February 2023 arXiv papers — page 2

Hongyan Mei, Guodong Ren, Boyang Zhao, Jad Salman

In modern optics, materials with large birefringence ({\Delta}n, where n is the refractive index) are sought after for polarization control (e.g. in wave plates, polarizing beam splitters, etc.), nonlinear optics and quantum optics (e.g. for phase matching and production of entangled photons), micromanipulation, and as a platform for unconventional light-mat

Dezhao Luo, Jiabo Huang, Shaogang Gong, Hailin Jin

The correlation between the vision and text is essential for video moment retrieval (VMR), however, existing methods heavily rely on separate pre-training feature extractors for visual and textual understanding. Without sufficient temporal boundary annotations, it is non-trivial to learn universal video-text alignments. In this work, we explore multi-modal c

Junjie Yang, Xuxi Chen, Tianlong Chen, Zhangyang Wang

Learning to Optimize (L2O) has drawn increasing attention as it often remarkably accelerates the optimization procedure of complex tasks by ``overfitting" specific task type, leading to enhanced performance compared to analytical optimizers. Generally, L2O develops a parameterized optimization method (i.e., ``optimizer") by learning from solving sample probl

Prateek Anand, Ganesh Subramanian

We study the cross-stream inertial migration of a torque-free neutrally buoyant spheroid, of an arbitrary aspect ratio $\kappa$, in wall-bounded plane Poiseuille flow for small particle Reynolds numbers\,($Re_p\ll1$) and confinement ratios\,($\lambda\ll1$), with the channel Reynolds number, $Re_c = Re_p/\lambda^2$, assumed to be arbitrary; here, $\lambda=L/H

Saurish Chakrabarty

We use a simple physics-inspired model to get an idea about how to enhance the speed with which a society becomes educated if we strategically place our knowledge spreading centers (teachers or educational institutions). We study knowledge spreading using the Ising model, a well-studied model used in physics, specifically statistical mechanics, to describe t

Rajarshi Saha, Mohamed Seif, Michal Yemini, Andrea J. Goldsmith

This work considers the problem of Distributed Mean Estimation (DME) over networks with intermittent connectivity, where the goal is to learn a global statistic over the data samples localized across distributed nodes with the help of a central server. To mitigate the impact of intermittent links, nodes can collaborate with their neighbors to compute local c

Uddipan Banik, Frank C. van den Bosch, Martin D. Weinberg

We develop a linear perturbative formalism to compute the response of an inhomogeneous stellar disk embedded in a non-responsive dark matter halo to perturbations like bars, spiral arms and satellite galaxy encounters. Without self-gravity to reinforce it, the response of a Fourier mode phase mixes away due to an intrinsic spread in the vertical ($\Omega_z$)

Franco Flandoli, Silvia Morlacchi, Andrea Papini

The effect of transport noise on a 2D fluid may depend on the space-scale of the noise. We investigate numerically the dissipation properties of very small-scale transport noise. As a test problem we consider the Kelvin-Helmholtz instability and we compare the inviscid case, the viscous one, both without noise, and the inviscid case perturbed by transport no

Mohammed S. Al-Abiad, Md. Zoheb Hassan, Md. Jahangir Hossain

It is anticipated that aerial-terrestrial integrated networks incorporating unmanned aerial vehicles (UAVs) mounted relays will offer improved coverage and connectivity in the beyond 5G era. Meanwhile, federated learning (FL) is a promising distributed machine learning technique for building inference models over wireless networks due to its ability to maint

Konstantinos Iordanou, Timothy Atkinson, Emre Ozer, Jedrzej Kufel

A typical machine learning (ML) development cycle for edge computing is to maximise the performance during model training and then minimise the memory/area footprint of the trained model for deployment on edge devices targeting CPUs, GPUs, microcontrollers, or custom hardware accelerators. This paper proposes a methodology for automatically generating predic

Erik Lindborg

Claims made by Zhu et al., PRL 120, 144502, (2018), that they had found evidence of a transition to the so called "ultimate regime" in 2D simulations of Rayleigh-B\'enard convection, have recently been repeated by Lohse & Shishkina, Rev. Mod. Phys. 96, 03501 (2024). The author questions the validity of these claims.

