July 2023 arXiv papers — page 115

Avinash Kori, Pedro Sanchez, Konstantinos Vilouras, Ben Glocker

Unsupervised representation learning with variational inference relies heavily on independence assumptions over latent variables. Causal representation learning (CRL), however, argues that factors of variation in a dataset are, in fact, causally related. Allowing latent variables to be correlated, as a consequence of causal relationships, is more realistic a

Boris Khesin, Klas Modin, Luke Volk

We introduce and study a simple model capturing the main features of unbalanced optimal transport. It is based on equipping the conical extension of the group of all diffeomorphisms with a natural metric, which allows a Riemannian submersion to the space of volume forms of arbitrary total mass. We describe its finite-dimensional version and present a concise

Stuart Pelletier, Ruozhou Yu, George Rouskas, Jianqing Liu

Quantum entanglement distillation is a process to extract a small number of high-fidelity entanglement from a large number of low-fidelity ones, which in essence is to trade yield (or survival rate) for fidelity. Among existing distillation approaches, Gisin's local filtering protocol is commonly adopted in photonic quantum systems for distilling entangled p

Nick Brettell, Jelle J. Oostveen, Sukanya Pandey, Daniël Paulusma

We consider a natural generalization of Vertex Cover: the Subset Vertex Cover problem, which is to decide for a graph $G=(V,E)$, a subset $T\subseteq V$ and integer $k$, if $V$ has a subset $S$ of size at most $k$, such that $S$ contains at least one end-vertex of every edge incident to a vertex of $T$. A graph is $H$-free if it does not contain $H$ as an in

Priyanka Goyal, Sohan Patnaik, Adway Mitra, Manjira Sinha

The accurate mapping of crop production is crucial for ensuring food security, effective resource management, and sustainable agricultural practices. One way to achieve this is by analyzing high-resolution satellite imagery. Deep Learning has been successful in analyzing images, including remote sensing imagery. However, capturing intricate crop patterns is

Vladislav Lialin, Namrata Shivagunde, Sherin Muckatira, Anna Rumshisky

Despite the dominance and effectiveness of scaling, resulting in large networks with hundreds of billions of parameters, the necessity to train overparameterized models remains poorly understood, while training costs grow exponentially. In this paper, we explore parameter-efficient training techniques as an approach to training large neural networks. We intr

Jeppe R. Andersen, Pier Francesco Monni, Luca Rottoli, Gavin P. Salam

Multi-parton interactions are a fascinating phenomenon that occur in almost every high-energy hadron--hadron collision, yet are remarkably difficult to study quantitatively. In this letter we present a strategy to optimally disentangle multi-parton interactions from the primary scattering in a collision. That strategy enables probes of multi-parton interacti

Christina Giannitsi, Michael T. Lacey

Let $Sf$ be a discrete martingale square function. Then, for any set $V$ of positive probability, we have $\mathbb{E} S(\mathbf{1}_V)^2 \geq \eta \mathbb{P}(V)$ for an absolute constant $\eta >0$. We extend this to wavelet square functions, and discuss some related open questions.

Emily J. Griffith, David W. Hogg, Julianne J. Dalcanton, Sten Hasselquist

The element abundance pattern found in Milky Way disk stars is close to two-dimensional, dominated by production from one prompt process and one delayed process. This simplicity is remarkable, since the elements are produced by a multitude of nucleosynthesis mechanisms operating in stars with a wide range of progenitor masses. We fit the abundances of 14 ele

Raphael A. P. Oliveira, Francisco F. S. Maia, Beatriz Barbuy, Bruno Dias

The formation of the Magellanic Bridge during an encounter between the Magellanic Clouds $\sim$200 Myr ago would be imprinted in the chemical evolution and kinematics of its stellar population, with sites of active star formation. Since it contains hundreds of stellar clusters and associations, we combined deep photometry from VISCACHA and SMASH surveys to e

H. Sun, C. -W. Wang, J. Yang, B. -B. Zhang

The central engine that powers gamma-ray bursts (GRBs), the most powerful explosions in the universe, is still not identified. Besides hyper-accreting black holes, rapidly spinning and highly magnetized neutron stars, known as millisecond magnetars, have been suggested to power both long and short GRBs. The presence of a magnetar engine following compact sta

Harshank Nimonkar, Suvodip Mukherjee

Accurate measurement of the Hubble constant from standard sirens such as the gravitational wave (GW) sources with electromagnetic counterparts relies on the robust peculiar velocity correction of the redshift of the host galaxy. We show in this work that the peculiar velocity of the host galaxies exhibits a correlation with the properties of the host galaxy

