August 2022 arXiv papers — page 83

Liuxian Zhao, Chuanxing Bi, Miao Yu

The ability to control and manipulate elastic waves is important for applications such as structural health monitoring, signal processing, and vibration isolations. In this paper, we investigated the feasibility of using the Rays Inserting Method, an approach originally proposed for optical elements, to design structural components for flexural wave manipula

Charbel Toumieh, Alain Lambert

In this paper, we propose a new method for multirotor planning in dynamic environments. The environment is represented as a temporal occupancy grid which gives the current as well as the future/predicted state of all the obstacles. The method builds on previous works in Safe Corridor generation and multirotor planning to avoid moving and static obstacles. It

Charbel Toumieh, Alain Lambert

In this paper, we propose a new framework for multi-agent collaborative exploration of unknown environments. The proposed method combines state-of-the-art algorithms in mapping, safe corridor generation and multi-agent planning. It first takes a volume that we want to explore, then proceeds to give the multiple agents different goals in order to explore a vo

Md Kamran Chowdhury Shisher, Yin Sun

In this paper, we analyze the impact of data freshness on real-time supervised learning, where a neural network is trained to infer a time-varying target (e.g., the position of the vehicle in front) based on features (e.g., video frames) observed at a sensing node (e.g., camera or lidar). One might expect that the performance of real-time supervised learning

Mahan Tabatabaie, James Maniscalco, Connor Lynch, Suining He

In this paper, we have proposed STC-GEF, a novel Spatio-Temporal Cross-platform Graph Embedding Fusion approach for the urban traffic flow prediction. We have designed a spatial embedding module based on graph convolutional networks (GCN) to extract the complex spatial features within traffic flow data. Furthermore, to capture the temporal dependencies betwe

Fangyi Yu, Miguel Vargas Martin

Honeywords are fictitious passwords inserted into databases in order to identify password breaches. The major difficulty is how to produce honeywords that are difficult to distinguish from real passwords. Although the generation of honeywords has been widely investigated in the past, the majority of existing research assumes attackers have no knowledge of th

Jessie Henshaw

Like all natural systems, great societies and their cultures emerge by a growth process from their environments, developing, organized, and behaving as wholes with their internal designs linked with their external worlds. So the general patterns of how growth produces both successful and failing new designs for new systems can be a great teacher of what does

Joaquin Delgado Fernandez, Tom Barbereau, Orestis Papageorgiou

With advancements in distributed ledger technologies and smart contracts, tokenized voting rights gained prominence within Decentralized Finance (DeFi). Voting rights tokens (aka. governance tokens) are fungible tokens that grant individual holders the right to vote upon the fate of a project. The motivation behind these tokens is to achieve decentral contro

Quadry Chance, Sarah Ballard, Keivan Stassun

The results of large-scale exoplanet transit surveys indicate that the distribution of small planet radii is likely sculpted by atmospheric loss. Several possible physical mechanisms exist for this loss of primordial atmospheres, each of which produces a different set of observational signatures. In this study, we investigate the impact-driven mode of atmosp

Mai Katada

The rational homology of the IA-automorphism group $\operatorname{IA}_n$ of the free group $F_n$ is still mysterious. We study the quotient of the rational homology of $\operatorname{IA}_n$ that is obtained as the image of the map induced by the abelianization map, which we call the Albanese homology of $\operatorname{IA}_n$. We obtain a representation-stabl

Hisham Sati, Urs Schreiber

In this book we prove unified classification results for equivariant principal bundles when the topological structure group is truncated. The conceptually transparent proof invokes a smooth Oka principle, which becomes available after faithfully embedding traditional equivariant topology into the singular-cohesive homotopy theory of globally equivariant high

Zihan Yin, Md Abdullah-Al Kaiser, Lamine Ousmane Camara, Mark Camarena

Neuromorphic image sensors draw inspiration from the biological retina to implement visual computations in electronic hardware. Gain control in phototransduction and temporal differentiation at the first retinal synapse inspired the first generation of neuromorphic sensors, but processing in downstream retinal circuits, much of which has been discovered in t

Wencai Liu

We discover that the distribution of (frequency and phase) resonances plays a role in determining the spectral type of supercritical quasi-periodic Schr\"odinger operators. In particular, we disprove the second spectral transition line conjecture of Jitomirskaya in the early 1990s.

