December 2020 arXiv papers — page 2

Nirmalya Brahma, Chethan Krishnan

We consider gauge theories of non-Abelian $finite$ groups, and discuss the 1+1 dimensional lattice gauge theory of the permutation group $S_N$ as an illustrative example. The partition function at finite $N$ can be written explicitly in a compact form using properties of $S_N$ conjugacy classes. A natural large-$N$ limit exists with a new 't Hooft coupling,

Qinyuan Ye, Belinda Z. Li, Sinong Wang, Benjamin Bolte

Closed-book question-answering (QA) is a challenging task that requires a model to directly answer questions without access to external knowledge. It has been shown that directly fine-tuning pre-trained language models with (question, answer) examples yields surprisingly competitive performance, which is further improved upon through adding an intermediate p

Anand Pathak, Shakti N. Menon, Sitabhra Sinha

In order to understand the complex cognitive functions of the human brain, it is essential to study the structural connectome, i.e., the wiring of different brain regions to each other through axonal pathways. However, the high degree of plasticity and cross-population variability in human brains makes it difficult to relate structure to function, motivating

Anna Jaskulska, Kinga Skorupska, Barbara Karpowicz, Cezary Biele

Voice User Interfaces (VUIs) owing to recent developments in Artificial Intelligence (AI) and Natural Language Processing (NLP), are becoming increasingly intuitive and functional. They are especially promising for older adults, also with special needs, as VUIs remove some barriers related to access to Information and Communications Technology (ICT) solution

Marcos A. Ramirez

The thermodynamic stability of braneworld cosmological solutions in five-dimensional Einstein-Gauss-Bonnet gravity is addressed, particularly in the context of the splitting vacuum thin shells in which the shells represent either an ephemeral or a branch-changing false vacuum bubble spontaneously emerging from the braneworld and there is more than one possib

Jonathan P. Keating, Mo Dick Wong

We study the 'critical moments' of subcritical Gaussian multiplicative chaos (GMCs) in dimensions $d \leq 2$. In particular, we establish a fully explicit formula for the leading order asymptotics, which is closely related to large deviation results for GMCs and demonstrates a similar universality feature. We conjecture that our result correctly describes th

Connor M. Holland, Yukai Lu, Lawrence W. Cheuk

Experimental control and detection of atoms and molecules often rely on optical transitions between different electronic states. In many cases, substructure such as hyperfine or spin-rotation structure leads to the need for multiple optical frequencies spaced by MHz to GHz. The task of creating multiple optical frequencies -- optical spectral engineering --

Nima Arkani-Hamed, Tzu-Chen Huang, Yu-tin Huang

We re-examine the constraints imposed by causality and unitarity on the low-energy effective field theory expansion of four-particle scattering amplitudes, exposing a hidden "totally positive" structure strikingly similar to the positive geometries associated with grassmannians and amplituhedra. This forces the infinite tower of higher-dimension operators to

Zachary Bradshaw, Igor Kukavica, Wojciech S. Ożański

We prove existence of global-in-time weak solutions of the incompressible Navier-Stokes equations in the half-space $\mathbb{R}^3_+$ with initial data in a weighted space that allow non-uniformly locally square integrable functions that grow at spatial infinity in an intermittent sense. The space for initial data is built on cubes whose sides $R$ are proport

Gaber Faisel, Jhih-Ying Su, Jusak Tandean

We investigate the possibility that scalar leptoquarks generate consequential effects on the flavor-changing neutral-current decays of charmed hadrons into final states with missing energy ($\not\!\!E$) carried away by either standard model or sterile neutrinos. We focus on scenarios involving the $R_2$, $\tilde R_2$, and $\bar S_1$ leptoquarks and take into

Amogh Gudi, Marian Bittner, Jan van Gemert

Remote photo-plethysmography (rPPG) uses a camera to estimate a person's heart rate (HR). Similar to how heart rate can provide useful information about a person's vital signs, insights about the underlying physio/psychological conditions can be obtained from heart rate variability (HRV). HRV is a measure of the fine fluctuations in the intervals between hea

Andrés M. Somoza, Pablo Serna, Adam Nahum

The simplest topologically ordered phase in 2+1D is the deconfined phase of $Z_2$ gauge theory, realized for example in the toric code. This phase permits a duality that exchanges electric and magnetic excitations (``$e$'' and ``$m$'' particles). Condensing either particle while the other remains gapped yields a phase transition with 3D Ising exponents. More

