August 2022 arXiv papers — page 119

B. Tripathi, A. E. Fraser, P. W. Terry, E. G. Zweibel

Visco-resistive magnetohydrodynamic turbulence, driven by a two-dimensional unstable shear layer that is maintained by an imposed body force, is examined by decomposing it into dissipationless linear eigenmodes of the initial profiles. The down-gradient momentum flux, as expected, originates from the large-scale instability. However, continual up-gradient mo

Ryo Mihashi, Yoshihiko Hasegawa

Indirect measurement can be used to read out the outcome of a quantum system without resorting to a straightforward approach, and it is the foundation of the measurement uncertainty relations that explain the incompatibility of conjugate observables. While measurement uncertainty has been established for the accuracy of quantum measurement, thermodynamic unc

John M Yelton

This is an experimentalist's list of questions concerning the physics of the charmed baryon sector which have no satisfactory answer.

Mokanarangan Thayaparan, Marco Valentino, André Freitas

Integer Linear Programming (ILP) provides a viable mechanism to encode explicit and controllable assumptions about explainable multi-hop inference with natural language. However, an ILP formulation is non-differentiable and cannot be integrated into broader deep learning architectures. Recently, Thayaparan et al. (2021a) proposed a novel methodology to integ

M. A. Aragon-Calvo, Joseph Silk, Mark Neyrinck

The Milky Way and the Local Sheet form a peculiar galaxy system in terms of the unusually low velocity dispersion in our neighbourhood and the seemingly high mass of the Milky Way for such an environment. Using the TNG300 simulation we searched for Milky Way analogues (MWA) located in cosmological walls with velocity dispersion in their local Hubble flow sim

Ryoi Ohashi, Ryota Nakai, Takehito Yokoyama, Yukio Tanaka

We studied the tunnel transport between the edge of a Pfaffian fractional quantum Hall state and that of an integer quantum Hall state. Based on the duality argument between the strong and weak tunnelings, we found that an Andreev-like reflection appeared in the strong tunneling regime. We calculated the charge conductance in the weak and strong tunneling re

Gastão A. Braga, Frederico Furtado, Jussara M. Moreira, Antônio Marcos da Silva

We study the large-time behavior of solutions to a generalized Burgers Equation, with initial zero mass data. Our main purpose is to present a modified version of the Renormalization Group map, which is able to provide the higher order asymptotic properties of the solution to the Cauchy problem of a class of nonlinear time-evolution problems.

Lucas Daguerre, Matias Ginzburg, Gonzalo Torroba

The vacuum entanglement entropy in quantum field theory provides nonperturbative information about renormalization group flows. Most studies so far have focused on the universal terms, related to the Weyl anomaly in even space-time dimensions, and the sphere free energy $F$ in odd dimensions. In this work we study the entanglement entropy on a sphere of radi

Dorota M. Grabowska, Christopher Kane, Benjamin Nachman, Christian W. Bauer

For many quantum systems of interest, the classical computational cost of simulating their time evolution scales exponentially in the system size. At the same time, quantum computers have been shown to allow for simulations of some of these systems using resources that scale polynomially with the system size. Given the potential for using quantum computers f

Pawan Kumar, Paz Beniamini

We describe how gravitational lensing of fast radio bursts (FRBs) is affected by a plasma screen in the vicinity of the lens or somewhere between the source and the observer. Wave passage through a turbulent medium affects gravitational image magnification, lensing probability (particularly for strong magnification events), and the time delay between images.

Evyatar Sabag, Matteo Sacchi

Compactifying 6d superconformal field theories (SCFTs) to 4d $\mathcal{N}=1$ theories on two-punctured spheres (tubes) and tori with flux is realized using duality domain walls in 5d $\mathcal{N}=1$ Kaluza-Klein (KK) theories, which are usually denoted by $flux$ $domain$ $walls$. We revisit this construction and study it in detail from the 5d perspective, sp

Katherine Freese, Martin Wolfgang Winkler

The origins of matter and radiation in the universe lie in a Hot Big Bang. We present a number of well-motivated cosmologies in which the Big Bang occurs through a strong first order phase transition -- either at the end of inflation, after a period of kination ("Kination-Induced Big Bang"), or after a second period of vacuum-domination in the early universe

J. T. Penedo, Yakefu Reyimuaji, Xinyi Zhang

We explore the connection between tree-level Dirac neutrino masses and axion physics in a scenario where the PQ symmetry enforces lepton number conservation perturbatively. Requiring that the PQ scale $f_a$ is the only heavy scale to play a role in neutrino mass generation, we are led to the construction of a KSVZ-type model where Dirac neutrino masses are i

