the $W$ boson mass ($M_W$) has been measured. The Parton Distribution Function (PDF) uncertainties are a potential limitation for measurements of $M_W$ with LHC data. It has recently been pointed out that, thanks t

David López-Pérez, Adrian Garcia-Rodriguez, Lorenzo Galati-Giordano, Mika Kasslin

Wi-Fi technology is continuously innovating to cater to the growing customer demands, driven by the digitalisation of everything, both in the home as well as the enterprise and hotspot spaces. In this article, we introduce to the wireless community the next generation Wi-Fi$-$based on IEEE 802.11be Extremely High Throughput (EHT)$-$, present the main objecti

Abhijit Bandyopadhyay, Anirban Chatterjee

We investigated implications of recently released `Joint Light-curve Analysis' (JLA) supernova Ia (SNe Ia) data for dark energy models with time varying equation of state of dark energy, usually expressed as $w(z)$ in terms of variation with corresponding redshift $z$. From a comprehensive analysis of the JLA data, we obtain the observational constraints

Sabah Suhail, Rasheed Hussain, Choong Seon Hong, Abid Khan

"Trustworthy data" is the fuel for ensuring transparent traceability, precise decision-making, and cogent coordination in the supply chain (SC) space. However, the disparate data silos act as a trade barrier in orchestrating the provenance of product story starting from the transformation of raw materials into the circuit board to the assembling of electroni

O. Inyang, L. Bouchenoire, B. Nicholson, M. Tokac

Proximity-induced magnetization (PIM) has broad implications across interface-driven spintronics applications employing spin-currents. We directly determine the scaling between PIM in Pt and the temperature-dependent interface magnetization in an adjacent ferromagnet (FM) using depth-resolved magnetometry. The magnetization due to PIM does not follow the gen

Chun-Jie Yang, Jun-Hong An, Hai-Qing Lin

Confining light to scales beyond the diffraction limit, quantum plasmonics supplies an ideal platform to explore strong light-matter couplings. The light-induced localized surface plasmons (LSPs) on the metal-dielectric interface acting as a quantum bus have wide potential in quantum information processing; however, the loss nature of light in the metal hind

Jun Jie Sim, Fook Mun Chan, Shibin Chen, Benjamin Hong Meng Tan

One way of investigating how genes affect human traits would be with a genome-wide association study (GWAS). Genetic markers, known as single-nucleotide polymorphism (SNP), are used in GWAS. This raises privacy and security concerns as these genetic markers can be used to identify individuals uniquely. This problem is further exacerbated by a large number of

Sebastian Arnold, Ilya Molchanov, Johanna F. Ziegel

This paper provides a characterization of all possible dependency structures between two stochastically ordered random variables. The answer is given in terms of copulas that are compatible with the stochastic order and the marginal distributions. The extremal values for Kendall's $τ$ and Spearman's $ρ$ for all these copulas are given in closed form.

Cristian Consonni, David Laniado, Alberto Montresor

Wikipedia articles contain multiple links connecting a subject to other pages of the encyclopedia. In Wikipedia parlance, these links are called internal links or wikilinks. We present a complete dataset of the network of internal Wikipedia links for the $9$ largest language editions. The dataset contains yearly snapshots of the network and spans $17$ years,

Jaeyoung Yoo, Hojun Lee, Nojun Kwak

In this paper, we treat the image generation task using an autoencoder, a representative latent model. Unlike many studies regularizing the latent variable's distribution by assuming a manually specified prior, we approach the image generation task using an autoencoder by directly estimating the latent distribution. To this end, we introduce 'latent density

Alessio Benavoli, Alessandro Facchini, Marco Zaffalon

Quantum theory (QT) has been confirmed by numerous experiments, yet we still cannot fully grasp the meaning of the theory. As a consequence, the quantum world appears to us paradoxical. Here we shed new light on QT by being based on two main postulates: 1. the theory should be logically consistent; 2. inferences in the theory should be computable in polynomi