Fangyi Yu, Miguel Vargas Martin

The security of passwords depends on a thorough understanding of the strategies used by attackers. Unfortunately, real-world adversaries use pragmatic guessing tactics like dictionary attacks, which are difficult to simulate in password security research. Dictionary attacks must be carefully configured and modified to represent an actual threat. This approac

Lucas H. R. de Souza

In this paper we prove that if some relatively hyperbolic groups have Bowditch boundary homeomorphic to the $n$-sphere, then they are also relatively hyperbolic with respect to another set of parabolic subgroups and its Bowditch boundary is homeomorphic to the $n-1$-dimensional Sierpi\'nski carpet.

Di Fang, Lin Lin, Yu Tong

The time-marching strategy, which propagates the solution from one time step to the next, is a natural strategy for solving time-dependent differential equations on classical computers, as well as for solving the Hamiltonian simulation problem on quantum computers. For more general linear differential equations, a time-marching based quantum solver can suffe

Terence Kevin Manfoumbi Djonguet, Guy Martial Nkiet

This work investigates the problem of testing whether $d$ functional random variables are jointly independent using a modified estimator of the $d$-variable Hilbert Schmidt Indepedence Criterion ($d$HSIC) which generalizes HSIC for the case where $d \geq 2$. We then get asymptotic normality of this estimator both under joint independence hypothesis and under

Sam P. Vaughan, Tania M. Barone, Scott M. Croom, Luca Cortese

In this work, we investigate how the central stellar metallicity ([Z/H]) of 1363 galaxies from the SAMI galaxy survey is related to their stellar mass and a proxy for the gravitational potential, $\Phi$ = log10(M/M*) - log10($r_e$/kpc). In agreement with previous studies, we find that passive and star-forming galaxies occupy different areas of the [Z/H]-M* p

Jason Bell, Dragos Ghioca, Zinovy Reichstein

Let $G$ be a semiabelian variety defined over an algebraically closed field $K$ of characteristic $0$. Let $\Phi\colon G\dashrightarrow G$ be a dominant rational self-map. Assume that an iterate $\Phi^m \colon G \to G$ is regular for some $m \geqslant 1$ and that there exists no non-constant homomorphism $\tau: G\to G_0$ of semiabelian varieties such that $\

C. Wei, S. H. Curnoe

We find exact solutions to the Hamiltonian of a 16-site spin-1/2 pyrochlore crystal with nearest neighbour exchange interactions. The methods of group theory (symmetry) are used to completely block-diagonalize the Hamiltonian, yielding precise details about symmetry of the eigenstates, in particular those components which are {\em spin ice} states, in order

Akshansh Mishra, Anish Dasgupta

The subject area known as computational neuroscience involves the investigation of brain function using mathematical techniques and theories. In order to comprehend how the brain processes information, it can also include various methods from signal processing, computer science, and physics. In the present work, for the first time a neurobiological based uns

Sophia Althammer, Sebastian Hofstätter, Suzan Verberne, Allan Hanbury

Robust test collections are crucial for Information Retrieval research. Recently there is a growing interest in evaluating retrieval systems for domain-specific retrieval tasks, however these tasks often lack a reliable test collection with human-annotated relevance assessments following the Cranfield paradigm. In the medical domain, the TripClick collection

Ehsan Mokhtarian, Mohammadsadegh Khorasani, Jalal Etesami, Negar Kiyavash

We propose ordering-based approaches for learning the maximal ancestral graph (MAG) of a structural equation model (SEM) up to its Markov equivalence class (MEC) in the presence of unobserved variables. Existing ordering-based methods in the literature recover a graph through learning a causal order (c-order). We advocate for a novel order called removable o

Martin Chuaqui, Rodrigo Hernández

We study classes of locally biholomorphic mappings defined in the $\P$ that have bounded Schwarzian operator in the Bergman metric. We establish important properties of specific solutions of the associated system of differential equations and show a geometric connection between the order of the classes and a covering property. We show for modified and slight

Siyan Dong, Shuzhe Wang, Yixin Zhuang, Juho Kannala

Visual (re)localization addresses the problem of estimating the 6-DoF (Degree of Freedom) camera pose of a query image captured in a known scene, which is a key building block of many computer vision and robotics applications. Recent advances in structure-based localization solve this problem by memorizing the mapping from image pixels to scene coordinates w

