November 2018 arXiv papers — page 61

Hana Hirose, Naoto Ito, Masashi Kawaguchi, Yong-Chang Lau

We have studied the circular photogalvanic effect (CPGE) in Cu/Bi bilayers. When a circularly polarized light in the visible range is irradiated to the bilayer from an oblique incidence, we find a photocurrent that depends on the helicity of light. Such photocurrent appears in a direction perpendicular to the light plane of incidence but is absent in the par

Haoxin Ma, Haotian Li, Zhiwen Qian, Shengxian Shi

The precise combination of image sensor and micro-lens array enables lenslet light field cameras to record both angular and spatial information of incoming light, therefore, one can calculate disparity and depth from light field images. In turn, 3D models of the recorded objects can be recovered, which is a great advantage over other imaging system. However,

Marat Akhmet, Mehmet Onur Fen, Ejaily Milad Alejaily

Fatou-Julia iteration (FJI) is an effective instrument to construct fractals. Famous Julia and Mandelbrot sets are strong confirmations of this. In the present study, we use the paradigm of FJI to construct and map Sierpinski fractals. The fractals can be mapped by developing a mapping iteration on the basis of FJI. Because of the close link between mappings

Chengzhi Qin, Yugui Peng, Ying Li, Xuefeng Zhu

Bloch oscillations (BOs) refer to a periodically oscillatory motion of particle in lattice systems driven by a constant force. By temporally modulating acoustic waveguides, BOs can be generalized from spatial to frequency domain, opening new possibilities for spectrum manipulations. The modulation can induce mode transitions in the waveguide band and form an

Wei-Xiang Chew, Kazunari Kaizu, Masaki Watabe, Sithi V. Muniandy

Microscopic models of reaction-diffusion processes on the cell membrane can link local spatiotemporal effects to macroscopic self-organized patterns often observed on the membrane. Simulation schemes based on the microscopic lattice method (MLM) can model these processes at the microscopic scale by tracking individual molecules, represented as hard-spheres,

Yukihiro Marui, Masashi Kawaguchi, Masamitsu Hayashi

We have studied spin orbit torque in heavy metal (HM)/ferromagnetic metal (FM) bilayers using magneto-optical Kerr effect. A double modulation technique is developed to separate signals from spin orbit torque and Joule heating. At a current density of ~1x10$^{10}$ A/m$^2$, we observe optical signals that scale linearly and quadratically with the current dens

Fang-Kun Peng, Shao-Qiang Xi, Xiang-Yu Wang, Qi-Jun Zhi

Star-forming regions on different scales, such as giant molecular clouds in our Galaxy and star-forming galaxies, emit GeV gamma-rays. These are thought to originate from hadronic interactions of cosmic-ray (CR) nuclei with the interstellar medium. It has recently been shown that the gamma-ray luminosity ($L_γ$) of star-forming galaxies is well correlated wi

Soochang Lee, Chul-Heung Kim, Seongbin Oh, Byung-Gook Park

We present a two-layer fully connected neuromorphic system based on a thin-film transistor (TFT)-type NOR flash memory array with multiple postsynaptic (POST) neurons. Unsupervised online learning by spike-timing-dependent plasticity (STDP) on the binary MNIST handwritten datasets is implemented, and its recognition result is determined by measuring firing r

Jinfa Cheng, Lukun Jia

By building a second order adjoint difference equations on nonuniform lattices, the generalized Rodrigues type representation for the second kind solution of a second order difference equation of hypergeometric type on nonuniform lattices is given. The general solution of the equation in the form of a combination of a standard Rodrigues formula and a general

Meng Yu

Determination of detection sensitivity in a number of previous pulsar search programmes was done via the straightfoward use of the radiometer equation. In the same surveys, the Fourier domain method was used to search for pulsars. As detection sensitivity is partially a function of the searching method, the straightfoward use of the radiometer equation for d

Meng Yu

Practical application of the harmonic summing technique in the power-spectrum analysis for searching pulsars has exhibited the technique's effectiveness. In this paper, theoretical verification of harmonic summing considering power's noise-signal probability distribution is given. With the top-hat and the modified von Mises pulse profile models, cont

Narong Borijindargoon, Boon Poh Ng

An algorithm called MUSIC-like algorithm was originally proposed as an alternative method to the MUltiple SIgnal Classification (MUSIC) algorithm for direction-of-arrival (DOA) estimation. Without requiring explicit model order estimation, it was shown to have robust performance particularly in low signal-to-noise ratio (SNR) scenarios. In this letter, the w