L. L. Cowie, A. J. Barger, F. E. Bauer, C. -C. Chen

We present deep SCUBA-2 450 micron and 850 micron imaging of ten strong lensing clusters. We provide a >4-sigma SCUBA-2 850 micron catalog of the 404 sources lying within a radius of 4.5' from the cluster centers. We also provide catalogs of the >4.5-sigma ALMA 870 micron detections in the clusters A370, MACSJ1149.5+2223, and MACSJ0717.5+3745 from our target

Gen Li, Yuting Wei

Approximate message passing (AMP) emerges as an effective iterative paradigm for solving high-dimensional statistical problems. However, prior AMP theory -- which focused mostly on high-dimensional asymptotics -- fell short of predicting the AMP dynamics when the number of iterations surpasses $o\big(\frac{\log n}{\log\log n}\big)$ (with $n$ the problem dime

Christopher Eckner, Francesca Calore, Denis Erkal, Sophia Lilleengen

Previous studies on astrophysical dark matter (DM) constraints have all assumed that the Milky Way's (MW) DM halo can be modelled in isolation. However, recent work suggests that the MW's largest dwarf satellite, the Large Magellanic Cloud (LMC), has a mass of 10-20$\%$ that of the MW and is currently merging with our Galaxy. As a result, the DM haloes of th

Rukhsan Ul Haq, Basit Iqbal, Mohsin Illahi, Baseer Ahmad

Schrieffer-Wolff transformation (SWT) has been extensively used in quantum many-body physics to calculate the low energy effective Hamiltonian. It provides a perturbative method to comprehend the renormalization effects of strong correlations in the quantum many-body models. The generator for Schrieffer-Wolff transformation is calculated usually by heuristic

Romain Loiseau, Baptiste Bouvier, Yann Teytaut, Elliot Vincent

Machine learning techniques have proved useful for classifying and analyzing audio content. However, recent methods typically rely on abstract and high-dimensional representations that are difficult to interpret. Inspired by transformation-invariant approaches developed for image and 3D data, we propose an audio identification model based on learnable spectr

Daniel Finkelstein-Shapiro

Non-Hermitian Hamiltonians and Lindblad operators are some of the most important generators of dynamics for describing quantum systems interacting with different kinds of environments. The first type differs from conservative evolution by an anti-Hermitian term that causes particle decay, while the second type differs by a dissipation operator in Lindblad fo

Wenxiao Wang, Alexander Levine, Soheil Feizi

Data poisoning considers an adversary that distorts the training set of machine learning algorithms for malicious purposes. In this work, we bring to light one conjecture regarding the fundamentals of data poisoning, which we call the Lethal Dose Conjecture. The conjecture states: If $n$ clean training samples are needed for accurate predictions, then in a s

Dharmaraja Selvamuthu, Paola Tardelli

This paper is devoted to the study of the number of customers in infinite-server systems driven by Hawkes processes. In these systems, the self-exciting arrival process is assumed to be represented by a Hawkes process and the self-exciting service process by a state-dependent Hawkes process (sdHawkes process). Under some suitable conditions, for the Hawkes/s

John A. Baldwin, Steven Sivek

We prove for the first time that knot Floer homology and Khovanov homology can detect non-fibered knots, and that HOMFLY homology detects infinitely many such knots; these theories were previously known to detect a mere six knots, all fibered. These results rely on our main technical theorem, which gives a complete classification of genus-1 knots in the 3-sp

Margaret Li, Suchin Gururangan, Tim Dettmers, Mike Lewis

We present Branch-Train-Merge (BTM), a communication-efficient algorithm for embarrassingly parallel training of large language models (LLMs). We show it is possible to independently train subparts of a new class of LLMs on different subsets of the data, eliminating the massive multi-node synchronization currently required to train LLMs. BTM learns a set of

Germain Morilhat, Naomi Kifle, Sandra FinesilverSmith, Bram Ruijsink

In many low-to-middle income (LMIC) countries, ultrasound is used for assessment of pleural effusion. Typically, the extent of the effusion is manually measured by a sonographer, leading to significant intra-/inter-observer variability. In this work, we investigate the use of deep learning (DL) to automate the process of pleural effusion segmentation from ul

Christian Porter, Andrew Mendelsohn

Let $K$ be a totally real number field of degree $n$ over $\mathbb{Q}$, with discriminant and regulator $\Delta_K, R_K$ respectively. In this paper, using a similar method to van Woerden, we prove that the number of classes of perfect unary forms, up to equivalence and scaling, can be bounded above by $O( \Delta_K \exp(2n \log(n)+f(n,R_K)))$, where $f(n,R_K)