Mohamed Omar

We introduce a universal approach for applying the partition rank method, an extension of Tao's slice rank polynomial method, to tensors that are not diagonal. This is accomplished by generalizing Naslund's distinctness indicator to what we call a partition indicator. The advantages of partition indicators are two-fold: they diagonalize tensors that are cons

Diana Benavides-Prado, Patricia Riddle

Continual learning of a stream of tasks is an active area in deep neural networks. The main challenge investigated has been the phenomenon of catastrophic forgetting or interference of newly acquired knowledge with knowledge from previous tasks. Recent work has investigated forward knowledge transfer to new tasks. Backward transfer for improving knowledge ga

Amine Ouazad

Measuring beliefs about natural disasters is challenging. Deep out-of-the-money options allow investors to hedge at a range of strikes and time horizons, thus the 3-dimensional surface of firm-level option prices provides information on (i) skewed and fat-tailed beliefs about the impact of natural disaster risk across space and time dimensions at daily frequ

Alfred Dolich, John Goodrick

We study the structure of infinite discrete sets D definable in expansions of ordered Abelian groups whose theories are strong and definably complete, with particular emphasis on the set D' comprised of differences between successive elements. In particular, if the burden of the structure is at most n, then the result of applying the operation taking D to D'

Haoying Wang, Rafael Garduno Rivera

With the recent administration change in Mexico, the fluctuations in national energy policy have generated widespread concerns among investors and the public. The debate centers around Mexico's energy dependence on the US and how Mexico's energy development should move forward. The goal of this study is two-fold. We first review the history and background of

Bhavana Doppalapudi, Bei Wang, Paul Rosen

Force-directed layouts belong to a popular class of methods used to position nodes in a node-link diagram. However, they typically lack direct consideration of global structures, which can result in visual clutter and the overlap of unrelated structures. In this paper, we use the principles of persistent homology to untangle force-directed layouts thus mitig

T. Bulmus, Y. Pehlivan

We study the phase effects driven by neutrino magnetic moment for Majorana neutrinos in a core collapse supernova. A neutrino with a large magnetic moment is emitted in a superposition of energy eigenstates from the neutrinosphere. These energy eigenstates can interfere to create a phase effect at a partially adiabatic spin flavor precession (SFP) resonance.

Fabijan Pavošević, Robert L. Smith, Angel Rubio

Achieving control over chemical reaction's rate and stereoselectivity realizes one of the Holy Grails in chemistry that can revolutionize chemical and pharmaceutical industries. Strong light-matter interaction in optical or nanoplasmonic cavities might provide the knob to reach such control. In this work, we demonstrate the catalytic and selectivity control

Maxwell J D Ramstead, Dalton A R Sakthivadivel, Karl J Friston

This paper presents a meta-theory of the usage of the free energy principle (FEP) and examines its scope in the modelling of physical systems. We consider the so-called `map-territory fallacy' and the fallacious reification of model properties. By showing that the FEP is a consistent, physics-inspired theory of inferences of inferences, we disprove the asser

Stefan Hiemer, Paolo Moretti, Stefano Zapperi, Michael Zaiser

Spatial and temporal features are studied with respect to their predictive value for failure time prediction in subcritical failure with machine learning (ML). Data are generated from simulations of a novel, brittle random fuse model (RFM), as well as elasto-plastic finite element simulations (FEM) of a stochastic plasticity model with damage, both models co

Peng Gao, Liangyi Zhao

We establish lower bounds for the discrete $2k$-th moment of the derivative of the Riemann zeta function at nontrivial zeros for all $k<0$ under the Riemann hypothesis (RH) and the assumption that all zeros of $\zeta(s)$ are simple.

Emmanuel Lecouturier, Jun Wang

Sharifi has constructed a map from the first homology of the modular curve $X_1(M)$ to the $K$-group $K_2(\mathbf{Z}[\zeta_M, \frac{1}{M}])$, where $\zeta_M$ is a primitive $M$th root of unity. We study how these maps relate when $M$ varies. Our method relies on the techniques developed by Sharifi and Venkatesh.

Çağatay Demirel, Livia Reguş, Hatice Köse

There have been many studies on intelligent robotic systems for patients with motor impairments, where different sensor types and different human-machine interface (HMI) methods have been developed. However, these studies fail to achieve complex activity detection at the minimum sensing level. In this paper, exploratory approaches are adopted to investigate

Y. I. Akakpo, M. N. Hounkonnou, K. Enakoutsa, V. S. K. Assiamoua

This work addresses an extension of Fourier-Stieltjes transform of a vector measure defined on compact groups to locally compact groups, by using a group representation induced by a representation of one of its compact subgroups.

