October 2020 arXiv papers — page 88

Xinyu Huang, Lijun He, Xing Chen, Liejun Wang

For in-vehicle application,task type and vehicle state information, i.e., vehicle speed, bear a significant impact on the task delay requirement. However, the joint impact of task type and vehicle speed on the task delay constraint has not been studied, and this lack of study may cause a mismatch between the requirement of the task delay and allocated comput

Z. C. Feng, Y. Charles Li

We introduced a more general predator-prey model to analyze the paradox of enrichment. We hope the results obtained for the model can guide us on identifying real field paradox of enrichment.

Michael C. Nelson

The random variate m is, in combinatorics, a basis for comparing permutations, as well as the solution to a centuries-old riddle involving the mishandling of hats. In statistics, m is the test statistic for a disused null hypothesis statistical test (NHST) of association, the matching method. In this paper, I show that the matching method has an absolute and

Klaus Ackermann, Simon D. Angus, Paul A. Raschky

Alternative data is increasingly adapted to predict human and economic behaviour. This paper introduces a new type of alternative data by re-conceptualising the internet as a data-driven insights platform at global scale. Using data from a unique internet activity and location dataset drawn from over 1.5 trillion observations of end-user internet connections

Yilin Shen, Wenhu Chen, Hongxia Jin

One major task of spoken language understanding (SLU) in modern personal assistants is to extract semantic concepts from an utterance, called slot filling. Although existing slot filling models attempted to improve extracting new concepts that are not seen in training data, the performance in practice is still not satisfied. Recent research collected questio

Lauren Baron, Brian Cohn, Roghayeh Barmaki

There have been a resurge lately on virtual therapy and other virtual- and tele-medicine services due to the new normal of practicing 'shelter at home'. In this paper, we propose a creative drawing game for virtual therapy and investigate user's comfort and movement freedom in a pilot study. In a mixed-design study, healthy participants (N=16, 8

Vu Dinh, Lam Si Tung Ho

One of the most important steps toward interpretability and explainability of neural network models is feature selection, which aims to identify the subset of relevant features. Theoretical results in the field have mostly focused on the prediction aspect of the problem with virtually no work on feature selection consistency for deep neural networks due to t

Chunlin Wang, Liping Yang

In this paper, we focus on a family of generalized Kloosterman sums over the torus. With a few changes to Haessig and Sperber's construction, we derive some relative $p$-adic cohomologies corresponding to the $L$-functions. We present explicit forms of bases of top dimensional cohomology spaces, so to obtain a concrete method to compute lower bounds of N

Aron Heleodoro

This paper introduces the notion of prestacks of Tate type and studies natural geometric conditions on them. We also develop a formalism of Tate-coherent sheaves and define a dualizing gerbe for Tate schemes locally almost of finite type.

Tao Zhong, Wonjik Kim, Masayuki Tanaka, Masatoshi Okutomi

Consecutive LiDAR scans compose dynamic 3D sequences, which contain more abundant information than a single frame. Similar to the development history of image and video perception, dynamic 3D sequence perception starts to come into sight after inspiring research on static 3D data perception. This work proposes a spatio-temporal neural network for human segme

Hongru Liang, Wenqiang Lei, Paul Yaozhu Chan, Zhenglu Yang

Definitive embeddings remain a fundamental challenge of computational musicology for symbolic music in deep learning today. Analogous to natural language, music can be modeled as a sequence of tokens. This motivates the majority of existing solutions to explore the utilization of word embedding models to build music embeddings. However, music differs from na

Chelsea Tanchip, Lei Yu, Aotao Xu, Yang Xu

We present a methodological framework for inferring symmetry of verb predicates in natural language. Empirical work on predicate symmetry has taken two main approaches. The feature-based approach focuses on linguistic features pertaining to symmetry. The context-based approach denies the existence of absolute symmetry but instead argues that such inference i

Yuncai Mei, Zehua Chen, Weitao Yang

The recently developed localized orbital scaling correction (LOSC) method shows the ability to systematically and size-consistently reduce the delocalization error existing in conventional density functional approximations (DFAs). Applying LOSC to conventional DFAs (LOSC-DFAs) gives much improvement for the description of related properties, including band g

W. H. Huang

The image classification machine learning model was trained with the intention to predict the category of the input image. While multiple state-of-the-art ensemble model methodologies are openly available, this paper evaluates the performance of a low-cost, simple algorithm that would integrate seamlessly into modern production-grade cloud-based applications

