November 2018 arXiv papers — page 105

Yuenan Hou, Zheng Ma, Chunxiao Liu, Chen Change Loy

The training of many existing end-to-end steering angle prediction models heavily relies on steering angles as the supervisory signal. Without learning from much richer contexts, these methods are susceptible to the presence of sharp road curves, challenging traffic conditions, strong shadows, and severe lighting changes. In this paper, we considerably impro

Yejun Feng, Yishu Wang, D. M. Silevitch, J. -Q. Yan

The magnetoresistance (MR) of a material is typically insensitive to reversing the applied field direction and varies quadratically with magnetic field in the low-field limit. Quantum effects [1], unusual topological band structures [2], and inhomogeneities that lead to wandering current paths [3, 4] can induce a crossover from quadratic to linear magnetores

Mooseok Jang, Hakseok Ko, Won Kyu Lee, Jae-Seung Lee

High-resolution optical microscopy suffers from a low contrast in scattering media where a multiply scattered wave obscures a ballistic wave used for image formation. To extend the imaging depth, various gating operations - confocal, coherence, and polarization gating - have been devised to filter out the multiply scattered wave. However, these gating method

Fangyang Tian

Studying the analytic properties of the partial Langlands $L$-function via Rankin-Selberg method has been proved to be successful in various cases. Yet in few cases is the local theory studied at the archimedean places, which causes a tremendous gap to complete the analytic theory of the complete $L$-function. In this paper, we will establish the meromorphic

Soo-Min Choi, Hyun Min Lee, Pyungwon Ko, Alexander Natale

Dark pion is the one of the most natural and realistic model to make $3 \rightarrow 2$ contact interactions among models of the Strongly Interacting Massive Particle (SIMP). In this model, there is a perturbativity problem to satisfy the relic density with the self-annihilation. So we show the perturbativity problem can be alleviated and the SIMP pion model

B. ODea, T. W. Boonstra, M. E. Larsen, T. Nguyen

Due to its popularity and availability, social media data may present a new way to identify individuals who are experiencing mental illness. By analysing blog content, this study aimed to investigate the associations between linguistic features and symptoms of depression, generalised anxiety, and suicidal ideation. This study utilised a longitudinal study de

Mikołaj K. Schmidt, Christopher G. Poulton, Goran Z. Mashanovich, Graham T. Reed

We theoretically investigate a new class of silicon waveguides for achieving Stimulated Brillouin Scattering (SBS) in the mid-infrared (MIR). The waveguide consists of a rectangular core supporting a low-loss optical mode, suspended in air by a series of transverse ribs. The ribs are patterned to form a finite quasi-one-dimensional phononic crystal, with the

Seyyedeh Atefeh Musavi, Mahmoud Reza Hashemi

Today's ubiquitous computing ecosystem involves various kinds of hardware and software technologies for different computing environments. As the result, computing systems can be seen as integrated system of hardware and software systems. Realizing such complex systems is crucial for providing safety, security, and maintenance. This is while the character

Yu-pei Huang, Chia-an Liu, Chih-wen Weng

Let G be a simple graph without isolated vertices. For a vertex i in G, the degree d_i is the number of vertices adjacent to i and the average 2-degree m_i is the mean of the degrees of the vertices which are adjacent to i. The sequence of pairs (d_i, m_i) is called the sequence of degree pairs of G. We provide some necessary conditions for a sequence of rea

Zhizhong Han, Mingyang Shang, Xiyang Wang, Yu-Shen Liu

A recent method employs 3D voxels to represent 3D shapes, but this limits the approach to low resolutions due to the computational cost caused by the cubic complexity of 3D voxels. Hence the method suffers from a lack of detailed geometry. To resolve this issue, we propose Y^2Seq2Seq, a view-based model, to learn cross-modal representations by joint reconstr

Zhizhong Han, Mingyang Shang, Yu-Shen Liu, Matthias Zwicker

In this paper we present a novel unsupervised representation learning approach for 3D shapes, which is an important research challenge as it avoids the manual effort required for collecting supervised data. Our method trains an RNN-based neural network architecture to solve multiple view inter-prediction tasks for each shape. Given several nearby views of a

Square Kilometre Array Cosmology Science Working Group, David J. Bacon, Richard A. Battye, Philip Bull

We present a detailed overview of the cosmological surveys that will be carried out with Phase 1 of the Square Kilometre Array (SKA1), and the science that they will enable. We highlight three main surveys: a medium-deep continuum weak lensing and low-redshift spectroscopic HI galaxy survey over 5,000 sqdeg; a wide and deep continuum galaxy and HI intensity