A. Margiotta

KM3NeT is a research infrastructure in construction under the Mediterranean Sea. It hosts two large volume neutrino Cherenkov telescopes: ARCA at a depth of 3500 m, located offshore Sicily, and ORCA, 2500 m under the sea level, offshore the southern French coast. The two detectors share the same detection principle and technology and the same data acquisitio

Lei Jiang, Yongqing Liu, Shihai Xiao, Yansong Chua

Lateral inhibitory connections have been observed in the cortex of the biological brain, and has been extensively studied in terms of its role in cognitive functions. However, in the vanilla version of backpropagation in deep learning, all gradients (which can be understood to comprise of both signal and noise gradients) flow through the network during weigh

Chao Feng, Jui Po Hung, Aishan Li, Jieping Yang

Diabetic Retinopathy (DR) has become one of the leading causes of vision impairment in working-aged people and is a severe problem worldwide. However, most of the works ignored the ordinal information of labels. In this project, we propose a novel design MTCSNN, a Multi-task Clinical Siamese Neural Network for Diabetic Retinopathy severity prediction task. T

Pankaj Kumar Kalita, Miriyala Jeevan Kumar, Subhajit Roy

Attribute grammars allow the association of semantic actions to the production rules in context-free grammars, providing a simple yet effective formalism to define the semantics of a language. However, drafting the semantic actions can be tricky and a large drain on developer time. In this work, we propose a synthesis methodology to automatically infer the s

Jozef Marus Coldenhoff, Chengkun Li, Yurui Zhu

Sharpness-Aware Minimization (SAM) and adaptive sharpness-aware minimization (ASAM) aim to improve the model generalization. And in this project, we proposed three experiments to valid their generalization from the sharpness aware perspective. And our experiments show that sharpness aware-based optimization techniques could help to provide models with strong

Michel Gaspar, Stefan Geschke

In this work, we continue the tradition initiated by Geschke, 2011 of viewing the uncountable Borel chromatic number of analytic graphs as cardinal invariants of the continuum. We show that various uncountable Borel chromatic numbers of closed graphs can be consistently different, as well as consistently equal to the continuum. This is done using arguments t

A. Marin, O. Ianc, T. O. Cheche

Two point charges are placed in a spherical dielectric core-shell embedded in a dielectric environment, one of the charges being located in the core and the other in the shell. The core, shell, and environment are characterized by different dielectric constants. Analytical solutions for the electrostatic energy of the system and the polarization charge densi

Ming Yuan, Qian Xu, Liang Jiang

Fault-tolerant quantum computation with depolarization error often requires demanding error threshold and resource overhead. If the operations can maintain high noise bias -- dominated by dephasing error with small bit-flip error -- we can achieve hardware-efficient fault-tolerant quantum computation with a more favorable error threshold. Distinct from two-l

Jamie Bishop, Rebekah Kuss, Benjamin Peet

This paper begins by exploring some old and new results about Ramsey numbers and minimum numbers of monochromatic triangles in $2$-colorings of complete graphs, both in the disjoint and non-disjoint cases. We then extend the theory, by defining line $2$-colorings of configurations of points and lines and considering the minimum number of non-disjoint monochr

Marcus Benghi Pinto

Considering the NJL model with a repulsive vector channel, parametrized by $G_V$, I show that one may generate a non-monotonic behavior for the speed of sound which peaks at $V_s^2 > 1/3$. This can be achieved by assuming $G_V$ to be density dependent so that the resulting EoS is stiff/repulsive at low densities and soft/non-repulsive at high densities. The

Z. J. Weiss, A. R. Massih

Starting from the hamiltonian for the Heisenberg ferromagnet which comprise randomly distributed nonmagnetic ions as impurities in a Bravais lattice, we express the spin operators by means of the Dyson-Maleev transformation in terms of the Bose operators of the second quantization. Then by using methods of quantum statistical field theory, we derive the part

Sami Boulebnane, Ashley Montanaro

The quantum approximate optimization algorithm (QAOA) is one of the most prominent proposed applications for near-term quantum computing. Here we study the ability of QAOA to solve hard constraint satisfaction problems, as opposed to optimization problems. We focus on the fundamental boolean satisfiability problem, in the form of random $k$-SAT. We develop a

