February 2019 arXiv papers — page 12

Jerzy A Filar, Michael Haythorpe, Walter Murray

We present an algorithm to find the determinant and its first and second derivatives of a rank-one corrected generator matrix of a doubly stochastic Markov chain. The motivation arises from the fact that the global minimiser of this determinant solves the Hamiltonian cycle problem. It is essential for algorithms that find global minimisers to evaluate both f

Raj Agrawal, Chandler Squires, Karren Yang, Karthik Shanmugam

Determining the causal structure of a set of variables is critical for both scientific inquiry and decision-making. However, this is often challenging in practice due to limited interventional data. Given that randomized experiments are usually expensive to perform, we propose a general framework and theory based on optimal Bayesian experimental design to se

Diego Berti

We consider the (viscosity) solution $u(x,t)$ of the nonlinear evolution equation $u_t-Δ^G_p u=0$ in a (not necessarily bounded) domain $Ω$, such that $u=0$ in $Ω$ at time $t=0$ and $u=1$ on the boundary of $Ω$ at all times. Here, $Δ_p^G$ is the game-theoretic $p$-laplacian, a $1$-homogeneous version of the standard $p$-laplacian. Also, we consider the (visc

Michael Haythorpe

It is well known that 3--regular graphs with arbitrarily large girth exist. Three constructions are given that use the former to produce non-Hamiltonian 3--regular graphs without reducing the girth, thereby proving that such graphs with arbitrarily large girth also exist. The resulting graphs can be 1--, 2-- or 3--edge-connected depending on the construction

Qinye Tang, Xiaozhe Wang

Sustained oscillations in power systems are dangerous. There are various mechanisms, for instance, limit cycle and forced oscillation, that may lead to sustained oscillations, which nevertheless are hard to differentiate. In this paper, a novel periodogram-based method to distinguish different oscillation mechanism is proposed, which can quantitatively extra

Jerzy A Filar, Michael Haythorpe, Serguei Rossomakhine

We analyse a polyhedron which contains the convex hull of all Hamiltonian cycles of a given undirected connected cubic graph. Our constructed polyhedron is defined by polynomially-many linear constraints in polynomially-many continuous (relaxed) variables. Clearly, the emptiness of the constructed polyhedron implies that the graph is non-Hamiltonian. However

Kaori Fuyuto, Xiao-Gang He, Gang Li, Michael Ramsey-Musolf

We introduce a scenario for CP-violating (CPV) dark photon interactions in the context of non-abelian kinetic mixing. Assuming an effective field theory that extends the Standard Model (SM) field content with an additional $U(1)$ gauge boson ($X$) and a $SU(2)_L$ triplet scalar, we show that there exist both CP-conserving and CPV dimension five operators inv

Tomoyuki Kimoto, Tatsuya Uezu

We study correspondence between a phase oscillator network with distributed natural frequencies and a classical XY model at finite temperatures with the same random and frustrated interactions used in the Sherrington-Kirkpatrick model. We perform numerical calculations of the spin glass order parameter $q$ and the distributions of the local fields. As a resu

Pouya Baniasadi, Vladimir Ejov, Jerzy A Filar, Michael Haythorpe

We present a polynomial complexity, deterministic, heuristic for solving the Hamiltonian Cycle Problem (HCP) in an undirected graph of order $n$. Although finding a Hamiltonian cycle is not theoretically guaranteed, we have observed that the heuristic is successful even in cases where such cycles are extremely rare, and it also performs very well on all HCP

Jike Lyu, Ignasi Fina, Raul Solanas, Josep Fontcuberta

The metastable orthorhombic phase of hafnia is generally obtained in polycrystalline films, whereas in epitaxial films, its formation has been much less investigated. We have grown Hf0.5Zr0.5O2 films by pulsed laser deposition, and the growth window (temperature and oxygen pressure during deposition and film thickness) for epitaxial stabilization of the ferr

F. Yang, Y. Zhao, Y. Qi, Y. Z. Tan

Hydrogen detection is of great importance in chemical and energy industries. Optical fiber hydrogen sensors show flexibility and compactness and have the potential for distributed analysis. However, traditional fiber sensors encounter a challenge for light to interact with hydrogen directly since hydrogen only display weak quadrupole absorption, and metallic

Jun Geng, Jinping Zhuge

In this paper, we consider a family of second-order elliptic systems subject to a periodically oscillating Robin boundary condition. We establish the qualitative homogenization theorem on any Lipschitz domains satisfying a non-resonance condition. We also use the quantitative estimates of oscillatory integrals to obtain the dimension-dependent convergence ra