Cheng Yu, Bijun Zuo

In this paper, the initial-boundary value problem to the three-dimensional inhomogeneous, incompressible and heat-conducting Navier-Stokes equations with temperature-depending viscosity coefficient is considered in a bounded domain. The viscosity coefficient is degenerate and may vanish in the region of absolutely zero temperature. Global existence of weak s

Pengzi Liu, Hyeuk Jin Han, Julia Wei, David J. Hynek

Topological crystalline insulator tin telluride (SnTe) provides a rich playground to examine interactions of correlated electronic states, such as ferroelectricity, topological surface states, and superconductivity. Making SnTe into nanowires further induces novel electronic states due to one-dimensional (1D) confinement effects. Thus, for transport measurem

Xiaoyi Yang, Nynke M. D. Niezink, Rebecca Nugent

Describing and characterizing the impact of historical figures can be challenging, but unraveling their social structures perhaps even more so. Historical social network analysis methods can help and may also illuminate people who have been overlooked by historians but turn out to be influential social connection points. Text data, such as biographies, can b

Emre Sariyildiz, Satoshi Hangai, Tarik Uzunovic, Takahiro Nozaki

This paper analyses the robust stability and performance of the Disturbance Observer- (DOb-) based digital motion control systems in discrete-time domain. It is shown that the phase margin and the robustness of the digital motion controller can be directly adjusted by tuning the nominal plant model and the bandwidth of the observer. However, they have upper

Yong Yang

This paper presents the best known bounds for a conjecture of Gluck and a conjecture of Navarro.

Michael Damron, Jack Hanson, Christopher Janjigian, Wai-Kit Lam

In first-passage percolation, we assign i.i.d.~nonnegative weights $(t_e)$ to the nearest-neighbor edges of $\mathbb{Z}^d$ and study the induced pseudometric $T = T(x,y)$. In this paper, we focus on geodesics, or optimal paths for $T$, and estimate the empirical distribution of weights along them. We prove an upper bound for the expected number of edges with

Nikolas Siapoutis, Donald Richards, Bharath K. Sriperumbudur

We study shrinkage estimation of the mean parameters of a class of multivariate distributions for which the diagonal entries of the corresponding covariance matrix are certain quadratic functions of the mean parameter. This class of distributions includes the diagonal multivariate natural exponential families. We propose two classes of semi-parametric shrink

Kurt Leimer, Przemyslaw Musialski

We analyze the performance of a reduced-order simulation of geometric meta-materials based on zigzag patterns using a simplified representation. As geometric meta-materials we denote planar cellular structures which can be fabricated in 2d and bent elastically such that they approximate doubly-curved 2-manifold surfaces in 3d space. They obtain their elastic

Craig R. Guilbault, Molly A. Moran

We generalize Bestvina's notion of a $\mathcal{Z}$-boundary for a group to that of a "coarse $\mathcal{Z}$-boundary." We show that established theorems about $\mathcal{Z}$-boundaries carry over nicely to the more general theory, and that some wished-for properties of $\mathcal{Z}$-boundaries become theorems when applied to coarse $\mathcal{Z}$-bo

Shakeeb Ahmad, Zachary N. Sunberg, J. Sean Humbert

This paper proposes a framework for 3D obstacle avoidance in the presence of partial observability of environment obstacles. The method focuses on the utility of the Artificial Potential Function (APF) controller in a practical setting where noisy and incomplete information about the proximity is inevitable. We propose a Particle Filter (PF) approach to esti

Nahum C. Chávez, Francesco Mattiotti, J. A. Méndez-Bermúdez, Fausto Borgonovi

Overcoming the detrimental effect of disorder at the nanoscale is very hard since disorder induces localization and an exponential suppression of transport efficiency. Here we unveil novel and robust quantum transport regimes achievable in nanosystems by exploiting long-range hopping. We demonstrate that in a 1D disordered nanostructure in the presence of lo

Yudi Dong, Yu-Dong Yao

As a result of the worldwide transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19) has evolved into an unprecedented pandemic. Currently, with unavailable pharmaceutical treatments and vaccines, this novel coronavirus results in a great impact on public health, human society, and global economy, whi

Jingpei Lu, Florian Richter, Michael Yip

Keypoint detection is an essential building block for many robotic applications like motion capture and pose estimation. Historically, keypoints are detected using uniquely engineered markers such as checkerboards or fiducials. More recently, deep learning methods have been explored as they have the ability to detect user-defined keypoints in a marker-less m

