November 2022 arXiv papers — page 49

Qiyue Zhang, Peng Zhang, Huizhong Xu, Weining Man

We propose and demonstrate the effectual generation and control of nonparaxial self-accelerating beams by using UV-resin pendant droplets. We show that the geometrical shape of the hanging droplets formed as a result of the interplay between surface tension and gravity offers a natural curvature enabling the generation of nonparaxial self-accelerating beams.

Bruce Hoeneisen

In the warm dark matter scenario, the Press-Schechter formalism is valid only for galaxy masses greater than the "velocity dispersion cut-off". In this work we extend the predictions to masses below the velocity dispersion cut-off, and thereby address the "Missing Satellites Problem", and the rest-frame ultra-violet luminosity cut-off required to not exceed

Tamer Elkafrawy, Marcus Hohlmann, Teruki Kamon, Paul Padley

We investigate the potential reach of a search for a long-lived/prompt dark vector boson $Z_D$, also called dark $Z$, and a prompt dark Higgs boson $h_D$ through exotic decays of the observed Higgs boson $h$ into either $Z_DZ_D$, $h_Dh_D$, or $ZZ_D$ with $Z$ being the hypercharge gauge boson. The $Z_D$ production through the Higgs portal is completed via one

Narek Tumanyan, Michal Geyer, Shai Bagon, Tali Dekel

Large-scale text-to-image generative models have been a revolutionary breakthrough in the evolution of generative AI, allowing us to synthesize diverse images that convey highly complex visual concepts. However, a pivotal challenge in leveraging such models for real-world content creation tasks is providing users with control over the generated content. In t

Colin Megill, Elizabeth Barry, Christopher Small

Systems for large scale deliberation have resolved polarized issues and shifted agenda setting into the public's hands. These systems integrate bridging-based ranking algorithms - including group informed consensus implemented in Polis and the continuous matrix factorization approach implemented by Twitter Birdwatch - making it possible to highlight statemen

Marcos Zampieri, Tharindu Ranasinghe, Mrinal Chaudhari, Saurabh Gaikwad

The presence of offensive language on social media is very common motivating platforms to invest in strategies to make communities safer. This includes developing robust machine learning systems capable of recognizing offensive content online. Apart from a few notable exceptions, most research on automatic offensive language identification has dealt with Eng

Barak Sabbagh, Noa Edri Fraiman, Alex Fish, Gilad Yossifon

This article presents the implementation of on-chip iontronic circuits via small-scale integration of multiple ionic logic gates made of bi-polar polyelectrolyte diodes. These ionic circuits are analogous to solid-state electronic circuits, with ions as the charge carriers instead of electrons/holes. We experimentally characterize the responses of a single f

Walaa Elmetenawee, gianluigi chiarello, Alessandro Corvaglia, Federica Cuna

The IDEA detector concept for a future e$^{+}$e$^{-}$ collider adopts an ultra-low mass drift chamber as a central tracking system. The He-based ultra-low mass drift chamber is designed to provide efficient tracking, a high-precision momentum measurement, and excellent particle identification by exploiting the cluster counting technique. This paper describes

Jose H. D. Rivero, Liang Feng, Li Ge

An imaginary gauge transformation is at the core of the non-Hermitian skin effect. Here we show that such a transformation can be performed in momentum space as well, which reveals that certain gain and loss modulated systems in their parity-time (PT) symmetric phases are equivalent to Hermitian systems with real potentials. Our analysis in momentum space al

Kang Wang, Subhashis Ghosal

We consider the nonparametric multivariate isotonic regression problem, where the regression function is assumed to be nondecreasing with respect to each predictor. Our goal is to construct a Bayesian credible interval for the function value at a given interior point with assured limiting frequentist coverage. We put a prior on unrestricted step-functions, b

Lingfeng Zhang, Nishard Abdeen, Jochen Lang

Polymicrogyria (PMG) is a disorder of cortical organization mainly seen in children, which can be associated with seizures, developmental delay and motor weakness. PMG is typically diagnosed on magnetic resonance imaging (MRI) but some cases can be challenging to detect even for experienced radiologists. In this study, we create an open pediatric MRI dataset

Yurii Kolomoitsev, Tetiana Lomako

We show that the Peetre $K$-functional between the space $L_p$ with $0<p<1$ and the corresponding smooth function space $W_p^\psi$ generated by the Weyl-type differential operator $\psi(D)$, where $\psi$ is a homogeneous function of any positive order, is identically zero. The proof of the main results is based on the properties of the de la Vall\'ee Poussin

