May 2022 arXiv papers — page 100

Javier Segovia-Aguas, Sergio Jiménez, Anders Jonsson

Although heuristic search is one of the most successful approaches to classical planning, this planning paradigm does not apply straightforwardly to Generalized Planning (GP). This paper adapts the planning as heuristic search paradigm to the particularities of GP, and presents the first native heuristic search approach to GP. First, the paper defines a prog

Alex Woodfinden, Seshadri Nadathur, Will J. Percival, Slađana Radinović

We present measurements of the anisotropic cross-correlation of galaxies and cosmic voids in data from the Sloan Digital Sky Survey Main Galaxy Sample (MGS), Baryon Oscillation Spectroscopic Survey (BOSS) and extended BOSS (eBOSS) luminous red galaxy catalogues from SDSS Data Releases 7, 12 and 16, covering the redshift range $0.07<z<1.0$. As in our previous

Abhinav Vaishya, Athreya Chandramouli, Srikar Kale, Prasad Krishnan

We consider replication-based distributed storage systems in which each node stores the same quantum of data and each data bit stored has the same replication factor across the nodes. Such systems are referred to as balanced distributed databases. When existing nodes leave or new nodes are added to this system, the balanced nature of the database is lost, ei

Fabio Centofanti, Antonio Lepore, Murat Kulahci, Max Peter Spooner

With the rise of Industry 4.0, huge amounts of data are now generated that are apt to be modelled as functional data. In this setting, standard profile monitoring methods aim to assess the stability over time of a completely observed functional quality characteristic. However, in some practical situations, evaluating the process state in real-time, i.e., as

Qianqian Wang, Zhengqi Li, David Salesin, Noah Snavely

We introduce 3D Moments, a new computational photography effect. As input we take a pair of near-duplicate photos, i.e., photos of moving subjects from similar viewpoints, common in people's photo collections. As output, we produce a video that smoothly interpolates the scene motion from the first photo to the second, while also producing camera motion with

Enric Corona, Gerard Pons-Moll, Guillem Alenyà, Francesc Moreno-Noguer

We propose a novel optimization-based paradigm for 3D human model fitting on images and scans. In contrast to existing approaches that directly regress the parameters of a low-dimensional statistical body model (e.g. SMPL) from input images, we train an ensemble of per-vertex neural fields network. The network predicts, in a distributed manner, the vertex de

David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A. Ross

While there have been significant gains in the field of automated video description, the generalization performance of automated description models to novel domains remains a major barrier to using these systems in the real world. Most visual description methods are known to capture and exploit patterns in the training data leading to evaluation metric incre

Muhsin Aljaf, Emilio Elizalde, Martiros Khurshudyan, Kairat Myrzakulov

Bayesian Machine Learning~(BML) and strong lensing time delay~(SLTD) techniques are used in order to tackle the $H_{0}$ tension in $f(T)$ gravity. The power of BML relies on employing a model-based generative process which already plays an important role in different domains of cosmology and astrophysics, being the present work a further proof of this. Three

Busheng Wang, Katerina P. Hilleke, Xiaoyu Wang, Danae N. Polsin

Ab initio evolutionary structure searches coupled with quasiharmonic calculations predict that the insulating Na hP4 phase transitions to a novel P63/m phase between 200 GPa at 150 K, and 350 GPa at 1900 K. P63/m Na is a topological semimetal with a Dirac nodal surface that is protected by a non-symmorphic symmetry, S2z . It is characterized by localized non

Ritvik Basant, Jeremy Dietrich, Daniel Apai

e Eridani, the fifth-closest Sun-like star, hosts at least three planets and could possibly harbor more. However, the veracity of the planet candidates in the system and its full planetary architecture remain unknown. Here we analyze the planetary architecture of e Eridani via DYNAMITE, a method providing an integrative assessment of the system architecture

Amol Aggarwal, Josh Alman

For any real numbers $B \ge 1$ and $\delta \in (0, 1)$ and function $f: [0, B] \rightarrow \mathbb{R}$, let $d_{B; \delta} (f) \in \mathbb{Z}_{> 0}$ denote the minimum degree of a polynomial $p(x)$ satisfying $\sup_{x \in [0, B]} \big| p(x) - f(x) \big| < \delta$. In this paper, we provide precise asymptotics for $d_{B; \delta} (e^{-x})$ and $d_{B; \delta} (

S. Friot, G. Suchet-Bernard

We explore the large set of linear transformations of Srivastava's $H_C$ triple hypergeometric function. This function has been recently linked to the massive one-loop conformal scalar 3-point Feynman integral. We focus here on the class of linear transformations of $H_C$ that can be obtained from linear transformations of the Gauss $_2F_1$ hypergeometric fu