Sarvesh Mangla, Abhirup Datta

The low-latitude ionosphere is a dynamic region with a wide range of disturbances in temporal and spatial scales. The Giant Metrewave Radio Telescope (GMRT) situated in the low-latitude region has demonstrated its ability to detect various ionospheric phenomena. It can detect total electron content (TEC) variation with precision of 1 mTECU and also can measu

Farokh Mivehvar

The Dicke model describes the collective behavior of a sub-wavelength--size ensemble of two-level atoms (i.e., spin-1/2) interacting identically with a single quantized radiation field of a cavity. Across a critical coupling strength it exhibits a zero-temperature phase transition from the normal state to the superradiant phase where the field is populated a

Angelo Russomanno, Giulia Piccitto, Davide Rossini

We study the asymptotic bipartite entanglement entropy of the quantum trajectories of a free-fermionic system, when subject to a continuous nonlocal monitoring. The measurements are described by Gaussian-preserving two-point operators, whose strength decays as a power-law with exponent $\alpha$. Different behaviors of the entanglement entropy with the system

Christian Soto, Trisha Ashley, Andrew J. Fox, Rongmon Bordoloi

The Galactic Center (GC) is surrounded by plasma lobes that extend up to ~14 kpc above and below the plane. Until now, UV absorption studies of these lobes have only focused on high-velocity components (|v_LSR| > 100 km/s) because low- and intermediate-velocity (LIV) components (|v_LSR| <100 km/s) are blended with foreground interstellar medium. To overcome

Pejvak Javaheri, Hanno Rein, Dan Tamayo

We describe the implementation of the symplectic N-body integrator WHFast512 using Single Instruction Multiple Data (SIMD) parallelism and 512-bit Advanced Vector Extensions (AVX512). We are able to speed up integrations of planetary systems by up to 4.7x compared to the non-vectorized version of WHFast. WHFast512 can integrate the Solar System with 8 planet

So-Myoung Park, Kyungwon Chun, Jihye Shin, Hyunjin Jeong

We investigate the fraction of quenched satellite galaxies in host galaxy groups and clusters using TNG300 in the IllustrisTNG cosmological magnetohydrodynamical simulations. Simulations show that most satellites are quenched after they fall into their final hosts: post-processing is a more dominant mechanism of galaxy quenching than pre-processing. We find

Fausto Borgonovi, Felix M. Izrailev, Lea F. Santos

We investigate quench dynamics in a one-dimensional spin model, comparing both quantum and classical descriptions. Our primary focus is on the different timescales involved in the evolution of the observables as they approach statistical relaxation. Numerical simulations, supported by semi-analytical analysis, reveal that the relaxation of single-particle en

Somsubhra Ghosh, K. Sengupta, Indranil Paul

We show that constraints imposed by strong Hilbert space fragmentation (HSF) along with the presence of certain global symmetries can ensure the reality of eigenspectra of non-Hermitian quantum systems; such a reality cannot be guaranteed by global symmetries alone. We demonstrate this insight for two interacting finite chains, namely the fermionic Nelson-Ha

Max Geier, Rubén Seoane Souto, Jens Schulenborg, Serwan Asaad

Bound states in quantum dots coupled to superconductors can be in a coherent superposition of states with different electron number but with the same fermion parity. Electrostatic gating can tune this superposition to a sweet spot, where the quantum dot has the same mean electric charge independent of its electron-number parity. Here, we propose to encode qu

Muteen Munawar, Zain Shabbir, Muhammad Akram

The Dadda algorithm is a parallel structured multiplier, which is quite faster as compared to array multipliers, i.e., Booth, Braun, Baugh-Wooley, etc. However, it consumes more power and needs a larger number of gates for hardware implementation. In this paper, a modified-Dadda algorithm-based multiplier is designed using a proposed half-adder-based carry-s

Zhenhao Song, Urban F. P. Seifert, Zhu-Xi Luo, Leon Balents

In this work, we study a slave-rotor mean-field theory of an extended Hubbard model, applicable to transition metal dichalcogenide moir\'e systems, that captures both the formation of Wigner crystals as well as exotic spin states on top of these charge backgrounds. Phase diagrams are mapped out for different choices of long-range Coulomb repulsion strength,

David Villaseñor, Pablo Barberis-Blostein

We present an analysis of chaos and regularity in the open Dicke model, when dissipation is due to cavity losses. Due to the infinite Liouville space of this model, we also introduce a criterion to numerically find a complex spectrum which approximately represents the system spectrum. The isolated Dicke model has a well-defined classical limit with two degre

