February 2023 arXiv papers

Andrew Beers, Joseph S. Schafer, Ian Kennedy, Morgan Wack

The 2020 United States presidential election was, and has continued to be, the focus of pervasive and persistent mis- and disinformation spreading through our media ecosystems, including social media. This event has driven the collection and analysis of large, directed social network datasets, but such datasets can resist intuitive understanding. In such lar

Yalong Jiang

The performance of video action recognition has been significantly boosted by using motion representations within a two-stream Convolutional Neural Network (CNN) architecture. However, there are a few challenging problems in action recognition in real scenarios, e.g., the variations in viewpoints and poses, and the changes in backgrounds. The domain discrepa

Zhefan Xu, Xiaoyang Zhan, Yumeng Xiu, Christopher Suzuki

Deploying autonomous robots in crowded indoor environments usually requires them to have accurate dynamic obstacle perception. Although plenty of previous works in the autonomous driving field have investigated the 3D object detection problem, the usage of dense point clouds from a heavy Light Detection and Ranging (LiDAR) sensor and their high computation c

Justin Curry, Washington Mio, Tom Needham, Osman Berat Okutan

We introduce decorated mapper graphs as a generalization of mapper graphs capable of capturing more topological information of a data set. A decorated mapper graph can be viewed as a discrete approximation of the cellular Leray cosheaf over the Reeb graph. We establish a theoretical foundation for this construction by showing that the cellular Leray cosheaf

Yiwen Tang, Siyuan Chen, Mark J. Bowick, Dapeng Bi

Biological tissues transform between solid-like and liquid-like states in many fundamental physiological events. Recent experimental observations further suggest that in two-dimensional epithelial tissues these solid-liquid transformations can happen via intermediate states akin to the intermediate hexatic phases observed in equilibrium two-dimensional melti

Juan Castorena

In this work, we propose the use of a causal collider structured model to describe the underlying data generative process assumptions in disentangled representation learning. This extends the conventional i.i.d. factorization assumption model $p(\mathbf{y}) = \prod_{i} p(\mathbf{y}_i )$, inadequate to handle learning from biased datasets (e.g., with sampling

Yaam Deckel, Lauren A. Lowe, Siddharth Rawat, Matthew Turner

The hydrodynamic effects of macromolecular crowding inside cells is often studied in vitro by using polymers as crowding reagents. Confinement of polymers inside cell-sized droplets has been shown to affect the diffusion of small molecules. Here we develop a method, based on digital holographic microscopy, to measure the diffusion of polystyrene microspheres

M. N. Agaras, A. Ahmad, A. Blanco, D. Boumediene

This article reports the laser calibration of the hadronic Tile Calorimeter of the ATLAS experiment in the LHC Run 2 data campaign. The upgraded Laser II calibration system is described. The system was commissioned during the first LHC Long Shutdown, exhibiting a stability better than 0.8% for the laser light monitoring. The methods employed to derive the de

Giulia Maniccia, Giovanni Montani, Leonardo Torcellini

After a brief review of the different approaches to predict the possible quantum gravity corrections to quantum field theory, we discuss in some detail the formulation based on a Gaussian reference frame fixing. Then, we implement this scenario to the determination of the inflationary spectrum of primordial perturbations. We consider the quantization of an i

Mevan Ekanayake, Kamlesh Pawar, Gary Egan, Zhaolin Chen

Deep learning (DL) models are capable of successfully exploiting latent representations in MR data and have become state-of-the-art for accelerated MRI reconstruction. However, undersampling the measurements in k-space as well as the over- or under-parameterized and non-transparent nature of DL make these models exposed to uncertainty. Consequently, uncertai

Jeanne N. Clelland

The August 2022 special election for the U.S. House of Representatives in Alaska featured three main candidates and was conducted by the single-winner ranked choice voting system known as "Instant Runoff Voting." The results of this election displayed a well-known but relatively rare phenomenon known as "Condorcet failure:" Nick Begich was el

