January 2022 arXiv papers — page 13

B. C. Sales, W. R. Meier, D. S. Parker, L. Yin

Destructive interference of electron hopping on the frustrated kagome lattice generates Dirac nodes, saddle points, and flat bands in the electronic structure. The latter provides the narrow bands and a peak in the density of states that can generate correlated electron behavior when the Fermi level lies within them. In the kagome metal CoSn, this alignment

Nikhil Sheoran, Subrata Mitra, Vibhor Porwal, Siddharth Ghetia

The goal of Approximate Query Processing (AQP) is to provide very fast but "accurate enough" results for costly aggregate queries thereby improving user experience in interactive exploration of large datasets. Recently proposed Machine-Learning based AQP techniques can provide very low latency as query execution only involves model inference as compared to t

Nathan C. Frey, Vijay Gadepally, Bharath Ramsundar

We propose a framework using normalizing-flow based models, SELF-Referencing Embedded Strings, and multi-objective optimization that efficiently generates small molecules. With an initial training set of only 100 small molecules, FastFlows generates thousands of chemically valid molecules in seconds. Because of the efficient sampling, substructure filters ca

V. Delgado, A. Muñoz Mateo

We assume dark matter to be a cosmological self-gravitating Bose-Einstein condensate of non-relativistic ultralight scalar particles with competing gravitational and repulsive contact interactions and investigate the observational implications of such model. The system is unstable to the formation of stationary self-bound structures that minimize the energy

Scott Fujimoto, David Meger, Doina Precup, Ofir Nachum

In this work, we study the use of the Bellman equation as a surrogate objective for value prediction accuracy. While the Bellman equation is uniquely solved by the true value function over all state-action pairs, we find that the Bellman error (the difference between both sides of the equation) is a poor proxy for the accuracy of the value function. In parti

Tyler Cody, Abdul Rahman, Christopher Redino, Lanxiao Huang

Reinforcement learning (RL), in conjunction with attack graphs and cyber terrain, are used to develop reward and state associated with determination of optimal paths for exfiltration of data in enterprise networks. This work builds on previous crown jewels (CJ) identification that focused on the target goal of computing optimal paths that adversaries may tra

Tim Dunker, Jon Tschudi, Marion O'Farrell

We present initial results from measurements of exhaled droplets by two singers during singing, speaking, laughing, and recitation of poetry. We also conducted measurements with a flute, a clarinet, a tuba, and only the tuba's mouthpiece. To be able to image and track droplets, we have developed and built a portable measurement set-up. We have detected dropl

Chen Wang, Christian Krattenthaler

The celebrated (First) Borwein Conjecture predicts that for all positive integers~$n$ the sign pattern of the coefficients of the ``Borwein polynomial'' $$(1-q)(1-q^2)(1-q^4)(1-q^5) \cdots(1-q^{3n-2})(1-q^{3n-1})$$ is $+--+--\cdots$. It was proved by the first author in [Adv. Math. 394 (2022), Paper No. 108028]. In the present paper, we extract the essential

Ryan R. Strauss, Junier B. Oliva

Arbitrary conditioning is an important problem in unsupervised learning, where we seek to model the conditional densities $p(\mathbf{x}_u \mid \mathbf{x}_o)$ that underly some data, for all possible non-intersecting subsets $o, u \subset \{1, \dots , d\}$. However, the vast majority of density estimation only focuses on modeling the joint distribution $p(\ma

Zhuohui Zhang

The cancellations of poles of degenerate Eisenstein series were studied by Hanzer and Mui\'{c}. This paper generalizes the method and the result to Eisenstein series constructed from inducing two Speh representations $\Delta(\tau,m)|\cdot|^{s_1}\otimes\Delta(\tau,n)|\cdot|^{s_2}$ for the group $GL(m+n,\mathbb{A}_\mathbb{Q})$ for self-dual cuspidal automorphi

Félix Foutel-Rodier, Emmanuel Schertzer

Consider a branching Markov process with values in some general type space. Conditional on survival up to generation $N$, the genealogy of the extant population defines a random marked metric measure space, where individuals are marked by their type and pairwise distances are measured by the time to the most recent common ancestor. In the present manuscript,

Paolo Ghiggini, Gilberto Spano

We prove that the Knot Floer homology group of a fibred knot of genus g in the Alexander grading 1-g is isomorphic to a version of the fixed point Floer homology of an area-preserving representative of the monodromy.

