December 2022 arXiv papers

Pedro A. Santos-Florez, Shinnosuke Hattori, Qiang Zhu

In recent years, certain molecular crystals have been reported to possess surprising flexibility by undergoing significant elastic or plastic deformation in response to mechanical loads. However, despite this experimental evidence, there currently exists no atomistic mechanism to explain the physical origin of this phenomenon from numerical simulations. In t

Rohit Kannan, Harsha Nagarajan, Deepjyoti Deka

We learn optimal instance-specific heuristics for the global minimization of nonconvex quadratically-constrained quadratic programs (QCQPs). Specifically, we consider partitioning-based convex mixed-integer programming relaxations for nonconvex QCQPs and propose the novel problem of strong partitioning to optimally partition variable domains without sacrific

Arash Ahmadian, Louis S. P. Liu, Yue Fei, Konstantinos N. Plataniotis

Differentiable Architecture Search (DARTS) has attracted considerable attention as a gradient-based neural architecture search method. Since the introduction of DARTS, there has been little work done on adapting the action space based on state-of-art architecture design principles for CNNs. In this work, we aim to address this gap by incrementally augmenting

Sebastian Czerwiński

A harmonious coloring of a $k$-uniform hypergraph $H$ is a vertex coloring such that no two vertices in the same edge have the same color, and each $k$-element subset of colors appears on at most one edge. The harmonious number $h(H)$ is the least number of colors needed for such a coloring. The paper contains a new proof of the upper bound $h(H)=O(\sqrt[k]{

Michael H. Freedman

This note initiates an investigation of packing links into a region of Euclidean space to achieve a maximal density subject to geometric constraints. The upper bounds obtained apply only to the class of homotopically essential links and even there seem extravagantly large, leaving much working room for the interested reader.

Marina Huerta, Guido van der Velde

We focus our attention on the one dimensional scalar theories that result from dimensionally reducing the free scalar field theory in arbitrary d dimensions. As is well known, after integrating out the angular coordinates, the free scalar theory can be expressed as an infinite sum of theories living in the semi-infinite line, labeled by the angular modes $\{

Markus Pelger, Jiacheng Zou

This paper proposes a novel testing procedure for selecting a sparse set of covariates that explains a large dimensional panel. Our selection method provides correct false detection control while having higher power than existing approaches. We develop the inferential theory for large panels with many covariates by combining post-selection inference with a n

Dean Wang

In this paper, we present a formal Fourier analysis (FA) of Picard iteration for the coupled neutronics/thermal hydraulics (N/TH) problem and derive theoretical predictions for the spectral radius of Picard iteration for such coupled calculations as a function of the temperature difference between the fuel and coolant, temperature coefficients of cross secti

Alexandru D. Ionescu, Sameer Iyer, Hao Jia

We give a proof of linear inviscid damping and vorticity depletion for non-monotonic shear flows with one critical point in a bounded periodic channel. In particular, we obtain quantitative depletion rates for the vorticity function without any symmetry assumptions.

Dean Wang

In this paper, we deal with the differential properties of the scalar flux defined over a two-dimensional bounded convex domain, as a solution to the integral radiation transfer equation. Estimates for the derivatives of the scalar flux near the boundary of the domain are given based on Vainikko's regularity theorem. A numerical example is presented to d

Emmanuel Hartman, Martin Bauer, Eric Klassen

The Square Root Normal Field (SRNF) framework is a method in the area of shape analysis that defines a (pseudo) distance between unparametrized surfaces. For piecewise linear (PL) surfaces it was recently proved that the SRNF distance between unparametrized surfaces is equivalent to the Wasserstein Fisher Rao (WFR) metric on the space of finitely supported m

G. Gandus, A. Jayaraj, D. Passerone, R. Stadler

Strongly correlated physics arises from electron-electron scattering within partially filled orbitals. Organic molecules in open-shell configurations are therefore good candidates to exhibit many-body effects. We focus on electron transport in a two-terminal single-molecule junction setup, in which the molecular bridge consists of an organic radical with a m

Mariam Zomorodi, Ismail Ghodsollahee, Jennifer H. Martin, Nicholas J. Talley

A comprehensive pharmaceutical recommendation system was designed based on the patients and drugs features extracted from Drugs.com and Druglib.com. First, data from these databases were combined, and a dataset of patients and drug information was built. Secondly, the patients and drugs were clustered, and then the recommendation was performed using differen