Carl Fredrik Berg, Muhammad Sahimi

Percolation theory and the associated conductance networks have provided deep insights into the flow and transport properties of a vast number of heterogeneous materials and media. In practically all cases, however, the conductance of the networks' bonds remains constant throughout the entire process. There are, however, many important problems in which

Ognjen Kundacina, Gorana Gojic, Mirsad Cosovic, Dragisa Miskovic

Data-driven state estimation (SE) is becoming increasingly important in modern power systems, as it allows for more efficient analysis of system behaviour using real-time measurement data. This paper thoroughly evaluates a phasor measurement unit-only state estimator based on graph neural networks (GNNs) applied over factor graphs. To assess the sample effic

A. P. Chetverikova, M. S. Sidorenko, K. B. Samusev, M. F. Limonov

A general picture of photonic eigenmodes of dielectric rings with a rectangular cross section is presented, which is fundamentally different from those of whispering gallery modes of the disc. The optical spectrum of a rectangular dielectric ring consists of an infinite set of individual galleries, each starting with broad transverse radial or axial Fabry-Pé

Noslen Hernández, Antonio Galves, Jesus Garcia, Marcos Dimas Gubitoso

In this article we address two related issues on the learning of probabilistic sequences of events. First, which features make the sequence of events generated by a stochastic chain more difficult to predict. Second, how to model the procedures employed by different learners to identify the structure of sequences of events. Playing the role of a goalkeeper i

Ethan Ackelsberg, Vitaly Bergelson

We prove new combinatorial results about polynomial configurations in large subsets of finite fields. Bergelson--Leibman--McCutcheon (2005) showed that for any polynomial $P(x) \in \mathbb{Z}[x]$ with $P(0) = 0$, if $A \subseteq \mathbb{F}_q$ is a subset of a $q$-element finite field and $A$ does not contains distinct $a, b$ such that $b - a = P(x)$ for some

Simone Coccia

We prove that the integral points are potentially Zariski dense in the complement of a reduced effective singular anticanonical divisor in a smooth del Pezzo surface, with the exception of $\mathbb{P}^2$ minus three concurrent lines (for which potential density does not hold). This answers positively a question raised by Hassett and Tschinkel and, combined w

Quentin Rebjock, Nicolas Boumal

Optimization algorithms can see their local convergence rates deteriorate when the Hessian at the optimum is singular. These singularities are inescapable when the optima are non-isolated. Yet, under the right circumstances, several algorithms preserve their favorable rates even when optima form a continuum (e.g., due to over-parameterization). This has been

Aaditya Panigrahi, Piers Coleman, Alexei Tsvelik

Although the ground-state energy of the Kitaev spin liquid can be calculated exactly, the associated vison gap energy has to date only been calculated numerically from finite size diagonalization. Here we show that the phase shift for scattering Majorana fermions off a single bond-flip can be calculated analytically, leading to a closed-form expression for t

David Kalaj

Let $\mathbb{A}=\{z: r< |z|<R\}$ and $\A^\ast=\{z: r^\ast<|z|<R^\ast\}$ be annuli in the complex plane. Let $p\in[1,2]$ and assume that $\mathcal{H}^{1,p}(\A,\A^*)$ is the class of Sobolev homeomorphisms between $\A$ and $\A^*$, $h:\A\onto \A^*$. Then we consider the following Dirichlet type energy of $h$: $$\mathcal{F}_p[h]=\int_{\A(1,r)}\frac{\|Dh\|^p}{|h|

Rajes Ghosh, Nicola Franchini, Sebastian H. Völkel, Enrico Barausse

Scalar, vector and tensor perturbations on the Kerr spacetime are governed by equations that can be solved by separation of variables, but the same is not true in generic stationary and axisymmetric geometries. This complicates the calculation of black-hole quasi-normal mode frequencies in theories that extend/modify general relativity, because one generally