Moshir Harsh, Peter Sollich

We present a method that captures the fluctuations beyond mean field in chemical reactions in the regime of small copy numbers and hence large fluctuations, using self-consistently determined memory: by integrating information from the past we can systematically improve our approximation for the dynamics of chemical reactions. This memory emerges from a pert

Kalvik Jakkala, Srinivas Akella

The sensor placement problem is a common problem that arises when monitoring correlated phenomena, such as temperature, precipitation, and salinity. Existing approaches to this problem typically formulate it as the maximization of information metrics, such as mutual information~(MI), and use optimization methods such as greedy algorithms in discrete domains,

Diego Cordoba, Alberto Enciso, Nastasia Grubic

We show that the water waves system is locally wellposed in weighted Sobolev spaces which allow for interfaces with corners. No symmetry assumptions are required. These singular points are not rigid: if the initial interface exhibits a corner, it remains a corner but generically its angle changes. Using a characterization of the asymptotic behavior of the fl

Giampaolo Folena, Francesco Zamponi

The weak ergodicity breaking hypothesis postulates that out-of-equilibrium glassy systems lose memory of their initial state despite being unable to reach an equilibrium stationary state. It is a milestone of glass physics, and has provided a lot of insight on the physical properties of glass aging. Despite its undoubted usefulness as a guiding principle, it

Lukas J. Furtak, Ramesh Mainali, Adi Zitrin, Adèle Plat

We report the discovery of a triply imaged active galactic nucleus (AGN), lensed by the galaxy cluster MACS J0035.4-2015 ($z_{\mathrm{d}}=0.352$). The object is detected in Hubble Space Telescope imaging taken for the RELICS program. It appears to have a quasi-stellar nucleus consistent with a point-source, with a de-magnified radius of $r_e\lesssim100$ pc.

Kevin P. Nuckolls, Ryan L. Lee, Myungchul Oh, Dillon Wong

Interactions among electrons create novel many-body quantum phases of matter with wavefunctions that often reflect electronic correlation effects, broken symmetries, and novel collective excitations. A wide range of quantum phases has been discovered in MATBG, including correlated insulating, unconventional superconducting, and magnetic topological phases. T

Yuri Cacchió

We consider the two-dimensional, $\beta$-plane, vorticity equations for an incompressible flow, where the zonally averaged flow varies on scales much larger than the perturbation. We prove global existence and uniqueness of the solution to the equations on periodic settings.

Juan Pablo Yañez, Anatoli Fedynitch

In this paper, we present a refined calculation of the atmospheric neutrino flux spanning from GeV to PeV energies. Our method, Daemonflux, utilizes data-driven inputs and incorporates adjustable parameters to take their uncertainties into account. By optimizing these parameters using a combination of muon data and constraints from fixed-target experiments,

Saurish Chakrabarty, Zohar Nussinov

We discuss our recent study of local quantum mechanical uncertainty relations in quantum many body systems. These lead to fundamental bounds for quantities such as the speed, acceleration, relaxation times, spatial gradients and the Lyapunov exponents. We additionally obtain bounds on various transport coefficients like the viscosity, the diffusion constant,

F. M. Vincentelli, J. Neilsen, A. J. Tetarenko, Y. Cavecchi

Accretion disks around compact objects are expected to enter an unstable phase at high luminosity. One instability may occur when the radiation pressure generated by accretion modifies the disk viscosity, resulting in the cyclic depletion and refilling of the inner disk on short timescales. Such a scenario, however, has only been quantitatively verified for

G. Surcis, W. H. T. Vlemmings, C. Goddi, J. M. Torrelles

Several radio sources have been detected in the HMSFR W75N(B), among them the massive YSOs VLA1 and VLA2 are of great interest. These are thought to be in different evolutionary stages. In particular, VLA1 is at the early stage of the photoionization and it is driving a thermal radio jet, while VLA2 is a thermal, collimated ionized wind surrounded by a dusty

Sean McBride, Fernando Iniguez

It was recently noted that the entanglement entropy for a subsystem of a chaotic eigenstate exhibits an enhanced correction when the subsystem approaches a phase transition at half the total system size. This enhanced correction was derived for general subsystems by Dong and Wang by summing over noncrossing permutations, which can be thought of as ``saddles'

Chetan Deshmukh, Eduardo Beattie, Bernardo Casabone, Samuele Grandi

Many quantum information protocols require the storage and manipulation of information over long times, and its exchange between nodes of a quantum network across long distances. Implementing these protocols requires an advanced quantum hardware, featuring, for example, a register of long-lived and interacting qubits with an efficient optical interface in th

Sofia Feltzing, Diane Feuillet

We have for the first time identified the early stellar disk in the Milky Way by using a combination of elemental abundances and kinematics. Using data from APOGEE DR17 and Gaia we select stars in the Mg-Mn-Al-Fe plane with elemental abundances indicative of accreted origin and find stars with both halo-like and disk-like kinematics. The stars with halo-like