Aleksey Buzmakov

In many practical tasks it is needed to estimate an effect of treatment on individual level. For example, in medicine it is essential to determine the patients that would benefit from a certain medicament. In marketing, knowing the persons that are likely to buy a new product would reduce the amount of spam. In this chapter, we review the methods to estimate

Jindong Chen, Ao Wang, Jiangjie Chen, Yanghua Xiao

Taxonomies play an important role in machine intelligence. However, most well-known taxonomies are in English, and non-English taxonomies, especially Chinese ones, are still very rare. In this paper, we focus on automatic Chinese taxonomy construction and propose an effective generation and verification framework to build a large-scale and high-quality Chine

Takuya Hosokawa

We study the weighted composition operators between the Lipschitz space and the space of bounded functions on the set of vertices of an infinite tree. We characterized the boundedness, the compactness, and the boundedness from below of weighted composition operators. We also determine the isometric weighted composition operators.

Carlos Floyd, Garegin A. Papoian, Christopher Jarzynski

Quantifying entropy production in various active matter phases will open new avenues for probing self-organization principles in these far-from-equilibrium systems. It has been hypothesized that the dissipation of free energy by active matter systems may be optimized to produce highly dissipative dynamical states, hence, leading to spontaneous emergence of m

Pengyu Chen, Xuping Zhang, Yongxiang Li

This paper deals with the following Cauchy problem to nonlinear time fractional non-autonomous integro-differential evolution equation of mixed type via measure of noncompactness $$ \left\{\begin{array}{ll} ^CD^α_tu(t)+A(t)u(t)= f(t,u(t),(Tu)(t), (Su)(t)),\quad t\in [0,a], \\[12pt] u(0)=A^{-1}(0)u_0 \end{array} \right. $$ in infinite-dimensional Banach space

Shromona Ghosh, Somil Bansal, Alberto Sangiovanni-Vincentelli, Sanjit A. Seshia

We consider the problem of extracting safe environments and controllers for reach-avoid objectives for systems with known state and control spaces, but unknown dynamics. In a given environment, a common approach is to synthesize a controller from an abstraction or a model of the system (potentially learned from data). However, in many situations, the relatio

Eric Liang, Hang Zhu, Xin Jin, Ion Stoica

Packet classification is a fundamental problem in computer networking. This problem exposes a hard tradeoff between the computation and state complexity, which makes it particularly challenging. To navigate this tradeoff, existing solutions rely on complex hand-tuned heuristics, which are brittle and hard to optimize. In this paper, we propose a deep reinfor

Myung Hwan Seo, Sueyoul Kim, Young-Joo Kim

We develop a Stata command xthenreg to implement the first-differenced GMM estimation of the dynamic panel threshold model, which Seo and Shin (2016, Journal of Econometrics 195: 169-186) have proposed. Furthermore, We derive the asymptotic variance formula for a kink constrained GMM estimator of the dynamic threshold model and include an estimation algorith

Kit Newton, Qin Li, Andrew Stuart

Many naturally-occuring models in the sciences are well-approximated by simplified models, using multiscale techniques. In such settings it is natural to ask about the relationship between inverse problems defined by the original problem and by the multiscale approximation. We develop an approach to this problem and exemplify it in the context of optical tom

Kyoung-Duck Park, Molly A. May, Haixu Leng, Jiarong Wang

Optical cavities can enhance and control light-matter interactions. This has recently been extended to the nanoscale, and with single emitter strong coupling regime even at room temperature using plasmonic nano-cavities with deep sub-diffraction-limited mode volumes. However, with emitters in static nano-cavities, this limits the ability to tune coupling str

Mishall Al-Zubaidie, Zhongwei Zhang, Ji Zhang

Public-key cryptography algorithms, especially elliptic curve cryptography (ECC) and elliptic curve digital signature algorithm (ECDSA) have been attracting attention from many researchers in different institutions because these algorithms provide security and high performance when being used in many areas such as electronic-healthcare, electronic-banking, e

Chenyang Xu, Liangde Tao, Huajingling Wu, Deshi Ye

In this paper, we consider the bandwidth-delay-hop constrained routing problem in large-scaled software defined networks. A number of demands, each of which specifies a source vertex and a sink vertex, are required to route in a given network. We are asked to select a subset of demands, and assign a routing path for each selected demand without violating the