José Figueroa-O'Farrill, Alfredo Pérez, Stefan Prohazka

We classify and relate unitary irreducible representations (UIRs) of the Carroll and dipole groups, i.e., we define elementary quantum Carroll and fracton particles and establish a correspondence between them. Whenever possible, we express the UIRs in terms of fields on Carroll/aristotelian spacetime subject to their free field equations. We emphasise that f

Ioannis D. Gialamas, Kyriakos Tamvakis

The bimetric theory of gravity is an extension of general relativity that describes a massive spin-$2$ particle in addition to the standard massless graviton. The theory is based on two dynamical metric tensors with their interactions constrained by requiring the absence of the so-called Boulware-Deser ghost. It has been realized that the quantum interaction

Joel Bregman, Renyue Cen, Yang Chen, Wei Cui

The Hot Universe Baryon Surveyor (HUBS) is a proposed space-based X-ray telescope for detecting X-ray emissions from the hot gas content in our universe. With its unprecedented spatially-resolved high-resolution spectroscopy and large field of view, the HUBS mission will be uniquely qualified to measure the physical and chemical properties of the hot gas in

Jia-Xin Zhang, Chuan Chen, Jian-Hao Zhang, Zheng-Yu Weng

We examine the dynamical magnetic response in a two-component resonating-valence-bond (RVB) description of the doped Mott insulator. The half-filled antiferromagnetic phase described by the Schwinger-boson mean-field theory will evolve into a bosonic-RVB state in the superconducting phase upon doping, where the doped holes introduce another fermionic itinera

Sierra A. Dodd, Arya Nukala, Isabelle Connor, Katie Auchettl

We study the properties of galaxies hosting mid-infrared outbursts in the context of a catalog of five hundred thousand galaxies from the Sloan Digital Sky Survey. We find that nuclear obscuration, as inferred by the surrounding dust mass, does not correlate with host galaxy type, stellar properties (e.g. total mass and mean age), or with the extinction of t

Zachary Reeves, Kevin C. Schlaufman, Henrique Reggiani

It has been suggested that a class of chemically peculiar metal-poor stars called iron-rich metal-poor (IRMP) stars formed from molecular cores with metal contents dominated by thermonuclear supernova nucleosynthesis. If this interpretation is accurate, then IRMP stars should be more common in environments where thermonuclear supernovae were important contri

Shang Ren, John Bonini, Massimiliano Stengel, Cyrus E. Dreyer

In conventional \textit{ab initio} methodologies, phonons are calculated by solving equations of motion involving static interatomic force constants and atomic masses. The Born-Oppenheimer approximation, where all electronic degrees of freedom are assumed to adiabatically follow the nuclear dynamics, is also adopted. This approach does not fully account for

José Ramon Espinosa, Julian Heeck, Mikheil Sokhashvili

Q-balls are bound-state configurations of complex scalars stabilized by a conserved Noether charge Q. They are solutions to a second-order differential equation that is structurally identical to Euclidean vacuum-decay bounce solutions in three dimensions. This enables us to translate the recent tunneling potential approach to Q-balls, which amounts to a refo

Daisuke Kawata, Hajime Kawahara, Naoteru Gouda, Nathan J. Secrest

Japan Astrometry Satellite Mission for INfrared Exploration (JASMINE) is a planned M-class science space mission by the Institute of Space and Astronautical Science, the Japan Aerospace Exploration Agency. JASMINE has two main science goals. One is the Galactic archaeology with Galactic Center Survey, which aims to reveal the Milky Way's central core structu

Daniel Butter, Falk Hassler, Christopher N. Pope, Haoyu Zhang

Using a recently developed formulation of double field theory in superspace, the graviton, $B$-field, gravitini, dilatini, and Ramond-Ramond bispinor are encoded in a single generalized supervielbein. Duality transformations are encoded as orthosymplectic transformations, extending the bosonic $O(D,D)$ duality group, and these act on all constituents of the

Zachary R. Claytor, Jennifer L. van Saders, Lyra Cao, Marc H. Pinsonneault

The TESS mission delivers time-series photometry for millions of stars across the sky, offering a probe into stellar astrophysics, including rotation, on a population scale. However, light curve systematics related to the satellite's 13.7-day orbit have prevented stellar rotation searches for periods longer than 13 days, putting the majority of stars beyond

Eugenio Carretta, Angela Bragaglia

We present the homogeneous abundance analysis for a combined sample of 185 giants in the bulge globular cluster (GC) NGC 6388. Our results are used to describe the multiple stellar populations and differences or analogies with bulge field stars. Proton-capture elements indicate that a single class of first-generation polluters is sufficient to reproduce both