Lanxiao Li, Michael Heizmann

To apply transformer-based models to point cloud understanding, many previous works modify the architecture of transformers by using, e.g., local attention and down-sampling. Although they have achieved promising results, earlier works on transformers for point clouds have two issues. First, the power of plain transformers is still under-explored. Second, th

Shrey Pareek, Harris Nisar, Thenkurussi Kesavadas

In this paper, we present AR3n (pronounced as Aaron), an assist-as-needed (AAN) controller that utilizes reinforcement learning to supply adaptive assistance during a robot assisted handwriting rehabilitation task. Unlike previous AAN controllers, our method does not rely on patient specific controller parameters or physical models. We propose the use of a v

Alexandre Revol, Émeline Bolmont, Gabriel Tobie, Caroline Dumoulin

The arrival of powerful instruments will provide valuable data for the characterization of rocky exoplanets. It is then crucial to accurately model the dynamical state of exoplanets. Rocky planets with sufficiently large orbits should have non-zero eccentricities and/or obliquities. Realistic models of tides for rocky planets can allow for higher spin states

Kevin Dano

Dynamic logit models are popular tools in economics to measure state dependence. This paper introduces a new method to derive moment restrictions in a large class of such models with strictly exogenous regressors and fixed effects. We exploit the common structure of logit-type transition probabilities and elementary properties of rational fractions, to formu

David W. Farmer, Sally Koutsoliotas, Stefan Lemurell, David P. Roberts

We extend previous lists by numerically computing approximations to many L-functions of degree $d=3$, conductor $N=1$, and small spectral parameters. We sketch how previous arguments extend to say that for very small spectral parameters there are no such L-functions. Using the case $(d,N) = (3,1)$ as a guide, we explain how the set of all L-functions with an

Cornelia A. Van Cott, Qiyu Zhang

The change-making problem asks: given a positive integer $v$ and a collection $C$ of integer coin values $c_1=1<c_2< c_3< \cdots< c_n$, what is the minimum number of coins needed to represent $v$ with coin values from $C$? For some coin systems $C$, the greedy algorithm finds a representation with a minimum number of coins for all $v$. We call such coin syst

Hassan Hajjdiab, Ashraf Khalil, Hichem Eleuch

Quantum computing has gained attention in recent years due to the significant progress in quantum computing technology. Today many companies like IBM, Google and Microsoft have developed quantum computers and simulators for research and commercial use. The development of quantum techniques and algorithms is essential to exploit the full power of quantum comp

Josef Janák, Markus Reiß

For the stochastic heat equation with multiplicative noise we consider the problem of estimating the diffusivity parameter in front of the Laplace operator. Based on local observations in space, we first study an estimator that was derived for additive noise. A stable central limit theorem shows that this estimator is consistent and asymptotically mixed norm

Madhav Gupta, Tongtong Zhang, Lambert Yeung, Jiahua Zhang

The contactless temperature measurement at micro/nanoscale is vital to a broad range of fields in modern science and technology. The nitrogen vacancy (NV) center, a kind of diamond defect with unique spin-dependent photoluminescence, has been recognized as one of the most promising nanothermometers. However, this quantum thermometry technique has been prone

Akhtar A. Khan, Dezhou Kong, Jinlu Li

The primary objective of this paper is to propose and analyze the notion of dual cones associated with the metric projection and generalized projection in Banach spaces. We show that the dual cones, related to the metric projection and generalized metric projection, lose many important properties in transitioning from Hilbert spaces to Banach spaces. We also

Masoud Tabatabaei, Wojciech Jamroga

Many important properties of multi-agent systems refer to the participants&#39; ability to achieve a given goal, or to prevent the system from an undesirable event. Among intelligent agents, the goals are often of epistemic nature, i.e., concern the ability to obtain knowledge about an important fact ϕ. Such properties can be e.g. expressed in ATLK, that is,