Dario Partipilo

Finding vacua of supergravity theories is an outstanding problem which has been tackled in several ways, and with this work we add a new method to the puzzle. We analyse the scalar sector of maximal gauged supergravity theories in seven space-time dimensions. We look for vacua of the theory by varying the embedding tensor, instead of directly minimising the

Arkya Chatterjee, Xiao-Gang Wen

Two global symmetries are holo-equivalent if their algebras of local symmetric operators are isomorphic. Holo-equivalent classes of global symmetries are classified by gappable-boundary topological orders (TO) in one higher dimension (called symmetry TO), which leads to a symmetry/topological-order (Symm/TO) correspondence. We establish that: (1) For systems

Clay Cordova, Kantaro Ohmori

We elucidate the fate of classical symmetries which suffer from abelian Adler-Bell-Jackiw anomalies. Instead of being completely destroyed, these symmetries survive as non-invertible topological global symmetry defects with worldvolume anyon degrees of freedom that couple to the bulk through a magnetic one-form global symmetry as in the fractional hall effec

Yang Chen, Cheng Cheng, Qiyu Sun

Graph Fourier transform (GFT) is a fundamental concept in graph signal processing. In this paper, based on singular value decomposition of Laplacian, we introduce a novel definition of GFT on directed graphs, and use singular values of Laplacian to carry the notion of graph frequencies. % of the proposed GFT. The proposed GFT is consistent with the conventio

Marko Tesic, Ulrike Hahn

Counterfactual (CF) explanations have been employed as one of the modes of explainability in explainable AI-both to increase the transparency of AI systems and to provide recourse. Cognitive science and psychology, however, have pointed out that people regularly use CFs to express causal relationships. Most AI systems are only able to capture associations or

Matthew Elley, Hector O. Silva, Helvi Witek, Nicolás Yunes

Particular couplings between a scalar field and the Gauss-Bonnet invariant lead to spontaneous scalarization of black holes. Here we continue our work on simulating this phenomenon in the context of binary black hole systems. We consider a negative coupling for which the black-hole spin plays a major role in the scalarization process. We find two main phenom

Morgan H. Lynch

The incorporation of classical general relativity into quantum field theory yields a surprising result -- thermodynamic particle production. One such phenomenon, known as the Unruh effect, causes empty space to effervesce a thermal bath of particles when viewed by an observer undergoing uniformly accelerated motion. These systems will have a Rindler horizon

Atasi Chakraborty, Debasis Dutta, Amit Agarwal

Flat bands in twisted moire superlattices support a variety of topological and strongly correlated phenomena along with easily tunable electrical and optical properties. Here, we demonstrate the existence of tunable, long-lived, and flat intraband and interband terahertz plasmons in twisted double bilayer graphene. We show that the interband plasmons origina

Yifan Chen, Rittick Roy, Sunny Vagnozzi, Luca Visinelli

Ultralight bosons can affect the dynamics of spinning black holes (BHs) via superradiant instability, which can lead to a time evolution of the supermassive BH shadow. We study prospects for witnessing the superradiance-induced BH shadow evolution, considering ultralight vector and tensor fields. We introduce two observables sensitive to the shadow time-evol

Félix Remigereau, Djebril Mekhazni, Sajjad Abdoli, Le Thanh Nguyen-Meidine

Despite the recent success of deep learning architectures, person re-identification (ReID) remains a challenging problem in real-word applications. Several unsupervised single-target domain adaptation (STDA) methods have recently been proposed to limit the decline in ReID accuracy caused by the domain shift that typically occurs between source and target vid

Gabriel Wang, Anish Thite, Rodd Talebi, Anthony D'Achille

Machine Learning models are used in a wide variety of domains. However, machine learning methods often require a large amount of data in order to be successful. This is especially troublesome in domains where collecting real-world data is difficult and/or expensive. Data simulators do exist for many of these domains, but they do not sufficiently reflect the

Emanuele De Angelis, Fabio Fioravanti, Alberto Pettorossi, Maurizio Proietti

We address the problem of verifying that the functions of a program meet their contracts, specified by pre/postconditions. We follow an approach based on constrained Horn clauses (CHCs) by which the verification problem is reduced to the problem of checking satisfiability of a set of clauses derived from the given program and contracts. We consider programs

Azizul Hoque

Generalized Mersenne numbers are defined as $M_{p,n} = p^n - p + 1$, where $p$ is any prime and $n$ is any positive integer. Here, we prove that for each pair $(c, p)$ with $c\geq 1$ an integer, there is at most one $M_{p, n}$ of the form $cx^2$ with a few exceptions.