Dibyayan Chakraborty, Jérémie Chalopin, Florent Foucaud, Yann Vaxès

A set $S$ of isometric paths of a graph $G$ is ``$v$-rooted'', where $v$ is a vertex of $G$, if $v$ is one of the endpoints of all the isometric paths in $S$. The isometric path complexity of a graph $G$, denoted by $ipco{G}$, is the minimum integer $k$ such that there exists a vertex $v\in V(G)$ satisfying the following property: the vertices of any

Matias D. Cattaneo, Max H. Farrell, Michael Jansson, Ricardo Masini

The density weighted average derivative (DWAD) of a regression function is a canonical parameter of interest in economics. Classical first-order large sample distribution theory for kernel-based DWAD estimators relies on tuning parameter restrictions and model assumptions that imply an asymptotic linear representation of the point estimator. These conditions

Edward B. Baker

We show that a class of previously defined maps, called self-dual and causal morphisms, form classical symmetries of Yang-Mills fields in four complex dimensions. These maps generalize conformal transformations, and admit a nonlocal pullback connection that preserves the equations of the theory. First it is shown that self-dual morphisms form symmetries of t

Ana Laura Boscolo, Valdir Barbosa da Silva Junior, Luiz Antonio Barreiro

The problem of a bouncing ball on a non-planar surface is investigated. We discovered that surface undulation adds a horizontal component to the impact force, which acquires a random character. Some aspects of Brownian motion are found in the horizontal distribution of the particle. On the x-axis, normal and super diffusion are observed. For the probability

Peter Bürgisser

Consider a system $f_1(x)=0,\ldots,f_n(x)=0$ of $n$ random real polynomials in $n$ variables, where each $f_i$ has a prescribed set of exponent vectors described by a set $A_i \subseteq \mathbb{Z}^n$ of cardinality $t_i$, whose convex hull is denoted $P_i$. Assuming that the coefficients of the $f_i$ are independent standard Gaussian, we prove that the expec

Vladimir Sauli

We extract the spectral function of quarks using the QCD functional formalism.The reliability of approximations is controlled by the masses and decays of pseudoscalar mesons. For light quarks, we select the pion; for charm quarks, we choose the ground and excited states of the $η_c$ meson. To this end, we solved the ladder-rainbow approximation of the spectr

Meng-Chieh Lee, Shubhranshu Shekhar, Jaemin Yoo, Christos Faloutsos

Given a large graph with few node labels, how can we (a) identify whether there is generalized network-effects (GNE) or not, (b) estimate GNE to explain the interrelations among node classes, and (c) exploit GNE efficiently to improve the performance on downstream tasks? The knowledge of GNE is valuable for various tasks like node classification, and targete

Ali Abedi, Haofan Lu, Alex Chen, Charlie Liu

WiFi communication should be possible only between devices inside the same network. However, we find that all existing WiFi devices send back acknowledgments (ACK) to even fake packets received from unauthorized WiFi devices outside of their network. Moreover, we find that an unauthorized device can manipulate the power-saving mechanism of WiFi radios and ke

Brad Rodgers, Harshith Sai Vallabhaneni

We find closed formulas for arbitrarily high mixed moments of characteristic polynomials of the Alternative Circular Unitary Ensemble (ACUE), as well as closed formulas for the averages of ratios of characteristic polynomials in this ensemble. A comparison is made to analogous results for the Circular Unitary Ensemble (CUE). Both moments and ratios are studi

Eva Miranda, Arnau Planas

This monograph explores classification and perturbation problems for integrable systems on a class of Poisson manifolds called $b^m$-Poisson manifolds. Even if the class of $b^m$-Poisson manifolds is not ample enough to represent general Poisson manifolds, this investigation can be seen as a first step for the study of perturbation theory for general Poisson

Yuqi Fang, Pew-Thian Yap, Weili Lin, Hongtu Zhu

Unsupervised domain adaptation (UDA) via deep learning has attracted appealing attention for tackling domain-shift problems caused by distribution discrepancy across different domains. Existing UDA approaches highly depend on the accessibility of source domain data, which is usually limited in practical scenarios due to privacy protection, data storage and t

Kohei Suzuki

We construct a strongly local symmetric Dirichlet form on the configuration space $Υ$ whose symmetrising (thus also invariant) measure is $\mathsf{sine}_β$, which is the law of the sine $β$ ensemble for every $β>0$. For every $β>0$, this Dirichlet form satisfies the Bakry-Émery gradient estimate $\mathsf{BE}(K, \infty)$ with $K=0$. This implies various funct

Parakh M. Gupta, Eric Pairet, Tiago Nascimento, Martin Saska

Landing an unmanned aerial vehicle unmanned aerial vehicle (UAV) on top of an unmanned surface vehicle (USV) in harsh open waters is a challenging problem, owing to forces that can damage the UAV due to a severe roll and/or pitch angle of the USV during touchdown. To tackle this, we propose a novel model predictive control (MPC) approach enabling a UAV to la