Matteo Puccioni, Marc Calaf, Eric R. Pardyjak, Sebastian Hoch

Recent works on wall-bounded flows have corroborated the coexistence of wall-attached eddies, whose statistical features are predicted through Townsend's attached eddy hypothesis (AEH), and very-large-scale motions (VLSMs), which are not encompassed in the AEH. Furthermore, it has been shown that the presence of wall-attached eddies within the logarithmic la

Wesley H. Holliday, Chase Norman, Eric Pacuit, Saam Zahedian

A fundamental principle of individual rational choice is Sen's $\gamma$ axiom, also known as expansion consistency, stating that any alternative chosen from each of two menus must be chosen from the union of the menus. Expansion consistency can also be formulated in the setting of social choice. In voting theory, it states that any candidate chosen from two

Ernest Davis

Drori et al. (2022) report that "A neural network solves, explains, and generates university math problems by program synthesis and few-shot learning at human level ... [It] automatically answers 81\% of university-level mathematics problems." The system they describe is indeed impressive; however, the above description is very much overstated. The work of s

Camron Farhang, Nader Zaki, Jingyuan Wang, Genda Gu

Recently evidence has emerged in the topological superconductor Fe-chalcogenide FeTe1-xSex for time-reversal symmetry breaking (TRSB), the nature of which has strong implications on the Majorana zero modes (MZM) discovered in this system. It remains unclear however whether the TRSB resides in the topological surface state (TSS) or in the bulk, and whether it

Meirav Pinkas, Or Katz, Jonathan Wengrowicz, Nitzan Akerman

Pairs of free particles cannot form bound states in elastic collision due to momentum and energy conservation. In many ultracold experiments, however, the particles collide in the presence of an external trapping potential which can couple the center-of-mass and relative motions and assist the formation of bound-states. Here, we report on observation of weak

Mohammadreza Sabzehali, Somayeh Davoodabadi Farahani, Amir Mosavi

In this study, the effect of inlet air cooling and fuel type on the performance parameters of thrust-specific fuel consumption (TSFC), thermal and exergetic efficiencies, entropy generation rate, and Nitrogen oxide emission intensity index (SNOx) of the GENX 1B70 engine is analyzed in two states of take-off and on design. The results show that with a 20-degr

Mahdi Godazgar, C. N. Pope, A. Saha, Haoyu Zhang

Motivated by the results of Anastasiou et al., we consider the convolutional double copy for BRST and anti-BRST covariant formulations of gravitational and gauge theories in more detail. We give a general BRST and anti-BRST invariant formulation of linearised $\mathcal{N}=0$ supergravity using superspace methods and show how this may be obtained from the squ

Ivan Carvalho

We introduce a new sorting algorithm that is the combination of ML-enhanced sorting with the In-place Super Scalar Sample Sort (IPS4o). The main contribution of our work is to achieve parallel ML-enhanced sorting, as previous algorithms were limited to sequential implementations. We introduce the In-Place Parallel Learned Sort (IPLS) algorithm and compare it

Seongyeon Kim

In this paper, we investigate the dichotomous behavior of solutions to the Kawahara equation with bounded variation initial data, analogous to the Talbot effect. Specifically, we observe that the solution is quantized at rational times, whereas at irrational times, it is a nowhere continuous differentiable function with a fractal profile. This phenomenon, ho

Nathan Lutes, Venkata Sriram Siddhardh Nadendla, K. Krishnamurthy

Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connections in biological systems and produce spike trains, which can be approximated by binary values for computational efficiency. Recently, the addition of convolutional layers to combine the feature extraction power of convolutional networks with the computationa

Marie-No\''elle Célérier

This article belongs to a series where the influence of anisotropic pressure on the gravitational properties of rigidly rotating fluids is studied using new exactsolutions of GR constructed for the purpose. For mathematical simplification, stationarity and cylindrical symmetry implying three Killing vectors are considered. Moreover, two pressure components a

Rong-Chun Ge, Saeed Rahmanian Koshkaki, Michael H. Kolodrubetz

In this manuscript, we explore the feasibility of achieving many-body localization in the context of cavity quantum electrodynamics at strong coupling. Working with a spinless electronic Hubbard chain sitting coupled to a single-mode cavity, we show that the global coupling between electrons and photons -- which generally would be expected to delocalize the