Igor M. Sokolov, William Guerin

Collective effects in atom-light interaction is of great importance for cold-atom-based quantum devices or fundamental studies on light transport in complex media. Here we discuss and compare three different approaches to light scattering by dilute cold atomic ensembles. The first approach is a coupled-dipole model, valid at low intensity, which includes coo

Cheng Lu, Ya-Feng Liu, Jing Zhou

In this paper, we consider a class of nonconvex complex quadratic programming (CQP) problems, which find a broad spectrum of signal processing applications. By using the polar coordinate representations of the complex variables, we first derive a new enhanced semidefinite relaxation (SDR) for problem (CQP). Based on the newly derived SDR, we further propose

Ohad Fried, Maneesh Agrawala

Dubbing puppet videos to make the characters (e.g. Kermit the Frog) convincingly speak a new speech track is a popular activity with many examples of well-known puppets speaking lines from films or singing rap songs. But manually aligning puppet mouth movements to match a new speech track is tedious as each syllable of the speech must match a closed-open-clo

Liwen Zhang, Ziqiang Shi, Jiqing Han, Anyan Shi

Deep dilated temporal convolutional networks (TCN) have been proved to be very effective in sequence modeling. In this paper we propose several improvements of TCN for end-to-end approach to monaural speech separation, which consists of 1) multi-scale dynamic weighted gated dilated convolutional pyramids network (FurcaPy), 2) gated TCN with intra-parallel co

Kunpeng Wang, Xiaodong He, Ruijun Guo, Peng Xu

We report the realization of a heteronuclear two-atom of $^{87}$Rb-$^{85}$Rb in the ground state of an optical tweezer (OT). Starting by trapping two different isotopic single atoms, a $^{87}$Rb and a $^{85}$Rb in two strongly focused and linearly polarized OT with 4 $μ$m apart, we perform simultaneously three dimensional Raman sideband cooling for both atom

L. Margolis, O. Schnabel

Similarly to how the classical group ring isomorphism problem asks, for a commutative ring $R$, which information about a finite group $G$ is encoded in the group ring $RG$, the twisted group ring isomorphism problem asks which information about $G$ is encoded in all the twisted group rings of $G$ over $R$. We investigate this problem over fields. We start w

Jorge Casalderrey-Solana, Diego Gutiez, Carlos Hoyos

We study the $q\bar{q}$ potential in strongly coupled non-conformal field theories with a non-trivial renormalization group flow via holography. We focus on the properties of this potential at an inter-quark separation $L$ large compared to the characteristic scale of the field theory. These are determined by the leading order IR physics plus a series of cor

Shangyun Wang, Songbai Chen, Jiliang Jing

We have studied entanglement entropy and Husimi $Q$ distribution as a tool to explore chaos in the quantum two-photon Dicke model. With the increase of the energy of system, the linear entanglement entropy of coherent state prepared in the classical chaotic and regular regions become more distinguishable, and the correspondence relationship between the distr

Kazuaki Tajima, Akihiko Yukie

We determine the set which parametrizes the GIT stratification for four prehomogeneous vector spaces in this paper.

Kazuaki Tajima, Akihiko Yukie

We determine all orbits of two prehomogeneous vector spaces rationally over an arbitrary perfect field in this paper.

Bernhard Müller

It has recently been proposed that global or local turbulence models can be used to simulate core-collapse supernova explosions in spherical symmetry (1D) more consistently than with traditional approaches for parameterised 1D models. However, a closer analysis of the proposed schemes reveals important consistency problems. Most notably, they systematically

Tatsuki Kuwagaki

Perverse schober defined by Kapranov--Schechtman is a categorification of the notion of perverse sheaf. In their definition, a key ingredient is certain purity property of perverse sheaves. In this short note, we attempt to describe a real analogue of the above story, as categorification of Legendrian points/knots. The notion turns out to include various not

A. Diaz-Fernandez, E. Diaz, Álvaro Gómez-León, Gloria Platero

We propose to Floquet-engineer Dirac cones at the surface of a three-dimensional topological insulator. We show that a large tunability of the Fermi velocity can be achieved as a function of the polarization, direction and amplitude of the driving field. Using this external control, the Dirac cones in the quasienergy spectrum may become elliptic or massive,