Andrei Jaikin-Zapirain, Diego López-Álvarez

Given a ring $R$, the notion of Sylvester rank function was conceived within the context of Cohn's classification theory of epic division $R$-rings. In this paper we study and describe the space of Sylvester rank functions on certain families of rings, including Dedekind domains, simple left noetherian rings and skew Laurent polynomial rings $\mathcal{D}[t^{

Shabnam Daghaghi, Tharun Medini, Nicholas Meisburger, Beidi Chen

Softmax classifiers with a very large number of classes naturally occur in many applications such as natural language processing and information retrieval. The calculation of full softmax is costly from the computational and energy perspective. There have been various sampling approaches to overcome this challenge, popularly known as negative sampling (NS).

Yu Liu, Ming-Guang Hu, Matthew A. Nichols, Dongzheng Yang

Chemical reactions represent a class of quantum problems that challenge both the current theoretical understanding and computational capabilities. Reactions that occur at ultralow temperatures provide an ideal testing ground for quantum chemistry and scattering theories, as they can be experimentally studied with unprecedented control, yet display dynamics t

Sarah E. Grefe, Hsin-Hua Lai, Silke Paschen, Qimiao Si

There is considerable interest in the intersection of correlations and topology, especially in metallic systems. Among the outstanding questions are how strong correlations drive novel topological states and whether such states can be readily controlled. Here we study the effect of a Zeeman coupling on a Weyl-Kondo semimetal in a nonsymmorphic and noncentros

Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu

Most recent semantic segmentation methods adopt a fully-convolutional network (FCN) with an encoder-decoder architecture. The encoder progressively reduces the spatial resolution and learns more abstract/semantic visual concepts with larger receptive fields. Since context modeling is critical for segmentation, the latest efforts have been focused on increasi

Manoj Mandal, Sabyasachi Pal

We made a detailed study of the timing and spectral properties of the X-ray pulsar 1A 0535+262 during the recent giant outburst in 2020 November and December. The flux of the pulsar reached a record value of $\sim$12.5 Crab as observed by Swift/BAT (15--50 keV) and the corresponding mass accretion rate was $\sim6.67\times10^{17}$ g s$^{-1}$ near the peak of

Nikolaos Kekatos

Hybrid systems can express a plethora of physical phenomena and systems as they can combine continuous and discrete dynamics. There exist several tools that enable the reachability analysis of hybrid systems modeled as hybrid automata. However, these tools exhibit certain limitations in the type of mathematical operations that they natively support. For exam

Sida Peng, Yuanqing Zhang, Yinghao Xu, Qianqian Wang

This paper addresses the challenge of novel view synthesis for a human performer from a very sparse set of camera views. Some recent works have shown that learning implicit neural representations of 3D scenes achieves remarkable view synthesis quality given dense input views. However, the representation learning will be ill-posed if the views are highly spar

Rajkumar Pujari, Dan Goldwasser

When evaluating an answer choice for Reading Comprehension task, other answer choices available for the question and the answers of related questions about the same paragraph often provide valuable information. In this paper, we propose a method to leverage the natural language relations between the answer choices, such as entailment and contradiction, to im

Dustin Lang, David W. Hogg

We review the well-known matched filter method for the detection of point sources in astronomical images. This is shown to be optimal (that is, to saturate the Cramer--Rao bound) under stated conditions that are very strong: an isolated source in background-dominated imaging with perfectly known background level, point-spread function, and noise models. We s

Robert B. Allen

We explore using the Suggested Upper Merged Ontology (SUMO) to develop a semantic simulation. We provide two proof-of-concept demonstrations modeling transitions in a simulated gasoline engine using a general-purpose programming language. Rather than focusing on computationally highly intensive techniques, we explore a less computationally intensive approach

Serguei Barannikov, Daria Voronkova, Alexander Mironenko, Ilya Trofimov

Neural network training is commonly based on SGD. However, the understanding of SGD's ability to converge to good local minima, given the non-convex nature of loss functions and the intricate geometric characteristics of loss landscapes, remains limited. In this paper, we apply topological data analysis methods to loss landscapes to gain insights into the le

Jiatao Gu, Xiang Kong

Fully non-autoregressive neural machine translation (NAT) is proposed to simultaneously predict tokens with single forward of neural networks, which significantly reduces the inference latency at the expense of quality drop compared to the Transformer baseline. In this work, we target on closing the performance gap while maintaining the latency advantage. We