Yi-Ting Tu, Sankar Das Sarma

The experimental work [J. Crossno et al., Science 351, 1058 (2016)], which reported the violation of the Wiedemann-Franz law in monolayer graphene characterized by a sharp peak of the Lorenz ratio at a finite temperature, has not been fully explained. Our previous work [Y.-T. Tu and S. Das Sarma, Phys. Rev. B 107, 085401 (2023)] provided a possible explanati

Karsten Jedamzik, Levon Pogosian

Magnetic fields appear to be present in essentially all astrophysical environments, including galaxies, clusters of galaxies and voids. There are both observational and theoretical motives for considering the possibility of their origin tracing back to the events in the very early universe, such as the electroweak phase transition or Inflation. Such a primor

Jian-Hao Zhang, Ke Ding, Shuo Yang, Zhen Bi

In this work, we study the generalization of decohered average symmetry-protected topological phases to open quantum systems with a combination of subsystem symmetries and global symmetries. In particular, we provide examples of two types of intrinsic average higher-order topological phases with average subsystem symmetries. A classification scheme for these

Tom Monnier, Jake Austin, Angjoo Kanazawa, Alexei A. Efros

Given a set of calibrated images of a scene, we present an approach that produces a simple, compact, and actionable 3D world representation by means of 3D primitives. While many approaches focus on recovering high-fidelity 3D scenes, we focus on parsing a scene into mid-level 3D representations made of a small set of textured primitives. Such representations

Matt Deitke, Ruoshi Liu, Matthew Wallingford, Huong Ngo

Natural language processing and 2D vision models have attained remarkable proficiency on many tasks primarily by escalating the scale of training data. However, 3D vision tasks have not seen the same progress, in part due to the challenges of acquiring high-quality 3D data. In this work, we present Objaverse-XL, a dataset of over 10 million 3D objects. Our d

Roland S. Zimmermann, Thomas Klein, Wieland Brendel

In light of the recent widespread adoption of AI systems, understanding the internal information processing of neural networks has become increasingly critical. Most recently, machine vision has seen remarkable progress by scaling neural networks to unprecedented levels in dataset and model size. We here ask whether this extraordinary increase in scale also

Luchao Qi, Jiaye Wu, Annie N. Wang, Shengze Wang

In recent years, generative 3D face models (e.g., EG3D) have been developed to tackle the problem of synthesizing photo-realistic faces. However, these models are often unable to capture facial features unique to each individual, highlighting the importance of personalization. Some prior works have shown promise in personalizing generative face models, but t

T. F. A. Alves, J. F. da Silva Neto, F. W. S. Lima, G. A. Alves

In this Letter we introduce some field-theoretic approach for computing the critical properties of systems undergoing continuous phase transitions governed by the $\kappa$-generalized statistics, namely $\kappa$-generalized statistical field theory. In particular, we show, by computations through analytic and simulation results, that the $\kappa$-generalized

Chih-Yuan Chiu, Chinmay Maheshwari, Pan-Yang Su, Shankar Sastry

Tolling in traffic networks offers a popular measure to minimize overall congestion. Existing toll designs primarily focus on congestion in route-based traffic assignment models (TAMs), in which travelers make a single route selection from their source to destination. However, these models do not reflect real-world traveler decisions because they preclude de

Siddhartha Jain, Xiaofei Ma, Anoop Deoras, Bing Xiang

Large Language Models (LLMs) can exhibit considerable variation in the quality of their sampled outputs. Reranking and selecting the best generation from the sampled set is a popular way of obtaining strong gains in generation quality. In this paper, we present a novel approach for reranking LLM generations. Unlike other techniques that might involve additio

Wéi Wú, Zhihui Luo, Dao-Xin Yao, Meng Wang

Recently, a bulk nickelate superconductor $\mathrm{La_3Ni_2O_7}$ is discovered at pressures with a remarkable high transition temperature $T_c \sim 80K$. Here, we study a Hubbard model with tight-binding parameters derived from \textit{ab initio} calculations of $\mathrm{La_3Ni_2O_7}$, by employing large scale determinant quantum Monte Carlo and cellular dyn

Shashwat Bhattacharya, Seyed Loghman Sanjari, Dmitry Krasnov, Thomas Boeck

We discuss the effects of nonhomogeneous magnetic fields in liquid metal flows in two different configurations. In the first configuration, we briefly report the impact of fringing magnetic fields in a turbulent Rayleigh-B{\'e}nard convection setup, where it was shown that the global heat transport decreases with an increase of fringe-width. The convective m