Jieliang Luo, Hui Li

In this work we propose a learning approach to high-precision robotic assembly problems. We focus on the contact-rich phase, where the assembly pieces are in close contact with each other. Unlike many learning-based approaches that heavily rely on vision or spatial tracking, our approach takes force/torque in task space as the only observation. Our training

Guangxu Ju, Dongwei Xu, Carol Thompson, Matthew J. Highland

Burton-Cabrera-Frank (BCF) theory has proven to be a versatile framework to relate surface morphology and dynamics during crystal growth to the underlying mechanisms of adatom diffusion and attachment at steps. For an important class of crystal surfaces, including the basal planes of hexagonal close-packed and related systems, the steps in a sequence on a vi

Filippo Calderoni, David Marker, Luca Motto Ros, Assaf Shani

We explore countable ordered Archimedean groups from the point of view of descriptive set theory. We introduce the space of Archimedean left-orderings $\mathrm{Ar}(G)$ for a given countable group $G$, and prove that the equivalence relation induced by the natural action of $\mathrm{GL}_2(\mathbb{Q})$ on $\mathrm{Ar}(\mathbb{Q}^2)$ is not concretely classifia

Ziping Xu, Amirhossein Meisami, Ambuj Tewari

This paper studies the decision making problem with Funnel Structure. Funnel structure, a well-known concept in the marketing field, occurs in those systems where the decision maker interacts with the environment in a layered manner receiving far fewer observations from deep layers than shallow ones. For example, in the email marketing campaign application,

Kirill Neklyudov, Max Welling

Markov Chain Monte Carlo (MCMC) algorithms ubiquitously employ complex deterministic transformations to generate proposal points that are then filtered by the Metropolis-Hastings-Green (MHG) test. However, the condition of the target measure invariance puts restrictions on the design of these transformations. In this paper, we first derive the acceptance tes

Charvi Rastogi, Yunfeng Zhang, Dennis Wei, Kush R. Varshney

Several strands of research have aimed to bridge the gap between artificial intelligence (AI) and human decision-makers in AI-assisted decision-making, where humans are the consumers of AI model predictions and the ultimate decision-makers in high-stakes applications. However, people's perception and understanding are often distorted by their cognitive b

Laetitia Rodet, Dong Lai

Recent observations suggest that a large fraction of Kepler super-Earth systems have external giant planet companions (cold Jupiters), which can shape the architecture of the inner planets, in particular their mutual inclinations. The dynamical perturbation from cold Jupiters may account for the population of misaligned planets in the Kepler data. The effect

Philipp Harms, Peter W. Michor, Xavier Pennec, Stefan Sommer

In statistics, independent, identically distributed random samples do not carry a natural ordering, and their statistics are typically invariant with respect to permutations of their order. Thus, an $n$-sample in a space $M$ can be considered as an element of the quotient space of $M^n$ modulo the permutation group. The present paper takes this definition of

Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi

In this paper, we compute finite sample bounds for data-driven approximations of the solution to stochastic reachability problems. Our approach uses a nonparametric technique known as kernel distribution embeddings, and provides probabilistic assurances of safety for stochastic systems in a model-free manner. By implicitly embedding the stochastic kernel of

Xiaosheng Mu, Luciano Pomatto, Philipp Strack, Omer Tamuz

We show that under plausible levels of background risk, no theory of choice under risk -- such as expected utility theory, prospect theory, or rank dependent utility -- can simultaneously satisfy the following three economic postulates: (i) Decision makers are risk-averse over small gambles, (ii) they respect stochastic dominance, and (iii) they account for

Michael P. Howard, Zachary M. Sherman, Delia J. Milliron, Thomas M. Truskett

We extend Wertheim's thermodynamic perturbation theory to derive the association free energy of a multicomponent mixture for which double bonds can form between any two pairs of the molecules' arbitrary number of bonding sites. This generalization reduces in limiting cases to prior theories that restrict double bonding to at most one pair of sites pe

Sylvain Brochard, Srikanth B. Iyengar, Chandrashekhar Khare

It is proved that if $\varphi\colon A\to B$ is a local homomorphism of commutative noetherian local rings, a nonzero finitely generated $B$-module $N$ whose flat dimension over $A$ is at most $\mathrm{edim}\, A - \mathrm{edim}\, B$, is free over $B$, and $\varphi$ is a special type of complete intersection. This result is motivated by a "patching method" dev