Chengdong Feng, Zhenbang Chen, Weijiang Hong, Hengbiao Yu

Deep Neural Network (DNN) is a widely used deep learning technique. How to ensure the safety of DNN-based system is a critical problem for the research and application of DNN. Robustness is an important safety property of DNN. However, existing work of verifying DNN's robustness is time-consuming and hard to scale to large-scale DNNs. In this paper, we p

Yifei Shen, Yuanming Shi, Jun Zhang, Khaled B. Letaief

Effective resource allocation plays a pivotal role for performance optimization in wireless networks. Unfortunately, typical resource allocation problems are mixed-integer nonlinear programming (MINLP) problems, which are NP-hard. Machine learning based methods recently emerge as a disruptive way to obtain near-optimal performance for MINLP problems with aff

Volodymyr I. Fesenko, Vladimir R. Tuz

Topological transitions of isofrequency surfaces of a composite magnetic-semiconductor structure influenced by an external static magnetic field are studied in the long-wavelength approximation. For the lossless case, the topological transitions of isofrequency surfaces from a closed ellipsoid to open Type I and Type II hyperboloids as well as a bi-hyperbolo

Yichen Wu, Yilin Luo, Gunvant Chaudhari, Yair Rivenson

Deep learning brings bright-field microscopy contrast to holographic images of a sample volume, bridging the volumetric imaging capability of holography with the speckle- and artifact-free image contrast of bright-field incoherent microscopy.

Li Zhang, Fei Lin, Xiaodong Qiu, Lixiang Chen

Nonlinear optical generation has been a well-established way to realize frequency conversion in nonlinear optics, whereas previous studies were just focusing on the scalar light fields. Here we report a concise yet efficient experiment to realize frequency conversion from vector fields to vector fields based on the vectorial nonlinear optical process, e.g.,

Xuan Guo

Taking advantages of high-throughput genotyping technology of single nucleotide polymorphism (SNP), large genome-wide association studies (GWASs) have been considered as the promise to unravel the complex relationships between genotypes and phenotypes, in particularly common diseases. However, current multi-locus-based methods are insufficient, in terms of c

Mohammed Aladsani, Ahmed Alkhateeb, Georgios C. Trichopoulos

In this work, we propose a novel approach for high accuracy user localization by merging tools from both millimeter wave (mmWave) imaging and communications. The key idea of the proposed solution is to leverage mmWave imaging to construct a high-resolution 3D image of the line-of-sight (LOS) and non-line-of-sight (NLOS) objects in the environment at one ante

Maziar Raissi, Hessam Babaee, Peyman Givi

Based on recent developments in physics-informed deep learning and deep hidden physics models, we put forth a framework for discovering turbulence models from scattered and potentially noisy spatio-temporal measurements of the probability density function (PDF). The models are for the conditional expected diffusion and the conditional expected dissipation of

Md. Shafayat Hossain, Meng K. Ma, Y. J. Chung, L. N. Pfeiffer

The fractional quantum Hall state (FQHS) observed at a half-filled Landau level in an interacting two-dimensional electron system (2DES) is among the most exotic states of matter as its quasiparticles are expected to be Majoranas with non-Abelian statistics. We demonstrate here the unexpected presence of such a state in a novel 2DES with a strong band-mass a

V. Riquelme, T. J. Quinn, H. Ramírez C

In this manuscript we investigate the long-term behavior of a single-species fishery, which is harvested by several fleets. The time evolution of this population is modeled by a discrete time stochastic age-structured model. We assume that incertitude only affects the recruitment. First, for the deterministic version of this model, we characterize the equili

Liang-Jian Deng, Roland Glowinski, Xue-Cheng Tai

Euler's elastica model has a wide range of applications in Image Processing and Computer Vision. However, the non-convexity, the non-smoothness and the nonlinearity of the associated energy functional make its minimization a challenging task, further complicated by the presence of high order derivatives in the model. In this article we propose a new oper

W. Li, R. Casini, S. Tomczyk, E. Landi Degl'Innocenti

We realized a laboratory experiment to study the scattering polarization of the Na I D-doublet at 589.0 and 589.6 nm in the presence of a magnetic field. This work was stimulated by solar observations of that doublet, which have proven particularly challenging to explain through available models of polarized line formation, even to the point of casting doubt

Patrick A. Lee

I propose a method to directly measure the space and time dependence of the pair field correlator of a pair density wave. The method is based on two separate ideas. First, we adopt the solenoid insertion method of Kapon et al (2017) to provide the momentum in a tunnel junction. Second, we suggest the use of optimal or over-doped Bi-2201 films as a tunneling