Edwin Ng, Ryotatsu Yanagimoto, Marc Jankowski, M. M. Fejer

The propagation of ultrafast pulses in dispersion-engineered waveguides, exhibiting strong field confinement in both space and time, is a promising avenue towards single-photon nonlinearities in an all-optical platform. However, quantum engineering in such systems requires new numerical tools and physical insights to harness their complicated multimode and n

Shraman Pramanick, Yale Song, Sayan Nag, Kevin Qinghong Lin

Video-language pre-training (VLP) has become increasingly important due to its ability to generalize to various vision and language tasks. However, existing egocentric VLP frameworks utilize separate video and language encoders and learn task-specific cross-modal information only during fine-tuning, limiting the development of a unified system. In this work,

Yinghao Xu, Wang Yifan, Alexander W. Bergman, Menglei Chai

Access to high-quality and diverse 3D articulated digital human assets is crucial in various applications, ranging from virtual reality to social platforms. Generative approaches, such as 3D generative adversarial networks (GANs), are rapidly replacing laborious manual content creation tools. However, existing 3D GAN frameworks typically rely on scene repres

Evan Leonard

Xuding Zhu introduced a refined scale of choosability in 2020 and observed that the four color theorem is tight on this scale. We formalize and explore this idea of tightness in what we call strictly colorable graphs. We then characterize all strictly colorable complete multipartite graphs.

Praveen Kumar, Rajarshi Chakrabarti

We perform computer simulations to explore the escape dynamics of a self-propelled (active) nanorod from circular confinements with narrow opening(s). Our results clearly demonstrate how the persistent and directed motion of the nanorod helps it to escape. Such escape events are absent if the nanorod is passive. To quantify the escape dynamics, we compute th

Sam C. Collingbourne

In this paper, we study the canonical energy associated with solutions to the linearised vacuum Einstein equation on a stationary spacetime. The main result of this paper establishes, in the context of the $4$-dimensional Schwarzschild exterior, a direct correspondence between the conservation law satisfied by the canonical energy and the conservation laws d

Sam C. Collingbourne, Gustav Holzegel

We consider the equations of linearised gravity on the Schwarzschild spacetime in a double null gauge. Applying suitably commuted versions of the conservation laws derived in earlier work of the second author we establish control on the gauge invariant Teukolsky quantities $\alpha^{[\pm 2]}$ without any reference to the decoupled Teukolsky wave equation sati

Sascha Gaudlitz

This paper discusses the non-parametric estimation of a non-linear reaction term in a semi-linear parabolic stochastic partial differential equation (SPDE). The estimator's consistency is due to the spatial ergodicity of the SPDE while the time horizon remains fixed. The analysis of the estimation error requires the concentration of spatial averages of non-l

Shoki Sugimoto, Yuto Ashida, Masahito Ueda

A bound state in the continuum (BIC) is a spatially bounded energy eigenstate lying in a continuous spectrum of extended eigenstates. While various types of single-particle BICs have been found in the literature, whether or not BICs can exist in genuinely many-body systems remains inconclusive. Here, we provide numerical and analytical pieces of evidence for

Gen Ye, Alessandra Silvestri

Recently the international pulsar timing array collaboration has announced the first strong evidence for an isotropic gravitational wave background (GWB). We propose that rapid small oscillations (wiggles) in the Hubble parameter would trigger a resonance with the propagating gravitational waves, leaving novel signature in the GWB spectrum in the form of sha

Tomoki Kurikawa, Kunihiko Kaneko

In neural information processing, an input modulates neural dynamics to generate a desired output. To unravel the dynamics and underlying neural connectivity enabling such input-output association, we proposed an exactly soluble neural-network model with a connectivity matrix explicitly consisting of inputs and required outputs. An analytic form of the respo

Ester Hlavnova, Sebastian Ruder

A challenge towards developing NLP systems for the world's languages is understanding how they generalize to typological differences relevant for real-world applications. To this end, we propose M2C, a morphologically-aware framework for behavioral testing of NLP models. We use M2C to generate tests that probe models' behavior in light of specific linguistic

Cristina Camara, Carlos Carteiro. William T. Ross

This paper offers a unified approach to determining when two generalized Toeplitz operators on L^2 are equivalent. This will be done through multipliers between closed subspaces of L^2. Our discussion will include Toeplitz operators (and their duals) on the Hardy space, Hankel operators, asymmetric truncated Toeplitz operators, and dual asymmetric truncated

Stefan Reissl, Ralf S. Klessen, Eric W. Pellegrini, Daniel Rahner

Magnetic fields are of critical importance for our understanding of the origin and long-term evolution of the Milky Way. This is due to their decisive role in the dynamical evolution of the interstellar medium (ISM) and their influence on the star-formation process. Faraday rotation measures (RM) along many different sightlines across the Galaxy are a primar