Stan Gudder

This article points out that observables and instruments can be combined in many ways that have natural and physical interpretations. We shall mainly concentrate on the mathematical properties of these combinations. Section~1 reviews the basic definitions and observables are considered in Section~2. We study parts of observables, post-processing, generalized

Jørn Olav Jensen, Boris Kruglikov

We consider the equivalence problem for symplectic and conformal symplectic group actions on submanifolds and functions of symplectic and contact linear spaces. This is solved by computing differential invariants via the Lie-Tresse theorem.

Gareth A. Jones, Alexander K. Zvonkin

As a consequence of the classification of finite simple groups, the classification of permutation groups of prime degree is complete, apart from the question of when the natural degree $(q^n-1)/(q-1)$ of ${\rm L}_n(q)$ is prime. We present heuristic arguments and computational evidence to support a conjecture that for each prime $n\ge 3$ there are infinitely

Yeonjong Shin, Zhongqiang Zhang, George Em Karniadakis

We propose an abstract framework for analyzing the convergence of least-squares methods based on residual minimization when feasible solutions are neural networks. With the norm relations and compactness arguments, we derive error estimates for both continuous and discrete formulations of residual minimization in strong and weak forms. The formulations cover

Stefano Filipazzi, Roberto Svaldi

Let $(X,B)$ be a pair, and let $f \colon X \rightarrow S$ be a contraction with $-(K_X + B)$ nef over $S$. A conjecture, known as the Shokurov-Koll\'{a}r connectedness principle, predicts that $f^{-1} (s) \cap \mathrm{Nklt}(X,B)$ has at most two connected components, where $s \in S$ is an arbitrary schematic point and $\mathrm{Nklt}(X,B)$ denotes the non-klt

Wesley P. Chan, Sina Radmard, Zhao Quan Hew, Jon Morris

Following a specific user is a desired or even required capability for service robots in many human-robot collaborative applications. However, most existing person-following robots follow people without knowledge of who it is following. In this paper, we proposed an identity-specific person tracker, capable of tracking and identifying nearby people, to enabl

Juan Jose Garau Luis, Edward Crawley, Bruce Cameron

The study and benchmarking of Deep Reinforcement Learning (DRL) models has become a trend in many industries, including aerospace engineering and communications. Recent studies in these fields propose these kinds of models to address certain complex real-time decision-making problems in which classic approaches do not meet time requirements or fail to obtain

Zi-Yi Dou, Pengfei Liu, Hiroaki Hayashi, Zhengbao Jiang

Neural abstractive summarization models are flexible and can produce coherent summaries, but they are sometimes unfaithful and can be difficult to control. While previous studies attempt to provide different types of guidance to control the output and increase faithfulness, it is not clear how these strategies compare and contrast to each other. In this pape

Shyam Balaji, Michael Spannowsky, Carlos Tamarit

In first-order cosmological phase transitions, the asymptotic velocity of expanding bubbles is of crucial relevance for predicting observables like the spectrum of stochastic gravitational waves, or for establishing the viability of mechanisms explaining fundamental properties of the universe such as the observed baryon asymmetry. In these dynamic phase tran

Yoji Yamato

In recent years, utilization of heterogeneous hardware other than small core CPU such as GPU, FPGA or many core CPU is increasing. However, when using heterogeneous hardware, barriers of technical skills such as OpenMP, CUDA and OpenCL are high. Based on that, I have proposed environment-adaptive software that enables automatic conversion, configuration, and

Shashank Singh

Continuum-armed bandits (a.k.a., black-box or $0^{th}$-order optimization) involves optimizing an unknown objective function given an oracle that evaluates the function at a query point, with the goal of using as few query points as possible. In the most well-studied case, the objective function is assumed to be Lipschitz continuous and minimax rates of simp

Gregg Musiker, Kayla Wright

We give a combinatorial model for F-polynomials and g-vectors for type D cluster algebras where the associated quiver is acyclic. Our model utilizes a combination of dimer configurations and double dimer configurations which we refer to as mixed dimer configurations. In particular, we give a graph theoretic recipe that describes which monomials appear in suc