Antonio Jesús Banegas-Luna, Horacio Pérez-Sánchez

Personalized medicine remains a major challenge for scientists. The rapid growth of Machine learning and Deep learning has made them a feasible al- ternative for predicting the most appropriate therapy for individual patients. However, the need to develop a custom model for every dataset, the lack of interpretation of their results and high computational req

M. M. Rahman, N. Hasan, M. A. Hoque, M. B. Hossen

In this study, a series of nanocrystalline ferrites of Ni0.7Cu0.30AlxFe2-xO4 (x=0.00 to 0.10 with a step of 0.02) has been synthesized through the sol-gel auto combustion technique. The structural, morphological, dielectric, and electrical properties of the Ni-Cu spinel ferrite nanoparticles are analyzed due to the substitution of Al3+ content. The crystalli

Rikpratik Sengupta, Shounak Ghosh, Mehedi Kalam

Wormholes with Ellis geometry have been successfully constructed using tachyon matter \cite{Das}. However, for such a wormhole, it is obtained that the redshift function is necessarily a constant, and also the wormhole is plagued with an imaginary tachyon potential and a constant field if the solutions are obtained in the absence of a cosmological constant t

Kadierdan Kaheman, Urban Fasel, Jason J. Bramburger, Benjamin Strom

The single, double, and triple pendulum has served as an illustrative experimental benchmark system for scientists to study dynamical behavior for more than four centuries. The pendulum system exhibits a wide range of interesting behaviors, from simple harmonic motion in the single pendulum to chaotic dynamics in multi-arm pendulums. Under forcing, even the

Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann

Combining simple architectures with large-scale pre-training has led to massive improvements in image classification. For object detection, pre-training and scaling approaches are less well established, especially in the long-tailed and open-vocabulary setting, where training data is relatively scarce. In this paper, we propose a strong recipe for transferri

Megan G. Frank, David G. Whelan, Jessica C. Junginger

The spectral classification of Algol C, the third star in the Algol triple system, has long been a matter of some uncertainty. There is good reason to suspect that it should be a metallic-line A-type star, and one study in particular showed that this was so, but further studies have cast doubt on that assessment. We utilized a simple spectral subtraction met

Xiaoqi Liu, Ramji Venkataramanan

We consider the problem of recovering an $n_1 \times n_2$ low-rank matrix with $k$-sparse singular vectors from a small number of linear measurements (sketch). We propose a sketching scheme and an algorithm that can recover the singular vectors with high probability, with a sample complexity and running time that both depend only on $k$ and not on the ambien

Haider Zia, Kaixuan Ye, Yvan Klaver, David Marpaung

Fully integrated supercontinuum sources on-chip are critical to enabling applications such as portable and mechanically-stable medical imaging devices, chemical sensing and LiDAR. However, the low-efficiency of current supercontinuum generation schemes prevent full on-chip integration. In this letter, we present a scheme where the input energy requirements f

Zixin Wen, Yuanzhi Li

Recently the surprising discovery of the Bootstrap Your Own Latent (BYOL) method by Grill et al. shows the negative term in contrastive loss can be removed if we add the so-called prediction head to the network. This initiated the research of non-contrastive self-supervised learning. It is mysterious why even when there exist trivial collapsed global optimal

Xiaotong Zhao, Siyuan Lu, Qingjiang Shi, Zhi-Quan Luo

Precoding design for maximizing weighted sum-rate (WSR) is a fundamental problem for downlink of massive multi-user multiple-input multiple-output (MU-MIMO) systems. It is well-known that this problem is generally NP-hard due to the presence of multi-user interference. The weighted minimum mean-square error (WMMSE) algorithm is a popular approach for WSR max

M. Ruzhansky, A. R. Safarov, G. A. Khasanov

In this paper we consider the uniform estimates for oscillatory integrals with a two-order homogeneous polynomial phase. The estimate is sharp and the result is an analogue of the more general theorem of V. N. Karpushkin \cite{Karpushkin1983} for sufficiently smooth functions.