Will Stafford, Victor Nascimento

Prawitz conjectured that the proof-theoretically valid logic is intuitionistic logic. Recent work on proof-theoretic validity has disproven this. In fact, it has been shown that proof-theoretic validity is not even closed under substitution. In this paper, we make a minor modification to the definition of proof-theoretic validity found in Prawitz (1973) and

Radu Alexandru Rosu, Sven Behnke

Neural radiance-density field methods have become increasingly popular for the task of novel-view rendering. Their recent extension to hash-based positional encoding ensures fast training and inference with visually pleasing results. However, density-based methods struggle with recovering accurate surface geometry. Hybrid methods alleviate this issue by opti

Michihiro Yasunaga, Armen Aghajanyan, Weijia Shi, Rich James

Recent multimodal models such as DALL-E and CM3 have achieved remarkable progress in text-to-image and image-to-text generation. However, these models store all learned knowledge (e.g., the appearance of the Eiffel Tower) in the model parameters, requiring increasingly larger models and training data to capture more knowledge. To integrate knowledge in a mor

Adam Hepworth, Aya Hussein, Darryn Reid, Hussein Abbass

An emerging challenge in swarm shepherding research is to design effective and efficient artificial intelligence algorithms that maintain a low-computational ceiling while increasing the swarm's abilities to operate in diverse contexts. We propose a methodology to design a context-aware swarm-control intelligent agent. The intelligent control agent (shepherd

Margaret Bayer, Marija Jelić Milutinović, Julianne Vega

A (general) polygonal line tiling is a graph formed by a string of cycles, each intersecting the previous at an edge, no three intersecting. In 2022, Matsushita proved the matching complex of a certain type of polygonal line tiling with even cycles is homotopy equivalent to a wedge of spheres. In this paper, we extend Matsushita's work to include a larger fa

Wolfgang Muschik

The wide-spread opinion is that original quantum mechanics is a reversible theory, but this statement is only true for undecomposed systems, that are those systems which sub-systems are out of consideration. Taking sub-systems into account, as it is by definition necessary for decomposed systems, the interaction Hamiltonians which are absent in undecomposed

Rakesh Mogul, Sanjay S. Limaye, Michael. J. Way

We present a significantly updated CO$_2$ altitude profile for Venus (64.2-0.9 km) and provide support for a potential deep lower atmospheric haze of particles (17 km and lower). We extracted this information by developing a new analytical model for mass spectra obtained by the Pioneer Venus Large Probe (PVLP) Neutral Mass Spectrometer (LNMS). Our model acco

Paul-Christian Bürkner, Philipp Doebler, Heinz Holling

In scientific research, many hypotheses relate to the comparison of two independent groups. Usually, it is of interest to use a design (i.e., the allocation of sample sizes $m$ and $n$ for fixed $N = m + n$) that maximizes the power of the applied statistical test. It is known that the two-sample t-tests for homogeneous and heterogeneous variances may lose s

Benjamin Basso, Lance J. Dixon, Yu-Ting Liu, Georgios Papathanasiou

We classify origin limits of maximally helicity violating multi-gluon scattering amplitudes in planar $\mathcal{N}=4$ super-Yang-Mills theory, where a large number of cross ratios approach zero, with the help of cluster algebras. By analyzing existing perturbative data, and bootstrapping new data, we provide evidence that the amplitudes become the exponentia

Massimo Boninsegni, Saverio Moroni

The second layer of He-4 adsorbed on a graphite substrate is studied by Quantum Monte Carlo simulations. We make use of a microscopic model of the substrate fully accounting for its corrugation, and compare the results to those obtained with a smooth substrate. The only effect of corrugation is a ~20% reduction of the value of the superfluid fraction of the

Stanislav Polyakov, Alexander Kryukov, Andrey Demichev, Julia Dubenskaya

High-energy particles hitting the upper atmosphere of the Earth produce extensive air showers that can be detected from the ground level using imaging atmospheric Cherenkov telescopes. The images recorded by Cherenkov telescopes can be analyzed to separate gamma-ray events from the background hadron events. Many of the methods of analysis require simulation

Wouter Deleersnyder, David Dudal, Benjamin Maveau, Marieke Paepen

If the magnetic field caused by a magnetic dipole is measured, the electrical conductivity of the subsurface can be determined by solving the inverse problem. For this problem a form of regularisation is required as the forward model is badly conditioned. Commonly, Tikhonov regularisation is used which adds the $\ell_2$-norm of the model parameters to the ob

Meihua Dang, Anji Liu, Guy Van den Broeck

Probabilistic circuits (PCs) are a tractable representation of probability distributions allowing for exact and efficient computation of likelihoods and marginals. There has been significant recent progress on improving the scale and expressiveness of PCs. However, PC training performance plateaus as model size increases. We discover that most capacity in ex