Ziqn Feng

A topological space $X$ is defined to have a neighborhood $P$-base at any $x\in X$ from some poset $P$ if there exists a neighborhood base $(U_p[x])_{p\in P}$ at $x$ such that $U_p[x]\subseteq U_{p'}[x]$ for all $p\geq p'$ in $P$. We prove that a compact space is countable, hence metrizable, if it has countable scattered height and a $\mathcal{K}(M)$

Georgios Bakirtzis, Cody H. Fleming, Christina Vasilakopoulou

Cyber-physical systems require the construction and management of various models to assure their correct, safe, and secure operation. These various models are necessary because of the coupled physical and computational dynamics present in cyber-physical systems. However, to date the different model views of cyber-physical systems are largely related informal

Long Zhao, Ting Liu, Xi Peng, Dimitris Metaxas

Adversarial data augmentation has shown promise for training robust deep neural networks against unforeseen data shifts or corruptions. However, it is difficult to define heuristics to generate effective fictitious target distributions containing "hard" adversarial perturbations that are largely different from the source distribution. In this paper,

B. Dober, Z. Ahmed, K. Arnold, D. T. Becker

A microwave SQUID multiplexer ($μ$MUX) has been optimized for coupling to large arrays of superconducting transition-edge sensor (TES) bolometers. We present the scalable cryogenic multiplexer chip design in a 1820-channel multiplexer configuration for the 4-8 GHz rf band. The key metrics of yield, sensitivity, and crosstalk are determined through measuremen

Yanyan Li, Raza Yunus, Nikolas Brasch, Nassir Navab

This work proposes a RGB-D SLAM system specifically designed for structured environments and aimed at improved tracking and mapping accuracy by relying on geometric features that are extracted from the surrounding. Structured environments offer, in addition to points, also an abundance of geometrical features such as lines and planes, which we exploit to des

Yuri G. Zarhin

Let $X$ be a polarized abelian variety over a field $K$. Let $O$ be a ring with an involution that acts on $X$ and this action is compatible with the polarization. We prove that the natural action of $O$ on $(X \times X^t)^4$ is compatible with a certain principal polarization.

Xander Faber, Jon Grantham

We extend the computations from our previous paper arXiv:2005.07054 to determine the maximum number of rational points on a curve over $\mathbb{F}_3$ and $\mathbb{F}_4$ with fixed gonality and small genus. We find, for example, that there is no curve of genus 5 and gonality 6 over a finite field. We propose two conjectures based on our data. First, an optima

Adrian de Wynter

We present an algorithm for solving binary classification problems when the dataset is not fully representative of the problem being solved, and obtaining more data is not possible. It relies on a trained model with loose accuracy constraints, an iterative hyperparameter searching-and-pruning procedure over a search space $\Theta$, and a data-generating func

Nadezhda Chirkova, Sergey Troshin

Initially developed for natural language processing (NLP), Transformers are now widely used for source code processing, due to the format similarity between source code and text. In contrast to natural language, source code is strictly structured, i.e., it follows the syntax of the programming language. Several recent works develop Transformer modifications

Siyu Dai, Wei Xu, Andreas Hofmann, Brian Williams

In order to provide adaptive and user-friendly solutions to robotic manipulation, it is important that the agent can learn to accomplish tasks even if they are only provided with very sparse instruction signals. To address the issues reinforcement learning algorithms face when task rewards are sparse, this paper proposes an intrinsic motivation approach that

Zhaoting Chen, Laura Wolz, Marta Spinelli, Steven G. Murray

We present a new halo model of neutral hydrogen (HI) calibrated to galaxy formation simulations at redshifts $z\sim0.1$ and $z\sim1.0$ that we employ to investigate the constraining power of interferometric HI intensity mapping on HI astrophysics. We demonstrate that constraints on the small-scale HI power spectrum can break the degeneracy between the HI den

W. G. Parrott, C. Bouchard, C. T. H. Davies, D. Hatton

We present the results of a lattice QCD calculation of the scalar and vector form factors for the unphysical $B_s\toη_s$ decay, over the full physical range of $q^2$. This is a useful testing ground both for lattice QCD and for our wider understanding of the behaviour of form factors. Calculations were performed using the highly improved staggered quark (HIS

S. Mazzi, J. Garcia, D. Zarzoso, Ye. O. Kazakov

Megaelectron volt (MeV) alpha particles will be the main source of plasma heating in magnetic confinement fusion reactors. Yet, instead of heating fuel ions, most of the energy of alpha particles is transferred to electrons. Furthermore, alpha particles can also excite Alfvenic instabilities, previously considered as detrimental. Contrary to expectations, we