Dzung L. Pham, Snehashis Roy

A key feature of magnetic resonance (MR) imaging is its ability to manipulate how the intrinsic tissue parameters of the anatomy ultimately contribute to the contrast properties of the final, acquired image. This flexibility, however, can lead to substantial challenges for segmentation algorithms, particularly supervised methods. These methods require atlase

Van-Thanh Hoang, Kang-Hyun Jo

Convolutional neural networks (CNNs) have shown remarkable performance in various computer vision tasks in recent years. However, the increasing model size has raised challenges in adopting them in real-time applications as well as mobile and embedded vision applications. Many works try to build networks as small as possible while still have acceptable perfo

David B. Ramsay, Ishwarya Ananthabhotla, Joseph A. Paradiso

Our aural experience plays an integral role in the perception and memory of the events in our lives. Some of the sounds we encounter throughout the day stay lodged in our minds more easily than others; these, in turn, may serve as powerful triggers of our memories. In this paper, we measure the memorability of everyday sounds across 20,000 crowd-sourced aura

Hui Yang, Wenming Zou

In this paper, we investigate the qualitative properties of positive solutions for the following two-coupled elliptic system in the punctured space: $$ \begin{cases} -Δu =μ_1 u^{2q+1} + βu^q v^{q+1} \\ -Δv =μ_2 v^{2q+1} + βv^q u^{q+1} \end{cases} \textmd{in} ~\mathbb{R}^n \backslash \{0\}, $$ where $μ_1, μ_2$ and $β$ are all positive constants, $n\geq 3$. We

Peixiang Zhong, Di Wang, Chunyan Miao

Affect conveys important implicit information in human communication. Having the capability to correctly express affect during human-machine conversations is one of the major milestones in artificial intelligence. In recent years, extensive research on open-domain neural conversational models has been conducted. However, embedding affect into such models is

Qiaofeng Zhu

A polyhedral product is a natural subspace of a Cartesian product, which is specified by a simplicial complex K. The automorphism group Aut(K) of K induces a group action on the polyhedral product. In this paper we study this group action and give a formula for the fixed point set of the polyhedral product for any subgroup H of Aut(K). We use the fixed point

Indrajit Lahiri, Sujoy Majumder

In connection to a conjecture of W. Lü. Q. Li and C. Yang we prove a result on small function sharing by a power of a meromorphic function with few poles and its derivative. Our results improve a number of known results.

Tie Liu, Kee-Tae Kim, Sheng-Yuan Liu, Mika Juvela

How stellar feedback from high-mass stars (e.g., H{\sc ii} regions) influences the surrounding interstellar medium and regulates new star formation is still unclear. To address this question, we observed the G9.62+0.19 complex in 850 $μ$m continuum with the JCMT/POL-2 polarimeter. An ordered magnetic field has been discovered in its youngest clump, the G9.62

Yuanbo Hou, Qiuqiang Kong, Jun Wang, Shengchen Li

Audio tagging aims to detect the types of sound events occurring in an audio recording. To tag the polyphonic audio recordings, we propose to use Connectionist Temporal Classification (CTC) loss function on the top of Convolutional Recurrent Neural Network (CRNN) with learnable Gated Linear Units (GLU-CTC), based on a new type of audio label data: Sequential

G. Bono, G. Iannicola, V. F. Braga, I. Ferraro

We developed a new approach to provide accurate estimates of metal content, reddening and true distance modulus of RR Lyrae stars (RRLs). The method is based on homogeneous optical ($BVI$) and near-infrared ($JHK$) mean magnitudes and on predicted period--luminosity--metallicity relations ($IJHK$) and absolute mean magnitude--metallicity relations ($BV$). We

Christian Remling, Kyle Scarbrough

Oscillation theory locates the spectrum of a differential equation by counting the zeros of its solutions. We present a version of this theory for canonical systems $Ju'=-zHu$ and then use it to discuss semibounded operators from this point of view. Our main new result is a characterization of systems with purely discrete spectrum in terms of the asympto

Bin Wang, Xinyuan Wu

In this paper, we analyse the long-time behaviour of the extended RKN (ERKN) integrators for solving highly oscillatory Hamiltonian systems with a slowly varying, solution-dependent high frequency. We prove that a symmetric ERKN integrator approximately conserves a modified action and a modified total energy over long time intervals based on the technique of