Mika Olsen, Christian Rubio-Montiel, Alejandra Silva-Ramírez

The dichromatic number and the diachromatic number are generalizations of the chromatic number and the achromatic number for digraphs considering acyclic colorings. In this paper, we determine the diachromatic number of digraphs arising from the Zykov sum of digraphs that admit a complete $k$-coloring with $k=\tfrac{1+\sqrt{1+4m}}{2}$ for a suitable $m$. Con

Ulrich Rückert, Srinivas Sunkara, Abhinav Rastogi, Sushant Prakash

In human-human conversations, Context Tracking deals with identifying important entities and keeping track of their properties and relationships. This is a challenging problem that encompasses several subtasks such as slot tagging, coreference resolution, resolving plural mentions and entity linking. We approach this problem as an end-to-end modeling task wh

Han-Ching Ou, Christoph Siebenbrunner, Jackson Killian, Meredith B Brooks

Motivated by a broad class of mobile intervention problems, we propose and study restless multi-armed bandits (RMABs) with network effects. In our model, arms are partially recharging and connected through a graph, so that pulling one arm also improves the state of neighboring arms, significantly extending the previously studied setting of fully recharging b

Boda Lin, Zijun Yao, Jiaxin Shi, Shulin Cao

Dependency parsing aims to extract syntactic dependency structure or semantic dependency structure for sentences. Existing methods suffer the drawbacks of lacking universality or highly relying on the auxiliary decoder. To remedy these drawbacks, we propose to achieve universal and schema-free Dependency Parsing (DP) via Sequence Generation (SG) DPSG by util

Adam Yala, Victor Quach, Homa Esfahanizadeh, Rafael G. L. D'Oliveira

Balancing privacy and predictive utility remains a central challenge for machine learning in healthcare. In this paper, we develop Syfer, a neural obfuscation method to protect against re-identification attacks. Syfer composes trained layers with random neural networks to encode the original data (e.g. X-rays) while maintaining the ability to predict diagnos

R. Bischoff, St. Raetz, M. Fernández, M. Mugrauer

The T Tauri star CVSO30, also known as PTFO8-8695, was studied intensively with ground based telescopes as well as with satellites over the last decade. It showed a variable light curve with additional repeating planetary transit-like dips every ~0.8h. However, these dimming events changed in depth and duration since their discovery and from autumn 2018 on,

S. A. Hosseini, B. Dorschner, I. V. Karlin

We propose a multiple relaxation time entropic realization of a two-phase flow lattice Boltzmann model we introduced in earlier works arXiv:2112.01975 S.A. Hosseini, B. Dorschner, and I. V. Karlin, arXiv preprint, arXiv:2112.01975 (2021). While the original model with a single relaxation time allows us to reach large density ratios, it is limited in terms of

Aviv Rosenberg, Assaf Hallak, Shie Mannor, Gal Chechik

Some of the most powerful reinforcement learning frameworks use planning for action selection. Interestingly, their planning horizon is either fixed or determined arbitrarily by the state visitation history. Here, we expand beyond the naive fixed horizon and propose a theoretically justified strategy for adaptive selection of the planning horizon as a functi

Hui Xu, Yue Wu

How does import competition from China affect engagement on ESG initiatives by US corporates? On the one hand, reduced profitability due to import competition and lagging ESG performance of Chinese exporters can disincentivize US firms to put more resources to ESG initiatives. On the other hand, the shift from labor-intensive production to capital/technology

Mohamed A. Abba, Jonathan P Williams, Brian J Reich

A key task in the emerging field of materials informatics is to use machine learning to predict a material's properties and functions. A fast and accurate predictive model allows researchers to more efficiently identify or construct a material with desirable properties. As in many fields, deep learning is one of the state-of-the art approaches, but fully tra

Guido Arnone, Guillermo Cortiñas

Let $G$ be a group and $\ell$ a commutative unital $\ast$-ring with an element $\lambda \in \ell$ such that $\lambda + \lambda^\ast = 1$. We introduce variants of hermitian bivariant $K$-theory for $\ast$-algebras equipped with a $G$-action or a $G$-grading. For any graph $E$ with finitely many vertices and any weight function $\omega \colon E^1 \to G$, a di

Monee Y. McGrady, Sean M. Colby, Jamie R Nuñez, Ryan S. Renslow

When considering large sets of molecules, it is helpful to place them in the context of a "chemical space" - a multidimensional space defined by a set of descriptors that can be used to visualize and analyze compound grouping as well as identify regions that might be void of valid structures. The chemical space of all possible molecules in a given biological

Adiba Yaseen, Imran Amin, Naeem Akhter, Asa Ben-Hur

Motivation: Machine learning based prediction of compound-protein interactions (CPIs) is important for drug design, screening and repurposing studies and can improve the efficiency and cost-effectiveness of wet lab assays. Despite the publication of many research papers reporting CPI predictors in the recent years, we have observed a number of fundamental is