Khondokar Fida Hasan, Yanming Feng, Yu-Chu Tian

Time synchronization is critical for the operation of distributed systems in networked environments. It is also demanded in vehicular ad-hoc networks (VANETs), which, as a special type of wireless networks, are becoming increasingly important for emerging cooperative intelligent transport systems. Global navigation satellite system (GNSS) is a proven technol

Rui Zhang, Sheng Tang, Yu Li, Junbo Guo

Style synthesis attracts great interests recently, while few works focus on its dual problem "style separation". In this paper, we propose the Style Separation and Synthesis Generative Adversarial Network (S3-GAN) to simultaneously implement style separation and style synthesis on object photographs of specific categories. Based on the assumption tha

Zhun-Yong Ong

The control of phonon scattering by interfaces is critical to the manipulation of heat conduction in composite materials and semiconducting nanostructures. However, one of the factors limiting our understanding of elastic phonon scattering is the lack of a computationally efficient approach for describing the phenomenon in a manner that accounts for the atom

L. Venuti, F. Damiani, L. Prisinzano

We aim to test a purely photometric approach to statistically identify a young clustered population embedded in a large population of field stars, with no prior knowledge on the nature of stars in the field. We conducted our blind test study on the NGC 2264 region, which hosts a well-known young cluster. We selected a large (4 sq. deg.) area around the NGC 2

L. G. Helt, M. M. Dignam

We consider the nonlinear terahertz response of n-doped monolayer graphene at room temperature using a microscopic theory of carrier dynamics. Our tight-binding model treats the carrier-field interaction in the length gauge, includes phonon as well as short-range neutral-impurity scattering, and fully accounts for the intrinsic nonlinear response of graphene

Prakash Pitchappa, Abhishek Kumar, Saurav Prakash, Hariom Jani

The advancement in capabilities enabled by handheld devices and the prospective internet of things has led to an explosion of wireless data consumption in the last decade. The ever-increasing demand for high speed data transfer has projected the unprecedented importance of terahertz spectral range for next generation wireless communication systems. However,

Rizal Fathony, Ashkan Rezaei, Mohammad Ali Bashiri, Xinhua Zhang

In many structured prediction problems, complex relationships between variables are compactly defined using graphical structures. The most prevalent graphical prediction methods---probabilistic graphical models and large margin methods---have their own distinct strengths but also possess significant drawbacks. Conditional random fields (CRFs) are Fisher cons

Yuichi Kitamura, Louise Laage

Finite mixture models are useful in applied econometrics. They can be used to model unobserved heterogeneity, which plays major roles in labor economics, industrial organization and other fields. Mixtures are also convenient in dealing with contaminated sampling models and models with multiple equilibria. This paper shows that finite mixture models are nonpa

Khrystyna Serhiyenko, Melissa Sherman-Bennett, Lauren Williams

We give an explicit combinatorial description of cluster structures in Schubert varieties of the Grassmannian in terms of (target labelings of) Postnikov's plabic graphs. This description is a natural generalization of the description given by (Scott 2006) for the Grassmannian and has been believed by experts essentially since (Scott 2006), though the st

Minh Tuan Doan, Jianzhong Qi, Sutharshan Rajasegarar, Christopher Leckie

Subspace clustering aims to find groups of similar objects (clusters) that exist in lower dimensional subspaces from a high dimensional dataset. It has a wide range of applications, such as analysing high dimensional sensor data or DNA sequences. However, existing algorithms have limitations in finding clusters in non-disjoint subspaces and scaling to large

Philip Greengard, Kirill Serkh

Zernike polynomials are a basis of orthogonal polynomials on the unit disk that are a natural basis for representing smooth functions. They arise in a number of applications including optics and atmospheric sciences. In this paper, we provide a self-contained reference on Zernike polynomials, algorithms for evaluating them, and what appear to be new numerica

Pablo Díaz, David Laroze, Andrés Ávila, Boris A. Malomed

We address a possibility of creating soliton states in oblate binary-fermionic clouds in the framework of the density-functional theory, which includes the spin-orbit coupling (SOC) and nonlinear attraction between spin-up and down-polarized components of the spinor wave function. In the limit when the inter-component attraction is much stronger than the eff

J. Vanterler da C. Sousa, E. Capelas de Oliveira

In this paper, we present the Leibniz rule for the $Ψ-$Hilfer ($Ψ-$H) fractional derivative in two versions, the first in relation to $Ψ-$RL fractional derivative and the second in relation to the $Ψ-$H fractional derivative. In this sense, we present some particular cases of Leibniz rules and Leibniz type rules from the investigated case.