Ofir Press, Noah A. Smith, Mike Lewis

Increasing the input length has been a driver of progress in language modeling with transformers. We identify conditions where shorter inputs are not harmful, and achieve perplexity and efficiency improvements through two new methods that decrease input length. First, we show that initially training a model on short subsequences before moving on to longer on

Baturalp Buyukates, Sennur Ulukus

We consider a federated learning framework in which a parameter server (PS) trains a global model by using $n$ clients without actually storing the client data centrally at a cloud server. Focusing on a setting where the client datasets are fast changing and highly temporal in nature, we investigate the timeliness of model updates and propose a novel timely

Anatoly Dymarsky, Alfred Shapere

We discuss the holographic description of Narain $U(1)^c\times U(1)^c$ conformal field theories, and their potential similarity to conventional weakly coupled gravity in the bulk, in the sense that the effective IR bulk description includes "$U(1)$ gravity" amended with additional light degrees of freedom. Starting from this picture, we formulate the hypothe

Aolin Xu

We study the continuity property of the generalized entropy as a function of the underlying probability distribution, defined with an action space and a loss function, and use this property to answer the basic questions in statistical learning theory: the excess risk analyses for various learning methods. We first derive upper and lower bounds for the entrop

Wenhui Wang, Hangbo Bao, Shaohan Huang, Li Dong

We generalize deep self-attention distillation in MiniLM (Wang et al., 2020) by only using self-attention relation distillation for task-agnostic compression of pretrained Transformers. In particular, we define multi-head self-attention relations as scaled dot-product between the pairs of query, key, and value vectors within each self-attention module. Then

Lucas Prado Osco, Mauro dos Santos de Arruda, Diogo Nunes Gonçalves, Alexandre Dias

In this paper, we propose a novel deep learning method based on a Convolutional Neural Network (CNN) that simultaneously detects and geolocates plantation-rows while counting its plants considering highly-dense plantation configurations. The experimental setup was evaluated in a cornfield with different growth stages and in a Citrus orchard. Both datasets ch

Shang-Wen Li

Since its introduction in 2011, there have been over 4000 MOOCs on various subjects on the Web, serving over 35 million learners. MOOCs have shown the ability to democratize knowledge dissemination and bring the best education in the world to every learner. However, the disparate distances between participants, the size of the learner population, and the het

Michał Oszmaniec, Ninnat Dangniam, Mauro E. S. Morales, Zoltán Zimborás

Fermionic Linear Optics (FLO) is a restricted model of quantum computation which in its original form is known to be efficiently classically simulable. We show that, when initialized with suitable input states, FLO circuits can be used to demonstrate quantum computational advantage with strong hardness guarantees. Based on this, we propose a quantum advantag

Gregory Gold, David A. McGady, Subodh P. Patil, Valeri Vardanyan

Particle-antiparticle pairs can be produced by background electric fields via the Schwinger mechanism provided they are unconfined. If, as in QED in (3+1)-$d$ these particles are massive, the particle production rate is exponentially suppressed below a threshold field strength. Above this threshold, the energy for pair creation must come from the electric fi

Mehdi Bahri, Gaétan Bahl, Stefanos Zafeiriou

Graph Neural Networks (GNNs) have emerged as a powerful and flexible framework for representation learning on irregular data. As they generalize the operations of classical CNNs on grids to arbitrary topologies, GNNs also bring much of the implementation challenges of their Euclidean counterparts. Model size, memory footprint, and energy consumption are comm

Marko Toroš, Uroš Delić, Fagin Hales, Tania S. Monteiro

The strong light-matter optomechanical coupling offered by Coherent Scattering (CS) set-ups have allowed the experimental realisation of quantum ground state cavity cooling of the axial motion of a levitated nanoparticle [U. Deli\'{c} et al., Science 367, 892 (2020)]. An appealing milestone is now quantum 2D cooling of the full in-plane motion, in any direct

Vishnu Jejjala, Damian Kaloni Mayorga Pena, Challenger Mishra

Ricci flat metrics for Calabi-Yau threefolds are not known analytically. In this work, we employ techniques from machine learning to deduce numerical flat metrics for the Fermat quintic, for the Dwork quintic, and for the Tian-Yau manifold. This investigation employs a single neural network architecture that is capable of approximating Ricci flat Kaehler met