Vladimir Strokov, Giacomo Fragione, Emanuele Berti

Galactic nuclei are potential hosts for intermediate-mass black holes (IMBHs), whose gravitational field can affect the motion of stars and compact objects. The absence of observable perturbations in our own Galactic Centre has resulted in a few constraints on the mass and orbit of a putative IMBH. Here, we show that the Laser Interferometer Space Antenna (L

Asher Berlin, Roni Harnik, Ryan Janish

A kinetically-mixed hidden photon is sourced as an evanescent mode by electromagnetic fields that oscillate at a frequency smaller than the hidden photon mass. These evanescent modes fall off exponentially with distance, but nevertheless yield detectable signals in a photon regeneration experiment if the electromagnetic barrier is made sufficiently thin. We

János Takátsy, Péter Kovács, György Wolf, Jürgen Schaffner-Bielich

The existence of quark matter inside the heaviest neutron stars has been the topic of numerous recent studies, many of them suggesting that a phase transition to strongly interacting conformal matter inside neutron stars is feasible. Here we examine this hybrid star scenario using a soft and a stiff hadronic model, a constituent quark model with three quark

Alexandre Emsenhuber, Christoph Mordasini, Remo Burn

Planetary population synthesis is a tool to understand the physics of planetary system formation. It builds on a model that includes a multitude of physical processes. The outcome can be statistically compared with exoplanet observations. Here, we review the population synthesis method and then use one population to explore how different planetary system arc

Gabriel-Dominique Marleau, Yuhiko Aoyama

Aoyama et al. (2021, ApJL) provided scaling relations between hydrogen-line luminosities and the accretion luminosity for planetary-mass objects. These fits should be an improvement over blind extrapolations of stellar relations. The fits go up only to the n = 8 electron energy level, but higher-n Balmer lines have been observed in the near-UV at Delorme 1 (

Nora L. Strotjohann, Eran O. Ofek, Avishay Gal-Yam, Jesper Sollerman

The direct detection of core-collapse supernova (SN) progenitor stars is a powerful way of probing the last stages of stellar evolution. However, detections in archival Hubble Space Telescope images are limited to about one per year. Here, we explore whether we can increase the detection rate by using data from ground-based wide-field surveys. Due to crowdin

M. Libralato, A. Bellini, R. P. van der Marel, J. Anderson

We develop and disseminate effective point-spread functions and geometric-distortion solutions for high-precision astrometry and photometry with the JWST NIRISS instrument. We correct field dependencies and detector effects, and assess the quality and the temporal stability of the calibrations. As a scientific application and validation, we study the proper

Adam M. Dillamore, Vasily Belokurov, N. Wyn Evans, Elliot Y. Davies

Using data from the Gaia satellite's Radial Velocity Spectrometer Data Release 3 (RVS, DR3), we find a new and robust feature in the phase space distribution of halo stars. It is a prominent ridge at constant energy and with angular momentum $L_z>0$. We run test particle simulations of a stellar halo-like distribution of particles in a realistic Milky Way po

Farzan Vafa, L. Mahadevan

Inspired by epithelial morphogenesis, we consider a minimal model for the shaping of a surface driven by $p$-atic topological defects. We show that a positive (negative) defect can dynamically generate a (hyperbolic) cone whose shape evolves diffusively, and predict that a defect of charge $+1/p$ leads to a final semi-cone angle $\beta$ which satisfies the i

Tiger Lu, Hanno Rein, Daniel Tamayo, Sam Hadden

We have introduced self-consistent spin, tidal and dynamical equations of motion into REBOUNDx, a library of additional effects for the popular N-body integrator REBOUND. The equations of motion used are derived from the constant time lag approximation to the equilibrium tide model of tidal friction. These effects will allow the study of a variety of systems

Matthew Ho, John Soltis, Arya Farahi, Daisuke Nagai

We evaluate the effectiveness of deep learning (DL) models for reconstructing the masses of galaxy clusters using X-ray photometry data from next-generation surveys. We establish these constraints using a catalogue of realistic mock eROSITA X-ray observations which use hydrodynamical simulations to model realistic cluster morphology, background emission, tel

Daniele De Bernardis, Francesco Piccioli, Peter Rabl, Iacopo Carusotto

We study light-matter interactions in the bulk of a two-dimensional photonic lattice system, where photons are subject to the combined effect of a synthetic magnetic field and an orthogonal synthetic electric field. In this configuration, chiral waveguide modes appear in the bulk region of the lattice, in direct analogy to transverse Hall currents in electro