Ido Kaplan, Muhammad Erew, Yonatan Piasetzky, Moshe Goldstein

Error mitigation schemes and error-correcting codes have been the center of much effort in quantum information processing research over the last few decades. While most of the successful proposed schemes for error mitigation are perturbative in the noise and assume deterministic systematic errors, studies of the problem considering the full noise and errors

Victor Y. Pan, Soo Go, Qi Luan, Liang Zhao

We approximate the d complex zeros of a univariate polynomial p(x) of a degree d or those zeros that lie in a fixed region of interest on the complex plane such as a disc or a square. Our divide and conquer algorithm of STOC 1995 supports solution of this problem in optimal Boolean time (up to a poly-logarithmic factor), that is, runs nearly as fast as one c

Maria Nareklishvili, Nicholas Polson, Vadim Sokolov

In this paper, we propose Forest-PLS, a feature selection method for analyzing policy effect heterogeneity in a more flexible and comprehensive manner than is typically available with conventional methods. In particular, our method is able to capture policy effect heterogeneity both within and across subgroups of the population defined by observable characte

Vladimir Markovic, Nathaniel Sagman

We establish the new main inequality as a minimizing criterion for minimal maps to products of $\mathbb{R}$-trees, and the infinitesimal new main inequality as a stability criterion for minimal maps to $\mathbb{R}^n$. Along the way, we develop a new perspective on destabilizing minimal surfaces in $\mathbb{R}^n$, and as a consequence we reprove the instabili

Henry Adams, Johnathan Bush, Nate Clause, Florian Frick

We explore emerging relationships between the Gromov--Hausdorff distance, Borsuk--Ulam theorems, and Vietoris--Rips simplicial complexes. The Gromov--Hausdorff distance between two metric spaces $X$ and~$Y$ can be lower bounded by the distortion of (possibly discontinuous) functions between them. The more these functions must distort the metrics, the larger

Grigorii Konovalov

This paper originated as an attempt to answer a question: what are the natural derived structures on Poisson degeneracy loci? We argue that the question could be possibly answered via a construction of differential graded operads that ``naturally'' act on the degeneracy loci. For each $m \ge 0$, we suggest what looks like a reasonable condition for a

Florian Kofler, Johannes Wahle, Ivan Ezhov, Sophia Wagner

Machine learning models are typically evaluated by computing similarity with reference annotations and trained by maximizing similarity with such. Especially in the biomedical domain, annotations are subjective and suffer from low inter- and intra-rater reliability. Since annotations only reflect one interpretation of the real world, this can lead to sub-opt

Abhishek Anand, Songyang Pu, G J Sreejith

A short-ranged, rotationally symmetric multi-Landau-level model Hamiltonian for strongly interacting electrons in a magnetic field was proposed [A. Anand et al, Phys. Rev. Lett. 126, 136601 (2021)] with the key feature that it allows exact many-body eigenfunctions on the disk not just for quasiholes but for all charged and neutral excitations of the entire J

Giacomo Zuccarini, Marisa Michelini

We describe the development of a course of quantum mechanics for secondary school designed to address the challenges related to the revision of classical knowledge, to the building of a well-organized knowledge structure on the discipline, and to the development of a plausible picture of the quantum world. The course is based on a systemic approach to concep

Isa E. Hafalir, Fuhito Kojima, M. Bumin Yenmez, Koji Yokote

We provide optimal solutions to an institution that has distributional objectives when choosing from a set of applications based on merit (or priority). For example, in college admissions, administrators may want to admit a diverse class in addition to choosing students with the highest qualifications. We provide a family of choice rules that maximize merit

Feiyu Chen

In this work we study a more restricted class of quasi-topological gravity theories where the higher curvature terms have no contribution to the equation of motion on general static spherically symmetric metric where $g_{tt} g_{rr} \ne \mathrm{constant}$. We construct such theories up to quintic order in Riemann tensor and observe an important property of th

Wei-Liang Qian, Pan-Pan Wang, Zhang-Qi Wu, Cheng-Gang Shao

Inspired by the combinatorial algebraic approach proposed by Dhurandhar {\it et al.}, we propose two novel classes of second-generation time-delay interferometry (TDI) solutions and their further generalization. The primary strategy of the algorithm is to enumerate specific types of residual laser frequency noise associated with second-order commutators in p