Yao Liu, Ying Tai, Jilin Li, Shouhong Ding

In this paper, we propose a light reflection based face anti-spoofing method named Aurora Guard (AG), which is fast, simple yet effective that has already been deployed in real-world systems serving for millions of users. Specifically, our method first extracts the normal cues via light reflection analysis, and then uses an end-to-end trainable multi-task Co

H. O. Jeschke, H. Nakano, T. Sakai

We investigate the connection between highly frustrated kagome based Hamiltonians and a recently synthesized family of materials containing Ti3+ S=1/2 ions. Employing a combination of all electron density functional theory and numerical diagonalization techniques, we establish the Heisenberg Hamiltonians for the distorted kagome antiferromagnets Rb2NaTi3F12,

Tyler Derr, Hamid Karimi, Xiaorui Liu, Jiejun Xu

Network alignment, in general, seeks to discover the hidden underlying correspondence between nodes across two (or more) networks when given their network structure. However, most existing network alignment methods have added assumptions of additional constraints to guide the alignment, such as having a set of seed node-node correspondences across the networ

Eiji Akiyama, Eduard I. Vorobyov, Hauyu Baobabu Liu, Ruobing Dong

We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of the CO ($J$=2--1) line emission from the protoplanetary disk around T-Tauri star SU Aurigae (hereafter SU Aur). Previous observations in optical and near infrared wavelengths find a unique structure in SU Aur. One of the highlights of the observational results is that an extended

Jin Hyoun Kang, Jeong Ho Han, Yong-il Shin

We report the experimental realization of a topological Creutz ladder for ultracold fermionic atoms in a resonantly driven 1D optical lattice. The two-leg ladder consists of the two lowest orbital states of the optical lattice and the cross inter-leg links are generated via two-photon resonant coupling between the orbitals by periodic lattice shaking. The ch

S. Seki, M. Garst, J. Waizner, R. Takagi

Magnetic skyrmions, topological solitons characterized by a two-dimensional swirling spin texture, have recently attracted attention as stable particle-like objects. In a three-dimensional system, a skyrmion can extend in the third dimension forming a robust and flexible string structure, whose unique topology and symmetry are anticipated to host nontrivial

Samuel L. Rudge, Daniel S. Kosov

The waiting time distribution has, in recent years, proven to be a useful statistical tool for characterising transport in nanoscale quantum transport. In particular, as opposed to moments of the distribution of transferred charge, which have historically been calculated in the long-time limit, waiting times are able to detect non-renewal behaviour in mesosc

Jingyi Wang, Jianwen Feng, Yijun Lou, Guanrong Chen

In this technical note, we propose a practicable quantized sampled velocity data coupling protocol for synchronization of a set of harmonic oscillators. The coupling protocol is designed in a quantized way via interconnecting the velocities encoded by a uniform quantizer with a zooming parameter in either a fixed or an adjustable form over a directed communi

Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Richard G. Baraniuk

We investigate the internal representations that a recurrent neural network (RNN) uses while learning to recognize a regular formal language. Specifically, we train a RNN on positive and negative examples from a regular language, and ask if there is a simple decoding function that maps states of this RNN to states of the minimal deterministic finite automato

Rui Shu, Hung H. Bui, Jay Whang, Stefano Ermon

The recognition network in deep latent variable models such as variational autoencoders (VAEs) relies on amortized inference for efficient posterior approximation that can scale up to large datasets. However, this technique has also been demonstrated to select suboptimal variational parameters, often resulting in considerable additional error called the amor

Shahriar Talebi, Marwan A. Simaan, Zhihua Qu

All-Against-One (AAO) games are a special class of multi-player games where all players except one are in direct conflict with the remaining player. In the case of Linear Quadratic Differential (LQD) games, the AAO structure can be used to describe a situation where all players except one are trying to regulate the state of the system (drive it towards the o

Sen Zhang, Xin Ma, Hongwang Lu, Weikai He

Echolocating bats locate the targets by echolocation. Many theoretical frameworks have been suggested the abilities of bats are related to the shapes of bats ears, but few artificial bat-like ears have been made to mimic the abilities, the difficulty of which lies in the determination of the elevation angle of the target. In this study, we present a device w

Samer Houri, Daiki Hatanaka, Yaroslav M. Blanter, Hiroshi Yamaguchi

The aim of this work is to theoretically investigate the possibility of Kerr frequency combs in mechanical systems. In particular, whether microelectrome-chanical devices (MEMS) can be used to generate frequency combs in a manner that is analogous to the optical frequency combs generated in optical microresona-tors with Kerr-type nonlinearity. The analysis a