Victoria J Wright, Máté Farkas

We present an invertible map between correlations in any bipartite Bell scenario and behaviours in a family of contextuality scenarios. The map takes local, quantum and non-signalling correlations to non-contextual, quantum and contextual behaviours, respectively. Consequently, we find that the membership problem of the set of quantum contextual behaviours i

Pablo Arratia López, Hernán Mella, Sergio Uribe, Daniel E. Hurtado

Heart failure is typically diagnosed with a global function assessment, such as ejection fraction. However, these metrics have low discriminate power, failing to distinguish different types of this disease. Quantifying local deformations in the form of cardiac strain can provide helpful information, but it remains a challenge. In this work, we introduce Warp

Gonzalo Prieto-Lyon, Victoria Strait, Charlotte A. Mason, Gabriel Brammer

The demographics of the production and escape of ionizing photons from UV-faint early galaxies is a key unknown in discovering the primary drivers of reionization. With the advent of JWST it is finally possible to observe the rest-frame optical nebular emission from individual sub-L$^*$ z>3 galaxies to measure the production of ionizing photons, $\xi_\mathrm

Frederik De Ceuster, Thomas Ceulemans, Jon Cockayne, Leen Decin

Electromagnetic radiation plays a crucial role in various physical and chemical processes. Hence, almost all astrophysical simulations require some form of radiative transfer model. Despite many innovations in radiative transfer algorithms and their implementation, realistic radiative transfer models remain very computationally expensive, such that one often

R. Benbrik, M. Boukidi, M. Ouchemhou, L. Rahili

Recently, ATLAS and CMS experiments at the LHC put on light the relevant results in the measurement precision of the Higgs and BSM. In such a report, where the resonance direct search was made in the $\gamma Z$ channel, a mass adjustment distribution for the reconstructed $Z$ boson and photon was established. Thus, simultaneously with the signal-from-backgro

Bowen Chen, Bartlomiej Czech, Ling-Yan Hung, Gabriel Wong

Modular parallel transport is a generalization of Berry phases, applied to modular (entanglement) Hamiltonians. Here we initiate the study of modular parallel transport for disjoint field theory regions. We study modular parallel transport in the kinematic space of multi-interval regions in the vacuum of 1+1-dimensional free fermion theory--one of the few th

Casey Peat, Oliver Batchelor, Richard Green, James Atlas

We present Zero-NeRF, a projective surface registration method that, to the best of our knowledge, offers the first general solution capable of alignment between scene representations with minimal or zero visual correspondence. To do this, we enforce consistency between visible surfaces of partial and complete reconstructions, which allows us to constrain oc

Meng Cheng, Nathan Seiberg

We analyze lattice Hamiltonian systems whose global symmetries have 't Hooft anomalies. As is common in the study of anomalies, they are probed by coupling the system to classical background gauge fields. For flat fields (vanishing field strength), the nonzero spatial components of the gauge fields can be thought of as twisted boundary conditions, or equival

Yan Xia, Mariia Gladkova, Rui Wang, Qianyun Li

Place recognition based on point clouds (LiDAR) is an important component for autonomous robots or self-driving vehicles. Current SOTA performance is achieved on accumulated LiDAR submaps using either point-based or voxel-based structures. While voxel-based approaches nicely integrate spatial context across multiple scales, they do not exhibit the local prec

Mahmut Levent Doğan, Jonathan Leake, Mohan Ravichandran

We give a method for computing asymptotic formulas and approximations for the volumes of spectrahedra, based on the maximum-entropy principle from statistical physics. The method gives an approximate volume formula based on a single convex optimization problem of minimizing $-\log \det P$ over the spectrahedron. Spectrahedra can be described as affine slices

Teodor Strömberg, Peter Schiansky, Robert W. Peterson, Marco Túlio Quintino

The quantum SWITCH is an example of a process with an indefinite causal structure, and has attracted attention for its ability to outperform causally ordered computations within the quantum circuit model. To date, realisations of the quantum SWITCH have relied on optical interferometers susceptible to minute path length fluctuations, complicating their desig

Nematollah Iri

We consider universal variable-to-fixed length compression of memoryless sources with a fidelity criterion. We design a dictionary codebook over the reproduction alphabet which is used to parse the source stream. Once a source subsequence is within a specified distortion of a dictionary codeword, the index of the codeword is emitted as the reproduced string.