Qingxiu Dong, Lei Li, Damai Dai, Ce Zheng

With the increasing capabilities of large language models (LLMs), in-context learning (ICL) has emerged as a new paradigm for natural language processing (NLP), where LLMs make predictions based on contexts augmented with a few examples. It has been a significant trend to explore ICL to evaluate and extrapolate the ability of LLMs. In this paper, we aim to s

Maor Ben-Shahar, Lucia Garozzo, Henrik Johansson

Scattering amplitudes in Yang-Mills theory are known to exhibit kinematic structures which hint to an underlying kinematic algebra that is dual to the gauge group color algebra. This color-kinematics duality is still poorly understood in terms of conventional Feynman rules, or from a Lagrangian formalism. In this work, we present explicit Lagrangians whose F

Isa E. Hafalir, Fuhito Kojima, M. Bumin Yenmez

Given an initial matching and a policy objective on the distribution of agent types to institutions, we study the existence of a mechanism that weakly improves the distributional objective and satisfies constrained efficiency, individual rationality, and strategy-proofness. We show that such a mechanism need not exist in general. We introduce a new notion of

Dipankar Das, Miguel Levy, Palash B. Pal, Anugrah M. Prasad

We study two novel aspects of democratic 3HDMs -- the custodial limit and the possibility of wrong-sign Yukawa couplings. In the custodial limit, the democratic 3HDMs can easily negotiate the constraints from the electroweak $T$-parameter. We also uncover the possibility of having wrong-sign Yukawa couplings in democratic 3HDMs, as in the case of 2HDMs. We s

V. Hocdé, R. Smolec, P. Moskalik, O. Ziółkowska

Estimating metallicity of classical Cepheids is of prime importance for studying metallicity effect on stellar evolution, chemical evolution of galaxies, and ultimately its impact on period-luminosity relation used in the extragalactic distance scale. We aim at establishing new empirical relations for estimating the iron content of classical Cepheids for sho

Susanna Terracini, Giorgio Tortone, Stefano Vita

As a first result we prove higher order Schauder estimates for solutions to singular/degenerate elliptic equations of type: \[ -\mathrm{div}\left(ρ^aA\nabla w\right)=ρ^af+\mathrm{div}\left(ρ^aF\right) \quad\textrm{in}\; Ω\] for exponents $a>-1$, where the weight $ρ$ vanishes in a non degenerate manner on a regular hypersurface $Γ$ which can be either a part

Xin Meng, Youwei Zhang, Xichang Zhang, Shenchao Jin

We propose a novel paradigm to vector magnetometry based on machine learning. Unlike conventional schemes where one measured signal explicitly connects to one parameter, here we encode the three-dimensional magnetic-field information in the set of four simultaneously acquired signals, i.e., the oscillating optical rotation signal's harmonics of a frequen

Fabian Bleitner, Camilla Nobili

We consider two-dimensional Rayleigh-Bénard convection with Navier-slip and fixed temperature boundary conditions at the two horizontal rough walls described by the height function $h$. We prove rigorous upper bounds on the Nusselt number $\text{Nu}$ which capture the dependence on the curvature of the boundary $κ$ and the (non-constant) friction coefficient

Nihar B. Shah

There is widespread debate on whether to anonymize author identities in peer review. The key argument for anonymization is to mitigate bias, whereas arguments against anonymization posit various uses of author identities in the review process. The Innovations in Theoretical Computer Science (ITCS) 2023 conference adopted a middle ground by initially anonymiz

Wei Tao, Ruilin Zhu, Zhen-Jun Xiao

We compute the matching coefficient between the quantum chromodynamics (QCD) and the non-relativistic QCD ( NRQCD) for the flavor-changing scalar current involving the heavy charm and bottom quark, up to the three-loop order within the NRQCD factorization. For the first time, we obtain the analytical expressions for the three-loop renormalization constant $\

Elena Mirela Babalic, Calin Iuliu Lazaroiu

We discuss the behavior of cosmological curves and their first order infrared approximants near critical ends of the scalar manifold $Σ$ and near interior critical points of the scalar potential for tame hyperbolizable two-field cosmological models by determining the universal forms of the asymptotic gradient flow of the classical effective potential with re

Wenqi Wei, Qinying Liu, Le Yuan, Jian Zhang

Nuclear magnetic resonance (NMR) technique benefits from high magnetic field not only due to the field-enhanced measurement sensitivity and resolution, but also because it is a powerful tool to investigate field-induced physics in modern material science. In this study, we successfully performed NMR measurements in high flat-top pulsed magnetic field (FTPMF)