Tim-Lukas Habich, Melvin Hueter, Moritz Schappler, Svenja Spindeldreier

Snake robots offer considerable potential for endoscopic interventions due to their ability to follow curvilinear paths. Telemanipulation is an open problem due to hyper-redundancy, as input devices only allow a specification of six degrees of freedom. Our work addresses this by presenting a unified telemanipulation strategy which enables follow-the-leader l

Richard M. K. van Dijk, Daniela Gawehns, Matthijs van Leeuwen

We present WEARDA, the open source WEARable sensor Data Acquisition software package. WEARDA facilitates the acquisition of human activity data with smartwatches and is primarily aimed at researchers who require transparency, full control, and access to raw sensor data. It provides functionality to simultaneously record raw data from four sensors -- tri-axis

Audrey Chatain, Nathalie Carrasco, Ludovic Vettier, Olivier Guaitella

Titan&#39;s organic aerosols are formed in the ionosphere, a layer ionized by solar VUV photons and energetic particles from the magnetosphere of Saturn, forming a natural N2-CH4-H2 plasma. Previous works showed some chemical evolution processes: VUV photons slightly alter the aerosols nitrile bands, hydrogen atoms tend to hydrogenate their surface and carbo

F. C. De Gerónimo, M. M. Miller Bertolami, M. Catelan, T. Battich

Stars with initial masses 7 Msun . MZAMS . 9 Msun reach temperatures high enough to ignite C under degenerate conditions after the end of He-core burning (Garcia-Berro & Iben 1994). These isolated stars are expected to evolve into the so-called super AGB (SAGB) phase and may end their lives as ultra-massive ONe WDs (see Siess 2006,2007, 2010; Camisassa et al

Alberto Megías, Andrés Santos

The importance of roughness in the modeling of granular gases has been increasingly considered in recent years. In this paper, a freely evolving homogeneous granular gas of inelastic and rough hard disks or spheres is studied under the assumptions of the Boltzmann kinetic equation. The homogeneous base state reached by the system is studied from a theoretica

Raphaël Berthier, Andrea Montanari, Kangjie Zhou

Gradient-based learning in multi-layer neural networks displays a number of striking features. In particular, the decrease rate of empirical risk is non-monotone even after averaging over large batches. Long plateaus in which one observes barely any progress alternate with intervals of rapid decrease. These successive phases of learning often take place on v

Francesco Battistel, Christopher Chamberland, Kauser Johar, Ramon W. J. Overwater

Quantum computing is poised to solve practically useful problems which are computationally intractable for classical supercomputers. However, the current generation of quantum computers are limited by errors that may only partially be mitigated by developing higher-quality qubits. Quantum error correction (QEC) will thus be necessary to ensure fault toleranc

Jun Li, Yaping Yang, C. M. Hu

We propose and experimentally realize a class of quasi-one-dimensional topological lattices whose unit cells are constructed by coupled multiple identical resonators, with uniform hopping and inversion symmetry. In the presence of path-induced effective zero hopping within the unit cells, the systems are characterized by complete multimerization with degener

Rong Zou, Boyue Lin, Marc Uetz, Matthias Walter

This paper addresses the optimization problem to maximize the total costs that can be shared among a group of agents, while maintaining stability in the sense of the core constraints of a cooperative transferable utility game, or TU game. When maximizing total shareable costs, the cost shares must satisfy all constraints that define the core of a TU game, ex

Cody D. Schimming, C. J. O. Reichhardt, C. Reichhardt

Using a minimal continuum model, we investigate the interplay between circular confinement and substrate friction in active nematics. Upon increasing the friction from low to high, we observe a dynamical phase transition from a circulating flow phase to an anisotropic flow phase in which the flow tends to align perpendicular to the nematic director at the bo

Ratijit Mitra, Indranil Saha

We present an online centralized path planning algorithm to cover a large, complex, unknown workspace with multiple homogeneous mobile robots. Our algorithm is horizon-based, synchronous, and on-demand. The recently proposed horizon-based synchronous algorithms compute all the robots&#39; paths in each horizon, significantly increasing the computation burden