Henrik Wyschka, Martin Siebenborn

We present an extension of an algorithm for the classical scalar $p$-Laplace Dirichlet problem to the vector-valued $p$-Laplacian with mixed boundary conditions in order to solve problems occurring in shape optimization using a $p$-harmonic approach. The main advantage of the proposed method is that no iteration over the order $p$ is required and thus allow

Terence L. J. Harris

Let $\gamma: I \to S^2$ be a $C^2$ curve with $\det(\gamma, \gamma', \gamma'')$ nonvanishing, and for each $\theta \in I$ let $\rho_{\theta}$ be orthogonal projection onto the span of $\gamma(\theta)$. It is shown that if $A \subseteq \mathbb{R}^3$ is a Borel set of Hausdorff dimension strictly greater than 1, then $\rho_{\theta}(A)$ has positive length for

Thomas E. Ouldridge, David H. Wolpert

Real-world computers have operational constraints that cause nonzero entropy production (EP). In particular, almost all real-world computers are ``periodic'', iteratively undergoing the same physical process; and ``local", in that subsystems evolve whilst physically decoupled from the rest of the computer. These constraints are so universal because decomposi

Brenda Praggastis, Davis Brown, Carlos Ortiz Marrero, Emilie Purvine

Deep neural networks used for image classification often use convolutional filters to extract distinguishing features before passing them to a linear classifier. Most interpretability literature focuses on providing semantic meaning to convolutional filters to explain a model's reasoning process and confirm its use of relevant information from the input doma

Manali Malakar, Sudip Sinha, S. Sinha

We study the finite temperature phases and collective excitations of hardcore as well as softcore bosons on a square lattice with nearest and next nearest neighbor interactions, focusing on the formation of various types of supersolid (SS) phases and their stability under thermal fluctuations. The interplay between the on-site, nearest, and next nearest neig

Jiawei Yang

Polymer brushes can grow on almost any solid surface, and by design, exhibit diverse properties and functionalities, thus they have been widely used in many emerging applications in engineering, energy, and medicine. In particular, some applications such as actuation, molecule release, and friction switch require the polymer brushes to change their heights b

Cui-Qun Chen, Xiao-Sheng Ni, Dao-Xin Yao, Yusheng Hou

Two-dimensional (2D) magnetic materials with nontrivial topological states have drawn considerable attention recently. Among them, 2D metal-organic frameworks (MOFs) are standing out due to their advantages, such as the easy synthesis in practice and less sensitivity to oxidation that are distinctly different from inorganic materials. By means of density-fun

David Lindemann

We classify all special homogeneous curves. A special homogeneous curve $\mathcal{H}$ consists of connected components of the hyperbolic points in the level set $\{h=1\}$ of a homogeneous polynomial $h$ in two real variables of degree at least three, and admits a transitive group action of a subgroup $G\subset\mathrm{GL}(2)$ on $\mathcal{H}$ that acts via li

Anton S. Kupriianov, Volodymyr I. Fesenko, Andrey B. Evlyukhin, Wei Han

Progress in developing advanced photonic devices relies on introducing new materials, discovered physical principles, and optimal designs when constructing their components. Optical systems operating on the principles of excitation of extremely high-quality factor trapped modes (also known as the bound states in the continuum, BICs) are of great interest sin

Mubashir Noman, Wafa Al Ghallabi, Daniya Najiha, Christoph Mayer

One of the key factors behind the recent success in visual tracking is the availability of dedicated benchmarks. While being greatly benefiting to the tracking research, existing benchmarks do not pose the same difficulty as before with recent trackers achieving higher performance mainly due to (i) the introduction of more sophisticated transformers-based me

Saikat Banerjee, Shi-Zeng Lin

Unambiguous identification of the Kitaev quantum spin liquid (QSL) in materials remains a huge challenge despite many encouraging signs from various measurements. To facilitate the experimental detection of the Kitaev QSL, here we propose to use remnant charge response in Mott insulators hosting QSL to identify the key signatures of QSL. We predict an emerge

Adam Bartoš, Wiesław Kubiś

We characterize the pseudo-arc as well as P-adic pseudo-solenoids (for a set of primes P) as generic structures, arising from a natural game in which two players alternate in building an inverse sequence of surjections. The second player wins if the limit of this sequence is homeomorphic to a concrete (fixed in advance) space, called generic whenever the sec

Gang He, Shaoyi Long, Li Xu, Chang Wu

Joint super-resolution and inverse tone-mapping (SR-ITM) aims to enhance the visual quality of videos that have quality deficiencies in resolution and dynamic range. This problem arises when using 4K high dynamic range (HDR) TVs to watch a low-resolution standard dynamic range (LR SDR) video. Previous methods that rely on learning local information typically