Jyun-Fong Wong, Ko-Hsuan Mandy Chen, Jui-Min Chia, Zih-Ping Huang

Topological Hall effect (THE), an electrical transport signature of systems with chiral spin textures like skyrmions, has been observed recently in topological insulator (TI)-based magnetic heterostructures. However, the intriguing interplay between the topological surface state and THE is yet to be fully understood. In this work, we report a large THE of ~1

Kush Kinra, Manil T. Mohan, Renhai Wang

This article is concerned with the \emph{asymptotically autonomous robustness} (almost surely and in probability) of non-autonomous random attractors for two stochastic versions of 3D convective Brinkman-Forchheimer (CBF) equations defined on the whole space $\mathbb{R}^3$: $$\frac{\partial\boldsymbol{v}}{\partial t}-μΔ\boldsymbol{v}+(\boldsymbol{v}\cdot\nab

Supritha Bhowmick, Diptimoy Ghosh, Divya Sachdeva

Elastic collisions with relativistic electrons from the blazar's jet can accelerate dark matter (DM) particles in the DM spike surrounding the supermassive black hole at its center. This can allow one to set stringent limits on the DM-electron scattering cross section ($\barσ_{eχ}$) for DM masses less than 100 MeV. We consider DM particles boosted by ene

Sayantan Choudhury

In this work, we study the signatures of quantum entanglement by computing entanglement negativity between two causally unrelated regions in $3+1$ dimensional global de Sitter space. We investigate a bipartite quantum field theoretic setup for this purpose, driven by an axionic Bell pair resulting from Type IIB string compactification on a Calabi-Yau three f

Qichen Xu, Zhuanglin Shen, Manuel Pereiro, Pawel Herman

A long-standing and difficult problem in, e.g., condensed matter physics is how to find the ground state of a complex many-body system where the potential energy surface has a large number of local minima. Spin systems containing complex and/or topological textures, for example spin spirals or magnetic skyrmions, are prime examples of such systems. We propos

Jiayin Du, Shuguan Ji, Yong Li

In this paper, we study the Melnikov's persistence for completely degenerate Hamiltonian systems with the following Hamiltonian \begin{equation*} H(x,y,u,v)=h(y)+g(u,v)+\varepsilon P(x,y,u,v),~~~(x,y,u,v)\in \mathbb{T}^n\times{G}\times \mathbb{R}^d\times \mathbb{R}^d, \end{equation*} where $n\geq2$ and $d\geq1$ are positive integers, $G\subset\mathbb{R}^

Marcin Moszyński, Grzegorz Świderski

We explore to what extent the relation between the absolute continuous spectrum and non-existence of subordinate generalized eigenvectors, known for scalar Jacobi operators, can be formulated also for block Jacobi operators with $d$-dimensional blocks. The main object here allowing to make some progress in that direction is the new notion of the barrier nons

A. M. Dmytrenko, P. N. Fedorov, V. S. Akhmetov, A. B. Velichko

We present the results of determining the coordinates of the vertices of various stellar systems, the centroids of which are located in the Galactic plane. To do this, the positions, parallaxes, proper motions, and radial velocities of red giants and subgiants contained in the $Gaia$~DR3 catalogue have been used. When determining the components of the deform

Patrick Wenzel, Nan Yang, Rui Wang, Niclas Zeller

In this paper, we present a novel visual SLAM and long-term localization benchmark for autonomous driving in challenging conditions based on the large-scale 4Seasons dataset. The proposed benchmark provides drastic appearance variations caused by seasonal changes and diverse weather and illumination conditions. While significant progress has been made in adv

Martin Andersson, Benny Avelin

We develop theory and methods that use the graph Laplacian to analyze the geometry of the underlying manifold of datasets. Our theory provides theoretical guarantees and explicit bounds on the functional forms of the graph Laplacian when it acts on functions defined close to singularities of the underlying manifold. We use these explicit bounds to develop te

Sebastian Erhardt, Mainak Ghosh, Erik Buunk, Michael E. Rose

Logic Mill is a scalable and openly accessible software system that identifies semantically similar documents within either one domain-specific corpus or multi-domain corpora. It uses advanced Natural Language Processing (NLP) techniques to generate numerical representations of documents. Currently it leverages a large pre-trained language model to generate

Frits Vaandrager, Thorsten Wißmann

We provide a new perspective on the problem how high-level state machine models with abstract actions can be related to low-level models in which these actions are refined by sequences of concrete actions. We describe the connection between high-level and low-level actions using \emph{action codes}, a variation of the prefix codes known from coding theory. F

Xue-Qun Yan, Yan-Jiao Du, Wen-Tao Hou, Xiao-Ming Liu

The first law of thermodynamics restates the law of conservation of energy. It partitions the change in energy of a system into two pieces, heat and work. While there is no ambiguity to define heat and work in classical thermodynamics, their classification in the quantum regime is not that obvious. Thus, the first law of thermodynamics becomes problematic in