Paul-Christian Bürkner, Philipp Doebler

The present study investigates the performance of several statistical tests to detect publication bias in diagnostic meta-analysis by means of simulation. While bivariate models should be used to pool data from primary studies in diagnostic meta-analysis, univariate measures of diagnostic accuracy are preferable for the purpose of detecting publication bias.

Runze Zhang

This article focus on the connected locus of the cubic polynomial slice $Per_1(\lambda)$ with a parabolic fixed point of multiplier $\lambda=e^{2\pi i\frac{p}{q}}$. We first show that any parabolic component, which is a parallel notion of hyperbolic component, is a Jordan domain. Moreover, a continuum $\mathcal{K}_\lambda$ called the central part in the conn

Yi Liu, Stefano Moretti, Harri Waltari

We study the possibility of measuring neutrino Yukawa couplings in the Next-to-Minimal Supersymmetric Standard Model with right-handed neutrinos (NMSSMr) when the lightest Supersymmetric partner (a right-handed sneutrino) is the Dark Matter (DM) candidate, by exploiting a `dijet + dilepton + Missing Transverse Energy' (MET) signature. We show that, unlike th

Vaisakh Mannalath, Anirban Pathak

Distributing entangled pairs among multiple users is a fundamental problem in quantum networks. Existing protocols like $X$ protocol introduced in (npj Quantum Information 5, 76 (2019)) use graph theoretic tools like local complementation to optimize the number of measurements required to extract any Bell pair among the network users. However, such a protoco

Nobuyuki Sakai, Bo Zhang, Shuangjing Xu, Daisuke Sakai

We aim to reveal the structure and kinematics of the Outer-Scutum-Centaurus (OSC) arm located on the far side of the Milky Way through very long baseline interferometry (VLBI) astrometry using KaVA, which is composed of KVN (Korean VLBI Network) and VERA (VLBI Exploration of Radio Astrometry). We report the proper motion of a 22 GHz H$_{2}$O maser source, wh

Riccardo Molinarolo

In this paper we analyse a boundary value problem for the Laplace equation with a nonlinear non-autonomous transmission conditions on the boundary of a small inclusion of size $\epsilon$. We show that the problem has solutions for $\epsilon$ small enough and we investigate the dependence of a specific family of solutions upon $\epsilon$. By adopting a functi

L. M. Stapper, M. R. Hogerheijde, E. F. van Dishoeck, T. Paneque-Carreño

Herbig stars can be classified into group I and group II depending on the shape of the far-IR excess from the spectral energy distribution. This separation may be evolutionary and related to the vertical structure of these disks. We aim to determine the emission height of Herbig disks and compare the resulting vertical extent of both groups. ALMA Band 6 obse

Nelson Martins-Ferreira

An answer to the question investigated in this paper brings a new characterization of internal groupoids such that: (a) it holds even when finite limits are not assumed to exist; (b) it is a full subcategory of the category of involutive-2-links, that is, a category whose objects are morphisms equipped with a pair of interlinked involutions. This result high

Martin Ammon, Michel Pannier

We utilise a quotient of the universal enveloping algebra of the Poincar\'e algebra in three spacetime dimensions, on which we formulate a covariant constancy condition. The equations so obtained contain the Fierz-Pauli equations for non-interacting, massive higher-spin fields, and can thus be regarded as an unfolding of the Fierz-Pauli system. All fundament

F. D. Priestley, A. P. Whitworth, E. Fogerty

Models of prestellar cores often assume that the cores are isolated from their environment - material outside the core boundary plays no role in the subsequent evolution. This is unlikely to be the case in reality, where cores are located within hierarchically substructured molecular clouds. We investigate the dynamical and chemical evolution of prestellar c

Yasemin Karacora, Aydin Sezgin

The enormous quality of service (QoS) demands posed by mission-critical use-cases of future 5G/6G wireless communication raise the need for resource-efficient highly reliable and low latency connectivity solutions. Multi-connectivity is considered a promising yet resource demanding approach to enhance reliability. In this work, we study the potential of the

Fotis Farakos, Matteo Morittu

We analyze the standard fermionic 4D Volkov-Akulov action with N global non-linear supersymmetries. We find that the stationary points of the system are described by an effective potential, written in terms of two composite real scalar fields, which approaches the exact quantum effective potential in the large N limit. We identify the existence of at least t

Nicholas O'Dea, Alan Morningstar, Sarang Gopalakrishnan, Vedika Khemani

Nascent quantum computers motivate the exploration of quantum many-body systems in nontraditional scenarios. For example, it has become natural to explore the dynamics of systems evolving under both unitary evolution and measurement. Such systems can undergo dynamical phase transitions in the entanglement properties of quantum trajectories conditional on the