Nicolas Arancibia Robert, Paul Mezo

Langlands defined L-packets for real reductive groups. In order to refine the local Langlands correspondence, Adams-Barbasch-Vogan combined L-packets over all real forms belonging to an inner class. Using different methods, Kaletha also defines such combined L-packets with a refinement to the local Langlands correspondence. We prove that the L-packets of Ada

O. Kobzar, V. Khalack, D. Bohlender, G. Mathys

Since the end of 2018, the Transiting Exoplanet Survey Satellite (TESS) has provided stellar photometry to the astronomical community. We have used TESS data to study rotational modulation in the light curves of a sample of chemically peculiar stars with measured large-scale magnetic fields (mCP stars). In general, mCP stars show inhomogeneous distributions

LHCb Collaboration

An amplitude analysis of the $D^+ \to \pi^- \pi^+ \pi^+$ decay is performed with a sample corresponding to $1.5\rm fb^{-1}$ of integrated luminosity of $pp$ collisions at a centre-of-mass energy $\sqrt{s}=8$ TeV collected by the LHCb detector in 2012. The sample contains approximately six hundred thousand candidates with a signal purity of $95\%$. The resona

Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini

Large language models have shown impressive few-shot results on a wide range of tasks. However, when knowledge is key for such results, as is the case for tasks such as question answering and fact checking, massive parameter counts to store knowledge seem to be needed. Retrieval augmented models are known to excel at knowledge intensive tasks without the nee

Allen Lin, Jianling Wang, Ziwei Zhu, James Caverlee

Conversational recommender systems (CRS) have shown great success in accurately capturing a user's current and detailed preference through the multi-round interaction cycle while effectively guiding users to a more personalized recommendation. Perhaps surprisingly, conversational recommender systems can be plagued by popularity bias, much like traditional re

Amit Kumar Chatterjee, Hisao Hayakawa

We analyze the cluster formation in a non-ergodic stochastic system as a result of counter-flow, with the aid of an exactly solvable model. To illustrate the clustering, a two species asymmetric simple exclusion process with impurities on a periodic lattice is considered, where the impurity can activate flips between the two non-conserved species. Exact anal

Nicolas Bertin, Fei Zhou

Discrete dislocation dynamics (DDD) is a widely employed computational method to study plasticity at the mesoscale that connects the motion of dislocation lines to the macroscopic response of crystalline materials. However, the computational cost of DDD simulations remains a bottleneck that limits its range of applicability. Here, we introduce a new DDD-GNN

Da Ju, Jing Xu, Y-Lan Boureau, Jason Weston

The promise of interaction between intelligent conversational agents and humans is that models can learn from such feedback in order to improve. Unfortunately, such exchanges in the wild will not always involve human utterances that are benign or of high quality, and will include a mixture of engaged (helpers) and unengaged or even malicious users (trolls).

Mingyang Gong, Brett Edgar, Jing Fan, Guohui Lin

Given a graph, the general problem to cover the maximum number of vertices by a collection of vertex-disjoint long paths seemingly escapes from the literature. A path containing at least $k$ vertices is considered long. When $k \le 3$, the problem is polynomial time solvable; when $k$ is the total number of vertices, the problem reduces to the Hamiltonian pa

Kyle Tilbury, Jesse Hoey

We present our preliminary work on a multi-agent system involving the complex human phenomena of identity and dynamic teams. We outline our ongoing experimentation into understanding how these factors can eliminate some of the naive assumptions of current multi-agent approaches. These include a lack of complex heterogeneity between agents and unchanging team

Soumyajit Karmakar, Abeer Banerjee, Prashant Sadashiv Gidde, Sumeet Saurav

Over the past few years, there has been a significant improvement in the domain of few-shot learning. This learning paradigm has shown promising results for the challenging problem of anomaly detection, where the general task is to deal with heavy class imbalance. Our paper presents a new approach to few-shot classification, where we employ the knowledge-bas

Tharathep Plienbumrung, Maria Daghofer, Michael Schmid, Andrzej M. Oleś

Starting from an effective two-dimensional two-band model for infinite layered nickelates, consisting of bands obtained from $d$ and $s$--like orbitals, we investigate to which extend it can be mapped onto a single-band Hubbard model. We identify screening of the more itinerant $s$-like band as an important driver. In absence of screening one strongly-correl

Nicolas Berkopec, Jacob Branch, Rachel Heikkinen, Caroline Nunn

Elliptic Dedekind sums were introduced by R. Sczech as generalizations of classical Dedekind sums to complex lattices. We show that for any lattice with real $j$-invariant, the values of suitably normalized elliptic Dedekind sums are dense in the real numbers. This extends an earlier result of Ito for Euclidean imaginary quadratic rings. Our proof is an adap