Panpan Yu, Qingna Li

Image ranking is to rank images based on some known ranked images. In this paper, we propose an improved linear ordinal distance metric learning approach based on the linear distance metric learning model. By decomposing the distance metric $A$ as $L^TL$, the problem can be cast as looking for a linear map between two sets of points in different spaces, mean

Behnam Malmir, Shing I Chang

This paper describes a method to convert Microsoft Kinect coordinates into gait parameters in order to detect a person's gait change. The proposed method can help quantify the progress of physical therapy. Microsoft Kinect, a popular platform for video games, was used to generate 25 joints to form a human skeleton, and then the proposed method converted

E. Sonbas, K. S. Dhuga, E. Gogus

By comparing the ratio of flux densities in the X-ray and UV wavebands by way of the spectral optical-X-Ray index, $α_{ox}$, we explore the relation between the emissions in the respective wavebands for a number of ULXs with known optical counterparts. We present a significant (anti)correlation between $α_{ox}$ and the L(2500 A)-UV luminosity. In comparison

Amin Jalali, Zhi Ding

In recent release of the new cellular standard known as 5G New Radio (5G-NR), the physical downlink control channel (PDCCH) has adopted polar codes for error protection. Similar to 4G-LTE, each active user equipment (UE) must blindly detect its own PDCCH in the downlink search space. This work investigates new ways to improve the accuracy of PDCCH blind dete

Yingjie Zhang, Pengfei Liu, Hongyi Sun, Hu Xu

It is recently noted that in certain centrosymmetric compounds, spin-orbit interaction couples each local sector that lacks inversion symmetry and thus leads to visible spin polarization effects in the real space, dubbed as 'hidden spin polarization (HSP)'. However, observable spin polarization of a given local sector suffers interference by its inve

Ali Cheraghian, Shafin Rahman, Lars Petersson

Recent deep learning architectures can recognize instances of 3D point cloud objects of previously seen classes quite well. At the same time, current 3D depth camera technology allows generating/segmenting a large amount of 3D point cloud objects from an arbitrary scene, for which there is no previously seen training data. A challenge for a 3D point cloud re

Hans Raj Tiwary, Victor Verdugo, Andreas Wiese

Linear programming is a powerful method in combinatorial optimization with many applications in theory and practice. For solving a linear program quickly it is desirable to have a formulation of small size for the given problem. A useful approach for this is the construction of an extended formulation, which is a linear program in a higher dimensional space

Karthikeya S Parunandi, Suman Chakravorty

Traditional stochastic optimal control methods that attempt to obtain an optimal feedback policy for nonlinear systems are computationally intractable. In this paper, we derive a decoupling principle between the open loop plan, and the closed loop feedback gains, that leads to a perturbation feedback control based solution to optimal control problems under a

Jin Wu

Magnetometer is a significant sensor for integrated navigation. However, it suffers from many kinds of unknown dynamic magnetic disturbances. We study the problem of online estimating such disturbances via a nonlinear optimization aided by intermediate quaternion estimation from inertial fusion. The proposed optimization is constrained by geographical distri

Afroza Shirin, Fabio Della Rossa, Isaac Klickstein, John Russell

The Glucose-Insulin-Glucagon nonlinear model [1-4] accurately describes how the body responds to exogenously supplied insulin and glucagon in patients affected by Type I diabetes. Based on this model, we design infusion rates of either insulin (monotherapy) or insulin and glucagon (dual therapy) that can optimally maintain the blood glucose level within desi

Tin Lai, Fabio Ramos, Gilad Francis

Sampling efficiency in a highly constrained environment has long been a major challenge for sampling-based planners. In this work, we propose Rapidly-exploring Random disjointed-Trees* (RRdT*), an incremental optimal multi-query planner. RRdT* uses multiple disjointed-trees to exploit local-connectivity of spaces via Markov Chain random sampling, which utili

Johan Helsing, Anders Karlsson

An integral equation-based numerical method for scattering from multi-dielectric cylinders is presented. Electromagnetic fields are represented via layer potentials in terms of surface densities with physical interpretations. The existence of null-field representations then adds superior flexibility to the modeling. Local representations are used for fast fi

Liyong Lin, Sander Thuijsman, Yuting Zhu, Simon Ware

In this work, we propose and develop a new discrete-event based actuator attack model on the closed-loop system formed by the plant and the supervisor. We assume the actuator attacker partially observes the execution of the closed-loop system and eavesdrops the control commands issued by the supervisor. The attacker can modify each control command on a speci