Zoubeir Mlika, Soumaya Cherkaoui

This paper studies the problem of massive Internet of things (IoT) access in beyond fifth generation (B5G) networks using non-orthogonal multiple access (NOMA) technique. The problem involves massive IoT devices grouping and power allocation in order to respect the low latency as well as the limited operating energy of the IoT devices. The considered objecti

Mitch Terrell, Yixuan Wang, Matt Dorow, Soumya Agrawal

With the global Internet of Things IoT market size predicted to grow to over 1 trillion dollars in the next 5 years, many large corporations are scrambling to solidify their product line as the defacto device suite for consumers. This has led to each corporation developing their devices in a siloed environment with unique protocols and runtime frameworks tha

Matej Lieskovský

We present an algorithm for computing upper bounds for the Online Bin Stretching Problem with a small number of bins and the resulting upper bounds for 4, 5 and 6 bins. This both demonstrates the possibility of using computer search for upper bounds on a fundamentally real-valued online problem and improves upon the best bounds know so far, some of which hav

Chandresh Pravin, Varun Ojha

We propose a novel deep learning based denoising filter selection algorithm for noisy Electrocardiograph (ECG) signal preprocessing. ECG signals measured under clinical conditions, such as those acquired using skin contact devices in hospitals, often contain baseline signal disturbances and unwanted artefacts; indeed for signals obtained outside of a clinica

Fangting Zhou, Kejun He, Yang Ni

We consider the problem of causal discovery (structure learning) from heterogeneous observational data. Most existing methods assume a homogeneous sampling scheme, which leads to misleading conclusions when violated in many applications. To this end, we propose a novel approach that exploits data heterogeneity to infer possibly cyclic causal structures from

Marco Pasetto, Zhaoxiang Shen, Marta D'Elia, Xiaochuan Tian

Casting nonlocal problems in variational form and discretizing them with the finite element (FE) method facilitates the use of nonlocal vector calculus to prove well-posedeness, convergence, and stability of such schemes. Employing an FE method also facilitates meshing of complicated domain geometries and coupling with FE methods for local problems. However,

Masaru Hongo, Xu-Guang Huang, Matthias Kaminski, Mikhail Stephanov

We compute the relaxation rate of the spin density of heavy quarks in a perturbative QCD plasma to leading-log order in the coupling constant $g$. The spin relaxation rate $\Gamma_s$ in spin hydrodynamics is shown to be $\Gamma_s\sim g^4\log(1/g)T (T/M)^2$ in the heavy-quark limit $T/M\ll 1$, which is smaller than the relaxation rate of other non-hydrodynami

Simindokht Jahangard, Mahdi Bonyani, Abbas Khosravi

Accurate segmentation of the vertebra is an important prerequisite in various medical applications (E.g. tele surgery) to assist surgeons. Following the successful development of deep neural networks, recent studies have focused on the essential rule of vertebral segmentation. Prior works contain a large number of parameters, and their segmentation is restri

Alisher Duspayev, Ansh Shah, Georg Raithel

Avoided crossings of level pairs with opposite slopes can form potential energy curves for the external degree of freedom of quantum particles. We investigate nonadiabatic decay of metastable states on such avoided crossings (MSACs) using diabatic and adiabatic representations. The system is described by a single scaled adiabaticity parameter, $V$. The time-

Evan L. Ray, Logan C. Brooks, Jacob Bien, Matthew Biggerstaff

The U.S. COVID-19 Forecast Hub aggregates forecasts of the short-term burden of COVID-19 in the United States from many contributing teams. We study methods for building an ensemble that combines forecasts from these teams. These experiments have informed the ensemble methods used by the Hub. To be most useful to policy makers, ensemble forecasts must have s

Mingxuan Gu, Sulaiman Vesal, Ronak Kosti, Andreas Maier

Unsupervised domain adaptation (UDA) methods intend to reduce the gap between source and target domains by using unlabeled target domain and labeled source domain data, however, in the medical domain, target domain data may not always be easily available, and acquiring new samples is generally time-consuming. This restricts the development of UDA methods for

Weimin Zhou, Miguel P. Eckstein

Humans process visual information with varying resolution (foveated visual system) and explore images by orienting through eye movements the high-resolution fovea to points of interest. The Bayesian ideal searcher (IS) that employs complete knowledge of task-relevant information optimizes eye movement strategy and achieves the optimal search performance. The