Adam Aurisano, Leigh H. Whitehead

End-to-end analyses of data from high-energy physics experiments using machine and deep learning techniques have emerged in recent years. These analyses use deep learning algorithms to go directly from low-level detector information directly to high-level quantities that classify the interactions. The most popular class of algorithms for these analyses are c

Thomas Y. Chen, Biprateep Dey, Aishik Ghosh, Michael Kagan

Estimating uncertainty is at the core of performing scientific measurements in HEP: a measurement is not useful without an estimate of its uncertainty. The goal of uncertainty quantification (UQ) is inextricably linked to the question, "how do we physically and statistically interpret these uncertainties?" The answer to this question depends not only on the

Chen-Yu Liu, Hsi-Sheng Goan

One of the major problems of most quantum computing applications is that the required number of qubits to solve a practical problem is much larger than that of today's quantum hardware. We propose an algorithm, called large-system sampling approximation (LSSA), to solve Ising problems with sizes up to $N_{\rm{gb}}2^{N_{\rm{gb}}}$ by an $N_{\rm{gb}}$-qubit ga

Nathan Rutherford, Geert Raaijmakers, Chanda Prescod-Weinstein, Anna Watts

Neutron stars can accumulate asymmetric dark matter (ADM) in their interiors, which affects the neutron star's measurable properties and makes compact objects prime targets to search for ADM. In this work, we use Bayesian inference to explore potential neutron star mass-radius measurements, from current and future x-ray telescopes, to constrain the bosonic A

Sandro Tacchella, Benjamin D. Johnson, Brant E. Robertson, Stefano Carniani

We present an interstellar medium and stellar population analysis of three spectroscopically confirmed $z>7$ galaxies in the ERO JWST NIRCam and JWST NIRSpec data of the SMACS J0723.3-7327 cluster. We use the Bayesian spectral energy distribution (SED) fitting code \texttt{Prospector} with a flexible star-formation history (SFH), a variable dust attenuation

Víctor Bravo, Rodrigo Hernández, Osvaldo Venegas

We establish two-point distortion theorems for sense-preserving planar harmonic mappings $f=h+\overline{g}$ which satisfies the univalence criteria in the unit disc such that, Becker's and Nehari`s harmonic version. In addition, we find the sharp two-point distortion theorem when $h$ is a convex function, and normalized mappings such that $h(\D)$ is a $c$-li

Yi-Fan Wang, Alexander H. Nitz, Collin D. Capano, Xiangyu Ivy Wang

The recent discovery of a kilonova associated with an apparent long-duration gamma-ray burst has challenged the typical classification that long gamma-ray bursts originate from the core collapse of massive stars and short gamma-ray bursts are from compact binary coalescence. The kilonova indicates a neutron star merger origin and suggests the viability of gr

N. S. Witte, L. Wei

The Bures metric and the associated Bures-Hall measure is arguably the best choice for studying the spectrum of the quantum mechanical density matrix with no apriori knowledge of the system. We investigate the probability of a gap in the spectrum of this model, either at the bottom $ [0,s) $ or at the top $ (s,1] $, utilising the connection of this Pfaffian

Qianyu Chen, Bradley Dirks, Mircea Mustaţă, Sebastián Olano

We define and study a notion of minimal exponent for a locally complete intersection subscheme $Z$ of a smooth complex algebraic variety $X$, extending the invariant defined by Saito in the case of hypersurfaces. Our definition is in terms of the Kashiwara-Malgrange $V$-filtration associated to $Z$. We show that the minimal exponent describes how far the Hod

Alesia Chernikova, Nicolò Gozzi, Simona Boboila, Nicola Perra

Self-propagating malware (SPM) has recently resulted in large financial losses and high social impact, with well-known campaigns such as WannaCry and Colonial Pipeline being able to propagate rapidly on the Internet and cause service disruptions. To date, the propagation behavior of SPM is still not well understood, resulting in the difficulty of defending a

Felix Stoehr, Alisdair Manning, Stewart McLay, Kyoko Ashigatawa

Science archives are cornerstones of modern astronomical facilities. In this paper we describe the version 1.0 milestone of the Atacama Large Millimeter/submillimeter Array Science Archive. This version features a comprehensive query interface with rich metadata and visualisation of the spatial and spectral locations of the observations, a complete set of vi