Feiyang Chen, Nan Chen, Hanyang Mao, Hanlin Hu

Although the image recognition has been a research topic for many years, many researchers still have a keen interest in it[1]. In some papers[2][3][4], however, there is a tendency to compare models only on one or two datasets, either because of time restraints or because the model is tailored to a specific task. Accordingly, it is hard to understand how wel

Xizhi Liu

Let $3\le d\le k$ and $\nu\ge 0$ be fixed and $\mathcal{F}\subset\binom{[n]}{k}$. The matching number of $\mathcal{F}$, denoted by $\nu(\mathcal{F})$, is the maximum number of pairwise disjoint sets in $\mathcal{F}$, and $\mathcal{F}$ is $d$-cluster-free if it does not contain $d$ sets with the union of size at most $2k$ and empty intersection. In this paper

Vardan Papyan

We apply state-of-the-art tools in modern high-dimensional numerical linear algebra to approximate efficiently the spectrum of the Hessian of modern deepnets, with tens of millions of parameters, trained on real data. Our results corroborate previous findings, based on small-scale networks, that the Hessian exhibits "spiked" behavior, with several ou

Zexi Chen, Bharathkumar Ramachandra, Tianfu Wu, Ranga Raju Vatsavai

Spatial and temporal relationships, both short-range and long-range, between objects in videos, are key cues for recognizing actions. It is a challenging problem to model them jointly. In this paper, we first present a new variant of Long Short-Term Memory, namely Relational LSTM, to address the challenge of relation reasoning across space and time between o

Jiquan Ngiam, Daiyi Peng, Vijay Vasudevan, Simon Kornblith

Transfer learning is a widely used method to build high performing computer vision models. In this paper, we study the efficacy of transfer learning by examining how the choice of data impacts performance. We find that more pre-training data does not always help, and transfer performance depends on a judicious choice of pre-training data. These findings are

Vatsal Shah, Anastasios Kyrillidis, Sujay Sanghavi

This work is substituted by the paper in arXiv:2011.14066. Stochastic gradient descent is the de facto algorithm for training deep neural networks (DNNs). Despite its popularity, it still requires fine tuning in order to achieve its best performance. This has led to the development of adaptive methods, that claim automatic hyper-parameter optimization. Recen

David Aulicino

We borrow a classical construction from the study of rational billiards in dynamical systems known as the "unfolding construction" and show that it can be used to study the automorphism group of a Platonic surface. More precisely, the monodromy group, or deck group in this case, associated to the cover of a regular polygon or double polygon by the unfolded P

Doron L. Bergman

Symmetry, a central concept in understanding the laws of nature, has been used for centuries in physics, mathematics, and chemistry, to help make mathematical models tractable. Yet, despite its power, symmetry has not been used extensively in machine learning, until rather recently. In this article we show a general way to incorporate symmetries into machine

Lingge Li, Nitish Nayak, Jianming Bian, Pierre Baldi

The unified approach of Feldman and Cousins allows for exact statistical inference of small signals that commonly arise in high energy physics. It has gained widespread use, for instance, in measurements of neutrino oscillation parameters in long-baseline experiments. However, the approach relies on the Neyman construction of the classical confidence interva

Newton Nath, Rahul Srivastava, José W. F. Valle

We examine the capabilities of the DUNE experiment in probing leptonic CP violation within the framework of theories with generalized CP symmetries characterized by the texture zeros of the corresponding CP transformation matrices. We investigate DUNE's potential to probe the two least known oscillation parameters, the atmospheric mixing angle $θ_{23}$ a

Galyna V. Livshyts

We are concerned with the small ball behavior of the smallest singular value of random matrices. Often, establishing such results involves, in some capacity, a discretization of the unit sphere. This requires bounds on the norm of the matrix, and the latter bounds require strong assumptions on the distribution of the entries, such as bounded fourth moments (

Amanda C. N. Quirk, Puragra Guhathakurta, Laurent Chemin, Claire E. Dorman

We analyze the kinematics of Andromeda's disk as a function of stellar age by using photometry from the Panchromatic Hubble Andromeda Treasury (PHAT) survey and spectroscopy from the Spectroscopic and Photometric Landscape of Andromeda's Stellar Halo (SPLASH) survey. We use HI 21-cm and CO ($\rm J=1 \rightarrow 0$) data to examine the difference betw

Xiaojun Yao, Thomas Mehen

We use the open quantum system formalism to study the dynamical in-medium evolution of quarkonium. The system of quarkonium is described by potential non-relativistic QCD while the environment is a weakly coupled quark-gluon plasma in local thermal equilibrium below the melting temperature of the quarkonium. Under the Markovian approximation, it is shown tha

A. S. Razafimahatratra, M. Zhukovskii

In this paper, we prove that for every positive $\varepsilon$, there exists an $α\in(1/(k-1),1/(k-1)+\varepsilon)$ such that the binomial random graph $G(n,n^{-α})$ does not obey 0-1 law w.r.t. first order sentences with k variables. In contrast, for every $α\in(0,1/(k-1)]$, $G(n,n^{-α})$ obeys 0-1 law w.r.t. this logic.