Ananya Dua, Pham Hung Minh, Sajid Fahmid, Shikhar Gupta

Today, more than 12 million people over the age of 40 suffer from ocular diseases. Most commonly, older patients are susceptible to age related macular degeneration, an eye disease that causes blurring of the central vision due to the deterioration of the retina. The former can only be detected through complex and expensive imaging software, markedly a visua

Chuan Guo, Brian Karrer, Kamalika Chaudhuri, Laurens van der Maaten

Differential privacy is widely accepted as the de facto method for preventing data leakage in ML, and conventional wisdom suggests that it offers strong protection against privacy attacks. However, existing semantic guarantees for DP focus on membership inference, which may overestimate the adversary's capabilities and is not applicable when membership statu

Mikołaj Małkiński, Jacek Mańdziuk

Abstract visual reasoning (AVR) domain encompasses problems solving which requires the ability to reason about relations among entities present in a given scene. While humans, generally, solve AVR tasks in a "natural" way, even without prior experience, this type of problems has proven difficult for current machine learning systems. The paper summarises rece

Jan Petr, Julien Portier

Petru\v{s}evski and \v{S}krekovski \cite{odd9} recently introduced the notion of an odd colouring of a graph: a proper vertex colouring of a graph $G$ is said to be \emph{odd} if for each non-isolated vertex $x \in V(G)$ there exists a colour $c$ appearing an odd number of times in $N(x)$. Petru\v{s}evski and \v{S}krekovski proved that for any planar graph $

Shichang Zhang, Yozen Liu, Neil Shah, Yizhou Sun

Explaining machine learning models is an important and increasingly popular area of research interest. The Shapley value from game theory has been proposed as a prime approach to compute feature importance towards model predictions on images, text, tabular data, and recently graph neural networks (GNNs) on graphs. In this work, we revisit the appropriateness

Toktam A. Oghaz, Ivan Garibay

Recent advances in natural language processing (NLP) in online social media are evidently owed to large-scale datasets. However, labeling, storing, and processing a large number of textual data points, e.g., tweets, has remained challenging. On top of that, in applications such as hate speech detection, labeling a sufficiently large dataset containing offens

Jarrod T. Reilly, Simon B. Jäger, John Cooper, Murray J. Holland

We propose a method to adiabatically control an atomic ensemble using a decoherence-free subspace (DFS) within a dissipative cavity. We can engineer a specific eigenstate of the system's Lindblad jump operators by injecting a field into the cavity which deconstructively interferes with the emission amplitude of the ensemble. In contrast to previous adiabatic

Shreyas Muralidhar, Afshin Houshang, Ademir Alemán, Roman Khymyn

We investigate the impact of localized laser heating on the auto-oscillation properties of a 170 nm wide nano-constriction spin Hall nano-oscillators (SHNO) fabricated from a NiFe/Pt bilayer on a sapphire substrate. A 532 nm continuous wave laser is focused down to a spot size of about 500 nm at a power ranging from 0 to 12 mW. Through a comparison with resi

Kai Qian, David J. Apigo, Karmela Padavić, Keun Hyuk Ahn

We experimentally demonstrate that Majorana-like bound states (MLBSs) can occur in quasi-one-dimensional metamaterials, analogous to Majorana zero modes (MZM) in the Kitaev chain. In a mechanical spinner ladder system, we observe a topological phase transition and spectral-gap-protected edge MLBSs. We characterize the decaying and oscillatory nature of these

Herbert L. Roitblat

In eDiscovery, a party to a lawsuit or similar action must search through available information to identify those documents and files that are relevant to the suit. Search efforts tend to identify less than 100% of the relevant documents and courts are frequently asked to adjudicate whether the search effort has been reasonable, or whether additional effort

Xiaojian Bai, Frank Lechermann, Yaohua Liu, Yongqiang Cheng

Fe3-xGeTe2 is a layered magnetic van der Waals material of interest for both fundamental and applied research. Despite the observation of intriguing physical properties, open questions exist even on the basic features related to magnetism: is it a simple ferromagnet or are there antiferromagnetic regimes and are the moments local or itinerant. Here, we demon

Samuel Epstein

We provide tight upper and lower bounds on the expected minimum Kolmogorov complexity of binary classifiers that are consistent with labeled samples. The expected size is not more than complexity of the target concept plus the conditional entropy of the labels given the sample.