Todor Markov, Chong Zhang, Sandhini Agarwal, Tyna Eloundou

We present a holistic approach to building a robust and useful natural language classification system for real-world content moderation. The success of such a system relies on a chain of carefully designed and executed steps, including the design of content taxonomies and labeling instructions, data quality control, an active learning pipeline to capture rar

K. Auinger, J. Bitterlich, M. Otto

For a finite connected graph $\mathcal{E}$ with set of edges $E$, a finite $E$-generated group $G$ is constructed such that the set of relations $p=1$ satisfied by $G$ (with $p$ a word over $E\cup E^{-1}$) is closed under deletion of generators (i.e.~edges). As a consequence, every element $g\in G$ admits a unique minimal set $\mathrm{C}(g)$ of edges (the \e

Seheon Ham, Hyerim Ko, Sanghyuk Lee, Sewook Oh

We study an analogue of Marstrand's circle packing problem for curves in higher dimensions. We consider collections of curves which are generated by translation and dilation of a curve $\gamma$ in $\mathbb R^d$, i.e., $ x + t \gamma$, $(x,t) \in \mathbb R^d \times (0,\infty)$. For a Borel set $F \subset \mathbb R^d\times (0,\infty)$, we show the unions of cu

Sebastian Olano

We study the Hodge and weight filtrations on the localization along a hypersurface, using methods from birational geometry and the $V$-filtration induced by a local defining equation. These filtrations give rise to ideal sheaves called weighted Hodge ideals, which include the adjoint ideal and a multiplier ideal. We analyze their local and global properties,

Jing Xu, Megan Ung, Mojtaba Komeili, Kushal Arora

Frozen models trained to mimic static datasets can never improve their performance. Models that can employ internet-retrieval for up-to-date information and obtain feedback from humans during deployment provide the promise of both adapting to new information, and improving their performance. In this work we study how to improve internet-driven conversational

Mikhail V. Sazhin, Valerian Sementsov, Sergey Sorokin, Dan Lubarskiy

The paper develops a method for detecting optical binary stars based on the use of astrometric catalogs in combination with machine learning (ML) methods. A computational experiment was carried out on the example of the HIPPARCOS mission catalog and the Pan-STARRS (PS1) catalog by applying the suggested method. It has shown that the reliability of predicting

Prathamesh Dharangutte, Christopher Musco

Let $\mathbf{A}\in \mathbb{R}^{n\times n}$ be a matrix with diagonal $\text{diag}(\mathbf{A})$ and let $\bar{\mathbf{A}}$ be $\mathbf{A}$ with its diagonal set to all zeros. We show that Hutchinson's estimator run for $m$ iterations returns a diagonal estimate $\tilde{d}\in \mathbb{R}^n$ such that with probability $(1-\delta)$, $$\|\tilde{d} - \text{diag}(\m

Minos Axenides, Emmanuel Floratos, Stam Nicolis

We construct Arnol'd cat map lattice field theories in phase space and configuration space. In phase space we impose that the evolution operator of the linearly coupled maps be an element of the symplectic group, in direct generalization of the case of one map. To this end we exploit the correspondence between the cat map and the Fibonacci sequence. The chao

Sebastián Andrade, Marat Siddikov, Iván Schmidt

In this paper we analyze the photoproduction of heavy quarkonia pairs which include $b$-quarks, such as $B_{c}^{+}B_{c}^{-}$-mesons or charmonium-bottomonium pairs. Compared to charmonia pair production, these channels get contributions only from some subsets of diagrams, and thus allow for a better theoretical understanding of different production mechanism

Marco Fanizza, Christoph Hirche, John Calsamiglia

Detecting abrupt changes in data streams is crucial because they are often triggered by events that have important consequences if left unattended. Quickest change point detection has become a vital sequential analysis primitive that aims at designing procedures that minimize the expected detection delay of a change subject to a bounded expected false alarm

Aaron Zweig, Joan Bruna

We study separations between two fundamental models (or \emph{Ans\"atze}) of antisymmetric functions, that is, functions $f$ of the form $f(x_{\sigma(1)}, \ldots, x_{\sigma(N)}) = \text{sign}(\sigma)f(x_1, \ldots, x_N)$, where $\sigma$ is any permutation. These arise in the context of quantum chemistry, and are the basic modeling tool for wavefunctions of Fe

Leonie Neuhäuser, Fariba Karimi, Jan Bachmann, Markus Strohmaier

Improving the position of minorities in networks via interventions is a challenge of high theoretical and societal importance. In this work, we examine how different network growth interventions impact the position of minority nodes in degree rankings over time. We distinguish between two kinds of interventions: (i) group size interventions, such as introduc