Bhanu Pratap Singh Rawat, Samuel Kovaly, Wilfred R. Pigeon, Hong Yu

Suicide is an important public health concern and one of the leading causes of death worldwide. Suicidal behaviors, including suicide attempts (SA) and suicide ideations (SI), are leading risk factors for death by suicide. Information related to patients' previous and current SA and SI are frequently documented in the electronic health record (EHR) notes. Ac

Ali Keramatipour, Jeffrey Shallit

Stern's diatomic series, denoted by $(a(n))_{n \geq 0}$, is defined by the recurrence relations $a(2n) = a(n)$ and $a(2n + 1) = a(n) + a(n + 1)$ for $n \geq 1$, and initial values $a(0) = 0$ and $a(1) = 1$. A record-setter for a sequence $(s(n))_{n \geq 0}$ is an index $v$ such that $s(i) < s(v)$ holds for all $i < v$. In this paper, we give a complete descr

Tomasz Klimsiak, Maurycy Rzymowski

We study reflected backward stochastic differential equation (RBSDEs) on the probability space equipped with a Brownian motion. The main novelty of the paper lies in fact that we consider the following weak assumptions on the data: barriers are optional of class (D) satisfying weak Mokobodzki's condition, generator is continuous and non-increasing with respe

Garima Shukla, Pratik Kumar, Sajal K. Paul

This paper proposes a new design for realizing grounded and floating meminductor emulators built with two operational transconductance amplifiers (OTAs) and two second-generation current conveyors. The proposed grounded and floating emulators claim that the circuits are much simpler in design and can be utilized in incremental and decremental topologies. The

James M. De Buizer, Wanggi Lim, Nicole Karnath, James T. Radomski

This is the fourth paper exploring the infrared properties of giant HII regions with the FORCAST instrument on the Stratospheric Observatory For Infrared Astronomy (SOFIA). Our survey utilizes the census of 56 Milky Way giant HII regions identified by Conti & Crowther (2004), and in this paper we present the 20 and 37 micron imaging data we have obtained fro

Hezi Halawi

Let $G$ be a split group of type $F_4$ defined over a number field. We study the square-integrable automorphic representations of $G$ that can be realized as leading terms of degenerate Eisenstein series associated to various maximal parabolic subgroups. These representations appear in the residual spectrum. The local representation theory over finite places

Kenny T. R. Voo, Liming Jiang, Chen Change Loy

This paper performs comprehensive analysis on datasets for occlusion-aware face segmentation, a task that is crucial for many downstream applications. The collection and annotation of such datasets are time-consuming and labor-intensive. Although some efforts have been made in synthetic data generation, the naturalistic aspect of data remains less explored.

Johannes Jakob Meyer, Marian Mularski, Elies Gil-Fuster, Antonio Anna Mele

Variational quantum machine learning is an extensively studied application of near-term quantum computers. The success of variational quantum learning models crucially depends on finding a suitable parametrization of the model that encodes an inductive bias relevant to the learning task. However, precious little is known about guiding principles for the cons

Andrea E. V. Ferrari

We consider 3d $\mathcal{N} = 4$ theories on the geometry $\Sigma\times\mathbb{R}$, where $\Sigma$ is a closed and connected Riemann surface, from the point of view of a quantum mechanics on $\mathbb{R}$. Focussing on the elementary mirror pair in the presence of real deformation parameters, namely SQED with one hypermultiplet (SQED[1]) and the free hypermul

Dror Aizik, Ioannis Gkioulekas, Anat Levin

Wavefront shaping correction makes it possible to image fluorescent particles deep inside scattering tissue. This requires determining a correction mask to be placed in both excitation and emission paths. Standard approaches select correction masks by optimizing various image metrics, a process that requires capturing a prohibitively large number of images.

Rogier A. Windhorst, Timothy Carleton, Rosalia O'Brien, Seth H. Cohen

We give an overview and describe the rationale, methods, and testing of the Hubble Space Telescope (HST) Archival Legacy project "SKYSURF." SKYSURF uses HST's unique capability as an absolute photometer to measure the ~0.2-1.7 $\mu$m sky surface brightness (SB) from 249,861 WFPC2, ACS, and WFC3 exposures in ~1400 independent HST fields. SKYSURF's panchromati

X. Gratens, B. de Abreu Silva, M. I. B. Bernardi, H. B. de Carvalho

The magnetization of Zn1-xCoxO (0.0055 < x < 0.073) nanoparticles has been measured as a function of temperature T (1.7 K < T , 10 K) and for magnetic field up to 65 kOe using a SQUID magnetometer. Samples were synthesized by three different growth methods: microwave-assisted hydrothermal, combustion reaction and sol-gel. For all studied samples, the magneti

Michael Eichelbeck, Hannah Markgraf, Matthias Althoff

Future power systems will rely heavily on micro grids with a high share of decentralised renewable energy sources and energy storage systems. The high complexity and uncertainty in this context might make conventional power dispatch strategies infeasible. Reinforcement-learning based (RL) controllers can address this challenge, however, cannot themselves pro