Chang-Tse Hsieh, Po-Yao Chang

We demonstrate three types of transformations that establish connections between Hermitian and non-Hermitian quantum systems at criticality, which can be described by conformal field theories (CFTs). For the transformation preserving both the energy and the entanglement spectra, the corresponding central charges obtained from the logarithmic scaling of the e

Lucila Peralta Gavensky, Gonzalo Usaj, C. A. Balseiro

Multi-terminal Josephson junctions were recently proposed as a versatile and tunable platform to emulate topological Bloch-like Hamiltonians in arbitrary dimensions. In this perspective article, we will give a brief overview of the subject and recognize these mesoscopic devices as realizations of topological flux networks as the ones envisioned by J. E. Avro

Lorenzo Piga, Marco Marinucci, Guido D'Amico, Massimo Pietroni

We develop a pipeline to set new constraints on scale-independent modified gravity, from the galaxy power spectrum in redshift space of BOSS DR12. The latter is modelled using the effective field theory of large-scale structure up to 1-loop order in perturbation theory. We test our pipeline on synthetic and simulated data, to assess systematic biases on the

Koji Yamaguchi, Hiroyasu Tajima

Metric adjusted skew information, induced from quantum Fisher information, is a well-known family of resource measures in the resource theory of asymmetry. However, its asymptotic rates are not valid asymmetry monotone since it has an asymptotic discontinuity. We here introduce a new class of asymmetry measures with the smoothing technique, which we term smo

Thomas Bilitewski, Ana Maria Rey

We study the non-equilibrium dynamics of dipoles confined in multiple stacked two-dimensional layers realising a long-range interacting quantum spin 1/2 XXZ model. We demonstrate that strong in-plane XXX interactions can protect a manifold of collective layer dynamics. This then allows us to map the many-body spin dynamics to bosonic models. In a bilayer con

Mathis Gerdes, Sven Krippendorf

We present the first version of CYJAX, a package for machine learning Calabi-Yau metrics using JAX. It is meant to be accessible both as a top-level tool and as a library of modular functions. CYJAX is currently centered around the algebraic ansatz for the K\"ahler potential which automatically satisfies K\"ahlerity and compatibility on patch overlaps. As of

Lennart Bittel, Sevag Gharibian, Martin Kliesch

Variational Quantum Algorithms (VQAs), such as the Quantum Approximate Optimization Algorithm (QAOA) of [Farhi, Goldstone, Gutmann, 2014], have seen intense study towards near-term applications on quantum hardware. A crucial parameter for VQAs is the \emph{depth} of the variational ``ansatz'' used -- the smaller the depth, the more amenable the ansatz is to

C. Bertemes, D. Wylezalek, M. Albán, M. Aravena

We present results from the first public data release of the MaNGA-ARO Survey of CO Targets (MASCOT), focussing our study on galaxies whose star-formation rates and stellar masses place them below the ridge of the star-forming Main Sequence. In optically-selected type 2 AGN/LINERs/Composites, we find an empirical relation between gas-phase metallicity gradie

Raymond T. Co, Valerie Domcke, Keisuke Harigaya

Generating axion dark matter through the kinetic misalignment mechanism implies the generation of large asymmetries for Standard Model fermions in the early universe. Even if these asymmetries are washed out at later times, they can trigger a chiral plasma instability in the early universe. Similarly, a direct coupling of the axion with the hypercharge gauge

Andreas Crivellin, Martin Hoferichter

In the phenomenology of strong interactions most physical states acquire a substantial width, and thus can only be defined in a model-independent way by pole positions and residues of the $S$-matrix. This information is incorporated in the K\"all\'en-Lehmann representation, whose spectral function characterizes the shape of the resonance and can be constrain

Kunal Deshmukh, Thomas Kupfer, Pasi Hakala, Evan B. Bauer

We report the results from follow-up observations of two Roche-lobe filling hot subdwarf binaries with white dwarf companions predicted to have accretion disks. ZTF J213056.71+442046.5 (ZTF J2130) with a 39-minute period and ZTF J205515.98+465106.5 (ZTF J2055) with a 56-minute period were both discovered as subdwarf binaries with light curves that could only

Chengjian Feng, Zequn Jie, Yujie Zhong, Xiangxiang Chu

Recent LSS-based multi-view 3D object detection has made tremendous progress, by processing the features in Brid-Eye-View (BEV) via the convolutional detector. However, the typical convolution ignores the radial symmetry of the BEV features and increases the difficulty of the detector optimization. To preserve the inherent property of the BEV features and ea