Alberto Caimo, Isabella Gollini

A new modelling approach for the analysis of weighted networks with ordinal/polytomous dyadic values is introduced. Specifically, it is proposed to model the weighted network connectivity structure using a hierarchical multilayer exponential random graph model (ERGM) generative process where each network layer represents a different ordinal dyadic category.

Jeremy J. Webb, Jo Bovy

We perform a large suite of direct N-body simulations aimed at revealing the location of the progenitor, or its remnant, of the GD-1 stream. Data from \gaia\ DR2 reveals the GD-1 stream extends over $\approx 100^\circ$, allowing us to determine the stream's leading and trailing ends. Our models suggest the length of the stream is consistent with a dynami

Rohit Voleti, Julie M. Liss, Visar Berisha

A key initial step in several natural language processing (NLP) tasks involves embedding phrases of text to vectors of real numbers that preserve semantic meaning. To that end, several methods have been recently proposed with impressive results on semantic similarity tasks. However, all of these approaches assume that perfect transcripts are available when g

Shagun Sodhani, Sarath Chandar, Yoshua Bengio

Catastrophic forgetting and capacity saturation are the central challenges of any parametric lifelong learning system. In this work, we study these challenges in the context of sequential supervised learning with an emphasis on recurrent neural networks. To evaluate the models in the lifelong learning setting, we propose a curriculum-based, simple, and intui

Konstantinos Zampogiannis, Cornelia Fermuller, Yiannis Aloimonos

In this paper, we introduce a non-rigid registration pipeline for pairs of unorganized point clouds that may be topologically different. Standard warp field estimation algorithms, even under robust, discontinuity-preserving regularization, tend to produce erratic motion estimates on boundaries associated with `close-to-open' topology changes. We overcome thi

CMS Collaboration

A search for a heavy W' resonance decaying to one B or T vector-like quark and a top or bottom quark, respectively, is presented. The search uses proton-proton collision data collected in 2016 with the CMS detector at the LHC, corresponding to an integrated luminosity of 35.9 fb$^{-1}$ at $\sqrt{s} =$ 13 TeV. Both decay channels result in a final state w

Dami Lee, Catherine Ray

The Narasimhan-Nori conjecture asks for a closed formula for the number of non-isomorphic principal polarizations of any given abelian variety. In this paper, we introduce a new algorithm that gives a lower bound on the number of non-isomorphic principal polarizations on any given abelian variety. We show, for example, that the Jacobian of the genus four und

Melanie F. Pradier, Weiwei Pan, Jiayu Yao, Soumya Ghosh

As machine learning systems get widely adopted for high-stake decisions, quantifying uncertainty over predictions becomes crucial. While modern neural networks are making remarkable gains in terms of predictive accuracy, characterizing uncertainty over the parameters of these models is challenging because of the high dimensionality and complex correlations o

Shirin Nilizadeh, Yannic Noller, Corina S. Pasareanu

Side-channel attacks allow an adversary to uncover secret program data by observing the behavior of a program with respect to a resource, such as execution time, consumed memory or response size. Side-channel vulnerabilities are difficult to reason about as they involve analyzing the correlations between resource usage over multiple program paths. We present

Jamer Roldan, Roberto Vila

This work is concerned with the theory of the Random Field Ising Model on the hypercubic lattice, in the presence of a independent disorder with finite fifth moment. We showed the absence of replica symmetry in any dimensions, at any temperature and field strength, almost surely.