Mario Hubert

Philosophers now seem to agree that frequentism is an untenable strategy to explain the meaning of probabilities. Nevertheless, I want to revive frequentism, and I will do so by grounding probabilities on typicality in the same way as the thermodynamic arrow of time can be grounded on typicality within statistical mechanics. This account, which I will call t

Navid Abbasi, Matthias Kaminski

We consider a holographic thermal state and perturb it by a scalar operator whose associated real-time Green's function has only gapped poles. These gapped poles correspond to the non-hydrodynamic quasinormal modes of a massive scalar perturbation around a Schwarzschild black brane. Relations between pole-skipping points, critical points and quasinormal mode

Lev Barinov, Sergey Ryabichko, William Bialek, Thomas Gregor

There is growing appreciation that gene function is connected to the dynamic structure of the chromosome. Here we explore the interplay between three-dimensional structure and transcriptional activity at the single cell level. We show that inactive loci are spatially more compact than active ones, and that within active loci the enhancer driving transcriptio

D. V. Bulgakova, N. Buzhinsky, Y. O. Goncharov

We revisit the question of classification of balanced circular words and focus on the case of a ternary alphabet. We propose a $3$-dimensional generalisation of the discrete approximation representation of Christoffel words. By considering the minimal bound $3$ for abelian complexity of balanced circular words over a ternary alphabet, we provide a classifica

Marianne Bauer, Mariela D. Petkova, Thomas Gregor, Eric F. Wieschaus

In genetic networks, information of relevance to the organism is represented by the concentrations of transcription factor molecules. In order to extract this information the cell must effectively "measure"' these concentrations, but there are physical limits to the precision of these measurements. We explore this trading between bits of precision in measuri

Luca Oneto, Silvia Chiappa

Machine learning based systems are reaching society at large and in many aspects of everyday life. This phenomenon has been accompanied by concerns about the ethical issues that may arise from the adoption of these technologies. ML fairness is a recently established area of machine learning that studies how to ensure that biases in the data and model inaccur

Brett T. Lopez, Jean-Jacques E. Slotine

This work develops a new direct adaptive control framework that extends the certainty equivalence principle to general nonlinear systems with unmatched model uncertainties. The approach adjusts the rate of adaptation online to eliminate the effects of parameter estimation transients on closed-loop stability. The method can be immediately combined with a prev

Ruocheng Wang, Jiayuan Mao, Samuel J. Gershman, Jiajun Wu

We present Language-mediated, Object-centric Representation Learning (LORL), a paradigm for learning disentangled, object-centric scene representations from vision and language. LORL builds upon recent advances in unsupervised object discovery and segmentation, notably MONet and Slot Attention. While these algorithms learn an object-centric representation ju

John Huerta

We show that every bundle gerbe on a supermanifold decomposes into a bundle gerbe over the underlying manifold and a 2-form on the supermanifold. This decomposition is not canonical, but is determined by the choice of a projection map to the underlying manifold. Along the way, we prove the familiar cohomological classification theorems for bundle gerbes and

Jorge Mago, Anders Schreiber, Marcus Spradlin, Akshay Yelleshpur Srikant

Symbol alphabets of n-particle amplitudes in N=4 super-Yang-Mills theory are known to contain certain cluster variables of Gr(4,n) as well as certain algebraic functions of cluster variables. The first paper arXiv:2007.00646 in this series focused on n=8 algebraic letters. In this paper we show that it is possible to obtain all rational symbol letters (in fa

Jaan Kasak, James Creswell, Hao Liu, Pavel Naselsky

The non-polarized points (NPP) of the $Q$ and $U$ Stokes parameters of the CMB can be classified according to the geometry of the polarization field. We describe a procedure to identify these points in the pixelized sky and present the shape of the polarization angles in the vicinity of NPPs. We design a test of Gaussianity using the Kullback-Leibler diverge

Omri Abend, Nathan Schneider, Dotan Dvir, Jakob Prange

This is the annotation manual for Universal Conceptual Cognitive Annotation (UCCA; Abend and Rappoport, 2013), specifically the Foundational Layer. UCCA is a graph-based semantic annotation scheme based on typological linguistic principles. It has been applied to several languages; for ease of exposition these guidelines give examples mainly in English. New

Adam J. Harper

We prove that if $f(n)$ is a Steinhaus or Rademacher random multiplicative function, there almost surely exist arbitrarily large values of $x$ for which $|\sum_{n \leq x} f(n)| \geq \sqrt{x} (\log\log x)^{1/4+o(1)}$. This is the first such bound that grows faster than $\sqrt{x}$, answering a question of Hal\'asz and proving a conjecture of Erd\H{o}s. It is p

Nicolò Defenu

Long lived quasi-stationary states (QSSs) are a signature characteristic of long-range interacting systems both in the classical and in the quantum realms. Often, they emerge after a sudden quench of the Hamiltonian internal parameters and present a macroscopic life-time, which increases with the system size. Despite their ubiquity, the fundamental mechanism

Jens Hoppe

Several examples are given illustrating the (presumably rather general) fact that bosonic Hamiltonians that are supersymmetrizable automatically possess Lax-pairs, and square-roots.