Laura Lopez-Honorez, Olga Mena, Pablo Villanueva-Domingo

Dark matter interactions with massless or very light Standard Model particles, as photons or neutrinos, may lead to a suppression of the matter power spectrum at small scales and of the number of low mass haloes. Bounds on the dark matter scattering cross section with light degrees of freedom in such interacting dark matter (IDM) scenarios have been obtained

E. Bachelet, V. Bozza, C. Han, A. Udalski

We present an analysis of the microlensing event OGLE-2015-BLG-0232. This event is challenging to characterize for two reasons. First, the light curve is not well sampled during the caustic crossing due to the proximity of the full Moon impacting the photometry quality. Moreover, the source brightness is difficult to estimate because this event is blended wi

Tonia Bell, Shakuan Frankson, Nikita Sachdeva, Myka Terry

Random walks are a series of up, down, and level steps that enumerate distinct paths from $(0,0)$ to $(2n,0)$, where $n$ is the semi-length of the path. We used these paths to analyze Catalan, Schröder, and Motzkin number sequences through a combination of matrix operations, quadratic functions, and inductive reasoning. Our results revealed a number of disti

Shakuan Frankson, Myka Terry

By definition, a first return is the immediate moment that a path, using vectors in the Cartesian plane, touches the $x$-axis after leaving it previously from a given point; the initial point is often the origin. In this case, using certain diagonal and horizontal vectors while restricting the movements to the first quadrant will cause almost every first ret

Gustav Markkula, Richard Romano, Rachel Waldram, Oscar Giles

It is well established that not only vision but also other sensory modalities affect drivers' control of their vehicles, and that drivers adapt over time to persistent changes in sensory cues (for example in driving simulators), but the mechanisms underlying these behavioural phenomena are poorly understood. Here, we consider the existing literature on h

Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Andreas Krause

Learning-based methods have been successful in solving complex control tasks without significant prior knowledge about the system. However, these methods typically do not provide any safety guarantees, which prevents their use in safety-critical, real-world applications. In this paper, we present a learning-based model predictive control scheme that can prov

Shaunak D. Bopardikar

Given a linear dynamical system, we consider the problem of constructing an approximate system using only a subset of the sensors out of the total set such that the observability Gramian of the new system is approximately equal to that of the original system. Our contributions are as follows. First, we present a randomized algorithm that samples the sensors

Christophe Lacave, Andrej Zlatos

When the velocity field is not a priori known to be globally almost Lipschitz, global uniqueness of solutions to the two-dimensional Euler equations has been established only in some special cases, and the solutions to which these results apply share the property that the diffuse part of the vorticity is constant near the points where the velocity is insuffi

Alessandro Miano, Oleg A. Mukhanov

We developed and experimentally tested a Symmetric Traveling Wave Parametric Amplifier (STWPA) based on Three-Wave Mixing, using the new concept of a Symmetric rf- SQUID. This allows to fully control the second and third order nonlinearities of the STWPA by applying external currents. In this way, the optimal bias point can be reached, taking into account bo

Gary Cheng, Armin Askari, Kannan Ramchandran, Laurent El Ghaoui

In this paper, we consider the problem of selecting representatives from a data set for arbitrary supervised/unsupervised learning tasks. We identify a subset $S$ of a data set $A$ such that 1) the size of $S$ is much smaller than $A$ and 2) $S$ efficiently describes the entire data set, in a way formalized via convex optimization. In order to generate $|S|

Alexander E Patkowski

We offer a solution to a functional equation using properties of the Mellin transform. A new criteria for the Riemann Hypothesis is offered as an application of our main result, through a functional relationship with the Riemann xi function.

MicroBooNE collaboration, C. Adams, M. Alrashed, R. An

We report the first measurement of the flux-integrated cross section of $\nu_{\mu}$ charged-current single $\pi^{0}$ production on argon. This measurement is performed with the MicroBooNE detector, an 85 ton active mass liquid argon time projection chamber exposed to the Booster Neutrino Beam at Fermilab. This result on argon is compared to past measurements

Felipe Benítez, Julio Aracena, Christopher Thraves Caro

The Sitting Closer to Friends than Enemies (SCFE) problem is to find an embedding in a metric space for the vertices of a given signed graph so that, for every pair of incident edges with different sign, the positive edge is shorter (in the metric of the space) than the negative edge. In this document, we present new results regarding the SCFE problem when t