I. C. Rodrigues, D. Bothner, G. A. Steele

Quantum control of electromagnetic fields was initially established in the optical domain and has been advanced to lower frequencies in the gigahertz range during the past decades extending quantum photonics to broader frequency regimes. In standard cryogenic systems, however, thermal decoherence prevents access to the quantum regime for photon frequencies b

Jonas Helsen, Ingo Roth, Emilio Onorati, Albert H. Werner

Randomized benchmarking (RB) refers to a collection of protocols that in the past decade have become central methods for characterizing quantum gates. These protocols aim at efficiently estimating the quality of a set of quantum gates in a way that is resistant to state preparation and measurement errors. Over the years many versions have been developed, how

Junjie Hu, Melvin Johnson, Orhan Firat, Aditya Siddhant

Pre-trained cross-lingual encoders such as mBERT (Devlin et al., 2019) and XLMR (Conneau et al., 2020) have proven to be impressively effective at enabling transfer-learning of NLP systems from high-resource languages to low-resource languages. This success comes despite the fact that there is no explicit objective to align the contextual embeddings of words

Zuxin Liu, Hongyi Zhou, Baiming Chen, Sicheng Zhong

This paper studies the constrained/safe reinforcement learning (RL) problem with sparse indicator signals for constraint violations. We propose a model-based approach to enable RL agents to effectively explore the environment with unknown system dynamics and environment constraints given a significantly small number of violation budgets. We employ the neural

Ramit Dey, Shauvik Biswas, Sumanta Chakraborty

In the context of higher dimensional braneworld scenario, we have argued that the occurrence of horizonless exotic compact objects, as an alternative to classical black holes, are more natural. These exotic compact objects carry a distinctive signature of the higher dimension, namely a tidal charge parameter, inherited from the projection of the higher dimen

Kaiyi Ji, Junjie Yang, Yingbin Liang

Bilevel optimization has arisen as a powerful tool for many machine learning problems such as meta-learning, hyperparameter optimization, and reinforcement learning. In this paper, we investigate the nonconvex-strongly-convex bilevel optimization problem. For deterministic bilevel optimization, we provide a comprehensive convergence rate analysis for two pop

Evan Sala, Joe Sawada, Abbas Alhakim

The greedy Prefer-same de Bruijn sequence construction was first presented by Eldert et al.[AIEE Transactions 77 (1958)]. As a greedy algorithm, it has one major downside: it requires an exponential amount of space to store the length $2^n$ de Bruijn sequence. Though de Bruijn sequences have been heavily studied over the last 60 years, finding an efficient c

Eric Jespers, Wei-Liang Sun

A finite group $G$ is said to have the nilpotent decomposition property (ND) if for every nilpotent element $\alpha$ of the integral group ring $\mathbb{Z}[G]$ one has that $\alpha e$ also belong to $\mathbb{Z}[G]$, for every primitive central idempotent $e$ of the rational group algebra $\mathbb{Q}[G]$. Results of Hales, Passi and Wilson, Liu and Passman sh

Theo Johnson-Freyd, Matthew Yu

We show that if $\mathcal{C}$ is a fusion $2$-category in which the endomorphism category of the unit object is $\rm{Vec}$ or $\rm{SVec}$, then the indecomposable objects of $\mathcal{C}$ form a finite group.

Rui-Xing Zhang, Zhi-Cheng Yang

Periodically-driven or Floquet systems can realize anomalous topological phenomena that do not exist in any equilibrium states of matter, whose classification and characterization require new theoretical ideas that are beyond the well-established paradigm of static topological phases. In this work, we provide a general framework to understand anomalous Floqu

Gilberto Colangelo, Martin Hoferichter, Peter Stoffer

At low energies hadronic vacuum polarization (HVP) is strongly dominated by two-pion intermediate states, which are responsible for about $70\%$ of the HVP contribution to the anomalous magnetic moment of the muon, $a_μ^\text{HVP}$. Lattice-QCD evaluations of the latter indicate that it might be larger than calculated dispersively on the basis of $e^+e^-\to\

Domenico Orlando, Vito Pellizzani, Susanne Reffert

In this note we discuss a non-relativistic system at large charge in a regime where Schrödinger symmetry is slightly broken by an explicit mass term for the dilaton field which non-linearly realizes non-relativistic scale invariance. To get there, we first develop the large-charge formalism from the linear sigma model perspective, including the harmonic trap