Pavel Putrov, Juven Wang

In the Standard Model, some combination of the baryon $\bf B$ and lepton $\bf L$ number symmetry is free of mixed anomalies with strong and electroweak $su(3) \times su(2) \times u(1)_{\tilde Y}$ gauge forces. However, it can still suffer from a mixed gravitational anomaly, hypothetically pertinent to leptogenesis in the very early universe. This happens whe

John Joseph M. Carrasco, Aslan Seifi

We find that unitarity cuts and the duality between color and kinematics are sufficient constraints to bootstrap $D$-dimensional QCD scattering amplitudes starting from three-particle tree-level. Specifically, we calculate tree level amplitudes through six-points, as well as the four-point one-loop correction for massive fermions in the fundamental represent

Prabhanjan Ananth, Alexander Poremba, Vinod Vaikuntanathan

Quantum cryptography leverages many unique features of quantum information in order to construct cryptographic primitives that are oftentimes impossible classically. In this work, we build on the no-cloning principle of quantum mechanics and design cryptographic schemes with key-revocation capabilities. We consider schemes where secret keys are represented a

Lior Yariv, Peter Hedman, Christian Reiser, Dor Verbin

We present a method for reconstructing high-quality meshes of large unbounded real-world scenes suitable for photorealistic novel view synthesis. We first optimize a hybrid neural volume-surface scene representation designed to have well-behaved level sets that correspond to surfaces in the scene. We then bake this representation into a high-quality triangle

Boris Daszuta

Compact finite-difference (FD) schemes specify derivative approximations implicitly, thus to achieve parallelism with domain-decomposition suitable partitioning of linear systems is required. Consistent order of accuracy, dispersion, and dissipation is crucial to maintain in wave propagation problems such that deformation of the associated spectra of the dis

J. A. Scott Kelso

In contrast to the critical brain hypothesis in which the brain tunes itself to a critical point between $states$ of chaos and order, analysis of Coordination Dynamics suggests that a vast repertoire of $coexisting$ $tendencies$ exists for regions of the brain to integrate and segregate at the same time. Rather than teetering between order and randomness, th

Aditya N. Singh, David T. Limmer

We present a time dependent variational method to learn the mechanisms of equilibrium reactive processes and efficiently evaluate their rates within a transition path ensemble. This approach builds off variational path sampling methodology by approximating the time dependent commitment probability within a neural network ansatz. The reaction mechanisms infer

Eddie Harris-Lee, John Kay Dewhurst, Peter Elliott, Sam Shallcross

In highly out-of-equilibrium states of matter, such as those induced by a pump laser, the applicability of well established spectroscopic probes of magnetic order are called into question. Here we address the validity of x-ray absorption techniques in pump laser conditions, focusing on magnetic linear dichroism (MLD), a crucial probe of antiferromagnetic (AF

Shuqiu Wang, Niall Kennedy, Kazuhiro Fujita, Shin-ichi Uchida

The primordial ingredient of cuprate superconductivity is the CuO2 unit cell. Here, theoretical attention usually concentrates on the intra-atom Coulombic interactions dominating the 3d^9 and 3d^10 configurations of each copper ion. However, if Coulombic interactions also occur between electrons of the 2p^6 orbitals of each planar oxygen atom, spontaneous or

Yunsong Zhang, Herbert Levine, Yanxiang Zhao

A phase field approach is proposed to model the chemotaxis of Dictyostelium discoideum. In this framework, motion is controlled by active forces as determined by the Meinhardt model of chemical dynamics which is used to simulate directional sensing during chemotaxis. Then, the movement of the cell is achieved by the phase field dynamics, while the reaction-d

Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

We give the first efficient algorithm for learning halfspaces in the testable learning model recently defined by Rubinfeld and Vasilyan (2023). In this model, a learner certifies that the accuracy of its output hypothesis is near optimal whenever the training set passes an associated test, and training sets drawn from some target distribution -- e.g., the Ga

Franklin Kenter, Erin Meger, Jérémie Turcotte

Andreae (1986) proved that the cop number of connected $H$-minor-free graphs is bounded for every graph $H$. In particular, the cop number is at most $|E(H-h)|$ if $H-h$ contains no isolated vertex, where $h\in V(H)$. The main result of this paper is an improvement on this bound, which is most significant when $H$ is small or sparse, for instance when $H-h$