Marco Cariglia

We obtain the complete theory of Newton-Cartan gravity in a curved spacetime by considering the large $c$ limit of the vielbein formulation of General Relativity. Milne boosts originate from local Lorentzian transformations, and the special cases of torsionless and twistless torsional geometries are explained in the context of the larger locally Lorentzian t

Ran Wang, Yao Wang, Adeen Flinker

The superior temporal gyrus (STG) region of cortex critically contributes to speech recognition. In this work, we show that a proposed WaveNet, with limited available data, is able to reconstruct speech stimuli from STG intracranial recordings. We further investigate the impulse response of the fitted model for each recording electrode and observe phoneme le

Jacob Rafati, Roummel F. Marcia

Reinforcement Learning (RL) algorithms allow artificial agents to improve their action selections so as to increase rewarding experiences in their environments. Deep Reinforcement Learning algorithms require solving a nonconvex and nonlinear unconstrained optimization problem. Methods for solving the optimization problems in deep RL are restricted to the cla

Kentaro Yoshioka, Edward Lee, Mark Horowitz

We propose an end-to-end framework for training domain specific models (DSMs) to obtain both high accuracy and computational efficiency for object detection tasks. DSMs are trained with distillation \cite{hinton2015distilling} and focus on achieving high accuracy at a limited domain (e.g. fixed view of an intersection). We argue that DSMs can capture essenti

Le Zhang, Ali Gooya, Marco Pereanez, Bo Dong

Cardiac magnetic resonance (CMR) images play a growing role in the diagnostic imaging of cardiovascular diseases. Full coverage of the left ventricle (LV), from base to apex, is a basic criterion for CMR image quality and necessary for accurate measurement of cardiac volume and functional assessment. Incomplete coverage of the LV is identified through visual

Alessandra Graf, Penny Haxell

We give an efficient algorithm that, given a graph $G$ and a partition $V_1,\ldots,V_m$ of its vertex set, finds either an independent transversal (an independent set $\{v_1,\ldots,v_m\}$ in $G$ such that $v_i\in V_i$ for each $i$), or a subset $\mathcal B$ of vertex classes such that the subgraph of $G$ induced by $\bigcup\mathcal B$ has a small dominating

M. Gerin, H. Liszt, D. Neufeld, B. Godard

The transition between atomic and molecular hydrogen is associated with important changes in the structure of interstellar clouds, and marks the beginning of interstellar chemistry. Because of the relatively simple networks controlling their abundances, molecular ions are usually good probes of the underlying physical conditions including for instance the fr

Avah Banerjee, Dana Richards

In this paper we revisit the well known set-maxima problem in the oblivious setting. Let $X=\{x_1,\ldots, x_n\}$ be a set of $n$ elements with an underlying total order. Let $\mathcal{S}=\{S_1,\ldots,S_m\}$ be a collection of $m$ distinct subsets of $X$. The set-maxima problem asks to determine the maxima of all the sets in the collection. In the comparison

Wiktor Ejsmont

In \cite{Bia97} Biane proposed a new statistic on set partitions which he called \emph{restricted crossings}. In a series of papers \cite{Ans01,Ans04,Ans04b,Ans05} Anshelevich showed that this statistic is an essential tool to investigate stochastic processes on $q$-Fock space. In particular, Anshelevich constructed operators whose moments count restricted c

Hua Wang, Jingshan Qi, Xiaofeng Qian

Identifying intrinsic low-dimensional ferromagnets with high transition temperature and electrically tunable magnetism is crucial for the development of miniaturized spintronics and magnetoelectrics. Recently long-range 2D ferromagnetism was observed in van der Waals crystals CrI$_3$ and Cr$_2$Ge$_2$Te$_6$, however their Curie temperature is significantly lo

Yi Su, Lequn Wang, Michele Santacatterina, Thorsten Joachims

The ability to perform offline A/B-testing and off-policy learning using logged contextual bandit feedback is highly desirable in a broad range of applications, including recommender systems, search engines, ad placement, and personalized health care. Both offline A/B-testing and off-policy learning require a counterfactual estimator that evaluates how some

D. R. Lehman, W. C. Parke

A general method for the reduction of coupled spherical harmonic products is presented. When the total angular coupling is zero, the reduction leads to an explicitly real expression in the scalar products within the unit vector arguments of the spherical harmonics. For non-scalar couplings, the reduction gives Cartesian tensor forms for the spherical harmoni