Hengrui Zhu, Daniel Baker, Ue-Li Pen, Dan R. Stinebring

In extreme scattering events, the brightness of a compact radio source drops significantly, as light is refracted out of the line of sight by foreground plasma lenses. Despite recent efforts, the nature of these lenses has remained a puzzle, because any roughly round lens would be so highly overpressurized relative to the interstellar medium that it could on

Chenxi Sun, Moxian Song, Derun Can, Baofeng Zhang

In the real world, the class of a time series is usually labeled at the final time, but many applications require to classify time series at every time point. e.g. the outcome of a critical patient is only determined at the end, but he should be diagnosed at all times for timely treatment. Thus, we propose a new concept: Continuous Classification of Time Ser

Manny Ko, Ujjawal K. Panchal, Héctor Andrade-Loarca, Andres Mendez-Vazquez

In a hybrid neural network, the expensive convolutional layers are replaced by a non-trainable fixed transform with a great reduction in parameters. In previous works, good results were obtained by replacing the convolutions with wavelets. However, wavelet based hybrid network inherited wavelet's lack of vanishing moments along curves and its axis-bias. We p

Marouan Mizmizi, Dario Tagliaferri, Misagh Khosronejad, Laura Resteghini

Intelligent reflecting surfaces (IRS) will represent a key technology in the upcoming sixth-generation (6G) communication networks to extend the network coverage and overcome link blockage. Research on IRS is expected to take a giant leap in the coming years to address the current technological limitations, mainly regarding the IRS re-configuration in highly

Chenjian Gao, Qian Yu, Lu Sheng, Yi-Zhe Song

Reconstructing a 3D shape based on a single sketch image is challenging due to the large domain gap between a sparse, irregular sketch and a regular, dense 3D shape. Existing works try to employ the global feature extracted from sketch to directly predict the 3D coordinates, but they usually suffer from losing fine details that are not faithful to the input

Christoph Benzmüller, David Fuenmayor, Alexander Steen, Geoff Sutcliffe

This paper reports on an exploration of Boolos' Curious Inference, using higher-order automated theorem provers (ATPs). Surprisingly, only suitable shorthand notations had to be provided by hand for ATPs to find a short proof. The higher-order lemmas required for constructing a short proof are automatically discovered by the ATPs. Given the observations and

Abhimanyu Sethia, Aayush

Much like most of cognition research, music cognition is an interdisciplinary field, which attempts to apply methods of cognitive science (neurological, computational and experimental) to understand the perception and process of composition of music. In this paper, we first motivate why music is relevant to cognitive scientists and give an overview of the ap

Christopher J. Geoga, Michael L. Stein

A common approach to approximating Gaussian log-likelihoods at scale exploits the fact that precision matrices can be well-approximated by sparse matrices in some circumstances. This strategy is motivated by the \emph{screening effect}, which refers to the phenomenon in which the linear prediction of a process $Z$ at a point $\mathbf{x}_0$ depends primarily

Li Fan, Jianchang Liu, Wenle Zhang, Peng Xu

Navigation functions provide both path and motion planning, which can be used to ensure obstacle avoidance and convergence in the sphere world. When dealing with complex and realistic scenarios, constructing a transformation to the sphere world is essential and, at the same time, challenging. This work proposes a novel transformation termed the conformal nav

Wenyan Liu, Juncheng Wan, Xiaoling Wang, Weinan Zhang

Users of a recommender system may want part of their data being deleted, not only from the data repository but also from the underlying machine learning model, for privacy or utility reasons. Such right-to-be-forgotten requests could be fulfilled by simply retraining the recommendation model from scratch, but that would be too slow and too expensive in pract

Hossam Amer, Young Jin Kim, Mohamed Afify, Hitokazu Matsushita

Multilingual Neural Machine Translation has been showing great success using transformer models. Deploying these models is challenging because they usually require large vocabulary (vocab) sizes for various languages. This limits the speed of predicting the output tokens in the last vocab projection layer. To alleviate these challenges, this paper proposes a

Roberta Musina, Alexander I. Nazarov

We relate non integer powers ${\mathcal L}^{s}$, $s>0$ of a given (unbounded) positive self-adjoint operator $\mathcal L$ in a real separable Hilbert space $\mathcal H$ with a certain differential operator of order $2\lceil{s}\rceil$, acting on even curves $\mathbb R\to \mathcal H$. This extends the results by Caffarelli--Silvestre and Stinga--Torrea regardi