Sijie Lin, Xuan Xie, Hui Feng, Bo Hu

This paper investigates the active sampling for estimation of approximately bandlimited graph signals. With the assistance of a graph filter, an approximately bandlimited graph signal can be formulated by a Gaussian random field over the graph. In contrast to offline sampling set design methods which usually rely on accurate prior knowledge about the model,

Biswajit Datta, Pratap Chandra Adak, Li-kun Shi, Kenji Watanabe

The accumulation of non-trivial geometric phases in a material's response is often a tell-tale sign of a rich underlying internal structure. Studying quantum oscillations provides one of the ways to determine these geometrical phases, such as Berry's phase, that play a central role in topological quantum materials. We report on magneto-transport meas

G. Puddu

In the past few years in-medium similarity renormalization group methods have been introduced and developed. In these methods the Hamiltonian is evolved using a unitary transformation in order to decouple a reference state from the rest of the Hilbert space. The evolution by itself will generate, even if we start from a two-body interaction, many-body forces

Tong Guo, Huilin Gao

Semantic parsing is the task of mapping natural language to logic form. In question answering, semantic parsing can be used to map the question to logic form and execute the logic form to get the answer. One key problem for semantic parsing is the hard label work. We study this problem in another way: we do not use the logic form any more. Instead we only us

Matthew Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan

Interactive Fiction (IF) games are complex textual decision making problems. This paper introduces NAIL, an autonomous agent for general parser-based IF games. NAIL won the 2018 Text Adventure AI Competition, where it was evaluated on twenty unseen games. This paper describes the architecture, development, and insights underpinning NAIL's performance.

Mingda Qiao, Gregory Valiant

We consider a model of selective prediction, where the prediction algorithm is given a data sequence in an online fashion and asked to predict a pre-specified statistic of the upcoming data points. The algorithm is allowed to choose when to make the prediction as well as the length of the prediction window, possibly depending on the observations so far. We p

Mumin Cebe, Kemal Akkaya

Advanced Metering Infrastructure forms a communication network for the collection of power data from smart meters in Smart Grid. As the communication between smart meters could be secured utilizing public-key cryptography, however, public-key cryptography still has certain challenges in terms of certificate revocation and management particularly related dist

Seungki Min, Costis Maglaras, Ciamac C. Moallemi

We consider a finite-horizon multi-armed bandit (MAB) problem in a Bayesian setting, for which we propose an information relaxation sampling framework. With this framework, we define an intuitive family of control policies that include Thompson sampling (TS) and the Bayesian optimal policy as endpoints. Analogous to TS, which, at each decision epoch pulls an

Catherine Braiding, G. F. Wong, N. I. Maxted, D. Romano

We present observations of fifty square degrees of the Mopra carbon monoxide (CO) survey of the Southern Galactic Plane, covering Galactic longitudes $l = 300$-$350^\circ$ and latitudes $|b| \le 0.5^\circ$. These data have been taken at 0.6 arcminute spatial resolution and 0.1 km/s spectral resolution, providing an unprecedented view of the molecular clouds

Alexander F. Lapanowski, Irina Gaynanova

We consider the two-group classification problem and propose a kernel classifier based on the optimal scoring framework. Unlike previous approaches, we provide theoretical guarantees on the expected risk consistency of the method. We also allow for feature selection by imposing structured sparsity using weighted kernels. We propose fully-automated methods fo

Kento Nozawa, Issei Sato

Learning sentence vectors from an unlabeled corpus has attracted attention because such vectors can represent sentences in a lower dimensional and continuous space. Simple heuristics using pre-trained word vectors are widely applied to machine learning tasks. However, they are not well understood from a theoretical perspective. We analyze learning sentence v

William A. Terrano, Eric G. Adelberger, Charles A. Hagedorn, Blayne R. Heckel

We analyzed an 6.7-year span of data from a rotating torsion-pendulum containing $\approx 10^{23}$ polarized electrons to search for the "wind" arising from ultralight, axionlike dark matter with masses between $10^{-23}$ and $10^{-18}$ eV/c$^2$. Over most of this range we obtain a 95\% confidence limit $F_{\rm a}/C_{\rm e} \geq 1 \times 10^{15}$ eV