Ivan P. Costa e Silva, José Luis Flores, Jónatan Herrera

We show that when a spacetime $\mathcal{M}(=M \cup \partial M)$ is globally hyperbolic with (possibly empty) smooth timelike boundary $\partial M$, a metrizable topology, the closed limit topology (CLT) introduced by F. Hausdorff himself in the 1950's in set theory, can be advantageously adopted on the Geroch-Kronheimer-Penrose causal completion of M, re

Alper Atamturk, Andres Gomez, Shaoning Han

Signal estimation problems with smoothness and sparsity priors can be naturally modeled as quadratic optimization with $\ell_0$-"norm" constraints. Since such problems are non-convex and hard-to-solve, the standard approach is, instead, to tackle their convex surrogates based on $\ell_1$-norm relaxations. In this paper, we propose a new iterative (co

Vipul Gupta, Shusen Wang, Thomas Courtade, Kannan Ramchandran

We propose OverSketch, an approximate algorithm for distributed matrix multiplication in serverless computing. OverSketch leverages ideas from matrix sketching and high-performance computing to enable cost-efficient multiplication that is resilient to faults and straggling nodes pervasive in low-cost serverless architectures. We establish statistical guarant

William Hutzel, John J. McCord, P. T. Raum, Ben Stern

The fractional quantum Hall effect (FQHE) observed at half filling of the second Landau level is believed to be caused by a pairing of composite fermions captured by the Moore-Read Pfaffian wave function. The generating Hamiltonian for the Moore-Read Pfaffian is a purely three-body model that breaks particle-hole symmetry and lacks other properties, such as

K. Kyriakou, K. Moulopoulos

The theory of orbital magnetization is reconsidered by defining additional quantities that incorporate a non-Hermitian effect due to anomalous operators that break the domain of definition of the Hermitian Hamiltonian. As a result, boundary contributions to the observable are rigorously and analytically taken into account. In this framework, we extend the st

Matthew Maciejewski, Gregory Sell, Leibny Paola Garcia-Perera, Shinji Watanabe

To date, the bulk of research on single-channel speech separation has been conducted using clean, near-field, read speech, which is not representative of many modern applications. In this work, we develop a procedure for constructing high-quality synthetic overlap datasets, necessary for most deep learning-based separation frameworks. We produced datasets th

Kashyap Chitta, Jose M. Alvarez, Adam Lesnikowski

In this paper, we introduce Deep Probabilistic Ensembles (DPEs), a scalable technique that uses a regularized ensemble to approximate a deep Bayesian Neural Network (BNN). We do so by incorporating a KL divergence penalty term into the training objective of an ensemble, derived from the evidence lower bound used in variational inference. We evaluate the unce

Philippe Schwaller, Teodoro Laino, Théophile Gaudin, Peter Bolgar

Organic synthesis is one of the key stumbling blocks in medicinal chemistry. A necessary yet unsolved step in planning synthesis is solving the forward problem: given reactants and reagents, predict the products. Similar to other work, we treat reaction prediction as a machine translation problem between SMILES strings of reactants-reagents and the products.

Bereneice Sephton, Adam Vallés, Fabian Steinlechner, Thomas Konrad

The efficient creation and detection of spatial modes of light has become topical of late, driven by the need to increase photon-bit-rates in classical and quantum communications. Such mode creation/detection is traditionally achieved with tools based on linear optics. Here we put forward a new spatial mode detection technique based on the nonlinear optical

Michael Lashkevich, Yaroslav Pugai

We study quasilocal operators in the quantum complex sinh-Gordon theory in the form factor approach. The free field procedure for descendant operators is developed by introducing the algebra of screening currents and related algebraic objects. We work out null vector equations in the space of operators. Further we apply the proposed algebraic structures to c

Shiqi Wang, Yizheng Chen, Ahmed Abdou, Suman Jana

Making neural networks robust against adversarial inputs has resulted in an arms race between new defenses and attacks. The most promising defenses, adversarially robust training and verifiably robust training, have limitations that restrict their practical applications. The adversarially robust training only makes the networks robust against a subclass of a

Ambra Nanni

In this work the optical properties of amorphous carbon (amC) dust condensed around carbon(C)-stars are constrained by comparing the observations for the Large Magellanic Cloud C-stars from the Two Micron All Sky Survey (2MASS) and from the Gaia data release 2 (DR2) with the synthetic photometry obtained by computing dust growth and radiative transfer in the

Yaqi Duan, Zheng Tracy Ke, Mengdi Wang

State aggregation is a popular model reduction method rooted in optimal control. It reduces the complexity of engineering systems by mapping the system's states into a small number of meta-states. The choice of aggregation map often depends on the data analysts' knowledge and is largely ad hoc. In this paper, we propose a tractable algorithm that est