Gargi Sharma, Kanwarpal Singh

Confocal microscopy is the backbone of cellular research labs across the world but unfortunately, the imaging is restricted to a single plane. Chromatic confocal microscopy offers the possibility to image multiple planes simultaneously thus providing a manifold increase in the imaging speed whereas eliminating the need for z-axis scanning. Standard chromatic

O. Chukova, S. A. Nedilko, S. G. Nedilko, T. Voitenko

Co-doped with calcium, europium and erbium ions lanthanum vanadate crystalline nanoparticles are synthesized and investigated with a goal to clarify the mechanisms of calcium and erbium impurities effects on europium ions luminescence and to find compositions with enhanced luminescence intensity. The XRD analysis reveals dependence of crystal structure on do

J. Betz, J. Manley, E. M. Wright, D. Grin

A light scalar field framework of dark energy, sometimes referred to as quintessence, introduces a fifth force between normal matter objects. Screening mechanisms, such as the chameleon model, allow the scalar field to be almost massless on cosmological scales while simultaneously evading laboratory constraints. We explore the ability of mechanical systems a

Robert M. Guralnick, John Shareshian, Russ Woodroofe

We verify that every alternating group of degree at most one quadrillion is invariably generated by an element of prime order together with an element of prime power order.

Veronica Biffi, John A. ZuHone, Tony Mroczkowski, Esra Bulbul

Major mergers between galaxy clusters can produce large turbulent and bulk flow velocities in the intra-cluster medium and thus imprint diagnostic features in X-ray spectral emission lines from heavy ions. As demonstrated by Hitomi in observations of the Perseus cluster, measurements of gas velocities in clusters from high-resolution X-ray spectra will be ac

Caleb R. Choban, Dusan Keres, Philip F. Hopkins, Karin M. Sandstrom

Recent strides have been made developing dust evolution models for galaxy formation simulations but these approaches vary in their assumptions and degree of complexity. Here we introduce and compare two separate dust evolution models (labelled 'Elemental' and 'Species'), based on recent approaches, incorporated into the GIZMO code and coupled with FIRE-2 ste

Kyle Kremer, James C. Lombardi, Wenbin Lu, Anthony L. Piro

Recent analyses have shown that close encounters between stars and stellar black holes occur frequently in dense star clusters. Depending upon the distance at closest approach, these interactions can lead to dissipating encounters such as tidal captures and disruptions, or direct physical collisions, all of which may be accompanied by bright electromagnetic

Troy J. Sewell, Christopher David White

Quantum hydrodynamics is the emergent classical dynamics governing transport of conserved quantities in generic strongly-interacting quantum systems. Recent matrix product operator methods have made simulations of quantum hydrodynamics in 1+1d tractable, but they do not naturally generalize to 2+1d or higher, and they offer limited guidance as to the difficu

Anna Y. Q. Ho, Daniel A. Perley, Yuhan Yao, Dmitry Svinkin

Dirty fireballs are a hypothesized class of relativistic massive-star explosions with an initial Lorentz factor $\Gamma_\mathrm{init}$ below the $\Gamma_\mathrm{init}\sim100$ required to produce a long-duration gamma-ray burst (LGRB), but which could still produce optical emission resembling LGRB afterglows. Here we present the results of a search for on-axi

Akos Bogdan, Lorenzo Lovisari, Patrick Ogle, Orsolya E. Kovacs

It is well established that brightest cluster galaxies (BCGs), residing in the center of galaxy clusters, are typically massive and quenched galaxies with cD or elliptical morphology. An optical survey suggested that an exotic galaxy population, superluminous spiral and lenticular galaxies could be the BCGs of some galaxy clusters. Because the cluster member

Jorick S. Vink, A. A. C. Sander, E. R. Higgins, G. N. Sabhahit

The link between hot and cool stellar outflows is shown to be critical for correctly predicting the masses of the most massive black holes (BHs) below the so-called pair-instability supernova (PISN) mass gap. Gravitational Wave (GW) event 190521 allegedly hosted an "impossibly" heavy BH of 85 Solar Masses. Here we show how our increased knowledge of both met

Rabah Abdul Khalek, Rhorry Gauld, Tommaso Giani, Emanuele R. Nocera

We present an updated determination of nuclear parton distributions (nPDFs) from a global NLO QCD analysis of hard processes in fixed-target lepton-nucleus and proton-nucleus together with collider proton-nucleus experiments. In addition to neutral- and charged-current deep-inelastic and Drell-Yan measurements on nuclear targets, we consider the information

Annika Franeck, Richard Wünsch, Sergio Martínez-González, Ivana Orlitová

Inspired by the excess soft X-ray emission recently detected in Green Pea galaxies, we model the soft X-ray emission (0.5 - 2.0 keV) of hot gas from star cluster winds. By combining individual star clusters, we estimate the soft X-ray emission expected from the typically unresolved diffuse hot gas in starburst galaxies, devoid of competing emission from e.g.