Ankan Kumar Bhunia, Salman Khan, Hisham Cholakkal, Rao Muhammad Anwer

The pose-guided person image generation task requires synthesizing photorealistic images of humans in arbitrary poses. The existing approaches use generative adversarial networks that do not necessarily maintain realistic textures or need dense correspondences that struggle to handle complex deformations and severe occlusions. In this work, we show how denoi

Wojciech Zielonka, Timo Bolkart, Justus Thies

We present Instant Volumetric Head Avatars (INSTA), a novel approach for reconstructing photo-realistic digital avatars instantaneously. INSTA models a dynamic neural radiance field based on neural graphics primitives embedded around a parametric face model. Our pipeline is trained on a single monocular RGB portrait video that observes the subject under diff

Fengyu Yang, Chenyang Ma, Jiacheng Zhang, Jing Zhu

The ability to associate touch with sight is essential for tasks that require physically interacting with objects in the world. We propose a dataset with paired visual and tactile data called Touch and Go, in which human data collectors probe objects in natural environments using tactile sensors, while simultaneously recording egocentric video. In contrast t

Shangzhe Wu, Ruining Li, Tomas Jakab, Christian Rupprecht

We consider the problem of predicting the 3D shape, articulation, viewpoint, texture, and lighting of an articulated animal like a horse given a single test image as input. We present a new method, dubbed MagicPony, that learns this predictor purely from in-the-wild single-view images of the object category, with minimal assumptions about the topology of def

Elazar Goldenberg, Tomasz Kociumaka, Robert Krauthgamer, Barna Saha

The edit distance between strings classically assigns unit cost to every character insertion, deletion, and substitution, whereas the Hamming distance only allows substitutions. In many real-life scenarios, insertions and deletions (abbreviated indels) appear frequently but significantly less so than substitutions. To model this, we consider substitutions be

The NNPDF Collaboration, Richard D. Ball, Juan Cruz-Martinez, Luigi Del Debbio

We respond to the criticism raised by Courtoy et al., in which the faithfulness of the NNPDF4.0 sampling is questioned and an under-estimate of the NNPDF4.0 PDF uncertainties is implied. We list, correct, and clarify in detail a number of inaccurate or misleading claims that are made in this Reference. Specifically, we explain and explicitly demonstrate why

Ruipeng Li, Jonas von Milczewski, Atac Imamoglu, Rafał Ołdziejewski

We study induced pairing between two identical fermions mediated by an attractively interacting quantum impurity in two-dimensional systems. Based on a Stochastic Variational Method (SVM), we investigate the influence of confinement and finite interaction range effects on the mass ratio beyond which the ground state of the quantum three-body problem undergoe

Paola Cascante-Bonilla, Leonid Karlinsky, James Seale Smith, Yanjun Qi

Generalized Zero-Shot Learning (GZSL) aims to train a classifier that can generalize to unseen classes, using a set of attributes as auxiliary information, and the visual features extracted from a pre-trained convolutional neural network. While recent GZSL methods have explored various techniques to leverage the capacity of these features, there has been an

David Chuan-En Lin, Fabian Caba Heilbron, Joon-Young Lee, Oliver Wang

This paper investigates the challenge of extracting highlight moments from videos. To perform this task, we need to understand what constitutes a highlight for arbitrary video domains while at the same time being able to scale across different domains. Our key insight is that photographs taken by photographers tend to capture the most remarkable or photogeni

David Chuan-En Lin, Fabian Caba Heilbron, Joon-Young Lee, Oliver Wang

Video editing is a creative and complex endeavor and we believe that there is potential for reimagining a new video editing interface to better support the creative and exploratory nature of video editing. We take inspiration from latent space exploration tools that help users find patterns and connections within complex datasets. We present VideoMap, a proo

Harshay Shah, Sung Min Park, Andrew Ilyas, Aleksander Madry

We study the problem of (learning) algorithm comparison, where the goal is to find differences between models trained with two different learning algorithms. We begin by formalizing this goal as one of finding distinguishing feature transformations, i.e., input transformations that change the predictions of models trained with one learning algorithm but not

Qihao Ye, Xiaochuan Tian

We design a monotone meshfree finite difference method for linear elliptic equations in the non-divergence form on point clouds via a nonlocal relaxation method. The key idea is a novel combination of a nonlocal integral relaxation of the PDE problem with a robust meshfree discretization on point clouds. Minimal positive stencils are obtained through a local

Alexander M. Dalzell, B. David Clader, Grant Salton, Mario Berta

We study quantum interior point methods (QIPMs) for second-order cone programming (SOCP), guided by the example use case of portfolio optimization (PO). We provide a complete quantum circuit-level description of the algorithm from problem input to problem output, making several improvements to the implementation of the QIPM. We report the number of logical q