Laurent Côté, Ciprian Manolescu

Using the theory of perverse sheaves of vanishing cycles, we define a homological invariant of knots in three-manifolds, similar to the three-manifold invariant constructed by Abouzaid and the second author. We use spaces of SL(2,C) flat connections with fixed holonomy around the meridian of the knot. Thus, our invariant is a sheaf-theoretic SL(2,C) analogue

D. J. J. Marchand, M. Noori, A. Roberts, G. Rosenberg

Discovering the low-energy conformations of a molecule is of great interest to computational chemists, with applications in {\em in silico} materials design and drug discovery. In this paper, we propose a variable neighbourhood search heuristic for the conformational search problem. Using the structure of a molecule, neighbourhoods are chosen to allow for th

Anton S. Buyskikh, Luca Tagliacozzo, Dirk Schuricht, Chris A. Hooley

We study the non-equilibrium dynamics of a 1D Bose-Hubbard model in a gradient potential and a superlattice, beginning from a deep Mott insulator regime with an average filling of one particle per site. Studying a quench that is near resonance to tunnelling of the particles over two lattice sites, we show how a spin model emerges consisting of two coupled Is

Anton S. Buyskikh, Luca Tagliacozzo, Dirk Schuricht, Chris A. Hooley

We show that atoms in tilted optical superlattices provide a platform for exploring coupled spin chains of forms that are not present in other systems. In particular, using a period-2 superlattice in 1D, we show that coupled Ising spin chains with XZ and ZZ spin coupling terms can be engineered. We use optimized tensor network techniques to explore the criti

Chia-Wen Kuo, Jacob Ashmore, David Huggins, Zsolt Kira

This paper presents a challenging computer vision task, namely the detection of generic components on a PCB, and a novel set of deep-learning methods that are able to jointly leverage the appearance of individual components and the propagation of information across the structure of the board to accurately detect and identify various types of components on a

Chris Ying, Sameer Kumar, Dehao Chen, Tao Wang

Deep learning is extremely computationally intensive, and hardware vendors have responded by building faster accelerators in large clusters. Training deep learning models at petaFLOPS scale requires overcoming both algorithmic and systems software challenges. In this paper, we discuss three systems-related optimizations: (1) distributed batch normalization t

Rachel A. Patton, C. S. Kochanek, S. M. Adams

SN 1954J in NGC 2403 and SN 1961V in NGC 1058 were two luminous transients whose definitive classification as either non-terminal eruptions or supernovae remains elusive. A critical question is whether a surviving star can be significantly obscured by dust formed from material ejected during the transient. We use three lines of argument to show that the cand

Daniel Junghans

It was recently argued that the swampland distance conjecture rules out dS vacua at parametrically large field distances. We point out that this conclusion can in principle be avoided in the presence of large fluxes that are not bounded by a tadpole cancellation condition. We then study this possibility in the concrete setting of classical type IIA flux comp

S. Samuroff, J. Blazek, M. A. Troxel, N. MacCrann

We perform a joint analysis of intrinsic alignments and cosmology using tomographic weak lensing, galaxy clustering and galaxy-galaxy lensing measurements from Year 1 (Y1) of the Dark Energy Survey. We define early- and late-type subsamples, which are found to pass a series of systematics tests, including for spurious photometric redshift error and point spr

Kyungjoo Noh, Stefano Pirandola, Liang Jiang

Quantum communication is an important branch of quantum information science, promising unconditional security to classical communication and providing the building block of a future large-scale quantum network. Noise in realistic quantum communication channels imposes fundamental limits on the communication rates of various quantum communication tasks. It is

Clay Cordova, G. Bruno De Luca, Alessandro Tomasiello

We find non-supersymmetric AdS$_8$ solutions of type IIA supergravity. The internal space is topologically an $S^2$ with a U(1) isometry. The only non-zero flux is $F_0$; an O8 sourcing it is present at the equator of the $S^2$. The warping function and dilaton are non-constant. It is also possible to add D8-branes on top of the O8. Possible destabilizing br

Upamanyu Moitra, Ronak M Soni, Sandip P. Trivedi

A definition for the entanglement entropy in both Abelian and non-Abelian gauge theories has been given in the literature, based on an extended Hilbert space construction. The result can be expressed as a sum of two terms, a classical term and a quantum term. It has been argued that only the quantum term is extractable through the processes of quantum distil

Zhong-Bo Kang, Kyle Lee, Xiaohui Liu, Felix Ringer

Jet angularities are a class of jet substructure observables where a continuous parameter is introduced in order to interpolate between different classic observables such as the jet mass and jet broadening. We consider jet angularities measured on an inclusive jet sample at the LHC where the soft drop grooming procedure is applied in order to remove soft con

Henry S. Grasshorn Gebhardt, Donghui Jeong, Humna Awan, Joanna S. Bridge

The galaxy catalogs generated from low-resolution emission line surveys often contain both foreground and background interlopers due to line misidentification, which can bias the cosmological parameter estimation. In this paper, we present a method for correcting the interloper bias by using the joint-analysis of auto- and cross-power spectra of the main and