Andrei V. Vasin, Evgueni Doubtsov

Let $D\subset \mathbb{R}^d$ be a bounded Lipschitz domain, $\omega$ be a high order modulus of continuity and let $T$ be a convolution Calder\'{o}n-Zygmund operator. We characterize the bounded restricted operators $T_D$ on the Zygmund space $\mathcal{C}_{\omega}(D)$. The characterization is based on properties of $T_D P$ for appropriate polynomials $P$ rest

Sourav Maiti, Sunayana Mitra, Clinton A. Johnson, Kai C. Gronborg

The dynamics of excess protons in the protic ionic liquid ethylammonium formate (EAF) have been investigated from femtosecond to microseconds using visible pump mid-infrared probe spectroscopy. The pH-jump following visible photoexcitation of a photoacid (8-hydroxypyrene-1,3,6-trisulfonic acid trisodium salt, HPTS) results in proton transfer to the formate o

R. Domínguez, Eric W. Pellegrini, Ralf S. Klessen, Daniel Rahner

We study the evolution of embedded star clusters as possible progenitors to reproduce 30 Doradus, specifically the compact star cluster known as R136 and its surrounding stellar family, which is believed to be part of an earlier star formation event. We employ the high-precision stellar dynamics code NBODY6++GPU to calculate the dynamics of the stars embedde

Mikhail Pavlov

In this note, we study a special case of the $4$-pt non-vacuum classical block associated with the $\mathcal{W}_3$ algebra. We formulate the monodromy problem for the block and derive monodromy equations within the heavy-light approximation. Fixing the remaining functional arbitrariness using parameters of the $4$-pt vacuum $\mathcal{W}_3$ block, we compute

Yuning Mao, Ming Zhong, Jiawei Han

Scientific extreme summarization (TLDR) aims to form ultra-short summaries of scientific papers. Previous efforts on curating scientific TLDR datasets failed to scale up due to the heavy human annotation and domain expertise required. In this paper, we propose a simple yet effective approach to automatically extracting TLDR summaries for scientific papers fr

Maximilian Nitzschner

We study the directed polymer model on infinite clusters of supercritical Bernoulli percolation containing the origin in dimensions $d \geq 3$, and prove that for almost every realization of the cluster and every strictly positive value of the inverse temperature, the polymer is in a strong disorder phase, answering a question from Cosco, Seroussi, and Zeito

Ahmed El-Kishky, Thomas Markovich, Kenny Leung, Frank Portman

Candidate retrieval is the first stage in recommendation systems, where a light-weight system is used to retrieve potentially relevant items for an input user. These candidate items are then ranked and pruned in later stages of recommender systems using a more complex ranking model. As the top of the recommendation funnel, it is important to retrieve a high-

Xintian Wu, Qihang Zhang, Yiming Wu, Huanyu Wang

Formulated as a conditional generation problem, face animation aims at synthesizing continuous face images from a single source image driven by a set of conditional face motion. Previous works mainly model the face motion as conditions with 1D or 2D representation (e.g., action units, emotion codes, landmark), which often leads to low-quality results in some

Antonio Laverghetta, Animesh Nighojkar, Jamshidbek Mirzakhalov, John Licato

Transformer-based language models (LMs) continue to achieve state-of-the-art performance on natural language processing (NLP) benchmarks, including tasks designed to mimic human-inspired "commonsense" competencies. To better understand the degree to which LMs can be said to have certain linguistic reasoning skills, researchers are beginning to adapt the tool

G. Janka, B. Ohayon, I. Cortinovis, Z. Burkley

Muons are puzzling physicists since their discovery when they were first thought to be the meson predicted by Yukawa to mediate the strong force. The recent results at Fermilab on the muon g-2 anomaly puts the muonic sector once more under the spotlight and calls for new measurements with this fascinating particle. Here we present the results of the first me

Soumyasree Jena, Sanjoy Datta

The electronic structure and thermodynamic stability of tetragonal $\rm{BiFeO_3}$(001) surfaces have been investigated using density functional theory. In this work, four different structures having different lattice constants with two possible surface terminations have been studied. We have found that the surface electronic structure and the thermodynamic s

Catherine Tony, Mohana Balasubramanian, Nicolás E. Díaz Ferreyra, Riccardo Scandariato

Conversational agents or chatbots are widely investigated and used across different fields including healthcare, education, and marketing. Still, the development of chatbots for assisting secure coding practices is in its infancy. In this paper, we present the results of an empirical study on SKF chatbot, a software-development bot (DevBot) designed to answe