Alex Sabol, Kyongsik Yun, Muhammad Adil, Changrak Choi

In this paper we describe a machine learning based framework for spacecraft swarm trajectory planning. In particular, we focus on coordinating motions of multi-spacecraft in formation flying through passive relative orbit(PRO) transfers. Accounting for spacecraft dynamics while avoiding collisions between the agents makes spacecraft swarm trajectory planning

Bahman Kalantari, Rahim Zaare-Nahandi

Omar Khayyam's studies on cubic equations inspired the 12th century Persian mathematician Sharaf al-Din Tusi to investigate the number of positive roots. According to the noted mathematical historian Rashed, Tusi analyzed the problem for five different types of equations. In fact all cubic equations are reducible to a form {\it Tusi form} $x^2-x^3=c$. Tusi d

Baptiste Royer, Shraddha Singh, Steven M. Girvin

Encoding logical quantum information in harmonic oscillator modes is a promising and hardware-efficient approach to the realization of a quantum computer. In this work, we propose to encode logical qubits in grid states of an ensemble of harmonic oscillator modes. We first discuss general results about these multimode bosonic codes; how to design them, how t

Duván Cardona

Let $G$ be an arbitrary compact Lie group. In this work we apply the method of the analytic continuation of traces in order to compute the Wodzicki residue for a classical pseudo-differential operator on $G$ in terms of its matrix-valued symbol (which is globally defined on the non-commutative phase space $G\times \widehat{G},$ with $\widehat{G}$ being the u

Yingyue Zhu, Zewen Zhang, Bhuvanesh Sundar, Alaina M. Green

Combinatorial optimization problems on graphs have broad applications in science and engineering. The Quantum Approximate Optimization Algorithm (QAOA) is a method to solve these problems on a quantum computer by applying multiple rounds of variational circuits. However, there exist several challenges limiting the real-world applications of QAOA. In this pap

Anirban Dutta, Vikram Rana

A simultaneous broadband analysis of X-ray data obtained with XMM-Newton and NuSTAR observatories for the asynchronous polar source CD Ind is presented. The spin folded lightcurve in soft 0.3-3.0 keV band shows single broad hump-like structure superimposed with occasional narrow dips, indicating a single-pole accretion model with a complex intrinsic absorber

Jennifer Gillenwater, Matthew Joseph, Andrés Muñoz Medina, Mónica Ribero

We present a differentially private algorithm for releasing the sequence of $k$ elements with the highest counts from a data domain of $d$ elements. The algorithm is a "joint" instance of the exponential mechanism, and its output space consists of all $O(d^k)$ length-$k$ sequences. Our main contribution is a method to sample this exponential mechanism in tim

Amrit Singh Bedi, Souradip Chakraborty, Anjaly Parayil, Brian Sadler

We focus on parameterized policy search for reinforcement learning over continuous action spaces. Typically, one assumes the score function associated with a policy is bounded, which fails to hold even for Gaussian policies. To properly address this issue, one must introduce an exploration tolerance parameter to quantify the region in which it is bounded. Do

Felipe Figueroa, Piotr Tourkine

The Coon amplitude is a deformation of the Veneziano amplitude with logarithmic Regge trajectories and an accumulation point in the spectrum, which interpolates between string theory and field theory. With string theory, it is the only other solution to duality constraints explicitly known and it constitutes an important data point in the modern S-matrix boo

E. Zapusek, A. Javadi, F. Reiter

Irreversible logic is at odds with unitary quantum evolution. Emulating such operations by classical measurements can result in disturbances and high resource demands. To overcome these limitations, we propose protocols that harness dissipation to realize the nonunitary evolution required for irreversible gate operations. Using additional excited states subj

Shilong Liu, Feng Li, Hao Zhang, Xiao Yang

We present in this paper a novel query formulation using dynamic anchor boxes for DETR (DEtection TRansformer) and offer a deeper understanding of the role of queries in DETR. This new formulation directly uses box coordinates as queries in Transformer decoders and dynamically updates them layer-by-layer. Using box coordinates not only helps using explicit p

Alexey Kurakin, Shuang Song, Steve Chien, Roxana Geambasu

Differential privacy (DP) is the de facto standard for training machine learning (ML) models, including neural networks, while ensuring the privacy of individual examples in the training set. Despite a rich literature on how to train ML models with differential privacy, it remains extremely challenging to train real-life, large neural networks with both reas

Zhusheng Wang, Sennur Ulukus

We consider the total (upload plus download) communication cost of two-database symmetric private information retrieval (SPIR) through its relationship to conditional disclosure of secrets (CDS). In SPIR, a user wishes to retrieve a message out of $K$ messages from $N$ non-colluding and replicated databases without learning anything beyond the retrieved mess