Naeem Akhtar, Jizhou Wu, Jia-Xin Peng, Wu-Ming Liu

The Wigner function of the compass state (a superposition of four coherent states) develops phase-space structures of dimension much less than the Planck scale, which are crucial in determining the sensitivity of these states to phase-space displacements. In the present work, we introduce compass-like states that may have connection to the contemporary exper

Jordi Castellví, Michael Drmota, Marc Noy, Clément Requilé

Given $t\geq 2$ and $0\leq k\leq t$, we prove that the number of labelled $k$-connected chordal graphs with $n$ vertices and tree-width at most $t$ is asymptotically $c n^{-5/2} γ^n n!$, as $n\to\infty$, for some constants $c,γ>0$ depending on $t$ and $k$. Additionally, we show that the number of $i$-cliques ($2\leq i\leq t$) in a uniform random $k$-connecte

Cyril Gadal, Matthieu Mercier, Marie Rastello, Laurent Lacaze

Most gravitational currents occur on sloping topographies, often in the presence of particles that can settle during the current propagation. Yet, an exhaustive exploration of associated parameters in experimental studies is still lacking. Here, we present an extensive experimental investigation of the slumping regime of turbidity (particle-laden) currents i

Abubakar Siddique, Henry Medeiros

We introduce a novel framework to track multiple objects in overhead camera videos for airport checkpoint security scenarios where targets correspond to passengers and their baggage items. We propose a Self-Supervised Learning (SSL) technique to provide the model information about instance segmentation uncertainty from overhead images. Our SSL approach impro

Mohammad Yousuf Jamal

We conducted a study on the collective modes within the hot QCD medium generated in heavy-ion collision experiments. These modes, whether real or imaginary, stable or unstable, play a crucial role in shaping the medium's evolution. To gain a deeper understanding, we considered several factors affecting the medium, including anisotropy, interactions among

Guixiang Hong, Wei Liu, Bang Xu

In this paper, we establish the quantitative mean ergodic theorems for two subclasses of power bounded operators on a fixed noncommutative $L_p$-space with $1<p<\infty$, which mainly concerns power bounded invertible operators and Lamperti contractions. Our approach to the quantitative ergodic theorems is the noncommutative square function inequalities. The

L. Ridgway Scott, Tabea Tscherpel

We examine the dimensions of various inf-sup stable mixed finite element spaces on tetrahedral meshes in 3D with exact divergence constraints. More precisely, we compare the standard Scott-Vogelius elements of higher polynomial degree and low order methods on split meshes, the Alfeld and the Worsey-Farin split. The main tool is a counting strategy to express

Wenhao Wu, Haipeng Luo, Bo Fang, Jingdong Wang

Most existing text-video retrieval methods focus on cross-modal matching between the visual content of videos and textual query sentences. However, in real-world scenarios, online videos are often accompanied by relevant text information such as titles, tags, and even subtitles, which can be utilized to match textual queries. This insight has motivated us to

Wenhao Wu, Xiaohan Wang, Haipeng Luo, Jingdong Wang

Vision-language models (VLMs) pre-trained on large-scale image-text pairs have demonstrated impressive transferability on various visual tasks. Transferring knowledge from such powerful VLMs is a promising direction for building effective video recognition models. However, current exploration in this field is still limited. We believe that the greatest value

Georgia Papacharalampous, Hristos Tyralis, Anastasios Doulamis, Nikolaos Doulamis

Merging satellite products and ground-based measurements is often required for obtaining precipitation datasets that simultaneously cover large regions with high density and are more accurate than pure satellite precipitation products. Machine and statistical learning regression algorithms are regularly utilized in this endeavour. At the same time, tree-base

P. Montero de Hijes, J. R. Espinosa, C. Vega, C. Dellago

Despite the importance of ice nucleation, this process has been barely explored at negative pressures. Here, we study homogeneous ice nucleation in stretched water by means of Molecular Dynamics Seeding simulations using the TIP4P/Ice model. We observe that the critical nucleus size, interfacial free energy, free energy barrier, and nucleation rate barely ch

Yun Zeng, Deren Han, Yansheng Su, Jiaxin Xie

We investigate the randomized Kaczmarz method that adaptively updates the stepsize using readily available information for solving inconsistent linear systems. A novel geometric interpretation is provided which shows that the proposed method can be viewed as an orthogonal projection method in some sense. We prove that this method converges linearly in expect