Hamid Afshar, Erfan Esmaeili, Hamid Safari

We present an interacting spin-2 gauge theory coupled to the two-dimensional dilaton-gravity in flat spacetime. The asymptotic symmetry group is enhanced to the central extension of Diff$(S^1)\ltimes C^\infty(S^1)\ltimes$Vec($S^1$) when the central element of the Heisenberg subgroup is zero (vanishing $U(1)$ level). Using the BF-formulation of the model we d

Monica Guica

It has been recently shown that classical $J\bar T$ - deformed CFTs possess an infinite-dimensional Witt-Ka\v{c}-Moody symmetry, generated by certain field-dependent coordinate and gauge transformations. On a cylinder, however, the equal spacing of the descendants' energies predicted by such a symmetry algebra is inconsistent with the known finite-size spect

Danylo Radchenko, Don Zagier

In this paper we study two functions $F(x)$ and $J(x)$, originally found by Herglotz in 1923 and later rediscovered and used by one of the authors in connection with the Kronecker limit formula for real quadratic fields. We discuss many interesting properties of these functions, including special values at rational or quadratic irrational arguments as ration

Marcin M. Wysokiński, Marcin Płodzień, Mircea Trif

Hole-spins localized in semiconductor structures, such as quantum dots or defects, serve to the realization of efficient gate-tunable solid-state quantum bits. Here we study two electrically driven spin $3/2$ holes coupled to the electromagnetic field of a microwave cavity. We show that the interplay between the non-Abelian Berry phases generated by local ti

Noel Brady, Hung Cong Tran

We construct families of $CAT(0)$ groups containing finitely presented groups whose divergence functions are of the form $r^\alpha$ for a dense set of exponents $\alpha \in [2,\infty)$ and $r^q\log(r)$ for integers $q \geq 2$. The same construction also yields examples of $CAT(0)$ groups containing contracting elements which are not contracting in certain fi

Ilias Diakonikolas, Daniel M. Kane

We study the problem of testing the covariance matrix of a high-dimensional Gaussian in a robust setting, where the input distribution has been corrupted in Huber's contamination model. Specifically, we are given i.i.d. samples from a distribution of the form $Z = (1-\epsilon) X + \epsilon B$, where $X$ is a zero-mean and unknown covariance Gaussian $\mathca

Paul Riggins, David McPherson

We develop methods to formally describe and compare games, in order to probe questions of game structure and design, and as a stepping stone to predicting player behavior from design patterns. We define a grammar-like formalism to describe finite discrete games without hidden information, allowing for randomness, and mixed sequential and simultaneous play. W

Bhargav Bhatt, Linquan Ma, Zsolt Patakfalvi, Karl Schwede

We establish the Minimal Model Program for arithmetic threefolds whose residue characteristics are greater than five. In doing this, we generalize the theory of global $F$-regularity to mixed characteristic and identify certain stable sections of adjoint line bundles. Finally, by passing to graded rings, we generalize a special case of Fujita's conjecture to

David Doty, Mahsa Eftekhari, Eric Severson

We study population protocols, a model of distributed computing appropriate for modeling well-mixed chemical reaction networks and other physical systems where agents exchange information in pairwise interactions, but have no control over their schedule of interaction partners. The well-studied *majority* problem is that of determining in an initial populati

Jiahui Chen, Wensheng Gan, Muchuang Hu, Chien-Ming Chen

Owing to some special characteristics and features, blockchain is a very useful technique that can securely organize diverse devices in a smart city. It finds wide applications, especially in distributed environments, where entities such as wireless sensors need to be certain of the authenticity of the server. As contemporary blockchain techniques that addre

Yuri D. Lensky, Xiao-Liang Qi

In this paper, we develop a general effective theory for two copies of the Sachdev-Ye-Kitaev (SYK) model with a time-dependent bilinear coupling. For a quantum quench problem with an initial state of the thermofield double state, we show how the evolution of the system is described by a complex reparametrization field with a classical Hamiltonian. We study c