Nick Dorey, Rishi Mouland

We study a limit in which a relativistic CFT reduces to conformal quantum mechanics, and relate the partition functions of the two theories. When the initial CFT is holographic, our limit coincides with an ultra-spinning limit in the gravity dual. We therefore propose that ultra-spinning black holes are dual to an appropriate ensemble in finite-dimensional c

Douglas Svensson Seth

We consider a multi-fluid system with several free interfaces. For this system we prove existence of three-dimensional steady gravity-capillary waves with non-zero vorticity. We obtain non-zero vorticity by prescribing the relative velocity fields to be Beltrami fields, for which the vorticity and velocity are parallel. The main result is a multi-parameter b

Ellen C. Czaplinski, Tuan H. Vu, Morgan L. Cable, Mathieu Choukroun

Titan, Saturn's largest moon, has a plethora of organic compounds in the atmosphere and on the surface that interact with each other. Cryominerals such as co-crystals may influence the geologic processes and chemical composition of Titan's surface, which in turn informs our understanding of how Titan may have evolved, how the surface is continuing to change,

Eanna E. Flanagan

In 2011 Blanchet and Marsat suggested a fully relativistic version of Milgrom's modified Newtonian dynamics (MOND) in which the dynamical degrees of freedom consist of the spacetime metric and a foliation of spacetime, the khronon field. This theory is simpler than the alternative relativsitic formulations. We show that the theory has a consistent non-relati

Akash Biswas, Bidya Karak, Ilya Usoskin, Eckhard Weisshaar

Solar activity has a cyclic nature with the ~11-year Schwabe cycle dominating its variability on the interannual timescale. However, solar cycles are significantly modulated in length, shape and magnitude, from near-spotless grand minima to very active grand maxima. The ~400-year-long direct sunspot-number series is inhomogeneous in quality and too short to

Zijian Liu, Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene

In this work, we describe a generic approach to show convergence with high probability for both stochastic convex and non-convex optimization with sub-Gaussian noise. In previous works for convex optimization, either the convergence is only in expectation or the bound depends on the diameter of the domain. Instead, we show high probability convergence with b

Tyler Chen, Thomas Trogdon

We study the stability of the Lanczos algorithm run on problems whose eigenvector empirical spectral distribution is near to a reference measure with well-behaved orthogonal polynomials. We give a backwards stability result which can be upgraded to a forward stability result when the reference measure has a density supported on a single interval with square

Charles F. Doran, Andrew Harder, Eric Pichon-Pharabod, Pierre Vanhove

We study the geometry and Hodge theory of the cubic hypersurfaces attached to two-loop Feynman integrals for generic physical parameters. We show that the Hodge structure attached to planar two-loop Feynman graphs decomposes into mixed Tate pieces and the Hodge structures of families of hyperelliptic, elliptic, or rational curves depending on the space-time

Angelica Chen, David M. Dohan, David R. So

Given the recent impressive accomplishments of language models (LMs) for code generation, we explore the use of LMs as adaptive mutation and crossover operators for an evolutionary neural architecture search (NAS) algorithm. While NAS still proves too difficult a task for LMs to succeed at solely through prompting, we find that the combination of evolutionar

Andreas Hohl

We study extension of scalars for sheaves of vector spaces, assembling results that follow from well-known statements about vector spaces, but also developing some complements. In particular, we formulate Galois descent in this context, and we also discuss the case of derived categories and perverse sheaves. Most of the results are not new, but our aim is to

Lander Vanroye, Joris De Schutter, Wilm Decré

This paper introduces a generalization of the well-known Riccati recursion for solving the discrete-time equality-constrained linear quadratic optimal control problem. The recursion can be used to compute the solutions as well as optimal feedback control policies. Unlike other tailored approaches for this problem class, the proposed method does not require r

Om Shah, Krti Tallam

In many developing nations, a lack of poverty data prevents critical humanitarian organizations from responding to large-scale crises. Currently, socioeconomic surveys are the only method implemented on a large scale for organizations and researchers to measure and track poverty. However, the inability to collect survey data efficiently and inexpensively lea

Arya Tanmay Gupta, Sandeep S Kulkarni

Consider the execution of a sequential algorithm that requires the program to converge to an optimal state, and then terminate/stutter. To design such an algorithm, we need to ensure that the state space that it traverses forms a directed acyclic graph (DAG) and its sink nodes are optimal states. However, if we run the same algorithm on multiple computing no

Carolin Schmidt, Daniele Gammelli, Francisco Camara Pereira, Filipe Rodrigues

Autonomous Mobility-on-Demand (AMoD) systems are an evolving mode of transportation in which a centrally coordinated fleet of self-driving vehicles dynamically serves travel requests. The control of these systems is typically formulated as a large network optimization problem, and reinforcement learning (RL) has recently emerged as a promising approach to so