Roberto Contino, Andrea Mitridate, Alessandro Podo, Michele Redi

We introduce the gluequark Dark Matter candidate, an accidentally stable bound state made of adjoint fermions and gluons from a new confining gauge force. Such scenario displays an unusual cosmological history where perturbative freeze-out is followed by a non-perturbative re-annihilation period with possible entropy injection. When the gluequark has electro

Federico Municchi, Pranay P. Nagrani, Ivan C. Christov

Suspension flows are ubiquitous in nature (hemodynamics, subsurface fluid mechanics, etc.) and industrial applications (hydraulic fracturing, CO$_2$ storage, etc.). However, such flows are notoriously difficult to model due to the variety of fluid-particle and particle-particle interactions that can occur. In this work, we focus on non-Brownian shear-dominat

Loris D'Antoni, Tiago Ferreira, Matteo Sammartino, Alexandra Silva

Symbolic Finite Automata and Register Automata are two orthogonal extensions of finite automata motivated by real-world problems where data may have unbounded domains. These automata address a demand for a model over large or infinite alphabets, respectively. Both automata models have interesting applications and have been successful in their own right. In t

Sudip Mishra, Subenoy Chakraborty

The present work deals with dynamical system analysis of a Quintom Model of Dark Energy. By suitable transformation of variables the Einstein field equations are converted to an autonomous system. The critical points are determined and stability of hyperbolic critical points are determined by Hartman-Grobman theorem. To analyze non-hyperbolic critical points

Chako Takahashi, Muneki Yasuda, Kazuyuki Tanaka

The adaptive Thouless--Anderson--Palmer (TAP) mean-field approximation is one of the advanced mean-field approaches, and it is known as a powerful accurate method for Markov random fields (MRFs) with quadratic interactions (pairwise MRFs). In this study, an extension of the adaptive TAP approximation for MRFs with many-body interactions (higher-order MRFs) i

Yanping Huang, Youlong Cheng, Ankur Bapna, Orhan Firat

Scaling up deep neural network capacity has been known as an effective approach to improving model quality for several different machine learning tasks. In many cases, increasing model capacity beyond the memory limit of a single accelerator has required developing special algorithms or infrastructure. These solutions are often architecture-specific and do n

Eric Jang, Coline Devin, Vincent Vanhoucke, Sergey Levine

Well structured visual representations can make robot learning faster and can improve generalization. In this paper, we study how we can acquire effective object-centric representations for robotic manipulation tasks without human labeling by using autonomous robot interaction with the environment. Such representation learning methods can benefit from contin

Dan Edidin

We consider the geometry associated to the ambiguities of the one-dimensional Fourier phase retrieval problem for vectors in ${\mathbb C}^{N+1}$. Our first result states that the space of signals has a finite covering (which we call the root covering) where any two signals in the covering space with the same Fourier intensity function differ by a trivial cov

Philipp J. Meyer, Javier Esparza, Philip Offtermatt

Free-Choice Workflow Petri nets, also known as Workflow Graphs, are a popular model in Business Process Modeling. In this paper we introduce Timed Probabilistic Workflow Nets (TPWNs), and give them a Markov Decision Process (MDP) semantics. Since the time needed to execute two parallel tasks is the maximum of the times, and not their sum, the expected time c

Daihui Lu, Federico Municchi, Ivan C. Christov

We present a theoretical and numerical study on the (in)stability of the interface between two immiscible liquids, i.e., viscous fingering, in angled Hele-Shaw cells across a range of capillary numbers ($Ca$). We consider two types of angled Hele-Shaw cells: diverging cells with a positive depth gradient and converging cells with a negative depth gradient, a

Alberto Della Vedova, Alice Gatti

We study the almost Kaehler geometry of adjoint orbits of non-compact real semisimple Lie groups endowed with the Kirillov-Kostant-Souriau symplectic form and a canonically defined almost complex structure. We give explicit formulas for the Chern-Ricci form, the Hermitian scalar curvature and the Nijenhuis tensor in terms of root data. We also discuss when t

Raniere de Menezes, Fabio Cafardo, Rodrigo Nemmen

Globular clusters (GCs) are evolved stellar systems containing entire populations of millisecond pulsars (MSPs), which are efficient gamma-ray emitters. Observations of this emission can be used as a powerful tool to explore the dynamical processes leading to binary system formation in GCs. In this work, 9 years of Fermi Large Area Telescope data were used t

Lorenzo Traldi

The multivariate Alexander module of a link L has several subsets that admit quandle operations defined using the module operations. One of them, the fundamental multivariate Alexander quandle, determines the link module sequence of L.