Dustin Lang

I present a method for the fast convolution of a model galaxy profile by a point-spread function (PSF) model represented as a pixel grid. The method relies upon three observations: First, most simple radial galaxy profiles of common interest (deVaucouleurs, exponential, Sersic) can be approximated as mixtures of Gaussians. Second, the Fourier transform of a

Zeki Hayran, Aobo Chen, Francesco Monticone

Causality - the principle stating that the output of a system cannot temporally precede the input - is a universal property of nature. Here, we show that analogous input-output relations can also be realized in the spectral domain by leveraging the peculiar properties of time-modulated non-Hermitian photonic systems. Specifically, we uncover the existence of

Sam Hopkins, Michael Joseph

The Lalanne-Kreweras involution is an involution on the set of Dyck paths which combinatorially exhibits the symmetry of the number of valleys and major index statistics. We define piecewise-linear and birational extensions of the Lalanne-Kreweras involution. Actually, we show that the Lalanne-Kreweras involution is a special case of a more general operator,

Michael J. Schlosser, Meesue Yoo

We study two types of dynamical extensions of Lucas sequences and give elliptic solutions for them. The first type concerns a level-dependent (or discrete time-dependent) version involving commuting variables. We show that a nice solution for this system is given by elliptic numbers. The second type involves a non-commutative version of Lucas sequences which

Alexander Hoyle, Ana Marasović, Noah Smith

Generating text from structured inputs, such as meaning representations or RDF triples, has often involved the use of specialized graph-encoding neural networks. However, recent applications of pretrained transformers to linearizations of graph inputs have yielded state-of-the-art generation results on graph-to-text tasks. Here, we explore the ability of the

Francesco Galvagno, Michelangelo Preti

We consider a family of $\mathcal{N}=2$ superconformal field theories in four dimensions, defined as $\mathbb{Z}_q$ orbifolds of $\mathcal{N}=4$ Super Yang-Mills theory. We compute the chiral/anti-chiral correlation functions at a perturbative level, using both the matrix model approach arising from supersymmetric localisation on the four-sphere and explicit

Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart

Traditional multi-agent reinforcement learning algorithms are not scalable to environments with more than a few agents, since these algorithms are exponential in the number of agents. Recent research has introduced successful methods to scale multi-agent reinforcement learning algorithms to many agent scenarios using mean field theory. Previous work in this

Christopher Yeung, Ryan Tsai, Benjamin Pham, Brian King

Understanding how nano- or micro-scale structures and material properties can be optimally configured to attain specific functionalities remains a fundamental challenge. Photonic metasurfaces, for instance, can be spectrally tuned through material choice and structural geometry to achieve unique optical responses. However, existing numerical design methods r

Jeremy Schwend

We find the precise range of $(p,q)$ for which local averages along graphs of a class of two-variable polynomials in $\mathbb{R}^3$ are of restricted weak type $(p,q)$, given the hypersurfaces have Euclidean surface measure. We derive these results using non-oscillatory, geometric methods, for a model class of polynomials bearing a strong connection to the g

James Thorne, Andreas Vlachos

This paper introduces the task of factual error correction: performing edits to a claim so that the generated rewrite is better supported by evidence. This extends the well-studied task of fact verification by providing a mechanism to correct written texts that are refuted or only partially supported by evidence. We demonstrate that it is feasible to train f

Michael C. Strayer

The $\Gamma$-colored $d$-complete and $\Gamma$-colored minuscule posets unify and generalize multiple classes of colored posets introduced by R.A. Proctor, J.R. Stembridge, and R.M. Green. In previous work, we showed that $\Gamma$-colored minuscule posets are necessary and sufficient to build from colored posets certain representations of Kac--Moody algebras

Shih-Ting Lin, Nathanael Chambers, Greg Durrett

Models of narrative schema knowledge have proven useful for a range of event-related tasks, but they typically do not capture the temporal relationships between events. We propose a single model that addresses both temporal ordering, sorting given events into the order they occurred, and event infilling, predicting new events which fit into an existing tempo

David Blaschke, Mateusz Cierniak

With the first multi-messenger observation of a binary neutron star merger (GW170817) new constraints became available for masses and radii of neutron stars. We introduce a class of hybrid EoS that fulfils all these constraints and predicts a region in the mass-radius diagram that could be populated only by hybrid neutron stars with quark matter cores. A con