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

An amplitude analysis of $\Lambda^+_c \to pK^-\pi^+$ decays together with a measurement of the $\Lambda^+_c$ polarization vector in semileptonic beauty hadron decays is presented. A sample of $400\,000$ candidates is selected from proton-proton collisions recorded by the LHCb detector at a center-of-mass energy of 13 TeV. An amplitude model is developed and

Manuel Rebol, Colton Hood, Claudia Ranniger, Adam Rutenberg

We present a volumetric communication system that is designed for remote assistance of procedural tasks. The system allows a remote expert to visually guide a local operator. The two parties share a view that is spatially identical, but for the local operator it is of the object on which they operate, while for the remote expert, the object is presented as a

Enrico Bertolazzi, Antonella Falini, Francesca Mazzia

The library QIBSH++ is a C++ object oriented library for the solution of Quasi Interpolation problems. The library is based on a Hermite Quasi Interpolating operator, which was derived as continuous extensions of linear multistep methods applied for the numerical solution of Boundary Value Problems for Ordinary Differential Equations. The library includes th

Alessandro Giacchetto, Reinier Kramer, Danilo Lewański, Adrien Sauvaget

We study the spin Gromov-Witten (GW) theory of $\mathbb{P}^1$. Using the standard torus action on $\mathbb{P}^1$, we prove that the associated equivariant potential can be expressed by means of operator formalism and satisfies the 2-BKP hierarchy. As a consequence of this result, we prove the spin analogue of the GW/Hurwitz correspondence of Okounkov-Pandhar

Oliver Roche-Newton, Audie Warren

We construct a convex set $A$ with cardinality $2n$ and with the property that an element of the difference set $A-A$ can be represented in $n$ different ways. We also show that this construction is optimal by proving that for any convex set $A$, the maximum possible number of representations an element of $A-A$ can have is $\lfloor |A|/2 \rfloor $.

Ziyi Zhao, Sena Kiciroglu, Hugues Vinzant, Yuan Cheng

Unsupervised self-rehabilitation exercises and physical training can cause serious injuries if performed incorrectly. We introduce a learning-based framework that identifies the mistakes made by a user and proposes corrective measures for easier and safer individual training. Our framework does not rely on hard-coded, heuristic rules. Instead, it learns them

Matthew Baker, Tong Jin

Let $r \leqslant n$ be nonnegative integers, and let $N = \binom{n}{r} - 1$. For a matroid $M$ of rank $r$ on the finite set $E = [n]$ and a partial field $k$ in the sense of Semple--Whittle, it is known that the following are equivalent: (a) $M$ is representable over $k$; (b) there is a point $p = (p_J) \in {\bf P}^N(k)$ with support $M$ (meaning that $\tex

Narayan Mohanta, Elbio Dagotto

Chiral magnetic phases with an unconventional topological twist in the magnetization are of huge interest due to their potential in spintronics applications. Here, we present a general method to induce such exotic magnetic phases using interfacial phase frustration within artificially grown superlattices. To demonstrate our method, we consider a multilayer w

Fabio Tanania

In this paper, we construct and study a Serre-type spectral sequence for motivic cohomology associated to a map of bisimplicial schemes with motivically cellular fiber. Then, we show how to apply it in order to approach the computation of the motivic cohomology of the Nisnevich classifying space of projective general linear groups. This naturally yields an e

Chiara Amorino, Arnaud Gloter

Let $(X_t)_{t \ge 0}$ be solution of a one-dimensional stochastic differential equation. Our aim is to study the convergence rate for the estimation of the invariant density in intermediate regime, assuming that a discrete observation of the process $(X_t)_{t \in [0, T]}$ is available, when $T$ tends to $\infty$. We find the convergence rates associated to t

Zhuoran Shang, Elena A. Erosheva, Gongjun Xu

Cognitive diagnosis models (CDMs) are a family of discrete latent attribute models that serve as statistical basis in educational and psychological cognitive diagnosis assessments. CDMs aim to achieve fine-grained inference on individuals' latent attributes, based on their observed responses to a set of designed diagnostic items. In the literature, CDMs usua

Sakirudeen A. Abdulsalaam, Montaz Ali

In this paper, we apply the Rank-Sparsity Matrix Decomposition to the planted Maximum Quasi-Clique Problem (MQCP). This problem has the planted Maximum Clique Problem (MCP) as a special case. The maximum clique problem is NP-hard. A Quasi-clique or $\gamma$-clique is a dense graph with the edge density of at least $\gamma$, where $\gamma \in (0, 1]$. The max