T. Shanks, B. Ansarinejad, R. M. Bielby, I. Heywood

High redshift sub-millimetre galaxies (SMGs) are usually assumed to be powered by star-formation. However, it has been clear for some time that $>$20% of such sources brighter than $\approx3$mJy host quasars. Here we analyse a complete sample of 12 sub-mm LABOCA/ALMA 870 $μ$m sources in the centre of the William Herschel Deep Field (WHDF) with multi-waveleng

Xiaozhou Feng, Brian Skinner

The thermoelectric properties of conductors with low electron density can be altered significantly by an applied magnetic field. For example, recent work has shown that Dirac/Weyl semimetals with a single pocket of carriers can exhibit a large enhancement of thermopower when subjected to a sufficiently large field that the system reaches the extreme quantum

Luke Pratley, Melanie Johnston-Hollitt, Bryan M. Gaensler

Next-generation spectro-polarimetric broadband surveys will probe cosmic magnetic fields in unprecedented detail, using the magneto-optical effect known as Faraday rotation. However, non-parametric methods such as RMCLEAN can introduce non-observable linearly polarized flux into a fitted model at negative wavelengths squared. This leads to Faraday rotation s

Hao Li, Chenxin Tao, Xizhou Zhu, Xiaogang Wang

Designing proper loss functions is essential in training deep networks. Especially in the field of semantic segmentation, various evaluation metrics have been proposed for diverse scenarios. Despite the success of the widely adopted cross-entropy loss and its variants, the mis-alignment between the loss functions and evaluation metrics degrades the network p

Nils Funk, Juan Tarrio, Sotiris Papatheodorou, Marija Popovic

With the aim of bridging the gap between high quality reconstruction and mobile robot motion planning, we propose an efficient system that leverages the concept of adaptive-resolution volumetric mapping, which naturally integrates with the hierarchical decomposition of space in an octree data structure. Instead of a Truncated Signed Distance Function (TSDF),

Ming Xie, Allan H. MacDonald

Near a magic twist angle, the lowest energy conduction and valence bands of bilayer graphene moiré superlattices become extremely narrow. The band dispersion that remains is sensitive to the moiré's strain pattern, nonlocal tunneling between layers, and filling-factor dependent Hartree and exchange band renormalizations. In this article we analyze the in

Mark P. Hertzberg, Fabrizio Rompineve, Jessie Yang

One of the most interesting candidates for dark matter are massive real scalar particles. A well-motivated example is from a pure Yang-Mills hidden sector, which locks up into glueballs in the early universe. The lightest glueball states are scalar particles and can act as a form of bosonic dark matter. If self-interactions are repulsive this can potentially

Soubhik Deb, Sreeram Kannan, David Tse

An important feature of Proof-of-Work (PoW) blockchains is full dynamic availability, allowing miners to go online and offline while requiring only 50% of the online miners to be honest. Existing Proof-of-stake (PoS), Proof-of-Space and related protocols are able to achieve this property only partially, either putting the additional assumption that adversary

Peter F. Faul, Graham Manuell, Jose Siqueira

In this paper we consider the conditions that need to be satisfied by two families of pseudofunctors with a common codomain for them to be collated into a bifunctor. We observe similarities between these conditions and distributive laws of monads before providing a unified framework from which both of these results may be inferred. We do this by proving a ve

Michele Ciampi, Alexandru Cojocaru, Elham Kashefi, Atul Mantri

Secure two-party computation considers the problem of two parties computing a joint function of their private inputs without revealing anything beyond the output. In this work, we consider the setting where the two parties (a classical Alice and a quantum Bob) can communicate only via a classical channel. Our first result shows that it is in general impossib

Joni Teräväinen

Let $\lambda$ denote the Liouville function. A problem posed by Chowla and by Cassaigne-Ferenczi-Mauduit-Rivat-S\'ark\"ozy asks to show that if $P(x)\in \mathbb{Z}[x]$, then the sequence $\lambda(P(n))$ changes sign infinitely often, assuming only that $P(x)$ is not the square of another polynomial. We show that the sequence $\lambda(P(n))$ indeed changes si

Yairon Cid-Ruiz, Jonathan Montaño

We show that the mixed volumes of arbitrary convex bodies are equal to mixed multiplicities of graded families of monomial ideals, and to normalized limits of mixed multiplicities of monomial ideals. This result evinces the close relation between the theories of mixed volumes from convex geometry and mixed multiplicities from commutative algebra.