Hyoungjun Kim, Thomas W Mattman, Seungsang Oh

A graph is intrinsically knotted if every embedding contains a nontrivially knotted cycle. It is known that intrinsically knotted graphs have at least 21 edges and that there are exactly 14 intrinsically knotted graphs with 21 edges, in which the Heawood graph is the only bipartite graph. The authors showed that there are exactly two graphs with at most 22 e

Arthur Aubret, Céline Teulière, Jochen Triesch

Recent time-contrastive learning approaches manage to learn invariant object representations without supervision. This is achieved by mapping successive views of an object onto close-by internal representations. When considering this learning approach as a model of the development of human object recognition, it is important to consider what visual input a t

Shakir Showkat Sofi, Nadezhda Alsahanova

Solving segmentation tasks with topological priors proved to make fewer errors in fine-scale structures. In this work, we use topological priors both before and during the deep neural network training procedure. We compared the results of the two approaches with simple segmentation on various accuracy metrics and the Betti number error, which is directly rel

Asuka Takai, Qiushi Fu, Yuzuru Doibata, Giuseppe Lisi

Collaboration frequently yields better results in decision making, learning, and haptic interactions than when these actions are performed individually. However, is collaboration always superior to solo actions, or do its benefits depend on whether collaborating individuals have different or the same roles? To answer this question, we asked human subjects to

Andrés I. Bertoni, Cristián G. Sánchez

In this work we propose a chemically-informed data-driven approach to benchmark the approximate density-functional tight-binding (DFTB) excited state (ES) methods that are currently available within the DFTB+ suite. By taking advantage of the large volume of low-detail ES-data in the machine learning (ML) dataset, QM8, we were able to extract valuable insigh

Roman Zwicky

In these lecture notes the basics of QED corrections to hadronic decays are reviewed with special emphasis on conceptual (e.g. counting and tracking of infrared sensitive logs) rather than numerical aspects. General matters are illustrated for the cases of increased complexity and decreased inclusiveness: $e^+ e^- \to hadrons$, the leptonic decay $\pi^+ \to

Joshua Leveillee, Samuel Ponce, Nicholas L. Adamski, Chris G. Van de Walle

The key obstacle toward realizing integrated gallium nitride (GaN) electronics is its low hole mobility. Here, we explore the possibility of improving the hole mobility of GaN via epitaxial matching to II-IV nitride materials that have recently become available, namely ZnGeN$_2$ and MgSiN$_2$. We perform state-of-the-art calculations of the hole mobility of

Yujiao Chen, Rongxin Yin

The smart control informed by IoT sensors and enabled by remotely controlled devices can optimize the building operation to minimize unnecessary energy consumption and improve indoor thermal comfort. This paper quantifies the potential for electricity savings in small office buildings from smart thermostat control and occupancy-informed smart plug control. T

Jhon Manuel Portella Delgado, Ankit Goel

In this paper, we consider the problem of input-output linearization of the longitudinal flight dynamics. In longitudinal flight dynamics, inputs are typically thrust and elevator deflection whereas the outputs are the velocity and the flight path angle. An input-output linearization-based controller can be designed to render the multi-input, multi-output sy

Y. F. Zolotarev, I. A. Luchnikov, J. A. López-Saldívar, A. K. Fedorov

We present a continuous monitoring system for intermediate-scale quantum processors that allows extracting estimates of noisy native gate and read-out measurements based on the set of executed quantum circuits and resulting measurement outcomes. In contrast to standard approaches for calibration and benchmarking quantum processors, the executed circuits, whi

Claudio Bonanno, Massimo D'Elia, Biagio Lucini, Davide Vadacchino

In commonly used Monte Carlo algorithms for lattice gauge theories the integrated autocorrelation time of the topological charge is known to be exponentially-growing as the continuum limit is approached. This $\mathit{topological}\,\,\textit{freezing}$, whose severity increases with the size of the gauge group, can result in potentially large systematics. To

Filippo Pascucci, Sara Conti, David Neilson, Jacques Tempere

We investigate a Josephson junction in an electron-hole superfluid in a double layer TMD heterostructure. Observation of a critical tunneling current is a clear signature of superfluidity. In addition, we find the BCS-BEC crossover physics in the narrow barrier region controls the critical current across the entire system. The corresponding critical velocity

Maximilian Prüfer, Daniel Spitz, Stefan Lannig, Helmut Strobel

The extensive control of spin makes spintronics a promising candidate for future scalable quantum devices. For the generation of spin-superfluid systems, a detailed understanding of the build-up of coherence and relaxation is necessary. However, to determine the relevant parameters for robust coherence properties and faithfully witnessing thermalization, the