Xiangju Qin, Paul Blomstedt, Eemeli Leppäaho, Pekka Parviainen

Bayesian matrix factorization (BMF) is a powerful tool for producing low-rank representations of matrices and for predicting missing values and providing confidence intervals. Scaling up the posterior inference for massive-scale matrices is challenging and requires distributing both data and computation over many workers, making communication the main comput

Ulrike Malmendier, Demian Pouzo, Victoria Vanasco

How do macro-financial shocks affect investor behavior and market dynamics? Recent evidence on experience effects suggests a long-lasting influence of personally experienced outcomes on investor beliefs and investment, but also significant differences across older and younger generations. We formalize experience-based learning in an OLG model, where differen

Percy Deift

The author discusses integrability of Hamiltonian dynamical systems in the aftermath of KdV. The author also discusses the role of integrable systems in certain numerical computations, particularly the computation of the eigenvalues of a random symmetric matrix.

Walid Saad, Mehdi Bennis, Mingzhe Chen

The ongoing deployment of 5G cellular systems is continuously exposing the inherent limitations of this system, compared to its original premise as an enabler for Internet of Everything applications. These 5G drawbacks are currently spurring worldwide activities focused on defining the next-generation 6G wireless system that can truly integrate far-reaching

Jorge Campos-Gonzalez-Angulo, Raphael F. Ribeiro, Joel Yuen-Zhou

In the regime of ensemble vibrational strong coupling (VSC), a macroscopic number $N$ of molecular transitions couple to each resonant cavity mode, yielding two hybrid light-matter (polariton) modes, and a reservoir of $N-1$ dark states whose chemical dynamics are essentially those of the bare molecules. This fact is seemingly in opposition to the recently r

Kristoffer Glover

We consider the problem of optimally stopping a Brownian bridge with an unknown pinning time so as to maximise the value of the process upon stopping. Adopting a Bayesian approach, we assume the stopper has a general continuous prior and is allowed to update their belief about the value of the pinning time through sequential observations of the process. Unce

Jonas Latz

The subject of this article is the introduction of a new concept of well-posedness of Bayesian inverse problems. The conventional concept of (Lipschitz, Hellinger) well-posedness in [Stuart 2010, Acta Numerica 19, pp. 451-559] is difficult to verify in practice and may be inappropriate in some contexts. Our concept simply replaces the Lipschitz continuity of

Carlos E. Yaguna

The first-year results from DEAP-3600, a single-phase liquid argon direct-detection dark matter experiment, were recently reported. At first sight, they seem to provide no new constraints, as the limit lies well within the region already excluded by three different xenon experiments: LUX, PandaX-II, and XENON1T. We point out, however, that this conclusion is

Eric E. Severson, David Haley, David Doty

We study the composability of discrete chemical reaction networks (CRNs) that stably compute (i.e., with probability 0 of error) integer-valued functions $f:\mathbb{N}^d\to\mathbb{N}$. We consider output-oblivious CRNs in which the output species is never a reactant (input) to any reaction. The class of output-oblivious CRNs is fundamental, appearing in earl

Jae Sung Park, Dinesh Manocha

We present an efficient algorithm to compute tight upper bounds of collision probability between two objects with positional uncertainties, whose error distributions are represented with non-Gaussian forms. Our approach can handle noisy datasets from depth sensors, whose distributions may correspond to Truncated Gaussian, Weighted Samples, or Truncated Gauss

D. Gaiotto, T. Johnson-Freyd, E. Witten

We explore the dynamics of a simple class of two-dimensional models with $(0,1)$ supersymmetry, namely sigma-models with target $S^3$ and the minimal possible set of fields. For any nonzero value of the Wess--Zumino coupling $k$, we describe a superconformal fixed point to which we conjecture that the model flows in the infrared. For $k=0$, we conjecture tha

Parinya Ekparinya, Vincent Gramoli, Guillaume Jourjon

In this paper, we explore vulnerabilities and countermeasures of the recently proposed blockchain consensus based on proof-of-authority. The proof-of-work blockchains, like Bitcoin and Ethereum, have been shown both theoretically and empirically vulnerable to double spending attacks. This is why Byzantine fault tolerant consensus algorithms have gained popul

Christian Fries, Peter Kohl-Landgraf, Björn Paffen, Stefanie Weddigen

In this note we describe the application of existing smart contract technologies with the aim to construct a new digital representation of a financial derivative contract. We compare several existing DLT based technologies. We provide a detailed description of two separate prototypes which are able to be executed on a centralized and on a DLT platform respec