Gyanendra Sharma, Hiroshi Yasuda, Manuel Kuehner

In order to provide perceptually accurate multimodal feedback during driving situations, it is vital to understand the threshold at which drivers are able to recognize asyncrony between multiple incoming Stimuli. In this work, we investigated and report the \textit{detection threshold} (DT) of asynchrony between audio and haptic feedback, in the context of a

Valery E. Lyubovitskij, Ivan Schmidt

We derive the equations of motion for the bulk-to-boundary propagators of the anti-de Sitter (AdS) boson and fermion fields with arbitrary total angular momentum $J$, in a soft-wall AdS/QCD model and solve it analytically. It provides the opportunity to study transition form factors induced by these bulk-to-boundary propagators, both for on-shell and off-she

Zohreh Aliabadi, Cem Güneri, Tekgül Kalaycı

We study one generator quasi-cyclic codes and four-circulant codes, which are also quasi-cyclic but have two generators. We state the hull dimensions for both classes of codes in terms of the polynomials in their generating elements. We prove results such as the hull dimension of a four-circulant code is even and one-dimensional hull for double-circulant cod

Gabriele Farina, Charilaos Pipis

No-regret learners seek to minimize the difference between the loss they cumulated through the actions they played, and the loss they would have cumulated in hindsight had they consistently modified their behavior according to some strategy transformation function. The size of the set of transformations considered by the learner determines a natural notion o

Xinyi Bai, Steffi Agino Priyanka, Hsiao-Jung Tung, Yuankai Wang

Due to the low accuracy of object detection and recognition in many intelligent surveillance systems at nighttime, the quality of night images is crucial. Compared with the corresponding daytime image, nighttime image is characterized as low brightness, low contrast and high noise. In this paper, a bio-inspired image enhancement algorithm is proposed to conv

Juhi Chaudhary, Meirav Zehavi

A matching $M$ in a graph $G$ is an \emph{acyclic matching} if the subgraph of $G$ induced by the endpoints of the edges of $M$ is a forest. Given a graph $G$ and a positive integer $\ell$, Acyclic Matching asks whether $G$ has an acyclic matching of size (i.e., the number of edges) at least $\ell$. In this paper, we first prove that assuming $\mathsf{W[1]\n

Ryan Liu, Steven Jecmen, Vincent Conitzer, Fei Fang

Peer review frequently follows a process where reviewers first provide initial reviews, authors respond to these reviews, then reviewers update their reviews based on the authors' response. There is mixed evidence regarding whether this process is useful, including frequent anecdotal complaints that reviewers insufficiently update their scores. In this study

Jianxiu Li, Urbashi Mitra

In this paper, a channel state information (CSI)-free, fake path injection (FPI) scheme is proposed for location-privacy preservation. By leveraging the geometrical feasibility of the fake paths, under mild conditions, it can be proved that the illegitimate device cannot distinguish between a fake and true path, thus degrading the illegitimate devices' abili

Oliver Janzer, Benny Sudakov

For $2\leq s<t$, the Erd\H{o}s-Rogers function $f_{s,t}(n)$ measures how large a $K_s$-free induced subgraph there must be in a $K_t$-free graph on $n$ vertices. There has been an extensive amount of work towards estimating this function, but until very recently only the case $t=s+1$ was well understood. A recent breakthrough of Mattheus and Verstra\"ete on

Abhinav Joshi, Susmit Agrawal, Ashutosh Modi

Sign languages are the primary means of communication for many hard-of-hearing people worldwide. Recently, to bridge the communication gap between the hard-of-hearing community and the rest of the population, several sign language translation datasets have been proposed to enable the development of statistical sign language translation systems. However, ther

Nic Fishman, Leo Klarner, Emile Mathieu, Michael Hutchinson

Denoising diffusion models have recently emerged as the predominant paradigm for generative modelling on image domains. In addition, their extension to Riemannian manifolds has facilitated a range of applications across the natural sciences. While many of these problems stand to benefit from the ability to specify arbitrary, domain-informed constraints, this

A. J. Newman, S. M. Graham, A. M. Edmonds, D. J. Twitchen

Vector magnetometry provides more information than scalar measurements for magnetic surveys utilized in space, defense, medical, geological and industrial applications. These areas would benefit from a mobile vector magnetometer that can operate in extreme conditions. Here we present a scanning fiber-coupled nitrogen vacancy (NV) center vector magnetometer.