Davis Brown, Charles Godfrey, Cody Nizinski, Jonathan Tu

The current trend toward ever-larger models makes standard retraining procedures an ever-more expensive burden. For this reason, there is growing interest in model editing, which enables computationally inexpensive, interpretable, post-hoc model modifications. While many model editing techniques are promising, research on the properties of edited models is l

Justin L. Sitler, Long Wang

Underwater vehicle-manipulator systems (UVMSs) are underwater robots equipped with one or more manipulators to perform intervention missions. This paper provides the mechanical, electrical, and software design of a novel UVMS equipped with a continuum manipulator, referred to as a continuum-UVMS. A kinematic model for the continuum-UVMS is derived in order t

Hongyan Mei, Guodong Ren, Boyang Zhao, Jad Salman

In modern optics, materials with large birefringence (Δn, 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-matter cou

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

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 &#34;ultimate regime&#34; in 2D simulations of Rayleigh-Bénard 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.

Yuri Cacchió

We consider the two-dimensional, $β$-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,

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

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

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&#39;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 Wa

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

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

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

Eanna E. Flanagan

In 2011 Blanchet and Marsat suggested a fully relativistic version of Milgrom&#39;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-re

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

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

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

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

Gianluca Curzi, Anupam Das

We study the computational expressivity of proof systems with fixed point operators, within the &#39;proofs-as-programs&#39; 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 &#39;circular&#39; calcul

Nicholas A. Cook, Raphael Ducatez, Alice Guionnet

We establish precise upper-tail asymptotics and large deviation principles for the rightmost eigenvalue $λ_1$ of Wigner matrices with sub-Gaussian entries. In contrast to the case of heavier tails, where deviations of $λ_1$ are due to the appearance of a few large entries, and the sharp sub-Gaussian case that is governed by the collective deviation of entrie

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

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

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

Riccardo Martini, Dario Sauro, Omar Zanusso

We discuss the renormalization of Einstein-Hilbert&#39;s gravity in $d=2+ε$ 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 in p

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

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

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

A. Schmitt, M. Rosticher, T. Taniguchi, K. Watanabe

One of the intrinsic drift velocity limit of the quantum Hall effect is the collective magneto-exciton (ME) instability. It has been demonstrated in bilayer graphene (BLG) using noise measurements. We reproduce this experiment in monolayer graphene (MLG), and show that the same mechanism carries a direct relativistic signature on the breakdown velocity. Base

Alfredo Deaño, Lucía Morey, Pablo Román

In this paper, we study parameter deformations of matrix valued orthogonal polynomials (MVOPs). These deformations are built on the use of certain matrix valued operators which are symmetric with respect to the matrix valued inner product defined by the orthogonality weight. We show that the recurrence coefficients associated with these operators satisfy gen

Mostafa Maslouhi, Kasso A. Okoudjou

The HRT conjecture states that any finite collection of time-frequency shifts of a non-zero square-integrable function on the real line is linearly independent. In this paper, we establish the linear independence of finite systems of time-frequency shifts of a non-zero meromorphic function. Consequently, we prove that the conjecture is true for any square-in

Sarah Greer, Laurent Demanet

Wave-based imaging techniques use wavefield data from receivers on the boundary of a domain to produce an image of the underlying structure in the domain of interest. These images are defined by the imaging condition, which maps recorded data to their reflection points in the domain. In this paper, we introduce a nonlinear modification to the standard imagin

Lewis Croney, Sarben Sarkar

The renormalisation group flow of a Hermitian field theory is shown to have trajectories which lead to a non-Hermitian Parity-Time ($\mathcal{PT}$) symmetric field theory for an axion coupled to a fermion in spacetime dimensions $D=4-ε$, where $ε>0 $. In this renormalisable field theory, the Dirac fermion field has a Yukawa coupling $g$ to a pseudoscalar (ax