Friedrich Martin Schneider, Andreas Thom

We study harmonic functions and Poisson boundaries for Borel probability measures on general (i.e., not necessarily locally compact) topological groups, and we prove that a second-countable topological group is amenable if and only if it admits a fully supported, regular Borel probability measure with trivial Poisson boundary. This generalizes work of Kaiman

Guodong Zhu, Peng Wei

This paper addresses the air traffic flow management research problem of determining reroute, ground delay and air delay for flights using stochastic weather forecast information. The overall goal is to minimize system-wide reroute and delay costs. This problem is a primary concern in United States and especially in its northeastern region, and is also the k

Don Daniel, William T. Taitano, Luis Chacón

Upon application of a sufficiently strong electric field, electrons break away from thermal equilibrium and approach relativistic speeds. These highly energetic runaway electrons (MeV) play a significant role in tokamak disruption physics, and therefore their accurate understanding is essential to develop reliable mitigation strategies. For this purpose, we

Sophie Arnaud-Haond, Solenn Stoeckel, Diane Bailleul

Seagrass meadows are among the most important coastal ecosystems, in terms of both spatial extent and ecosystem services, but they are also declining worldwide. Understanding the drivers of seagrass meadow dynamics is essential for designing sound management, conservation, and restoration strategies. However, the poor knowledge of the effect of clonality on

Sebastián Donoso, Andreas Koutsogiannis, Wenbo Sun

Exploiting the recent work of Tao and Ziegler on a concatenation theorem on factors, we find explicit characteristic factors for multiple averages along polynomials on systems with commuting transformations, and use them to study criteria of joint ergodicity for sequences of the form $(T^{p_{1,j}(n)}_{1}\cdot\ldots\cdot T^{p_{d,j}(n)}_{d})_{n\in\mathbb{Z}},$

Fréderic Godin, Anjishnu Kumar, Arpit Mittal

In this paper, we investigate the challenges of using reinforcement learning agents for question-answering over knowledge graphs for real-world applications. We examine the performance metrics used by state-of-the-art systems and determine that they are inadequate for such settings. More specifically, they do not evaluate the systems correctly for situations

Yotam Fine

Let $G,D_{0},D_{1}$ be finite groups such that $D_{0}\trianglelefteq D_{1}$ are groups of automorphisms of $G$ that contain the inner automorphisms of $G$. Assume that $D_{1}/D_{0}$ has a normal $2$-complement and that $D_{1}$ acts fixed-point-freely on the set of $D_{0}$-conjugacy classes of involutions of $G$ (i.e., $C_{D_{1}}(a)D_{0}<D_{1}$ for every invo

Hong Xiao, Eky Febrianto, Qiaoling Zhang, Fehmi Cirak

We introduce an immersed high-order discontinuous Galerkin method for solving the compressible Navier-Stokes equations on non-boundary-fitted meshes. The flow equations are discretised with a mixed discontinuous Galerkin formulation and are advanced in time with an explicit time marching scheme. The discretisation meshes may contain simplicial (triangular or

Giacomo Mauro D&#39;Ariano, Marco Erba, Paolo Perinotti

Quantum walks (QWs) describe the evolution of quantum systems on graphs. An intrinsic degree of freedom---called the coin and represented by a finite-dimensional Hilbert space---is associated to each node. Scalar quantum walks are QWs with a one-dimensional coin. We propose a general strategy allowing one to construct scalar QWs on a broad variety of graphs,

Mukul Bhattacharya, Pawan Kumar

We present a method to estimate the source properties of FRBs from observations by assuming a fixed DM contribution from a MW-like host galaxy, pulse temporal broadening models for turbulent plasma and a flat FRB energy spectrum. We then perform Monte Carlo simulations to constrain the properties of the FRB source, its host galaxy and scattering in the inter

Richa Tripathi, Amit Reza, Dinesh Garg

The application of machine learning (ML) techniques span a vast spectrum ranging from speech, face and character recognition, medical diagnosis, anomaly detection in data to the general classification, prediction, and regression problems. In the present work, we solve the problem of predicting R_0 for disease spreading on complex networks using the regressio

Duvalier Madrid-Úsuga, Cristian E. Susa, John H. Reina

Understanding electron transfer in organic molecules is of great interest in quantum materials for light harvesting, energy conversion, and integration of molecules into solar cells. This, however, poses the challenge of designing specific optimal molecular structure for which the processes of ultrafast quantum coherence and electron transport are not so wel

Pierre Nazé, Marcus V. S. Bonança

The reliability of physical theories depends on whether they agree with well established physical laws. In this work, we address the compatibility of the Hamiltonian formulation of linear-response theory with the Second Law of Thermodynamics. In order to do so, we verify three complementary aspects often understood as statements of the Second Law: 1. No diss

Michael I. Ganzburg

Let $V\subset\R^m$ be a centrally symmetric convex body and let $V^*\subset\R^m$ be its polar. We prove limit relations between the sharp constants in the multivariate Markov-Bernstein-Nikolskii type inequalities for algebraic polynomials on $V^*$ and the corresponding constants for entire functions of exponential type with the spectrum in $V$.