Kieran Greer

This paper presents a batch classifier that has been improved from the earlier version and fixed a mistake in the earlier paper. Two important changes have been made. Each category is represented by a classifier, where each classifier classifies its own subset of data rows, using batch input values to represent the centroid. The first change is to use the ca

Yiwei Sun, Ngot Bui, Tsung-Yu Hsieh, Vasant Honavar

Real-world social networks and digital platforms are comprised of individuals (nodes) that are linked to other individuals or entities through multiple types of relationships (links). Sub-networks of such a network based on each type of link correspond to distinct views of the underlying network. In real-world applications, each node is typically linked to o

Kirti Joshi

This paper proves two theorems (1) Let $k$ be an algebraically closed field of characteristic $p>0$. I prove (Theorem 2.1.1) that if, $p > 13$ or $p = 11$, then the isomorphism class of any supersingular elliptic curve is a zero divisor in the ring of smooth, complete $k$-varieties and Bittner relations. In particular, this ring contains zero divisors. The p

Luca Tanzi, Eleonora Lucioni, Francesca Famà, Jacopo Catani

The competition of dipole-dipole and contact interactions leads to exciting new physics in dipolar gases, well-illustrated by the recent observation of quantum droplets and rotons in dipolar condensates. We show that the combination of the roton instability and quantum stabilization leads under proper conditions to a novel regime that presents supersolid pro

Nicholas Ma, David Nualart

In this paper we obtain a rate of convergence in the central limit theorem for high order weighted Hermite variations of the fractional Brownian motion. The proof is based on the techniques of Malliavin calculus and the quantitative stable limit theorems proved by Nourdin, Nualart and Peccati in 2016.

Aleksandr Berdnikov

This work focuses on important step in quantitative topology: given homotopic mappings from $S^m$ to $S^n$ of Lipschitz constant $L$, build the (asymptotically) simplest homotopy between them (meaning having the least Lipschitz constant). The present paper resolves this problem for the first case where Hopf invariant plays a role: $m = 3$, $n = 2$, construct

Sufeng Duan, Jiangtong Li, Hai Zhao

Rapidly developed neural models have achieved competitive performance in Chinese word segmentation (CWS) as their traditional counterparts. However, most of methods encounter the computational inefficiency especially for long sentences because of the increasing model complexity and slower decoders. This paper presents a simple neural segmenter which directly

Domingos S. P. Salazar, Sérgio A. Lira

We perform an analytic study on the stochastic thermodynamics of a small classical particle trapped in a time dependent single-well potential in the highly underdamped limit. It is shown that the nonequilibrium probability density function for the system's energy is a Maxwell-Boltzmann distribution (as in equilibrium) with a closed form time dependent ef

Damiano Anselmi

Several particles are not observed directly, but only through their decay products. We consider the possibility that they might be fakeons, i.e. fake particles, which mediate interactions but are not asymptotic states. A crucial role to determine the true nature of a particle is played by the imaginary parts of the one-loop radiative corrections, which are a

Lázaro L. Sales, Jonatas A. Silva, Eliângela P. Bento, Hidalyn T. C. M. Souza

In this paper, we have proposed a new method for solving the Gaussian integral. Introducing a parameter that depends on a $n$ index, we have found a general solution for this type of integral inspired by Taylor series of a simple function. We have demonstrated that this parameter represents the Taylor series coefficients of this function, a result very newsw

Kirti Joshi

The famous theorem of Belyi can be viewed as a characterization of compact Riemann surfaces which admit a non-empty open subset uniformized by a subgroup of $SL_2(\mathbb{Z})$ of finite index. I show that if $q\geq 5$, then ${\bf F}_q(T)$ is the one and only function field of positive characteristic for which such an analogous characterization of rigid analy

Luuk Stehouwer, Jan de Boer, Jorrit Kruthoff, Hessel Posthuma

Topological phases for free fermions in systems with crystal symmetry are classified by the topology of the valence band viewed as a vector bundle over the Brillouin zone. Additional symmetries, such as crystal symmetries which act non-trivially on the Brillouin zone, or time-reversal symmetry, endow the vector bundle with extra structure. These vector bundl

O. Grace Telford, Jessica K. Werk, Julianne J. Dalcanton, Benjamin F. Williams

As galaxies evolve, they must enrich and exchange gas with the surrounding medium, but the timing of these processes and how much gas is involved remain poorly understood. In this work, we leverage metals as tracers of past gas flows to constrain the history of metal ejection and redistribution in M31. This roughly $L*$ galaxy is a unique case where spatiall