Clara Fernandez, Alex Pomarol, Francesco Riva, Francesco Sciotti

The simple analytic structure of meson scattering amplitudes in the large-$N_c$ limit, combined with positivity of the spectral density, provides precise predictions on low-energy observables. Building upon previous studies, we explore the allowed regions of chiral Lagrangian parameters and meson couplings to pions. We reveal a structure of kinks at all orde

Doruk Aksoy, David J. Gorsich, Shravan Veerapaneni, Alex A. Gorodetsky

We present a new algorithm for incrementally updating the tensor train decomposition of a stream of tensor data. This new algorithm, called the {\em tensor train incremental core expansion} (TT-ICE) improves upon the current state-of-the-art algorithms for compressing in tensor train format by developing a new adaptive approach that incurs significantly slow

Alexander Binder, Leander Weber, Sebastian Lapuschkin, Grégoire Montavon

While the evaluation of explanations is an important step towards trustworthy models, it needs to be done carefully, and the employed metrics need to be well-understood. Specifically model randomization testing is often overestimated and regarded as a sole criterion for selecting or discarding certain explanation methods. To address shortcomings of this test

Jason Phang, Yi Mao, Pengcheng He, Weizhu Chen

Fine-tuning large language models for different tasks can be costly and inefficient, and even methods that reduce the number of tuned parameters still require full gradient-based optimization. We propose HyperTuning, a novel approach to model adaptation that uses a hypermodel to generate task-specific parameters for a fixed downstream model. We demonstrate a

Joe D. Morrow, John L. A. Gardner, Volker L. Deringer

Machine learning (ML) approaches enable large-scale atomistic simulations with near-quantum-mechanical accuracy. With the growing availability of these methods there arises a need for careful validation, particularly for physically agnostic models - that is, for potentials which extract the nature of atomic interactions from reference data. Here, we review t

Pedro C. Neto, Ana F. Sequeira, Jaime S. Cardoso, Philipp Terhörst

In the context of biometrics, matching confidence refers to the confidence that a given matching decision is correct. Since many biometric systems operate in critical decision-making processes, such as in forensics investigations, accurately and reliably stating the matching confidence becomes of high importance. Previous works on biometric confidence estima

Cunzhi Zhao, Xingpeng Li, Yan Yao

The installation capacity of energy storage system, especially the battery energy storage system (BESS), has increased significantly in recent years, which is mainly applied to mitigate the fluctuation caused by renewable energy sources (RES) due to the fast response and high round-trip energy efficiency of BESS. The main components of majority of BESSs are

Manas Gogoi, Sambhavi Tiwari, Shekhar Verma

Prototypical network for Few shot learning tries to learn an embedding function in the encoder that embeds images with similar features close to one another in the embedding space. However, in this process, the support set samples for a task are embedded independently of one other, and hence, the inter-class closeness is not taken into account. Thus, in the

Xiaonan Lu, Mark Cannon

We propose a robust adaptive Model Predictive Control (MPC) strategy with online set-based estimation for constrained linear systems with unknown parameters and bounded disturbances. A sample-based test applied to predicted trajectories is used to ensure convergence of parameter estimates by enforcing a persistence of excitation condition on the closed loop

A. C. Caligula do E. S. Pedreira, N. Fraija, A. Galvan-Gamez, B. Betancourt Kamenetskaia

While the dominant radiation mechanism gamma-ray bursts (GRBs) remains a question of debate, synchrotron emission is one of the foremost candidates to describe the multi-wavelength afterglow observations. As such, it is expected that GRBs should present some degree of polarization across their evolution - presenting a feasible means of probing these bursts'

Emil J. Martinec, Stefano Massai, David Turton

The BPS sector in AdS_3/CFT_2 duality has been fertile ground for the exploration of gauge/gravity duality, from the match between black hole entropy and the CFT elliptic genus to the construction of large families of geometrical microstates and the identification of the corresponding states in the CFT. Worldsheet methods provide a tool to further explore th

Xinyu Li

Over the past decades, breakthroughs such as Reinforcement Learning (RL) and Agent-based modeling (ABM) have made simulations of economic models feasible. Recently, there has been increasing interest in applying ABM to study the impact of residential preferences on neighborhood segregation in the Schelling Segregation Model. In this paper, RL is combined wit

Said Mesloub, Hassan Eltayeb Gadian, Lotfi Kasmi

This paper is devoted to the study of the well-posedness of a singular nonlinear fractional pseudo-hyperbolic system. The fractional derivative is described in Caputo sense. The equations are supplemented by classical and nonlocal boundary conditions. Upon some a priori estimates and density arguments, we establish the existence and uniqueness of the strongl