Will Boney, Michael Lieberman

We provide comprehensive, level-by-level characterizations of large cardinals, in the range from weakly compact to strongly compact, by closure properties of powerful images of accessible functors. In the process, we show that these properties are also equivalent to various forms of tameness for abstract elementary classes. This systematizes and extends resu

Zheming Liang, Desong Bian, Dawei Su, Ruisheng Diao

Neglecting consumers&#39; comfort always leads to failure or slow-response to demand response request. In this paper, we propose several comprehensive comfort level models for various appliances in campus-based commercial buildings (CBs). The objective of the proposed system is to minimize O\&M costs of campus-based CBs and maximize various comfort levels si

Dmitrii V. Semenok, Alexander G. Kvashnin, Anna G. Ivanova, Volodymyr Svitlyk

Here we report targeted high-pressure synthesis of two novel high-$T_C$ hydride superconductors, $P6_3/mmc$-$ThH_9$ and $Fm\bar{3}m$-$ThH_{10}$, with the experimental critical temperatures ($T_C$) of 146 K and 159-161 K and upper critical magnetic fields ($μ$$H_C$) 38 and 45 Tesla at pressures 170-175 Gigapascals, respectively. Superconductivity was evidence

Gábor Korchmáros, Stefano Lia, Marco Timpanella

Let $\mathcal{C}$ be an irreducible plane curve of $\text{PG}(2,\mathbb{K})$ where $\mathbb{K}$ is an algebraically closed field of characteristic $p\geq 0$. A point $Q\in \mathcal{C}$ is an inner Galois point for $\mathcal{C}$ if the projection $π_Q$ from $Q$ is Galois. Assume that $\mathcal{C}$ has two different inner Galois points $Q_1$ and $Q_2$, both si

Moshiko Raboh, Roei Herzig, Gal Chechik, Jonathan Berant

Reasoning about complex visual scenes involves perception of entities and their relations. Scene graphs provide a natural representation for reasoning tasks, by assigning labels to both entities (nodes) and relations (edges). Unfortunately, reasoning systems based on SGs are typically trained in a two-step procedure: First, training a model to predict SGs fr

Shijia Liu, Hongyuan Mei, Adina Williams, Ryan Cotterell

While idiosyncrasies of the Chinese classifier system have been a richly studied topic among linguists (Adams and Conklin, 1973; Erbaugh, 1986; Lakoff, 1986), not much work has been done to quantify them with statistical methods. In this paper, we introduce an information-theoretic approach to measuring idiosyncrasy; we examine how much the uncertainty in Ma

Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma

Graph representation learning resurges as a trending research subject owing to the widespread use of deep learning for Euclidean data, which inspire various creative designs of neural networks in the non-Euclidean domain, particularly graphs. With the success of these graph neural networks (GNN) in the static setting, we approach further practical scenarios

Atul Ingle, Andreas Velten, Mohit Gupta

Single-photon avalanche diodes (SPADs) are an emerging technology with a unique capability of capturing individual photons with high timing precision. SPADs are being used in several active imaging systems (e.g., fluorescence lifetime microscopy and LiDAR), albeit mostly limited to low photon flux settings. We propose passive free-running SPAD (PF-SPAD) imag

Konstantin Posch, Jan Steinbrener, Jürgen Pilz

We present a novel approach for training deep neural networks in a Bayesian way. Classical, i.e. non-Bayesian, deep learning has two major drawbacks both originating from the fact that network parameters are considered to be deterministic. First, model uncertainty cannot be measured thus limiting the use of deep learning in many fields of application and sec

Paul C. Bell, Igor Potapov, Pavel Semukhin

We consider the following variant of the Mortality Problem: given $k\times k$ matrices $A_1, A_2, \dots,A_{t}$, does there exist nonnegative integers $m_1, m_2, \dots,m_t$ such that the product $A_1^{m_1} A_2^{m_2} \cdots A_{t}^{m_{t}}$ is equal to the zero matrix? It is known that this problem is decidable when $t \leq 2$ for matrices over algebraic numbers

Sarthak Jain, Byron C. Wallace

Attention mechanisms have seen wide adoption in neural NLP models. In addition to improving predictive performance, these are often touted as affording transparency: models equipped with attention provide a distribution over attended-to input units, and this is often presented (at least implicitly) as communicating the relative importance of inputs. However,

Mattia Cafferata, Alberto Perelli, Alessandro Zaccagnini

We prove an extension of the Bourgain-Sarnak-Ziegler theorem and then apply it to bound certain polynomial exponential sums with modular coefficients.