Tommaso Dreossi, Daniel J. Fremont, Shromona Ghosh, Edward Kim

We present VERIFAI, a software toolkit for the formal design and analysis of systems that include artificial intelligence (AI) and machine learning (ML) components. VERIFAI particularly seeks to address challenges with applying formal methods to perception and ML components, including those based on neural networks, and to model and analyze system behavior i

Samuel Pinilla, Tamir Bendory, Yonina C. Eldar, Henry Arguello

Frequency-resolved optical gating (FROG) is a popular technique for complete characterization of ultrashort laser pulses. The acquired data in FROG, called FROG trace, is the Fourier magnitude of the product of the unknown pulse with a time-shifted version of itself, for several different shifts. To estimate the pulse from the FROG trace, we propose an algor

Xiaoyan Lu, Brendan Cross, Boleslaw K. Szymanski

The maximization of generalized modularity performs well on networks in which the members of all communities are statistically indistinguishable from each other. However, there is no theory bounding the maximization performance in more realistic networks where edges are heterogeneously distributed within and between communities. Using the random graph proper

Gour Jana, Anamitra Mukherjee

We investigate the finite temperature properties of the half filled Hubbard model in two dimensions, with onsite interaction ($U$), in presence of (frustrating) next nearest neighbor hopping ($t^{\prime}$) using a semiclassical approximation scheme. We show that introduction of $t^{\prime}$ results in a finite temperature pseudogapped (PG) phase that separat

Kyoung-Whan Kim

We examine a modified drift-diffusion formalism to describe spin transport near an ultrathin magnet whose thickness is similar to or less than the spin dephasing length. Most of the previous theories on spin torque assume the transverse component of a injected spin current dephases perfectly thus are fully absorbed into the ferromagnet. However, in the state

Vignesh Ravichandran, Balamurali Murugesan, Vaishali Balakarthikeyan, Sharath M Shankaranarayana

Respiratory ailments afflict a wide range of people and manifests itself through conditions like asthma and sleep apnea. Continuous monitoring of chronic respiratory ailments is seldom used outside the intensive care ward due to the large size and cost of the monitoring system. While Electrocardiogram (ECG) based respiration extraction is a validated approac

Yi-Zheng Fan, Jiang-Chao Wan, Yi Wang

Let $G$ be a connected non-odd-bipartite hypergraph with even uniformity. The least H-eigenvalue of the signless Laplacian tensor of $G$ is simply called the least eigenvalue of $G$ and the corresponding H-eigenvectors are called the first eigenvectors of $G$. In this paper we give some numerical and structural properties about the first eigenvectors of $G$

Alex Simpson, Prado Martin-Moruno, Matt Visser

We consider a non-static evolving version of the regular "black-bounce"/traversable wormhole geometry recently introduced in JCAP02(2019)042 [arXiv:1812.07114 [gr-qc]]. We first re-write the static metric using Eddington-Finkelstein coordinates, and then allow the mass parameter $m$ to depend on the null time coordinate (a la Vaidya). The spacetime m

R. S. Vieira

The classical problem of counting the number of real zeros of a real polynomial was solved a long time ago by Sturm. The analogous problem of counting the number of zeros that a polynomial has on the unit circle is, however, still an open problem. In this paper, we show that the second problem can be reduced to the first one through the use of a suitable pai

Dominic Culver

The purpose of this short article is to record the computation of the homotopy groups of 3-local $\mathrm{tmf}$ via the Adams spectral sequence.

Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta

We present a multi-objective Bayesian optimisation algorithm that allows the user to express preference-order constraints on the objectives of the type "objective A is more important than objective B". These preferences are defined based on the stability of the obtained solutions with respect to preferred objective functions. Rather than attempting t

C. T. H. Davies, C. DeTar, A. X. El-Khadra, E. Gamiz

We calculate the contribution to the muon anomalous magnetic moment hadronic vacuum polarization from {the} connected diagrams of up and down quarks, omitting electromagnetism. We employ QCD gauge-field configurations with dynamical $u$, $d$, $s$, and $c$ quarks and the physical pion mass, and analyze five ensembles with lattice spacings ranging from $a \app

Cari Cesarotti, Yotam Soreq, Matthew J. Strassler, Jesse Thaler

We study dimuon events in 2.11/fb of 7 TeV pp collisions, using CMS Open Data, and search for a narrow dimuon resonance with moderate mass (14-66 GeV) and substantial transverse momentum (pT). Applying dimuon pT cuts of 25 GeV and 60 GeV, we explore two overlapping samples: one with isolated muons, and one with prompt muons without an isolation requirement.

Eddy Keming Chen

In a quantum universe with a strong arrow of time, it is standard to postulate that the initial wave function started in a particular macrostate--the special low-entropy macrostate selected by the Past Hypothesis. Moreover, there is an additional postulate about statistical mechanical probabilities according to which the initial wave function is a "typical"

Wenqi Wang, Run Wang, Lina Wang, Zhibo Wang

Deep neural networks (DNNs) have achieved remarkable success in various tasks (e.g., image classification, speech recognition, and natural language processing (NLP)). However, researchers have demonstrated that DNN-based models are vulnerable to adversarial examples, which cause erroneous predictions by adding imperceptible perturbations into legitimate inpu

Yuxiang Ren, Charu C. Aggarwal, Jiawei Zhang

Network alignment aims at inferring a set of anchor links matching the shared entities between different information networks, which has become a prerequisite step for effective fusion of multiple information networks. In this paper, we will study the network alignment problem to fuse online social networks specifically. Social network alignment is extremely

Fu-Guo Deng, Gui Lu Long

Classical one-time-pad key can only be used once. We show in this Letter that with quantum mechanical information media classical one-time-pad key can be repeatedly used. We propose a specific realization using single photons. The reason why quantum mechanics can make the classical one-time-pad key repeatable is that quantum states can not be cloned and eave

Omar Montasser, Steve Hanneke, Nathan Srebro

We study the question of learning an adversarially robust predictor. We show that any hypothesis class $\mathcal{H}$ with finite VC dimension is robustly PAC learnable with an improper learning rule. The requirement of being improper is necessary as we exhibit examples of hypothesis classes $\mathcal{H}$ with finite VC dimension that are not robustly PAC lea

Wei Qin, Vincenzo Macrì, Adam Miranowicz, Salvatore Savasta

To observe the dynamical Casimir effect (DCE) induced by a moving mirror is a long-standing challenge because the mirror velocity needs to approach the speed of light. Here, we present an experimentally feasible method for observing this mechanical DCE in an optomechanical system. It employs a detuned, parametric driving to squeeze a cavity mode, so that the

Chaorui Deng, Qi Wu, Guanghui Xu, Zhuliang Yu

Visual Grounding (VG) aims to locate the most relevant region in an image, based on a flexible natural language query but not a pre-defined label, thus it can be a more useful technique than object detection in practice. Most state-of-the-art methods in VG operate in a two-stage manner, wherein the first stage an object detector is adopted to generate a set

John Maclean, Erik S Van Vleck

We introduce a framework for Data Assimilation (DA) in which the data is split into multiple sets corresponding to low-rank projections of the state space. Algorithms are developed that assimilate some or all of the projected data, including an algorithm compatible with any generic DA method. The major application explored here is PROJ-PF, a projected Partic

Cisco Gooding, William G. Unruh

There is widespread disagreement about how the general covariance of a theory affects its quantization. Without a complete quantum theory of gravity, one can examine quantum consequences of coordinate choices only in highly idealized `toy' models. In this work, we extend our previous analysis of a self-gravitating shell model [1], and demonstrate that co

Xuezhe Ma, Xiang Kong, Shanghang Zhang, Eduard Hovy

Flow-based generative models, conceptually attractive due to tractability of both the exact log-likelihood computation and latent-variable inference, and efficiency of both training and sampling, has led to a number of impressive empirical successes and spawned many advanced variants and theoretical investigations. Despite their computational efficiency, the