Javier Osca, Jiri Vala

We are concerned with numerical simulations of quantum optical circuits under certain realistic conditions, specifically that photon quantum states are not perfectly indistinguishable. The partial photon distinguishability presents a serious limitation in implementation of optical quantum information processing. In order to properly assess its effect on quan

Talip Ucar, Ehsan Hajiramezanali

Neural Networks are known to be sensitive to initialisation. The methods that rely on neural networks for feature ranking are not robust since they can have variations in their ranking when the model is initialized and trained with different random seeds. In this work, we introduce a novel method based on parameter averaging to estimate accurate and robust f

M. Ginolfi, E. Piconcelli, L. Zappacosta, G. C. Jones

The phase transition between galaxies and quasars is often identified with the rare population of hyper-luminous, hot dust-obscured galaxies. Galaxy formation models predict these systems to grow via mergers, that can deliver large amounts of gas toward their centers, induce intense bursts of star formation and feed their supermassive black holes. Here we re

Zaiwei Chen, Siva Theja Maguluri

In this work, we consider policy-based methods for solving the reinforcement learning problem, and establish the sample complexity guarantees. A policy-based algorithm typically consists of an actor and a critic. We consider using various policy update rules for the actor, including the celebrated natural policy gradient. In contrast to the gradient ascent a

Omar Al Ghattas, Daniel Sanz-Alonso

Many modern algorithms for inverse problems and data assimilation rely on ensemble Kalman updates to blend prior predictions with observed data. Ensemble Kalman methods often perform well with a small ensemble size, which is essential in applications where generating each particle is costly. This paper develops a non-asymptotic analysis of ensemble Kalman up

Jan-Philipp Hoffknecht, Alina Wettstein, Jaschar Atik, Christian Krause

Lithium salts with low coordinating anions like bis(trifluoromethanesulfonyl)imide (TFSI) have been the state-of-the-art for PEO-based 'dry' polymer electrolytes for three decades. Plasticizing PEO with TFSI-based ionic liquids (ILs) to form ternary solid polymer electrolytes (TSPEs) increases conductivity and Li$^+$ diffusivity. However, the Li$^+$ transpor

Manuel Rebol, Christian Gütl, Krzysztof Pietroszek

We propose a real-time system for synthesizing gestures directly from speech. Our data-driven approach is based on Generative Adversarial Neural Networks to model the speech-gesture relationship. We utilize the large amount of speaker video data available online to train our 3D gesture model. Our model generates speaker-specific gestures by taking consecutiv

Norman Danner

With one exception, our previous work on recurrence extraction and denotational semantics has focused on a source language that supports inductive types and structural recursion. The exception handles general recursion via an initial translation into call-by-push-value. In this note we give an extraction function from a language with general recursive functi

Danny Stax, Manel Slokom, Martha Larson

Recently, researchers have turned their attention to recommender systems that use only minimal necessary data. This trend is informed by the idea that recommender systems should use no more user interactions than are needed in order to provide users with useful recommendations. In this position paper, we make the case for applying the idea of minimal necessa

Roy Gotlib, Tali Kaufman

One of the most important properties of high dimensional expanders is that high dimensional random walks converge rapidly. This property has proven to be extremely useful in variety of fields in the theory of computer science from agreement testing to sampling, coding theory and more. In this paper we present a state of the art result in a line of works anal

Roberto Ribatti

Two measurements of mixing and $CP$ violation in charm decays performed at the LHCb experiment are presented. The former is a measurement of the mixing observable $y_{CP}-y_{CP}^{K\pi}$ in two-body $D^0$ decays, while the latter is a search for direct $CP$ violation in $D^+_{(s)}\rightarrow\eta^{(')}\pi^+$ decays.

Elizabeth Denne, Troy Larsen

We study Kauffman's model of folded ribbon knots: knots made of a thin strip of paper folded flat in the plane. The folded ribbonlength is the length to width ratio of such a folded ribbon knot. The folded ribbon knot is also a framed knot, and the ribbon linking number is the linking number of the knot and one boundary component of the ribbon. We find the m

Céline Hocquette, Andrew Cropper

A magic value in a program is a constant symbol that is essential for the execution of the program but has no clear explanation for its choice. Learning programs with magic values is difficult for existing program synthesis approaches. To overcome this limitation, we introduce an inductive logic programming approach to efficiently learn programs with magic v

Valerie Domcke, Kohei Kamada, Kyohei Mukaida, Kai Schmitz

A chiral chemical potential present in the early universe can source helical hypermagnetic fields through the chiral plasma instability. If these hypermagnetic fields survive until the electroweak phase transition, they source a contribution to the baryon asymmetry of the universe. In this letter, we demonstrate that lepton flavour asymmetries above $|\mu|/T