A. Vazan, C. W. Ormel, L. Noack, C. Dominik

Sub-Neptune planets are a very common type of planets. They are inferred to harbour a primordial (H/He) envelope, on top of a (rocky) core, which dominates the mass. Here, we investigate the long-term consequences of the core properties on the planet mass-radius relation. We consider the role of various core energy sources resulting from core formation, its

Tommi Markkanen, Arttu Rajantie, Tommi Tenkanen

The observed dark matter abundance in the Universe can be fully accounted for by a minimally coupled spectator scalar field that was light during inflation and has sufficiently strong self-coupling. In this scenario, dark matter was produced during inflation by amplification of quantum fluctuations of the spectator field. The self-interaction of the field su

Micha Berkooz, Mikhail Isachenkov, Vladimir Narovlansky, Genis Torrents

We compute the exact, all energy scale, 4-point function of the large $N$ double-scaled SYK model, by using only combinatorial tools and relating the correlation functions to sums over chord diagrams. We apply the result to obtain corrections to the maximal Lyapunov exponent at low temperatures. We present the rules for the non-perturbative diagrammatic desc

Giuseppe Calajò, Yao-Lung L. Fang, Harold U. Baranger, Francesco Ciccarello

Excitation of a bound state in the continuum (BIC) through scattering is problematic since it is by definition uncoupled. Here, we consider a type of dressed BIC and show that it can be excited in a nonlinear system through multi-photon scattering and delayed quantum feedback. The system is a semi-infinite waveguide with linear dispersion coupled to a qubit,

S. Biondini, S. Vogl

We investigate the phenomenology of a simplified model with a Majorana fermion as dark matter candidate which interacts with Standard Model quarks via a colour-charged coannihilation partner. Recently it has been realized that non-perturbative dynamics, including the Sommerfeld effect, bound state formation/dissociation and thermal corrections, play an impor

J. -L. Fischer, H. Domínguez Sánchez, M. Bernardi

We describe the SDSS-IV MaNGA PyMorph Photometric (MPP-VAC) and MaNGA Deep Learning Morphology (MDLM-VAC) Value Added Catalogs. The MPP-VAC provides photometric parameters from Sérsic and Sérsic+Exponential fits to the 2D surface brightness profiles of the MaNGA DR15 galaxy sample. Compared to previous PyMorph analyses of SDSS imaging, our analysis of the Ma

Dallas Card, Michael Zhang, Noah A. Smith

Recent advances in deep learning have achieved impressive gains in classification accuracy on a variety of types of data, including images and text. Despite these gains, however, concerns have been raised about the calibration, robustness, and interpretability of these models. In this paper we propose a simple way to modify any conventional deep architecture

Arthur Loureiro, Andrei Cuceu, Filipe B. Abdalla, Bruno Moraes

We investigate the impact of prior models on the upper bound of the sum of neutrino masses, $\sum m_ν$. We use data from Large Scale Structure of galaxies, Cosmic Microwave Background, Type Ia SuperNovae, and Big Bang Nucleosynthesis. We probe physically motivated neutrino mass models (respecting oscillation experiment constraints) and compare them to constr

Ariane Dekker, Shin'ichiro Ando

Astrophysical neutrino events have been measured in the last couple of years, which show an isotropic distribution, and the current discussion is their astrophysical origin. We use both isotropic and anisotropic components of the diffuse neutrino data to constrain the contribution of a broad number of extra-galactic source populations to the observed neutrin

Samuel Homiller, Patrick Meade

The currently unmeasured triple Higgs coupling is one of the strong motivations for future physics programs at the LHC and beyond. A sufficiently precise measurement can lead to qualitative changes in our understanding of electroweak symmetry breaking and the cosmological history of the Higgs potential. As such, the quantitative measurement of this coupling

Thomas W. Grimm, Chongchuo Li, Eran Palti

The Swampland Distance Conjecture proposes that approaching infinite distances in field space an infinite tower of states becomes exponentially light. We study this conjecture for the complex structure moduli space of Calabi-Yau manifolds. In this context, we uncover significant structure within the proposal by showing that there is a rich spectrum of differ

Lauranne Lanz, Ryan C. Hickox, Mislav Baloković, Taro Shimizu

We present an analysis of a sample of 69 local obscured Swift/Burst Alert Telescope active galactic nuclei (AGNs) with X-ray spectra from NuSTAR and infrared (IR) spectral energy distributions from Herschel and WISE. We combine this X-ray and IR phenomenological modeling and find a significant correlation between reflected hard X-ray emission and IR AGN emis