J. K. Hoormann, P. Martini, T. M. Davis, A. King

Black hole mass measurements outside the local universe are critically important to derive the growth of supermassive black holes over cosmic time, and to study the interplay between black hole growth and galaxy evolution. In this paper we present two measurements of supermassive black hole masses from reverberation mapping (RM) of the broad CIV emission lin

Ikuya Kaneko

Via the work of Ramanujan, we establish the asymptotic behaviour of partial Euler products for Dirichlet $L$-functions under the Generalised Riemann Hypothesis (GRH). Understanding the behaviour of Euler products on the critical line is called the Deep Riemann Hypothesis (DRH). This work manifests the relation between GRH and DRH.

Andreas Gustavsson

We study the abelian M5 brane on $S^6$. From the spectrum we extract a series expansion for the heat kernel. In particular we determine the normalization for the coefficient $a$ in the M5 brane conformal anomaly. When we compare our result with what one gets by computing the Hadamard-Minakshisundaram-DeWitt-Seeley coefficients from local curvature invariants

Alexander P. Keil, Jessie P. Buckley, Katie M. OBrien, Kelly K. Ferguson

Exposure mixtures frequently occur in data across many domains, particularly in the fields of environmental and nutritional epidemiology. Various strategies have arisen to answer questions about mixtures, including methods such as weighted quantile sum (WQS) regression that estimate a joint effect of the mixture components.We demonstrate a new approach to es

Hailong Zhu

For linear stochastic differential equations (SDEs) with bounded coefficients, we establish the robustness of nonuniform mean-square exponential dichotomy (NMS-ED) on $[t_{0},+\oo)$, $(-\oo,t_{0}]$ and the whole $\R$ separately, in the sense that such an NMS-ED persists under a sufficiently small linear perturbation. The result for the nonuniform mean-square

Rohin Shah, Dmitrii Krasheninnikov, Jordan Alexander, Pieter Abbeel

Reinforcement learning (RL) agents optimize only the features specified in a reward function and are indifferent to anything left out inadvertently. This means that we must not only specify what to do, but also the much larger space of what not to do. It is easy to forget these preferences, since these preferences are already satisfied in our environment. Th

Ryan Hynd

We consider the dynamics of a collection of particles that interact pairwise and are restricted to move along the real line. Moreover, we focus on the situation in which particles undergo perfectly inelastic collisions when they collide. The equations of motion are a pair of partial differential equations for the particles' mass distribution and local ve

Yuan Liu

It is known that the Poincaré inequality is equivalent to the quadratic transportation-variance inequality (namely $W_2^2(fμ,μ) \leqslant C_V \mathrm{Var}_μ(f)$), see Jourdain \cite{Jourdain} and most recently Ledoux \cite{Ledoux18}. We give two alternative proofs to this fact. In particular, we achieve a smaller $C_V$ than before, which equals the double of

Cassiano O. Becker, Sérgio Pequito, George J. Pappas, Victor M. Preciado

In this paper, we consider the problem of tuning the edge weights of a networked system described by linear time-invariant dynamics. We assume that the topology of the underlying network is fixed and that the set of feasible edge weights is a given polytope. In this setting, we first consider a feasibility problem consisting of tuning the edge weights such t

Shilin Ma, Kevin J. McGown, Devon Rhodes, Mathias Wanner

Let $χ$ be a Dirichlet character modulo a prime~$p$. We give explicit upper bounds on $q_1<q_2<\dots<q_n$, the $n$ smallest prime nonresidues of $χ$. More precisely, given $n_0$ and $p_0$ there exists an absolute constant $C=C(n_0,p_0)>0$ such that $q_n\leq Cp^{\frac{1}{4}}(\log p)^{\frac{n+1}{2}}$ whenever $n\leq n_0$ and $p\geq p_0$.