Douglas Farenick, Michelle McBurney

A new proof is presented of a theorem of L.~Gurvits, which states that the cone of positive block-Toeplitz matrices with matrix entries has no entangled elements. The proof of the Gurvits separation theorem is achieved by making use of the structure of the operator system dual of the operator system $C(S^1)^{(n)}$ of $n\times n$ Toeplitz matrices over the co

Jan Niklas Adams, Daniel Schuster, Seth Schmitz, Günther Schuh

The execution of processes leaves traces of event data in information systems. These event data can be analyzed through process mining techniques. For traditional process mining techniques, one has to associate each event with exactly one object, e.g., the company's customer. Events related to one object form an event sequence called a case. A case describes

S. J. Thomson

It is widely believed that many-body localisation in one dimension is fragile and can be easily destroyed by thermal inclusions, however there are still many open questions regarding the stability of the localised phase and under what conditions it breaks down. Here I construct models with dilute disorder, which interpolate between translationally invariant

Jeremiah Jones, Ashkan Ertefaie, James R. McKay, David W. Oslin

Q-learning facilitates the development of an optimal adaptive treatment strategy through stagewise regression on a pre-specified set of tailoring variables and confounders. Semiparametric robust Q-learning eliminates the residual confounding that can occur when parametric working models for confounding influences are misspecified. However, in the presence of

Samuel Joutard, Reuben Dorent, Sebastien Ourselin, Tom Vercauteren

Inter-patient abdominal registration has various applications, from pharmakinematic studies to anatomy modeling. Yet, it remains a challenging application due to the morphological heterogeneity and variability of the human abdomen. Among the various registration methods proposed for this task, probabilistic displacement registration models estimate displacem

Qingshan Shen, Qingbo Wang

State-of-the-art automotive radar sensors use a Mutliple-Input Mutiple-Output (MIMO) approach to obtain a better angular resolution. Time-Division Multiplexing (TDM) scheme is commonly applied to realize the orthogonality in time at the transmitter. Apart from its simplicity in implementation, TDM scheme has the drawback of a reduced maximum unambiguous Dopp

Sebastian Oberbauer, Shamil Erkenov, Werner Biberacher, Natalia D. Kushch

The physics of the Mott metal-insulator transition (MIT) has attracted huge interest in the last decades. However, despite broad efforts, some key theoretical predictions are still lacking experimental confirmation. In particular, it is not clear whether the large coherent Fermi surface survives in immediate proximity to the bandwidth-controlled first-order

Wanjun Zhong, Yifan Gao, Ning Ding, Zhiyuan Liu

Task generalization has been a long standing challenge in Natural Language Processing (NLP). Recent research attempts to improve the task generalization ability of pre-trained language models by mapping NLP tasks into human-readable prompted forms. However, these approaches require laborious and inflexible manual collection of prompts, and different prompts

P. Vemareddy

Using time-sequence vector magnetic field and coronal observations from \textit{Solar Dynamics Observatory}, we report the observations of the magnetic field evolution and coronal activity in four emerging active regions (ARs). The ARs emerge with leading polarity being the same as for the majority of ARs in a hemisphere of solar cycle 24. After emergence, t

Shinichiro Akiyama

Recently, the tensor network description with bond weights on its edges has been proposed as a novel improvement for the tensor renormalization group algorithm. The bond weight is controlled by a single hyperparameter, whose optimal value is estimated in the original work via the numerical computation of the two-dimensional critical Ising model. We develop t

Grace Halferty, Vishnu Reddy, Tanner Campbell, Adam Battle

Starlink is a low-Earth orbit (LEO) satellite constellation operated by Space Exploration Technologies Corp. (SpaceX) which aims to provide global satellite internet access. Thus far, most photometric observations of Starlink satellites have primarily been from citizen scientists' visual observations without using quantitative detectors. This paper aims to c

Nadhir Ben Rached, Abdul-Lateef Haji-Ali, Shyam Mohan Subbiah Pillai, Raúl Tempone

This work combines multilevel Monte Carlo (MLMC) with importance sampling to estimate rare-event quantities that can be expressed as the expectation of a Lipschitz observable of the solution to a broad class of McKean--Vlasov stochastic differential equations. We extend the double loop Monte Carlo (DLMC) estimator introduced in this context in (Ben Rached et

Andrew James Bruce

We introduce the notion of a Lie semiheap as a smooth manifold equipped with a para-associative ternary product. For a particular class of Lie semiheaps we establish the existence of left-invariant vector fields. Furthermore, we show how such manifolds are related to Lie groups and establish the analogue of principal bundles in this ternary setting. In parti