George Webber

Making contactless payments using a smartwatch is increasingly popular, but this payment medium lacks traditional biometric security measures such as facial or fingerprint recognition. In 2022, Sturgess et al. proposed WatchAuth, a system for authenticating smartwatch payments using the physical gesture of reaching towards a payment terminal. While effective

Stefan Ivanov, Alexander Petkov

It is shown that on compact $Spin(7)$--manifold with exterior derivative of the Lee form lying in the Lie algebra $spin(7)$ the curvature $R$ of the $Spin(7)$--torsion connection $R\in S^2\Lambda^2$ with vanishing Ricci tensor if and only if the $3$-form torsion is parallel with respect to the Levi-Civita connection. It is also proved that $R$ satisfies the

Vincent Pecastaing

We consider conformal actions of solvable Lie groups on closed Lorentzian manifolds. With anterior results in which we addressed similar questions for semi-simple Lie group actions, this work contributes to the understanding of the identity component $G$ of the conformal group of closed Lorentzian manifolds. In the first part of the article, we prove that $G

Michal Golovanevsky, Eva Schiller, Akira Nair, Eric Han

Multimodal learning models have become increasingly important as they surpass single-modality approaches on diverse tasks ranging from question-answering to autonomous driving. Despite the importance of multimodal learning, existing efforts focus on NLP applications, where the number of modalities is typically less than four (audio, video, text, images). How

Eric Parish, Payton Lindsay, Timothy Shelton, John Mersch

We present a machine-learning strategy for finite element analysis of solid mechanics wherein we replace complex portions of a computational domain with a data-driven surrogate. In the proposed strategy, we decompose a computational domain into an "outer" coarse-scale domain that we resolve using a finite element method (FEM) and an "inner" fine-scale domain

Shah Mohammad Bahauddin, Mark Peter Rast

In this paper we refine a previously developed acoustic-source filter (Bahauddin & Rast 2021), improving its reliability and extending its capabilities. We demonstrate how to fine-tune the filter to meet observational constraints and to focus on specific wavefront speeds. This refinement enables discrimination of acoustic-source depths and tracking of local-

Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman

Machine learning for differential equations paves the way for computationally efficient alternatives to numerical solvers, with potentially broad impacts in science and engineering. Though current algorithms typically require simulated training data tailored to a given setting, one may instead wish to learn useful information from heterogeneous sources, or f

Emile Mathieu, Vincent Dutordoir, Michael J. Hutchinson, Valentin De Bortoli

Denoising diffusion models have proven to be a flexible and effective paradigm for generative modelling. Their recent extension to infinite dimensional Euclidean spaces has allowed for the modelling of stochastic processes. However, many problems in the natural sciences incorporate symmetries and involve data living in non-Euclidean spaces. In this work, we

Y. Liu, R. Weisberg, S. Vignudelli, L. Roblou

The performance of coastal altimetry over a wide continental shelf is assessed using multiple-year ocean current observations by moored Acoustic Doppler Current Profilers (ADCP) and high frequency (HF) radar on the West Florida Shelf. Across track, surface geostrophic velocity anomalies, derived from the XTRACK along-track sea level anomalies are compared wi

Gil Silva, Andreia Mordido, Vasco T. Vasconcelos

Context-free session types describe structured patterns of communication on heterogeneously-typed channels, allowing the specification of protocols unconstrained by tail recursion. The enhanced expressive power provided by non-regular recursion comes, however, at the cost of the decidability of subtyping, even if equivalence is still decidable. We present an

Sanjoy Chatterjee, Sushil Gorai

In this paper, we prove that the closure of a bounded pseudoconvex domain, which is spirallike with respect to a globally asymptotic stable holomorphic vector field, is polynomially convex. We also provide a necessary and sufficient condition, in terms of polynomial convexity, on a univalent function defined on a strongly convex domain for embedding it into

Giovanni Amelino-Camelia, Domenico Frattulillo, Giulia Gubitosi, Giacomo Rosati

Studies of in-vacuo dispersion are the most active area of quantum-gravity phenomenology. The way in which in-vacuo dispersion produces redshift-dependent corrections to the time of flight of astrophysics particles depends on the model-dependent interplay between Planck-scale effects and spacetime curvature/expansion, and we here derive the most general form

Eurico Covas

For both public and private firms, comparable companies' analysis is widely used as a method for company valuation. In particular, the method is of great value for valuation of private equity companies. The several approaches to the comparable companies' method usually rely on a qualitative approach to identifying similar peer companies, which tend to use es