Manuel Grande, Linli Guo, Michel Blanc, Advenit Makaya

The main objective of this chapter is to present an overview of the different areas of key technologies that will be needed to fly the technically most challenging of the representative missions identified in chapter 4 (the Pillar 2 Horizon 2061 report). It starts with a description of the future scientific instruments which will address the key questions of

Meshia Cédric Oveneke, Rucha Vaishampayan, Deogratias Lukamba Nsadisa, Jenny Ambukiyenyi Onya

This work proposes to solve the problem of few-shot biometric authentication by computing the Mahalanobis distance between testing embeddings and a multivariate Gaussian distribution of training embeddings obtained using pre-trained CNNs. Experimental results show that models pre-trained on the ImageNet dataset significantly outperform models pre-trained on

Elchanan Mossel, Jonathan Niles-Weed, Youngtak Sohn, Nike Sun

A major question in the study of the Erd\H{o}s--R\'enyi random graph is to understand the probability that it contains a given subgraph. This study originated in classical work of Erd\H{o}s and R\'enyi (1960). More recent work studies this question both in building a general theory of sharp versus coarse transitions (Friedgut and Bourgain 1999; Hatami, 2012)

Lorenzo Bertolini, Valentina Elce, Adriana Michalak, Giulio Bernardi

In the field of dream research, the study of dream content typically relies on the analysis of verbal reports provided by dreamers upon awakening from their sleep. This task is classically performed through manual scoring provided by trained annotators, at a great time expense. While a consistent body of work suggests that natural language processing (NLP) t

Carl Pearson

Demand for low-latency and high-bandwidth data transfer between GPUs has driven the development of multi-GPU nodes. Physical constraints on the manufacture and integration of such systems has yielded heterogeneous intra-node interconnects, where not all devices are connected equally. The next generation of supercomputing platforms are expected to feature AMD

Gianluca Curzi, Anupam Das

We study the computational expressivity of proof systems with fixed point operators, within the 'proofs-as-programs' paradigm. We start with a calculus muLJ (due to Clairambault) that extends intuitionistic logic by least and greatest positive fixed points. Based in the sequent calculus, muLJ admits a standard extension to a 'circular' calculus CmuLJ. Our ma

Nicholas A. Cook, Raphael Ducatez, Alice Guionnet

We establish precise upper-tail asymptotics and large deviation principles for the rightmost eigenvalue $\lambda_1$ of Wigner matrices with sub-Gaussian entries. In contrast to the case of heavier tails, where deviations of $\lambda_1$ are due to the appearance of a few large entries, and the sharp sub-Gaussian case that is governed by the collective deviati

D. D. Wangsawijaya, P. Jaiswal, B. Ganapathisubramani

Boundary layer flow over a realistic porous wall might contain both the effects of wall-permeability and wall-roughness. These two effects are typically examined in the context of a rough-wall flow, i.e., by defining a ``roughness'' length or equivalent to capture the effect of the surface on momentum deficit/drag. In this work, we examine the hypothesis of

Arthur O. T. Pang, Noah Lupu-Gladstein, Hugo Ferretti, Y. Batuhan Yilmaz

Information capacity enhancement through the coherent control of channels has attracted much attention of late, with work exploring the effect of coherent control of channel causal orders, channel superpositions, and information encoding. Coherently controlling channels necessitates a non-trivial expansion of the channel description, which for superposing qu

Bereket A. Yilma, Luis A. Leiva

Artwork recommendation is challenging because it requires understanding how users interact with highly subjective content, the complexity of the concepts embedded within the artwork, and the emotional and cognitive reflections they may trigger in users. In this paper, we focus on efficiently capturing the elements (i.e., latent semantic relationships) of vis

Yunfan Ren, Yixi Cai, Fangcheng Zhu, Siqi Liang

Recent advances in LiDAR technology have opened up new possibilities for robotic navigation. Given the widespread use of occupancy grid maps (OGMs) in robotic motion planning, this paper aims to address the challenges of integrating LiDAR with OGMs. To this end, we propose ROG-Map, a uniform grid-based OGM that maintains a local map moving along with the rob

Saurabh Saxena, Abhishek Kar, Mohammad Norouzi, David J. Fleet

We formulate monocular depth estimation using denoising diffusion models, inspired by their recent successes in high fidelity image generation. To that end, we introduce innovations to address problems arising due to noisy, incomplete depth maps in training data, including step-unrolled denoising diffusion, an $L_1$ loss, and depth infilling during training.