Sabine Thater, Davor Krajnovic, Michele Cappellari, Timothy A. Davis

Different massive black hole mass - host galaxy scaling relations suggest that the growth of massive black holes is entangled with the evolution of their host galaxies. The number of measured black hole masses is still limited, and additional measurements are necessary to understand the underlying physics of this apparent co-evolution. We add six new black h

David Vaknin, Daniel M. Pajerowski, Deborah L. Schlagel, Kevin W. Dennis

Employing elastic and inelastic neutron scattering (INS) techniques, we report on detailed microscopic properties of the ferromagnetism in he magnetic topological insulator (Bi$_{0.95}$Mn$_{0.05}$)$_{2}$Te$_{3}$. Neutron diffraction of polycrystalline samples show the ferromagnetic (FM) ordering is long-range within the basal plane, and mainly 2D in characte

Vladimir V&#39;yugin, Vladimir Trunov

Probabilistic forecasts in the form of probability distributions over future events have become popular in several fields of statistical science. The dissimilarity between a probability forecast and an outcome is measured by a loss function (scoring rule). Popular example of scoring rule for continuous outcomes is the continuous ranked probability score (CRP

Yunseong Nam, Jwo-Sy Chen, Neal C. Pisenti, Kenneth Wright

Quantum computing leverages the quantum resources of superposition and entanglement to efficiently solve computational problems considered intractable for classical computers. Examples include calculating molecular and nuclear structure, simulating strongly-interacting electron systems, and modeling aspects of material function. While substantial theoretical

Zuowei Shen, Haizhao Yang, Shijun Zhang

Given a function dictionary $\cal D$ and an approximation budget $N\in\mathbb{N}^+$, nonlinear approximation seeks the linear combination of the best $N$ terms $\{T_n\}_{1\le n\le N}\subseteq{\cal D}$ to approximate a given function $f$ with the minimum approximation error\[\varepsilon_{L,f}:=\min_{\{g_n\}\subseteq{\mathbb{R}},\{T_n\}\subseteq{\cal D}}\|f(x)

Caio Alves, Rodrigo Ribeiro, Remy Sanchis

In this work we prove general bounds for the diameter of random graphs generated by a preferential attachment model whose parameter is a function $f:\mathbb{N}\to[0,1]$ that drives the asymptotic proportion between the numbers of vertices and edges. These results are sharp when $f$ is a \textit{regularly varying function at infinity} with strictly negative i

Brant Jones

The game of best choice (also known as the secretary problem) is a model for sequential decision making with a long history and many variations. The classical setup assumes that the sequence of candidate rankings are uniformly distributed. Given a statistic on the symmetric group, one can instead weight each permutation according to an exponential function i

Jiayi Huang, Mostofa Patwary, Gregory Diamos

We show that recent innovations in deep reinforcement learning can effectively color very large graphs -- a well-known NP-hard problem with clear commercial applications. Because the Monte Carlo Tree Search with Upper Confidence Bound algorithm used in AlphaGoZero can improve the performance of a given heuristic, our approach allows deep neural networks trai

Andrea Prudenziati

We use the formalism of geodesic Witten diagrams to study the holographic realization of the conformal block expansion for entanglement entropy of two disjoint intervals. The agreement between the Ryu-Takayanagi formula and the identity block contribution has a dual realization as the product of bulk to boundary propagators. Quantum bulk corrections instead

Scott A Burns

A color appearance model (CAM) is an advanced colorimetric tool used to predict color appearance under a wide variety of viewing conditions. A chromatic adaptation transform (CAT) is an integral part of a CAM. Its role is to predict &#34;corresponding colors,&#34; that is, a pair of colors that have the same color appearance when viewed under different illum

Michelle Ntampaka, Camille Avestruz, Steven Boada, Joao Caldeira

In recent years, machine learning (ML) methods have remarkably improved how cosmologists can interpret data. The next decade will bring new opportunities for data-driven cosmological discovery, but will also present new challenges for adopting ML methodologies and understanding the results. ML could transform our field, but this transformation will require t