Rajkumar Pujari, Dan Goldwasser

Politicians often have underlying agendas when reacting to events. Arguments in contexts of various events reflect a fairly consistent set of agendas for a given entity. In spite of recent advances in Pretrained Language Models (PLMs), those text representations are not designed to capture such nuanced patterns. In this paper, we propose a Compositional Read

Saeed Khorram, Tyler Lawson, Fuxin Li

The black-box nature of the deep networks makes the explanation for "why" they make certain predictions extremely challenging. Saliency maps are one of the most widely-used local explanation tools to alleviate this problem. One of the primary approaches for generating saliency maps is by optimizing a mask over the input dimensions so that the output of the n

Robert J. Wagner, Kristen Such, Ethan Hobbs, Franck J. Vernerey

Condensed active matter is exemplary for its capacity to morph and exhibit internal flows despite remaining cohered. To facilitate understanding of this ability, we investigate the cause of finger-like protrusions that emerge from super-organismal, aggregated rafts of fire ants (Solenopsis invicta). While these features are easily observed, what permits thei

Han Guo, Nazneen Fatema Rajani, Peter Hase, Mohit Bansal

Influence functions approximate the "influences" of training data-points for test predictions and have a wide variety of applications. Despite the popularity, their computational cost does not scale well with model and training data size. We present FastIF, a set of simple modifications to influence functions that significantly improves their run-time. We us

Jaroslav Trnka

In this paper, we present new expressions for n-point NMHV tree-level gravity amplitudes. We introduce a method of factorization diagrams which is a simple graphical representation of R-invariants in Yang-Mills theory. We define the gravity analogues which we call G-invariants, and expand the NMHV gravity amplitudes in terms of these objects. We provide expl

Egor Ershov, Alex Savchik, Ilya Semenkov, Nikola Banić

Illumination estimation is the essential step of computational color constancy, one of the core parts of various image processing pipelines of modern digital cameras. Having an accurate and reliable illumination estimation is important for reducing the illumination influence on the image colors. To motivate the generation of new ideas and the development of

Ben Brubaker, Valentin Buciumas, Daniel Bump, Henrik P. A. Gustafsson

In this paper we compute new values of Iwahori Whittaker functions on $n$-fold metaplectic covers $\widetilde{G}$ of $\mathbf{G}(F)$ with $\mathbf{G}$ a split reductive group over a non-archimedean local field $F$. For every Iwahori Whittaker function $\phi$, and for every $g\in\widetilde{G}$, we evaluate $\phi(g)$ by recurrence relations over the Weyl group

Ana Alvarez, I-Wei Chen

This study of highly accelerated lifetime tests of SrTiO$_3$, a model semiconducting oxide, is motivated by the interest in reliable multilayer ceramic capacitors and resistance-switching thin-film devices. Our analytical solution to oxygen-vacancy migration under a DC voltage -- the cause of resistance degradation in SrTiO$_3$ -- agrees with previous numeri

Ka Ho Yuen, Ka Wai Ho, Alex Lazarian

Based on the theoretical description of Position-Position-Velocity(PPV) statistics in Lazarian & Pogosyan(2000), we introduce a new technique called the Velocity Decomposition Algorithm(VDA) in separating the PPV fluctuations arising from velocity and density fluctuations. Using MHD turbulence simulations, we demonstrate its promise in retrieving the velocit

Katarzyna Paluch, Mateusz Wasylkiewicz

We consider three variants of the problem of finding a maximum weight restricted $2$-matching in a subcubic graph $G$. (A $2$-matching is any subset of the edges such that each vertex is incident to at most two of its edges.) Depending on the variant a restricted $2$-matching means a $2$-matching that is either triangle-free or square-free or both triangle-

Thibault D. Décoppet

We give a 3-universal property for the Karoubi envelope of a 2-category. Using this, we show that the 3-categories of finite semisimple 2-categories (as introduced in arXiv:1812.11933) and of multifusion categories are equivalent.

Aishwarya Ashok, Gail Zasowski, Anil Seth, Sten Hasselquist

Integrated light spectroscopy from galaxies can be used to study the stellar populations that cannot be resolved into individual stars. This analysis relies on stellar population synthesis (SPS) techniques to study the formation history and structure of galaxies. However, the spectral templates available for SPS are limited, especially in the near-infrared.