Davide Lonigro, Dariusz Chruściński

The quantum regression formula for an open quantum system consists in an infinite hierarchy of conditions for its multi-time correlation functions, thus requiring full access to the total "system+environment" evolution, and providing a stronger requirement than CP-divisibility. Here, we analyze CP-divisibility and check the validity of quantum regression bey

Sundara Rajan Srinivasavaradhan, Pavlos Nikolopoulos, Christina Fragouli, Suhas Diggavi

We study the problem of group testing with non-identical, independent priors. So far, the pooling strategies that have been proposed in the literature take the following approach: a hand-crafted test design along with a decoding strategy is proposed, and guarantees are provided on how many tests are sufficient in order to identify all infections in a populat

Marco Cuturi, Laetitia Meng-Papaxanthos, Yingtao Tian, Charlotte Bunne

Optimal transport tools (OTT-JAX) is a Python toolbox that can solve optimal transport problems between point clouds and histograms. The toolbox builds on various JAX features, such as automatic and custom reverse mode differentiation, vectorization, just-in-time compilation and accelerators support. The toolbox covers elementary computations, such as the re

Ruiqi Zhong, Charlie Snell, Dan Klein, Jacob Steinhardt

How do two distributions of texts differ? Humans are slow at answering this, since discovering patterns might require tediously reading through hundreds of samples. We propose to automatically summarize the differences by "learning a natural language hypothesis": given two distributions $D_{0}$ and $D_{1}$, we search for a description that is more often true

Meric Yucel, Serdar Bagis, Ahmet Sertbas, Mehmet Sarikaya

A major archetype of artificial intelligence is developing algorithms facilitating temporal efficiency and accuracy while boosting the generalization performance. Even with the latest developments in machine learning, a key limitation has been the inefficient feature extraction from the initial data, which is essential in performance optimization. Here, we i

Faruk F. Abi-Khuzam

Let f be an entire function of finite order less than 1. The maximum modulus M(r) of f and the counting function of the zeros N(r) are connected by a best possible growth inequality known as Valiron's Theorem: For functions subharmonic in d-dimensional Euclidean space, Hayman obtained a corresponding result with a best possible constant involving the dimensi

Sylvain Lamprier, Thomas Scialom, Antoine Chaffin, Vincent Claveau

Generative Adversarial Networks (GANs) have known a tremendous success for many continuous generation tasks, especially in the field of image generation. However, for discrete outputs such as language, optimizing GANs remains an open problem with many instabilities, as no gradient can be properly back-propagated from the discriminator output to the generator

Fabian Korthauer

We adapt methods from quiver representation theory and Hall algebra techniques to the counting of representations of virtually free groups over finite fields. This gives rise to the computation of the E-polynomials of $\mathbf{GL}_d(\mathbb{C})$-character varieties of virtually free groups. As examples we discuss the representation theory of $\mathbb{D}_\inf

Alex Pandya, Elias R. Most, Frans Pretorius

We present the first conservative finite volume numerical scheme for the causal, stable relativistic Navier-Stokes equations developed by Bemfica, Disconzi, Noronha, and Kovtun (BDNK). BDNK theory has arisen very recently as a promising means of incorporating entropy-generating effects (viscosity, heat conduction) into relativistic fluid models, appearing as

Nathan Pflueger

This paper gives a novel and compact proof that a metric graph consisting of a chain of loops of torsion order $0$ is Brill-Noether general (a theorem of Cools-Draisma-Payne-Robeva), and a finite or metric graph consisting of a chain of loops of torsion order $k$ is Hurwitz-Brill-Noether general in the sense of splitting loci (a theorem of Cook-Powell-Jensen

Edward Shaya, R. Brent Tully, Daniel Pomarède, Alan Peel

The trajectories since z=4 of systems of galaxies (`halos') with cz < 8,000 km/s are found through Numerical Action reconstructions. A set of 9,719 halos from a 2MASS group catalog and Cosmicflows-3 catalogs are given attention. Present distances are adjusted to minimize departures from observed redshifts. For those with the most precisely determined distanc

Alphonse C. Sterling, Ronald L. Moore, Navdeep K. Panesar

We examine 21 solar polar coronal jets that we identify in soft X-ray images obtained from the Hinode/X-ray telescope (XRT). We identify 11 of these jets as blowout jets and four as standard jets (with six uncertain), based on their X-ray-spire widths being respectively wide or narrow (compared to the jet's base) in the XRT images. From corresponding Extreme

Matija Ćuk, Maryame El Moutamid

Saturn has a dynamically rich satellite system, which includes at least three orbital resonances between three pairs of moons: Mimas-Tethys 4:2, Enceladus-Dione 2:1, and Titan-Hyperion 4:3 mean-motion resonances. Studies of the orbital history of Saturn's moons usually assume that their past dynamics was also dominated solely by two-body resonances. Using di

Vikraman Arvind, Ilia Ponomarenko, Grigory Ryabov

An arc-colored tournament is said to be $k$-spanning for an integer $k\geq 1$ if the union of its arc-color classes of maximal valency at most $k$ is the arc set of a strongly connected digraph. It is proved that isomorphism testing of $k$-spanning tournaments is fixed-parameter tractable.