Martin Helmer, Anton Leykin, Vidit Nanda

We describe new algorithms to compute Whitney stratifications of real algebraic varieties. Using either conormal or polar techniques, these algorithms stratify a complexification of a given real variety. We then show that the resulting stratification can be described by real polynomials. We also extend these methods to stratification problems involving the s

Mohammad Ansari

We apply the well-known and also the newly introduced notions from bounded linear dynamics to unbounded linear operators. We present a hypermixing criterion similar to that given for bounded linear operators and then we show that the derivative operator in $H^2$, the Laplacian operator in $L^2(\Omega)$, and all unbounded weighted translations in $L_p(0,\inft

George B. Field, Sean M. Carroll

We argue that if axions are the dark matter, their coupling to electromagnetism results in exponential growth of a helical magnetic field when the axion field first rolls down its potential. After an inverse cascade, the relevant length scales to day are of order 10-100 kpc, of astrophysical interest. Our mechanism for allowing the field to grow relies on a

Pei-Hong Gu

In the standard model QCD Lagrangian, a term of CP violating gluon density is theoretically expected to have a physical coefficient $\bar{\theta}$ of the order of unity. However, the upper bound on the electric dipole moment of neutron enforces the value of $\bar{\theta}$ to be extremely small. Such a huge gap between theoretical expectation and experimental

Duligur Ibeling, Thomas Icard, Krzysztof Mierzewski, Milan Mossé

This paper explores the space of (propositional) probabilistic logical languages, ranging from a purely `qualitative' comparative language to a highly `quantitative' language involving arbitrary polynomials over probability terms. While talk of qualitative vs. quantitative may be suggestive, we identify a robust and meaningful boundary in the space by distin

Tomer Avrahami, Ofer Amrani, Avishai Wool

A shared secret key is necessary for encrypted communications. Since Wi-Fi relies on OFDM, we suggest a method to generate such a key by utilizing Wi-Fi's channel state information (CSI). CSI is typically reciprocal but very sensitive to location: While the legitimate Alice and Bob observe the same CSI, an eavesdropper Eve observes an uncorrelated CSI when p

Hao Fu, Prashanth Krishnamurthy, Siddharth Garg, Farshad Khorrami

This paper proposes a data-efficient detection method for deep neural networks against backdoor attacks under a black-box scenario. The proposed approach is motivated by the intuition that features corresponding to triggers have a higher influence in determining the backdoored network output than any other benign features. To quantitatively measure the effec

Matheus Bernini-Peron, Wagner L. F. Marcolino, Andreas A. C. Sander, Jean-Claude Bouret

B supergiants (BSGs) are evolved stars with effective temperatures between 10 to 30 kK and are important to understand massive star evolution. Located on the edge of the line-driven wind regime, the study of their atmospheres is helpful to understand phenomena such as the bi-stability jump. Key UV features of their spectra have so far not been reproduced by

Alexey Galda, Eesh Gupta, Jose Falla, Xiaoyuan Liu

The quantum approximate optimization algorithm (QAOA) is one of the most promising candidates for achieving quantum advantage through quantum-enhanced combinatorial optimization. A near-optimal solution to the combinatorial optimization problem is achieved by preparing a quantum state through the optimization of quantum circuit parameters. Optimal QAOA param

Pedro Enrique Iturria-Rivera, Marcel Chenier, Bernard Herscovici, Burak Kantarci

Dense and unplanned IEEE 802.11 Wireless Fidelity(Wi-Fi) deployments and the continuous increase of throughput and latency stringent services for users have led to machine learning algorithms to be considered as promising techniques in the industry and the academia. Specifically, the ongoing IEEE 802.11be EHT -- Extremely High Throughput, known as Wi-Fi 7 --

Alberto Domínguez Corella, Gerd Wachsmuth

We analyse the role of the bang-bang property in affine optimal control problems. We show that many essential stability properties of affine problems are only satisfied when minimizers are bang-bang. Moreover, we prove that almost any perturbation in an affine optimal control problem leads to a bang-bang strict global minimizer. We work in an abstract framew

Jonathon Riddell, Nathan Pagliaroli

In this article we investigate no-resonance conditions for quantum many body chaotic systems and random matrix models. No-resonance conditions are properties of the spectrum of a model, usually employed as a theoretical tool in the analysis of late time dynamics. The first order no-resonance condition holds when a spectrum is non-degenerate, while higher ord

Yuanjian Liu, Sheng Di, Kyle Chard, Ian Foster

The increasing volume and velocity of science data necessitate the frequent movement of enormous data volumes as part of routine research activities. As a result, limited wide-area bandwidth often leads to bottlenecks in research progress. However, in many cases, consuming applications (e.g., for analysis, visualization, and machine learning) can achieve acc