Ilse Fischer

An identity that is reminiscent of the Littlewood identity plays a fundamental role in recent proofs of the facts that alternating sign triangles are equinumerous with totally symmetric self-complementary plane partitions and that alternating sign trapezoids are equinumerous with holey cyclically symmetric lozenge tilings of a hexagon. We establish a bounded

T. Kangas, A. Ahola, C. Fransson, J. Larsson

We use adaptive-optics imaging and integral field spectroscopy from the Very Large Telescope, together with images from the \emph{Hubble Space Telescope}, to study the near-infrared (NIR) evolution of the equatorial ring (ER) of SN~1987A. We study the NIR line and continuum flux and morphology over time in order to lay the groundwork for \emph{James Webb Spa

Jialin Lei, Qiang Zhang

For an automorphism $ϕ$ of a free group $F_n$ of rank $n$, Bestvina and Handel showed that the rank $rk Fix(ϕ)$ of the fixed subgroup is not greater than $n$ (the so-called Scott conjecture). Soon after Bestvina and Handel&#39;s announcement, their result was generalized by many authors in various directions. In this paper, we are interested in the fixed sub

Armand Bernou, Mitia Duerinckx, Antoine Gloria

We consider a suspension of active rigid particles (swimmers) in a steady Stokes flow, where particles are distributed according to a stationary ergodic random process, and we study its homogenization in the macroscopic limit. A key point in the model is that swimmers are allowed to adapt their propulsion to the surrounding fluid deformation: swimming forces

Ahmed Naguib, Dina Reda Eldamak

According to the World Health Organization (WHO), 30 million people are in need of prosthetic and orthotic devices. Some people are born with this limb loss, while others lose limbs due to diseases such as Cancer, diabetes, and work accidents. Additionally, limb amputation is among the most severe and heavily reported injuries among veterans during war. The

Florian Nill

As shown recently by the author, constant population SI(R)S models map to Hethcote&#39;s classic endemic model originally proposed in 1973. This unifies a whole class of models with up to 10 parameters, all being isomorphic to a simple 2-parameter master model for endemic bifurcation. In this work this procedure is extended to a 14-parameter SSISS Model, inc

Di Huang, Sida Peng, Tong He, Honghui Yang

We propose a novel approach to self-supervised learning of point cloud representations by differentiable neural rendering. Motivated by the fact that informative point cloud features should be able to encode rich geometry and appearance cues and render realistic images, we train a point-cloud encoder within a devised point-based neural renderer by comparing

Spiros Cotsakis, John Miritzis

We study the effects of trans-planckian censorship conjecture (TCC) bounds on geodesic completeness of spacetime and the associated existence for an infinite proper time. Using Gronwall&#39;s lemma, TCC bounds can be derived directly, leading to a result about the absence of blowup solutions. We show that the TCC provides part of the required criteria for ge

Livia Campo

We show that five of Reid&#39;s Fano 3-fold hyperurfaces containing at least one compound Du Val singularity of type $cA_n$ have pliability at least two. The two elements of the pliability set are the singular hypersurface itself, and another non-isomorphic Fano hypersurface of the same degree, embedded in the same weighted projective space, but with differe

Zixiang Luo, Kaining Peng, Zhichao Liang, Shengyuan Cai

Effective connectivity (EC), indicative of the causal interactions between brain regions, is fundamental to understanding information processing in the brain. Traditional approaches, which infer EC from neural responses to stimulations, are not suited for mapping whole-brain EC in humans due to being invasive and having limited spatial coverage of stimulatio

Liguang Zhou, Junjie Hu, Yuhongze Zhou, Tin Lun Lam

Unbiased scene graph generation (USGG) is a challenging task that requires predicting diverse and heavily imbalanced predicates between objects in an image. To address this, we propose a novel framework peer learning that uses predicate sampling and consensus voting (PSCV) to encourage multiple peers to learn from each other. Predicate sampling divides the p

Pengju Chen, Nan Yang, Austen Couvertier, Quanzhen Ding

We study the chaotic motion of a semi-classical optomechanical system coupled to a non-Markovian environment with a finite correlation time. We show that the non-Markovian environment can significantly enhance chaos, by studying the emergence of chaos using Lyapunov exponent with the changing non-Markovian parameter. It is observed that non-Markovian environ

Xu Gu, Yuchong Sun, Feiyue Ni, Shizhe Chen

A video storyboard is a roadmap for video creation which consists of shot-by-shot images to visualize key plots in a text synopsis. Creating video storyboards, however, remains challenging which not only requires cross-modal association between high-level texts and images but also demands long-term reasoning to make transitions smooth across shots. In this p