Alex Foote, Amina Asif, Nasir Rajpoot, Fayyaz Minhas

Motivation: Digitization of pathology laboratories through digital slide scanners and advances in deep learning approaches for objective histological assessment have resulted in rapid progress in the field of computational pathology (CPath) with wide-ranging applications in medical and pharmaceutical research as well as clinical workflows. However, the estim

Sandro Mereghetti

The INTEGRAL satellite, in orbit since October 2002, has significantly contributed to the study of magnetars and, thanks to its unique capabilities for the study of transient gamma-ray phenomena, it is now playing an important role in multimessenger astrophysics. The most recent results include the discovery of a peculiar burst from SGR J1935+2154, which gav

István Tomon

We present several results in extremal graph and hypergraph theory of topological nature. First, we show that if $\alpha>0$ and $\ell=\Omega(\frac{1}{\alpha}\log\frac{1}{\alpha})$ is an odd integer, then every graph $G$ with $n$ vertices and at least $n^{1+\alpha}$ edges contains an $\ell$-subdivision of the complete graph $K_t$, where $t=n^{\Theta(\alpha)}$

Ryan Hausen, Brant Robertson

The visual inspection of image and catalog data continues to be a valuable aspect of astronomical data analysis. As the scale of astronomical image and catalog data continues to grow, visualizing the data becomes increasingly difficult. In this work, we introduce FitsMap, a simple, lightweight tool for visualizing astronomical image and catalog data. FitsMap

Carlos Ruiz Herrera, Thomas Grandits, Gernot Plank, Paris Perdikaris

We propose FiberNet, a method to estimate \emph{in-vivo} the cardiac fiber architecture of the human atria from multiple catheter recordings of the electrical activation. Cardiac fibers play a central role in the electro-mechanical function of the heart, yet they are difficult to determine in-vivo, and hence rarely truly patient-specific in existing cardiac

Josep M. Gallegos

Let $\Omega \subset \mathbb R^d$ be a $C^1$ domain or, more generally, a Lipschitz domain with small Lipschitz constant and $A(x)$ be a $d \times d$ uniformly elliptic, symmetric matrix with Lipschitz coefficients. Assume $u$ is harmonic in $\Omega$, or with greater generality $u$ solves $\operatorname{div}(A(x)\nabla u)=0$ in $\Omega$, and $u$ vanishes on $

Abhishek Dhankar, Osmar R. Zaïane, Francois Bolduc

Identifying fake news is a very difficult task, especially when considering the multiple modes of conveying information through text, image, video and/or audio. We attempted to tackle the problem of automated misinformation/disinformation detection in multi-modal news sources (including text and images) through our simple, yet effective, approach in the FACT

Gecia Bravo-Hermsdorff, Robert Busa-Fekete, Lee M. Gunderson, Andrés Munõz Medina

Data anonymization is an approach to privacy-preserving data release aimed at preventing participants reidentification, and it is an important alternative to differential privacy in applications that cannot tolerate noisy data. Existing algorithms for enforcing $k$-anonymity in the released data assume that the curator performing the anonymization has comple

Ludovico Lami, Daniel Goldwater, Gerardo Adesso

Associative memories are devices storing information that can be fully retrieved given partial disclosure of it. We examine a toy model of associative memory and the ultimate limitations it is subjected to within the framework of general probabilistic theories (GPTs), which represent the most general class of physical theories satisfying some basic operation

Arijit Roy, Min-Gyu Cho, Pil-Ryung Cha

The morphological evolution of the conducting filament (CF) predominantly controls the electric response of the resistive random access memory (ReRAM) devices. However, the parameters -- in terms of the material and the processing -- which control the growth of such CF are plenty. Extending the phase field technique for ReRAM systems presented by Roy and Cha

Robin Fritsch, Roger Wattenhofer

We consider the problem of finding a compromise between the opinions of a group of individuals on a number of mutually independent, binary topics. In this paper, we quantify the loss in representativeness that results from requiring the outcome to have majority support, in other words, the "price of majority support". Each individual is assumed to support an