A. Amorim, M. Bauböck, J. P. Berger, W. Brandner

During its orbit around the four million solar mass black hole Sagittarius A* the star S2 experiences significant changes in gravitational potential. We use this change of potential to test one part of the Einstein equivalence principle: the local position invariance (LPI). We study the dependency of different atomic transitions on the gravitational potentia

Luka Boc Thaler, Uroš Kuzman

We consider the dynamics of complex rational maps on the Riemann sphere. We prove that, after reducing their orbits to a fixed number of positive values representing the Fubini-Study distances between finitely many initial elements of the orbit and the origin, ergodic properties of the rational map are preserved.

G. Koolstra, Ge Yang, D. I. Schuster

Electrons on helium form a unique two-dimensional electron system on the interface of liquid helium and vacuum. On liquid helium, trapped electrons can arrange into strongly correlated states known as Wigner molecules, which can be used to study electron interactions in the absence of disorder, or as a highly promising resource for quantum computation. Wigne

Ting Bai, Pan Du, Wayne Xin Zhao, Ji-Rong Wen

Recommending the right products is the central problem in recommender systems, but the right products should also be recommended at the right time to meet the demands of users, so as to maximize their values. Users&#39; demands, implying strong purchase intents, can be the most useful way to promote products sales if well utilized. Previous recommendation mo

Mauro Barni, Kassem Kallas, Benedetta Tondi

Backdoor attacks against CNNs represent a new threat against deep learning systems, due to the possibility of corrupting the training set so to induce an incorrect behaviour at test time. To avoid that the trainer recognises the presence of the corrupted samples, the corruption of the training set must be as stealthy as possible. Previous works have focused

Urs Frauenfelder, Joa Weber

In this paper we determine in second order in the fine structure constant the energy levels of Weber&#39;s Hamiltonian admitting a quantized torus. Our formula coincides with the formula obtained by Wesley using the Schrödinger equation for Weber&#39;s Hamiltonian.

Mehdi Salehi Heydar Abad, Emre Ozfatura, Ozgur Ercetin, Deniz Gunduz

Content storage at the network edge is a promising solution to mitigate the excessive traffic load due to on-demand streaming applications as well as to reduce the streaming delay. To this end, cache-enabled cellular architectures can be utilized to increase the provided quality-of-service (QoS) and to reduce the network cost. However, there are certain issu

Mayeul Arminjon

We prove that, up to multiplication by a scalar, the Minkowski metric tensor is the only second-order tensor that is Lorentz-invariant. To prove this, we show that a specific set of three $4\times 4$ matrices, made of two rotation matrices plus a Lorentz boost, is irreducible.

Damian C. Swift, Dayne E. Fratanduono, Evan A. Dowling, Richard G. Kraus

Ramp compression experiment are used to deduce the relation between compression and normal stress in a material, by measuring how a compression wave evolves as it propagates through different thicknesses of the sample material. The compression wave is generally measured by Doppler velocimetry from a surface that can be observed with optical or near-optical p

Mohammad Ghoniem, Fintan Mcgee, Guy Melançon, Benoit Otjacques

Modelling relationships between entities in real-world systems with a simple graph is a standard approach. However, reality is better embraced as several interdependent subsystems (or layers). Recently the concept of a multilayer network model has emerged from the field of complex systems. This model can be applied to a wide range of real-world datasets. Exa

Anisse Ismaili

In this paper we study a max-min $k$-partition problem on a weighted graph, that could model a robust $k$-coalition formation. We settle the computational complexity of this problem as complete for class $Σ_2^P$. This hardness holds even for $k=2$ and arbitrary weights, or $k=3$ and non-negative weights, which matches what was known on \textsc{MaxCut} and \t

Roman Plotnikov, Adil Erzin

We consider a Min-Power Bounded-Hops Symmetric Connectivity problem that consists in the construction of communication spanning tree on a given graph, where the total energy consumption spent for the data transmission is minimized and the maximum number of hops between two nodes is bounded by some predefined constant. We focus on the planar Euclidian case of

Sadaoui Boualem

In this paper, we provide an alternative method to calculate the values of generalized multiple Hurwitz zeta function at non-positive integers by means of \emph{Raabe}&#39;s formula and the \textit{Bernoulli} numbers.