Matthew Ng, Fumin Guo, Labonny Biswas, Steffen E. Petersen

Objective: Convolutional neural networks (CNNs) have demonstrated promise in automated cardiac magnetic resonance image segmentation. However, when using CNNs in a large real-world dataset, it is important to quantify segmentation uncertainty and identify segmentations which could be problematic. In this work, we performed a systematic study of Bayesian and

Linda M. Carpenter, Taylor Murphy

In this work we study the collider phenomenology of color-octet scalars (sgluons) in supersymmetric models with Dirac gaugino masses that feature an explicitly broken $R$ symmetry ($R$-broken models). We construct such models by augmenting minimal $R$-symmetric models with a fairly general set of supersymmetric and softly supersymmetry-breaking operators tha

Philipp Mertsch, Andrea Vittino

Carbon monoxide (CO) is the best tracer of Galactic molecular hydrogen (H2). Its lowest rotational emission lines are in the radio regime and thanks to Galactic rotation emission at different distances is Doppler shifted. For a given gas flow model the observed spectra can thus be deprojected along the line of sight to infer the gas distribution. We use the

Angel Ballesteros, Flaminia Giacomini, Giulia Gubitosi

Recently, it was shown that when reference frames are associated to quantum systems, the transformation laws between such quantum reference frames need to be modified to take into account the quantum and dynamical features of the reference frames. This led to a relational description of the phase space variables of the quantum system of which the quantum ref

A. Bourgoin, M. Zannoni, L. Gomez Casajus, P. Tortora

Context: Occultation experiments represent unique opportunities for probing remotely physical properties of atmospheres. The data processing requires one to properly account for refractivity while modeling the time/frequency transfers of an electromagnetic signal. On theoretical grounds, little work have been done concerning the elaboration of a covariant ap

Abdelrahman Mohamed, Dimiter Vassilev

We show that a compact quaternionic contact manifold of dimension seven that satisfies a Lichnerowicz-type lower Ricci-type bound and has the $P$-function of any eigenfunction of the sub-Laplacian non-negative achieves its smallest possible eigenvalue only if the structure is qc-Einstein. In particular, under the stated conditions, the lowest eigenvalue is a

Giulio Bresciani

The strong Bombieri-Lang conjecture postulates that, for every variety $X$ of general type over a field $k$ finitely generated over $\mathbb{Q}$, there exists an open subset $U\subset X$ such that $U(K)$ is finite for every finitely generated extension $K/k$. The weak Bombieri-Lang conjecture postulates that, for every positive dimensional variety $X$ of gen

Joshua Peeples, Sarah Walker, Connor McCurley, Alina Zare

Feature representation is an important aspect of remote-sensing based image classification. While deep convolutional neural networks are able to effectively amalgamate information, large numbers of parameters often make learned features inscrutable and difficult to transfer to alternative models. In order to better represent statistical texture information f

Parinya Karndumri, Chawakorn Maneerat

We give a large class of supersymmetric Janus solutions in $\omega$-deformed (dyonic) $SO(8)$ maximal gauged supergravity with $\omega=\frac{\pi}{8}$. Unlike the purely electric counterpart, the dyonic $SO(8)$ gauged supergravity exhibits a richer structure of $AdS_4$ vacua with $N=8,2,1,1$ supersymmetries and $SO(8)$, $U(3)$, $G_2$ and $SU(3)$ symmetries, r

Michael Whittaker, Ailidani Ailijiang, Aleksey Charapko, Murat Demirbas

State machine replication protocols, like MultiPaxos and Raft, are a critical component of many distributed systems and databases. However, these protocols offer relatively low throughput due to several bottlenecked components. Numerous existing protocols fix different bottlenecks in isolation but fall short of a complete solution. When you fix one bottlenec

Bertie Vidgen, Tristan Thrush, Zeerak Waseem, Douwe Kiela

We present a human-and-model-in-the-loop process for dynamically generating datasets and training better performing and more robust hate detection models. We provide a new dataset of ~40,000 entries, generated and labelled by trained annotators over four rounds of dynamic data creation. It includes ~15,000 challenging perturbations and each hateful entry has

Tomáš Husek, Kevin Monsálvez-Pozo, Jorge Portolés

Within the Standard Model Effective Field Theory framework, with operators up to dimension 6, we perform a model-independent analysis of the lepton-flavour-violating processes involving tau leptons. Namely, we study hadronic tau decays and $\ell$-$\tau$ conversion in nuclei ($\ell=e,\mu$). Based on available experimental limits, we establish constraints on t