Mingyu Yang, Yu Chen, Hun-Seok Kim

In recent years, deep learning-based approaches for visual-inertial odometry (VIO) have shown remarkable performance outperforming traditional geometric methods. Yet, all existing methods use both the visual and inertial measurements for every pose estimation incurring potential computational redundancy. While visual data processing is much more expensive th

E. Pancino, P. M. Marrese, S. Marinoni, N. Sanna

(Shortened). In the era of large surveys and space missions, it is necessary to rely on large samples of well-characterized stars for inter-calibrating and comparing measurements from different sources. Among the most employed photometric systems, the Johnson-Kron-Cousins has been used for decades and for a large amount of important datasets. Using Gaia DR3

Henry Fallet

Ginzburg, Guay, Opdam and Rouquier established an equivalence of categories between a quotient category of the category $\mathcal{O}$ for the rational Cherednik algebra and the category of finite dimension modules of the Hecke algebra of a complex reflection group $W$. We establish two generalizations of this result. On the one hand to the extension of the H

Imed Basdouri, Mohamed Fadous, Sami Mabrouk, Abdenacer Makhlouf

We introduce the notion of Poisson superbialgebra as an analogue of Drinfeld's Lie superbialgebras. We extend various known constructions dealing with representations on Lie superbialgebras to Poisson superbialgebras. We introduce the notions of Manin triple of Poisson superalgebras and Poisson superbialgebras and show the equivalence between them in terms o

Florian Munkelt

Let $\mathscr{M}$ be a compact submanifold of $\mathbb{R}^{M}$. In this article we establish an asymptotic formula for the number of rational points within a given distance to $\mathscr{M}$ and with bounded denominators under the assumption that $\mathscr{M}$ fulfills a certain curvature condition. Our result generalizes earlier work from Schindler and Yamag

Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo

Inspired by progress in large-scale language modeling, we apply a similar approach towards building a single generalist agent beyond the realm of text outputs. The agent, which we refer to as Gato, works as a multi-modal, multi-task, multi-embodiment generalist policy. The same network with the same weights can play Atari, caption images, chat, stack blocks

Fabio Ancona, Laura Caravenna, Cleopatra Christoforou

We consider a $2\times 2$ system of hyperbolic balance laws, in one-space dimension, that describes the evolution of a granular material with slow erosion and deposition. The dynamics is expressed in terms of the thickness of a moving layer on top and of a standing layer at the bottom. The system is linearly degenerate along two straight lines in the phase p

Tuna Altınel, Joshua Wiscons

We investigate faithful representations of $\operatorname{Alt}(n)$ as automorphisms of a connected group $G$ of finite Morley rank. We target a lower bound of $n$ on the rank of such a nonsolvable $G$, and our main result achieves this in the case when $G$ is without involutions. In the course of our analysis, we also prove a corresponding bound for solvable

Alejandro Gomez-Leos, Anoosheh Heidarzadeh

This paper introduces a generalization of the Private Information Retrieval with Side Information (PIR-SI) problem called Popularity-Aware PIR-SI (PA-PIR-SI). The PA-PIR-SI problem includes one or more remote servers storing copies of a dataset of $K$ messages, and a user who knows $M$ out of $K$ messages -- the identities of which are unknown to the server

M. A. Bubenchikov, D. S. Kaparulin, O. D. Nosyrev

We consider a statistical mechanics of rotating ideal gas consisting of classical non-relativistic spinning particles. The microscopic structure elements of the system are massive point particles with a nonzero proper angular momentum. The norm of proper angular momentum is determined by spin. The direction of proper angular momentum changes continuously. Ap

A. A. Mazanik, Ya. V. Fominov

We study the density of states (DoS) $\nu(E)$ in a normal-metallic (N) film contacted by a bulk superconductor (S). We assume that the system is diffusive and the SN interface is transparent. In the limit of thin N layer (compared to the coherence length), we analytically find three different types of the DoS peculiarity at energy equal to the bulk supercond

Xu-Jia Ouyang, Yong Zhang, Albert Zijlstra, Chuan-Peng Zhang

Using the Five-hundred-meter Aperture Spherical radio Telescope (FAST) in Guizhou, China, we detect the 21cm neutral atomic hydrogen absorption in the young planetary nebula IC 4997. The absorption arises from a shell also associated with Na I D lines. The H I shell has a mass of $1.46\times10^{-2}$ M$_\odot$ and a dynamic age of 990yr. The column density of

Nils Heyer, Christian Glaser

The detection of high-energy neutrinos in the EeV range requires new detection techniques to cope with the small expected flux. The radio detection method, utilizing Askaryan emission, can be used to detect these neutrinos in polar ice. The propagation of the radio pulses has to be modeled carefully to reconstruct the energy, direction, and flavor of the neu