Kohei Inayoshi, Yuichi Harikane, Akio K. Inoue, Wenxiu Li

Early results of JWST observations have delivered bright $z\gtrsim 10$ galaxy candidates in greater numbers than expected, enabling construction of the rest-frame UV luminosity functions (LFs). The LFs contain key information on the galaxy assembly history, star formation activity, and stellar population in the distant universe. Given an upper bound of the t

Chinedu Izuchukwu, Simeon Reich, Yekini Shehu, Adeolu Taiwo

In this paper, we propose and study several strongly convergent versions of the forward-reflected-backward splitting method of Malitsky and Tam for finding a zero of the sum of two monotone operators in a real Hilbert space. Our proposed methods only require one forward evaluation of the single-valued operator and one backward evaluation of the set-valued op

Rizqi Hersyandika, Yang Miao, Sofie Pollin

Human blockage is one of the main challenges for mmWave communication networks in dynamic environments. The shadowing by a human body results in significant received power degradation and could occur abruptly and frequently. A shadowing period of hundred milliseconds might interrupt the communication and cause significant data loss, considering the huge band

Hiranmaya Mishra, Prasanta K. Panigrahi, Sudhanwa Patra, Utpal Sarkar

With the recent findings from various astrophysical results hinting towards possible existence of strange quark matters with the baryonic resonances such as $\Lambda^0, \Sigma^0, \Xi, \Omega$ in the core of neutron stars, we investigate the MSW effect, in general, in quark matter. We find that the resonance condition for the complete conversion of down-quark

Jaime Céspedes-Sisniega, Álvaro López-García

Frouros is an open-source Python library capable of detecting drift in machine learning systems. It provides a combination of classical and more recent algorithms for drift detection: both concept and data drift. We have designed it with the objective of making it compatible with any machine learning framework and easily adaptable to real-world use cases. Th

Stephan Simonis, Mathias J. Krause

We establish the notion of limit consistency as a modular part in proving the consistency of lattice Boltzmann equations (LBEs) with respect to a given partial differential equation (PDE) system. The incompressible Navier--Stokes equations (NSE) are used as paragon. Based upon the hydrodynamic limit of the Bhatnagar--Gross--Krook (BGK) Boltzmann equation tow

Chengyin Xu, Zenghao Chai, Zhengzhuo Xu, Chun Yuan

Image retrieval has become an increasingly appealing technique with broad multimedia application prospects, where deep hashing serves as the dominant branch towards low storage and efficient retrieval. In this paper, we carried out in-depth investigations on metric learning in deep hashing for establishing a powerful metric space in multi-label scenarios, wh

Sarah Eberle, Bastian Harrach

We deal with the reconstruction of inclusions in elastic bodies based on monotonicity methods and construct conditions under which a resolution for a given partition can be achieved. These conditions take into account the background error as well as the measurement noise. As a main result, this shows us that the resolution guarantees depend heavily on the La

Asif Ali, Syeda Rida Tahir, Muhammad Adnan

The spin-selective reflection to introduce chirality which can have a lot of applications in real life such as spectroscopy, optical setups, media industry etc. In this paper, a reflection based metasurface proposed to introduce the giant chiroptical effects at broadband visible and infrared (IR) regimes. The optimization and results of basic unit also terme

Amnon Neeman

In a striking 2019 article, Antieau, Gepner and Heller found {\it K--}theoretic obstructions to bounded t-structures. We will survey their work, as well as some progress since. The focus will be on the open problems that arise from this.

Anwesh Ray

Given an odd prime number $p$ and an imaginary quadratic field $K$, we establish a relationship between the $p$-rank of the class group of $K$, and the classical $\lambda$-invariant of the cyclotomic $\mathbb{Z}_p$-extension of $K$. Exploiting this relationship, we prove statistical results for the distribution of $\lambda$-invariants for imaginary quadratic

Kaushiki Mukherjee, Indranil Chakrabarty, Ganesh Mylavarapu

Linear n-local networks are compatible with quantum repeaters based entanglement distribution protocols. Different sources of imperfections such as error in entanglement generation, communication over noisy quantum channels and imperfections in measurements result in decay of quantumness across such networks. From practical perspectives it becomes imperative