Hepeng Li, Haibo He

We extend trust region policy optimization (TRPO) to multi-agent reinforcement learning (MARL) problems. We show that the policy update of TRPO can be transformed into a distributed consensus optimization problem for multi-agent cases. By making a series of approximations to the consensus optimization model, we propose a decentralized MARL algorithm, which w

Georgiana Neculae, Oliver Rhodes, Gavin Brown

This paper demonstrates how to construct ensembles of spiking neural networks producing state-of-the-art results, achieving classification accuracies of 98.71%, 100.0%, and 99.09%, on the MNIST, NMNIST and DVS Gesture datasets respectively. Furthermore, this performance is achieved using simplified individual models, with ensembles containing less than 50% o

Sergei Treil, Constanze Liaw

We consider contractive operators $T$ that are trace class perturbations of a unitary operator $U$. We prove that the dimension functions of the absolutely continuous spectrum of $T$, $T^*$ and of $U$ coincide. In particular, if $U$ has a purely singular spectrum then the characteristic function $θ$ of $T$ is a two-sided inner function, i.e. $θ(ξ)$ is unitar

Cheng-En Tsai, Jih-Chiang Tsai

The tribology between surfaces can have a profound impact on the response of a mechanical system, such as how granular particles are driven to flow. In this work, we perform experiments that time-resolve the tangential and normal components of the force between two semi-cylindrical PDMS (polydimethylsiloxane) samples immersed in fluid, as they slide against

Aliza U. Siddiqui, Mark M. Wilde

Bidirectional teleportation is a fundamental protocol for exchanging quantum information between two parties by means of a shared resource state and local operations and classical communication (LOCC). Here we develop two seemingly different ways of quantifying the simulation error of unideal bidirectional teleportation by means of the normalized diamond dis

Zixin Zhong, Wang Chi Cheung, Vincent Y. F. Tan

We consider a best arm identification (BAI) problem for stochastic bandits with adversarial corruptions in the fixed-budget setting of T steps. We design a novel randomized algorithm, Probabilistic Sequential Shrinking($u$) (PSS($u$)), which is agnostic to the amount of corruptions. When the amount of corruptions per step (CPS) is below a threshold, PSS($u$)

Markus Grassl, Felix Huber, Andreas Winter

We show that a relatively simple reasoning using von Neumann entropy inequalities yields a robust proof of the quantum Singleton bound for quantum error-correcting codes (QECC). For entanglement-assisted quantum error-correcting codes (EAQECC) and catalytic codes (CQECC), a type of generalized quantum Singleton bound [Brun et al., IEEE Trans. Inf. Theory 60(

Johannes Rau

In this follow-up to arXiv:2007.11642, our main result is a tropical Lefschetz-Hopf trace formula for matroidal automorphisms. We show that both sides of the formula are equal to the (generalized) beta invariant of the lattice of fixed flats.

Stelios Tsampas, Christian Williams, Andreas Nuyts, Dominique Devriese

We introduce three general compositionality criteria over operational semantics and prove that, when all three are satisfied together, they guarantee weak bisimulation being a congruence. Our work is founded upon Turi and Plotkin's mathematical operational semantics and the coalgebraic approach to weak bisimulation by Brengos. We demonstrate each criteri

Satvik Singh, Ion Nechita

We analyze bipartite matrices and linear maps between matrix algebras, which are respectively, invariant and covariant, under the diagonal unitary and orthogonal groups' actions. By presenting an expansive list of examples from the literature, which includes notable entries like the Diagonal Symmetric states and the Choi-type maps, we show that this clas

Dennis Stock

The past lightcone of an observer in a cosmological spacetime is the unique geometric structure directly linked to observations. After general properties of the Hawking energy along slices of the past lightcone have previously been studied, the present work continues along this path by providing explicit cosmological applications of the Hawking energy associ

Tarik P. Cysne, Marcio Costa, Luis M. Canonico, M. Buongiorno Nardelli

It has been recently shown that monolayers of transition metal dichalcogenides (TMDs) in the 2H structural phase exhibit relatively large orbital Hall conductivity plateaus within their energy band gaps, where their spin Hall conductivities vanish. However, since the valley Hall effect (VHE) in these systems also generates a transverse flow of orbital angula