Manjunath Mulimani, Annamaria Mesaros

In this paper, we propose a method for incremental learning of two distinct tasks over time: acoustic scene classification (ASC) and audio tagging (AT). We use a simple convolutional neural network (CNN) model as an incremental learner to solve the tasks. Generally, incremental learning methods catastrophically forget the previous task when sequentially trai

A. Bylinkin, F. Calavalle, M. Barra-Burillo, R. V. Kirtaev

Strong coupling (SC) between light and matter excitations such as excitons and molecular vibrations bear intriguing potential for controlling chemical reactivity, conductivity or photoluminescence. So far, SC has been typically achieved either between mid-infrared (mid-IR) light and molecular vibrations or between visible light and excitons. Achieving SC sim

Prabhav Gaur, Andrew Grieco, Yeshaiahu Fainman

Optical coherence tomography is state-of-the-art in non-invasive imaging of biological structures. Spectral Domain Optical Co-herence Tomography is the popularly used variation of this technique, but its performance is limited by the bandwidth and res-olution of the system. In this work, we theoretically formulate the use of phase modulators and delay lines

M. Pardal, A. Sainte-Marie, A. Reboul-Salze, R. A. Fonseca

This work describes a novel radiation algorithm designed to capture the three-dimensional, space-time resolved electromagnetic field structure emitted by large ensembles of charged particles. % in particle-in-cell (PIC) codes. The algorithm retains the full set of degrees of freedom that characterize electromagnetic waves by employing the Li\'enard-Wiechert

Ishraq Al-Awamleh, Robert Smits

We find discrete analogs to continuous mean value principles that are used in the numerical analysis of the normalized p-Laplacian for particular values of p, specifically when p is 4.

Kouhei Nakaji, Mohsen Bagherimehrab, Alan Aspuru-Guzik

Hamiltonian simulation is known to be one of the fundamental building blocks of a variety of quantum algorithms such as its most immediate application, that of simulating many-body systems to extract their physical properties. In this work, we present qSWIFT, a high-order randomized algorithm for Hamiltonian simulation. In qSWIFT, the required number of gate

Dimbihery Rabenoro, Xavier Pennec

Consider a smooth manifold and an action on it of a compact connected Lie group with a bi-invariant metric. Then, any orbit is an embedded submanifold that is isometric to a normal homogeneous space for the group. In this paper, we establish new explicit and intrinsic formulas for the geometry of any such orbit. We derive our formula of the Levi-Civita conne

Maryam Viqar, Violeta Madjarova, Vipul Baghel, Elena Stoykova

Human veins are important for carrying the blood from the body-parts to the heart. The improper functioning of the human veins may arise from several venous diseases. Varicose vein is one such disease wherein back flow of blood can occur, often resulting in increased venous pressure or restricted blood flow due to changes in the structure of vein. To examine

Mohamed Nagy, Majid Khonji, Jorge Dias, Sajid Javed

Persistent multi-object tracking (MOT) allows autonomous vehicles to navigate safely in highly dynamic environments. One of the well-known challenges in MOT is object occlusion when an object becomes unobservant for subsequent frames. The current MOT methods store objects information, like objects' trajectory, in internal memory to recover the objects after

Xinliang Liu, Bingxin Zhou, Chutian Zhang, Yu Guang Wang

Graph neural networks (GNNs) have achieved champion in wide applications. Neural message passing is a typical key module for feature propagation by aggregating neighboring features. In this work, we propose a new message passing based on multiscale framelet transforms, called Framelet Message Passing. Different from traditional spatial methods, it integrates

Arash Mousaei, Sahar Aziz Mohammadabadi

In this paper, the Hook-Jews (HJ) optimization method is used to optimize a 3-phase Squirrel-Cage Induction Motor (SCIM) as an Electric Vehicle's (EV) motor. Optimal designs with different numbers of poles, different nominal and maximum speeds, and different numbers of grooves are compared and the best one is selected. The optimization method used has advant

Chad Nathe, Chandra Pappu, Nicholas A. Mecholsky, Joseph D. Hart

This paper investigates in detail the effects of noise on the performance of reservoir computing. We focus on an application in which reservoir computers are used to learn the relationship between different state variables of a chaotic system. We recognize that noise can affect differently the training and testing phases. We find that the best performance of