Jie Feng, Ruimin Feng, Qing Wu, Zhiyong Zhang

Supervised Deep-Learning (DL)-based reconstruction algorithms have shown state-of-the-art results for highly-undersampled dynamic Magnetic Resonance Imaging (MRI) reconstruction. However, the requirement of excessive high-quality ground-truth data hinders their applications due to the generalization problem. Recently, Implicit Neural Representation (INR) has

Samen Hossein, Shannon Starr

Given a uniform random permutation $π\in S_n$, let $Z_{n,k}$ be equal to the number of increasing subsequences of length $k$: so $Z_{n,k}=|\{(i_1,\dots,i_k) \in \mathbb{Z}^k\, :\, 1\leq i_1<\dots<i_k\leq n\, ,\ π_{i_1}<\dots<π_{i_k}\}|$. In an important paper, Ross Pinsky proved $\mathbf{E}\big[Z_{n,k}^2\big]$ is equal to $\sum_{i} A(k-i,i)B(n,2k-i)$, where

Mrinmoy Roy, Anica Tasnim Protity

Almost 80 million Americans suffer from hair loss due to aging, stress, medication, or genetic makeup. Hair and scalp-related diseases often go unnoticed in the beginning. Sometimes, a patient cannot differentiate between hair loss and regular hair fall. Diagnosing hair-related diseases is time-consuming as it requires professional dermatologists to perform

S. M. Roy

The De Broglie-Bohm (DeBB)\cite{DeBB} Causal Quantum Mechanics played a crucial role in Bell&#39;s discovery \cite{Bell1964} that quantum mechanics violates EPR local reality \cite{EPR1935}, and also in Bell&#39;s search for an exact quantum mechanics. The experiments of Aspect et al \cite{Aspect1981} confirm quantum correlations between plane polarizations

Masatake Kitano, Keisuke Hasegawa

Phased arrays of airborne ultrasound transducers are widely utilized as a key technology to achieve mid-air convergence of intense ultrasound, which is applied to a variety of systems, such as contactless tactile presentation, acoustic-levitation and its application, mid-air-flow acceleration, etc. However, it requires considerably precise phase control with

Jiaming Zhang, Xingjun Ma, Qi Yi, Jitao Sang

There is a growing interest in developing unlearnable examples (UEs) against visual privacy leaks on the Internet. UEs are training samples added with invisible but unlearnable noise, which have been found can prevent unauthorized training of machine learning models. UEs typically are generated via a bilevel optimization framework with a surrogate model to r

Chengyang Shao

In this note, we propose several unsolved problems concerning the irrotational oscillation of a water droplet under zero gravity. We will derive the governing equation of this physical model, and convert it to a quasilinear dispersive partial differential equation defined on the sphere, which formally resembles the capillary water waves equation but describe

Pratik K. Mishra, Alex Mihailidis, Shehroz S. Khan

The existing methods for video anomaly detection mostly utilize videos containing identifiable facial and appearance-based features. The use of videos with identifiable faces raises privacy concerns, especially when used in a hospital or community-based setting. Appearance-based features can also be sensitive to pixel-based noise, straining the anomaly detec

Jian-Cheng Li, Jin-Long Xiao, Yue-De Yang, You-Ling Chen

Chaotic semiconductor lasers have been widely investigated for high-speed random bit generation, which is applied for the generation of cryptographic keys for classical and quantum cryptography systems. Here, we propose and demonstrate a self-chaotic microlaser with enhanced chaotic bandwidth for high-speed random bit generation. By designing tri-mode intera

Greeshma Krishna, Malavika S Nair, Pramod P Nair, Anil Lal S

Deep learning techniques with neural networks have been used effectively in computational fluid dynamics (CFD) to obtain solutions to nonlinear differential equations. This paper presents a physics-informed neural network (PINN) approach to solve the Blasius function. This method eliminates the process of changing the non-linear differential equation to an i

Naoya Yamaguchi, Yuka Yamaguchi, Maiya Hori

We assume that the forecast error follows a probability distribution which is symmetric and monotonically non-increasing on non-negative real numbers, and if there is a mismatch between observed and predicted value, then we suffer a loss. Under the assumptions, we solve a minimization problem with an asymmetric loss function. In addition, we give an inequali

Badih Ghazi, Rahul Ilango, Pritish Kamath, Ravi Kumar

Computational differential privacy (CDP) is a natural relaxation of the standard notion of (statistical) differential privacy (SDP) proposed by Beimel, Nissim, and Omri (CRYPTO 2008) and Mironov, Pandey, Reingold, and Vadhan (CRYPTO 2009). In contrast to SDP, CDP only requires privacy guarantees to hold against computationally-bounded adversaries rather than