Jan Kalinowski, Wojciech Kotlarski, Tania Robens, Dorota Sokolowska

We investigate the prospect of discovering the Inert Doublet Model scalars at CLIC. As signal processes, we consider the pair-production of inert scalars, namely e+e- -> H+H- and e+e- -> AH, followed by decays of charged scalars H+ and neutral scalars A into leptonic final states and missing transverse energy. We focus on signal signatures with two muons or

Avy Soffer, Minh-Binh Tran

In weak turbulence theory, the Kolmogorov-Zakharov spectra is a class of time-independent solutions to the kinetic wave equations. In this paper, we construct a new class of time-dependent isotropic solutions to the decaying turbulence problems (whose solutions are energy conserved), with general initial conditions. These solutions exhibit the interesting pr

Viktor Jahnke

We review recent developments encompassing the description of quantum chaos in holography. We discuss the characterization of quantum chaos based on the late time vanishing of out-of-time-order correlators and explain how this is realized in the dual gravitational description. We also review the connections of chaos with the spreading of quantum entanglement

Han Bao, Junlei Duan, Xingda Lu, Pengxiong Li

Quantum probes using $N$ uncorrelated particles give a limit on the measurement sensitivity referred to as the standard quantum limit (SQL). The SQL, however, can be overcome by exploiting quantum entangled states, such as spin squeezed states. We report generation of a quantum state, that surpasses the SQL for probing of the collective spin of $10^{11}$ $\t

T. M. Mishonov, I. M. Dimitrova, A. M. Varonov

We re-derive the Nyquist theorem and Callen-Welton fluctuation-dissipation theorem (FDT) as a consequence of detailed balance principle applied to a harmonic oscillator. The usage of electrical notions in the beginning makes the consideration understandable for every physicists. Perhaps it is the simplest derivation of these well-known theorems in statistica

Anton Karpishkov, Vladimir Saleev, Alexandra Shipilova

We study associated production of prompt photon and two jets at high energies in the framework of the parton Reggeization approach, which is based on multi-Regge factorization of hard processes and Lipatov's effective theory of Reggeized gluons and quarks. In this approach, initial-state off-shell effects and transverse momenta of initial partons are include

Christina Goldschmidt, Bénédicte Haas, Delphin Sénizergues

For $\alpha \in (1,2]$, the $\alpha$-stable graph arises as the universal scaling limit of critical random graphs with i.i.d. degrees having a given $\alpha$-dependent power-law tail behavior. It consists of a sequence of compact measured metric spaces (the limiting connected components), each of which is tree-like, in the sense that it consists of an $\math

M. Puppin, Y. Deng, C. W. Nicholson, J. Feldl

Time- and angle-resolved photoelectron spectroscopy (trARPES) employing a 500 kHz extreme-ultravioled (XUV) light source operating at 21.7 eV probe photon energy is reported. Based on a high-power ytterbium laser, optical parametric chirped pulse amplification (OPCPA), and ultraviolet-driven high-harmonic generation, the light source produces an isolated hig

Andrew W. Mann, Trent Dupuy, Adam L. Kraus, Eric Gaidos

The mass-luminosity relation for late-type stars has long been a critical tool for estimating stellar masses. However, there is growing need for both a higher-precision relation and a better understanding of systematic effects (e.g., metallicity). Here we present an empirical relationship between Mks and mass spanning $0.075M_\odot<M<0.70M_\odot$. The relati

Adrien Koutsos

Computational indistinguishability is a key property in cryptography and verification of security protocols. Current tools for proving it rely on cryptographic game transformations. We follow Bana and Comon&#39;s approach, axiomatizing what an adversary cannot distinguish. We prove the decidability of a set of first-order axioms that are both computationally

Sam Cole, Yizhe Zhu

We consider the exact recovery problem in the hypergraph stochastic block model (HSBM) with $k$ blocks of equal size. More precisely, we consider a random $d$-uniform hypergraph $H$ with $n$ vertices partitioned into $k$ clusters of size $s = n / k$. Hyperedges $e$ are added independently with probability $p$ if $e$ is contained within a single cluster and $

Sorin Popa, Dimitri Shlyakhtenko, Stefaan Vaes

We prove that the regular von Neumann subalgebras $B$ of the hyperfinite II_1 factor $R$ satisfying the condition $B'\cap R=Z(B)$ are completely classified (up to conjugacy by an automorphism of $R$) by the associated discrete measured groupoid $G$. We obtain a similar classification result for triple inclusions $A\subset B \subset R$, where $A$ is a Cartan