Riccardo Martini, Dario Sauro, Omar Zanusso

We discuss the renormalization of Einstein-Hilbert's gravity in $d=2+\epsilon$ dimensions. We show that the application of the path-integral approach leads naturally to scheme- and gauge-independent results on-shell, but also gives a natural notion of quantum metric off-shell, which is the natural argument of the effective action, even at the leading order i

Ross Allen, Wei Xiao, Daniela Rus

We present Learned Risk Metric Maps (LRMM) for real-time estimation of coherent risk metrics of high dimensional dynamical systems operating in unstructured, partially observed environments. LRMM models are simple to design and train -- requiring only procedural generation of obstacle sets, state and control sampling, and supervised training of a function ap

Viktoriia Kornich

We study theoretically a junction consisting of a normal metal, PT-symmetric non-Hermitian superconductor, and an insulating thin layer between them (N-I-PTS junction). We calculate current-voltage characteristics for this junction using left-right and right-right bases and compare the results. We find that in the left-right basis, the Andreev-scattered part

Markus Schütz, Bernhard Kerbl, Philip Klaus, Michael Wimmer

About: We introduce a GPU-accelerated LOD construction process that creates a hybrid voxel-point-based variation of the widely used layered point cloud (LPC) structure for LOD rendering and streaming. The massive performance improvements provided by the GPU allow us to improve the quality of lower LODs via color filtering while still increasing construction

Kate Pattle, Walter Gear, Christine D. Wilson

We present 850$\mu$m observations of a sample of 8 nearby spiral galaxies, made using the SCUBA-2 camera on the James Clerk Maxwell Telescope (JCMT) as part of the JCMT Nearby Galaxies Legacy Survey (NGLS). We corrected our data for the presence of the $^{12}$CO $J=3\to 2$ line in the SCUBA-2 850$\mu$m bandwidth using NGLS HARP data, finding a typical $^{12}

Lorenzo Tinacci, Simón Ferrada-Chamorro, Cecilia Ceccarelli, Stefano Pantaleone

The gas-phase reaction networks are the backbone of astrochemical models. However, due to their complexity and non-linear impact on the astrochemical modeling, they can be the first source of error in the simulations if incorrect reactions are present. Over time, following the increasing number of species detected, astrochemists have added new reactions, bas

Eric Chitambar, Felix Leditzky

Quantum teleportation is a quantum communication primitive that allows a long-distance quantum channel to be built using pre-shared entanglement and one-way classical communication. However, the quality of the established channel crucially depends on the quality of the pre-shared entanglement. In this work, we revisit the problem of using noisy entanglement

Nancy Abdallah

We study the free resolutions of some Artin Gorenstein algebras of Hilbert function $(1,4,k,k,4,1)$ and we prove that all such algebras have the Strong Lefschetz property if they have the Weak Lefschetz property. In the case $k=4$ we prove that the Hilbert function alone fixes the betti table. For higher $k$ stronger conditions on the algebras are needed to

Yifan Yang, Chang Liu, Zheng Zhang

Online optimization has gained increasing interest due to its capability of tracking real-world streaming data. Although online optimization methods have been widely studied in the setting of frequentist statistics, few works have considered online optimization with the Bayesian sampling problem. In this paper, we study an Online Particle-based Variational I

Germán González-Almagro, Daniel Peralta, Eli De Poorter, José-Ramón Cano

Clustering is a well-known unsupervised machine learning approach capable of automatically grouping discrete sets of instances with similar characteristics. Constrained clustering is a semi-supervised extension to this process that can be used when expert knowledge is available to indicate constraints that can be exploited. Well-known examples of such constr

Kit Mills Bransby, Vincenzo Tufaro, Murat Cap, Greg Slabaugh

X-ray coronary angiography (XCA) is used to assess coronary artery disease and provides valuable information on lesion morphology and severity. However, XCA images are 2D and therefore limit visualisation of the vessel. 3D reconstruction of coronary vessels is possible using multiple views, however lumen border detection in current software is performed manu

Ivona Najdenkoska, Xiantong Zhen, Marcel Worring

Multimodal few-shot learning is challenging due to the large domain gap between vision and language modalities. Existing methods are trying to communicate visual concepts as prompts to frozen language models, but rely on hand-engineered task induction to reduce the hypothesis space. To make the whole process learnable, we introduce a multimodal meta-learning

Evgeny Posenitskiy, Vijay Gopal Chilkuri, Abdallah Ammar, Michał Hapka

TREXIO is an open-source file format and library developed for the storage and manipulation of data produced by quantum chemistry calculations. It is designed with the goal of providing a reliable and efficient method of storing and exchanging wave function parameters and matrix elements, making it an important tool for researchers in the field of quantum ch