Pedro D. Alvarez, Rafael A. Chavez, Jorge Zanelli

We present a scheme to construct grand unified models based on the superconformal algebra and the inclusion of matter fields in the adjoint representation of supersymmetry. As an illustration, we implemented the Georgi-Glashow $SU(5)$ model. The model predics the existence of a hidden $(\mathbf{1},\mathbf{24},0) + (\mathbf{5},\mathbf{5}^\ast,-y') + (\mathbf{

Paul C Bressloff

In this paper we analyze the narrow capture problem for a single Brownian particle diffusing in a three-dimensional (3D) bounded domain containing a set of small, spherical traps. The boundary surface of each trap is taken to be a semipermeable membrane. That is, the continuous flux across the interface is proportional to an associated jump discontinuity in

Abinash Barthakur, Jakub Karcz, Przemyslaw Kula, Surajit Dhara

The recent discovery of nematic liquid crystals with polar order (ferroelectric nematic) has created immense interest. Despite intensive research, several physical properties of this liquid crystal are yet to be investigated and understood. Here, we report experimental studies on the birefringence and exoelectric coefficient of a polar nematic (NF) liquid cr

Anthony Corso, Kyu-Young Kim, Shubh Gupta, Grace Gao

An important step in the design of autonomous systems is to evaluate the probability that a failure will occur. In safety-critical domains, the failure probability is extremely small so that the evaluation of a policy through Monte Carlo sampling is inefficient. Adaptive importance sampling approaches have been developed for rare event estimation but do not

Sushanth Kini Manjeshwar, Anastasiia Ciers, Fia Hellman, Jürgen Bläsing

Tensile-strained materials have been used to fabricate nano- and micromechanical resonators with ultra-low mechanical dissipation in the kHz to MHz frequency range. These mechanical resonators are of particular interest for force sensing applications and quantum optomechanics at room temperature. Tensile-strained crystalline materials that are compatible wit

Paul C Bressloff

In this paper we consider the diffusive search for a bounded target $\Omega \in \R^d$ with its boundary $\partial \Omega$ totally absorbing. We assume that the target is surrounded by a semipermeable interface given by the closed surface $\partial \calM$ with $\Omega \subset \calM\subset \R^d$. That is, the interface totally surrounds the target and thus par

Hung M. Bui, Kyle Pratt, Alexandru Zaharescu

Erd\H{o}s, Graham, and Selfridge considered, for each positive integer $n$, the least value of $t_n$ so that the integers $n+1, n+2, \dots, n+t_n $ contain a subset the product of whose members with $n$ is a square. An open problem posed by Granville concerns the size of $t_n$, under the assumption of the ABC Conjecture. We establish some results on the dist

Carolina Duczek, Norbert Weber, Omar E. Godinez-Brizuela, Tom Weier

In this work a 1D finite volume based model using coupled meshes is introduced to capture potential and species distribution throughout the discharge process in a lithium bismuth liquid metal battery while neglecting hydrodynamic effects, focusing on the electrochemical properties of the cell and the mass transport in electrolyte and cathode. Interface react

Daniel Chan, Adam Nyman

In this paper we introduce a noncommutative analogue of the notion of linear system, which we call a helix $\underline{\mathcal{L}} := (\mathcal{L}_{i})_{i \in \mathbb{Z}}$ in an abelian category ${\sf C}$ over a quadratic $\mathbb{Z}$-indexed algebra $A$. We show that, under natural hypotheses, a helix induces a morphism of noncommutative spaces from ${\sf

Peter Tingley

These notes are intended as a fairly self contained explanation of Fock space and various algebras that act on it, including a Clifford algebra, a Weyl algebra, an infinite rank matrix algebra, and an affine Kac-Moody algebra. We also discuss how the various algebras are related, and in particular describe the celebrated boson-fermion correspondence. We fini

Jiayi Fu, Jack B Prothero, Jan Hannig

The lottery is a very lucrative industry. Popular fascination often focuses on the largest prizes. However, less attention has been paid to detecting unusual lottery buying behaviors at lower stakes. Our paper introduces a new model to detect illegal discounting in the North Carolina Education Lottery using statistical analysis of net gains and ticket buying

Alexis Goujon, Sebastian Neumayer, Pakshal Bohra, Stanislas Ducotterd

The emergence of deep-learning-based methods to solve image-reconstruction problems has enabled a significant increase in reconstruction quality. Unfortunately, these new methods often lack reliability and explainability, and there is a growing interest to address these shortcomings while retaining the boost in performance. In this work, we tackle this issue