Stefania Preda, Guy Emerson

In this work, we explore the novel idea of employing dependency parsing information in the context of few-shot learning, the task of learning the meaning of a rare word based on a limited amount of context sentences. Firstly, we use dependency-based word embedding models as background spaces for few-shot learning. Secondly, we introduce two few-shot learning

Deeksha Adil, Brian Bullins, Arun Jambulapati, Sushant Sachdeva

In this work, we present new simple and optimal algorithms for solving the variational inequality (VI) problem for $p^{th}$-order smooth, monotone operators -- a problem that generalizes convex optimization and saddle-point problems. Recent works (Bullins and Lai (2020), Lin and Jordan (2021), Jiang and Mokhtari (2022)) present methods that achieve a rate of

Xiao Liu, Heyan Huang, Ge Shi, Bo Wang

We consider event extraction in a generative manner with template-based conditional generation. Although there is a rising trend of casting the task of event extraction as a sequence generation problem with prompts, these generation-based methods have two significant challenges, including using suboptimal prompts and static event type information. In this pa

Mateo Londoño, Julio C. Arce

We propose an optical control scheme for driving a polar molecule from a high-lying vibrational level to a target low-lying one, within the same electronic state. The scheme utilizes an infrared chirped laser pulse with an analytical shape, whose parameters are optimized by means of a heuristic formulation of quantum optimal control based on a genetic algori

G. Bouzerar

It is a well known fact, that the disorder has its most dramatic effects on the conventional quantum transport in one dimensional systems. In flat band (FB) systems, it is revealed that the conductivity at the FB energy is robust against the disorder and can even be tremendously boosted. Furthermore, challenging our understanding of the physical phenomena, t

David Bolin, Alexandre B. Simas, Jonas Wallin

We define a new class of Gaussian processes on compact metric graphs such as street or river networks. The proposed models, the Whittle--Mat\'ern fields, are defined via a fractional stochastic differential equation on the compact metric graph and are a natural extension of Gaussian fields with Mat\'ern covariance functions on Euclidean domains to the non-Eu

Ruowan Ji, Anoosheh Heidarzadeh, Krishna R. Narayanan

We introduce two generalizations to the paradigm of using Random Khatri-Rao Product (RKRP) codes for distributed matrix multiplication. We first introduce a class of codes called Sparse Random Khatri-Rao Product (SRKRP) codes which have sparse generator matrices. SRKRP codes result in lower encoding, computation and communication costs than RKRP codes when t

Samuel Baker, Pietro Biroli, Hans van Kippersluis, Stephanie von Hinke

Adverse conditions in early life can have consequential impacts on individuals' health in older age. In one of the first papers on this topic, Barker and Osmond 1986 show a strong positive relationship between infant mortality rates in the 1920s and ischaemic heart disease in the 1970s. We go 'beyond Barker', first by showing that this relationship is robust

Martin Khannouz, Tristan Glatard

Supervised learning algorithms generally assume the availability of enough memory to store their data model during the training and test phases. However, in the Internet of Things, this assumption is unrealistic when data comes in the form of infinite data streams, or when learning algorithms are deployed on devices with reduced amounts of memory. In this pa

Chirag Falor, Paul L. Schechter

The quadruple image configurations of gravitational lenses with vanishing ellipticity are examined. Even though such lenses asymptotically approach circularity, the configurations are stable if the position of the source relative to the vanishing diamond caustic is held constant. The configurations are the solutions of a quartic equation, an "Asymptotically

Maria A. Bravo, Sudhanshu Mittal, Thomas Brox

In this work, we propose an open-vocabulary object detection method that, based on image-caption pairs, learns to detect novel object classes along with a given set of known classes. It is a two-stage training approach that first uses a location-guided image-caption matching technique to learn class labels for both novel and known classes in a weakly-supervi

Nasim Soltani, Hai Cheng, Mauro Belgiovine, Yanyu Li

Orthogonal Frequency Division Multiplexing (OFDM)-based waveforms are used for communication links in many current and emerging Internet of Things (IoT) applications, including the latest WiFi standards. For such OFDM-based transceivers, many core physical layer functions related to channel estimation, demapping, and decoding are implemented for specific cho

Vladimir Fanaskov, Ivan Oseledets

We consider an automatic construction of locally optimal preconditioners for positive definite linear systems. To achieve this goal, we introduce a differentiable loss function that does not explicitly include the estimation of minimal eigenvalue. Nevertheless, the resulting optimization problem is equivalent to a direct minimization of the condition number.