Giulia Despali, Martin Sparre, Simona Vegetti, Mark Vogelsberger

We use high-resolution hydrodynamical simulation to test the difference of halo properties in cold dark matter (CDM) and a self-interacting dark matter (SIDM) scenario with a constant cross-section of $σ^\text{T}/m_χ=1\;\text{cm}^{2}\text{g}^{-1}$. We find that the interplay between dark matter self-interaction and baryonic physics induces a complex evolutio

Ayuki Kamada, Masaki Yamada, Tsutomu T. Yanagida

A spontaneously broken hidden U(1)$_h$ gauge symmetry can explain both the dark matter stability and the observed relic abundance. In this framework, the light gauge boson can mediate the strong dark matter self-interaction, which addresses astrophysical observations that are hard to explain in collisionless cold dark matter. Motivated by flavoured grand uni

S. Brendle

It is known from work of Perelman that any finite-time singularity of the Ricci flow on a compact three-manifold is modeled on an ancient $κ$-solution. We prove that the every noncompact ancient $κ$-solution in dimension $3$ is isometric to either the shrinking cylinders (or a quotient thereof), or the Bryant soliton.

Yuan-Zhu Wang, Dong-Sheng Shao, Jin-Liang Jiang, Shao-Peng Tang

As revealed recently by the modeling of the multi-wavelength data of the emission following GW170817/GRB 170817A, there was an off-axis energetic relativistic outflow component launched by this historic double neutron star merger event. In this work we use the results of these modeling to examine the energy extraction process of the central engine. We show t

Tudor D. Stanescu, Sumanta Tewari

Robust topologically trivial low-energy Andreev bound states (ABSs) induced by position-dependent effective potentials have recently come under renewed focus, in light of a remarkable set of experiments observing robust quantized zero-bias conductance plateaus in semiconductor-superconductor heterostructures. We show that (1) the partial spatial separation o

Yuta Suzuki

Walfisz (1963) proved the asymptotic formula \[ \sum_{n\le x}φ(n) = \frac{3}{π^2}x^2+O(x(\log x)^{\frac{2}{3}}(\log\log x)^{\frac{4}{3}}), \] which improved the error term estimate of Mertens (1874) and had been the best possible estimate for more than 50 years. Recently, H.-Q. Liu (2016) improved Walfisz's error term estimate to \[ \sum_{n\le x}φ(n) = \

Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras

We study how the behavior of deep policy gradient algorithms reflects the conceptual framework motivating their development. To this end, we propose a fine-grained analysis of state-of-the-art methods based on key elements of this framework: gradient estimation, value prediction, and optimization landscapes. Our results show that the behavior of deep policy

J. Belletête, A. M. Gainutdinov, J. L. Jacobsen, H. Saleur

This paper is the first in a series where we attempt to define defects in critical lattice models that give rise to conformal field theory topological defects in the continuum limit. We focus mostly on models based on the Temperley-Lieb algebra, with future applications to restricted solid-on-solid (also called anyonic chains) models, as well as non-unitary

Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle

Generating high-quality text with sufficient diversity is essential for a wide range of Natural Language Generation (NLG) tasks. Maximum-Likelihood (MLE) models trained with teacher forcing have consistently been reported as weak baselines, where poor performance is attributed to exposure bias (Bengio et al., 2015; Ranzato et al., 2015); at inference time, t

Jan E. Gerken, Axel Kleinschmidt, Oliver Schlotterer

We investigate one-loop four-point scattering of non-abelian gauge bosons in heterotic string theory and identify new connections with the corresponding open-string amplitude. In the low-energy expansion of the heterotic-string amplitude, the integrals over torus punctures are systematically evaluated in terms of modular graph forms, certain non-holomorphic

Paul Yaworsky

The overarching problem in artificial intelligence (AI) is that we do not understand the intelligence process well enough to enable the development of adequate computational models. Much work has been done in AI over the years at lower levels, but a big part of what has been missing involves the high level, abstract, general nature of intelligence. We addres

A. V. Plavin, Y. Y. Kovalev, A. B. Pushkarev, A. P. Lobanov

The apparent position of jet base (core) in radio-loud active galactic nuclei changes with frequency because of synchrotron self-absorption. Studying this `core shift` effect enables us to reconstruct properties of the jet regions close to the central engine. We report here results from core shift measurements in AGNs observed with global VLBI at 2 and 8 GHz