March 2023 arXiv papers — page 96

Sabir Ahammed, Molla Basir Ahamed

In this paper, we first obtain a refined version of the Bohr inequality of norm-type for holomorphic mappings with lacunary series on the polydisk in $\mathbb{C}^n$ under some restricted conditions. Next, we determine the refined version of the Bohr inequality for holomorphic functions defined on a balanced domain $ G $ of a complex Banach space $ X $ and ta

Marco Cirelli, Nicolao Fornengo, Jordan Koechler, Elena Pinetti

Sub-GeV dark matter particles can annihilate or decay producing e^\pm pairs which upscatter the low-energy photon fields in the Galaxy and generate an X-ray emission (via the Inverse Compton effect). Using X-ray data from XMM-Newton, INTEGRAL, NuSTAR and Suzaku, we derive new constraints on this class of dark matter (DM). For annihilating DM, they are signif

Gabriel López Garza

A finite transformation method is introduced. This method is equivalent to the $Z$ transform method to a certain extent but generalizes it. By applying the presented method to the Bessel functions, it is possible to solve related ordinary differential equations of order higher than two with given initial conditions.

Gwenaël Ferrando, Amit Sever, Adar Sharon, Elior Urisman

We argue that for any single-trace operator in ${\cal N}=4$ SYM theory there is a large twist double-scaling limit in which the Feynman graphs have an iterative structure. Such structure can be recast using a graph-building operator. Generically, this operator mixes between single-trace operators with different scaling limits. The mixing captures both the fi

Victor Mishnyakov, Alexei Morozov, Pavel Suprun

The answers for Feynman diagrams satisfy various kinds of differential equations -- which is not a surprise, because they are defined as Gaussian correlators, possessing a vast variety of Ward identities and superintegrability properties. We study these equations in the simplest example of banana diagrams. They contain any number of loops, but can be efficie

Alvaro Florez, Alejandro Astudillo, Wilm Decré, Jan Swevers

We present IMPACT, a flexible toolchain for nonlinear model predictive control (NMPC) specification with automatic code generation capabilities. The toolchain reduces the engineering complexity of NMPC implementations by providing the user with an easy-to-use application programming interface, and with the flexibility of using multiple state-of-the-art tools

John C. Raymond, Parviz Ghavamian, Artem Bohdan, Dongsu Ryu

Collisionless shock waves in supernova remnants and the solar wind heat electrons less effectively than they heat ions, as is predicted by kinetic simulations. However, the values of T$_e$/T$_p$ inferred from the H alpha profiles of supernova remnant shocks behave differently as a function of Mach number or Alfv\'{e}n Mach number than what is measured in the

Yang Zhou, Giuseppe Loianno

In recent years, compact and efficient scene understanding representations have gained popularity in increasing situational awareness and autonomy of robotic systems. In this work, we illustrate the concept of a panoptic edge segmentation and propose PENet, a novel detection network called that combines semantic edge detection and instance-level perception i

Yuri Shirman, Shreya Shukla, Michael Waterbury

Chirality plays an important role in understanding the dynamics of quantum field theories. In this paper, we study the dynamics of models where renormalization group flows change the chiral structure of the theory. We introduce model building tools and construct models with a variety of chirality flows: from the appearance of new massless composite matter, t

Dhruba Dutta Chowdhury, Frank C. van den Bosch, Pieter van Dokkum, Victor Robles

Fuzzy Dark Matter (FDM), consisting of ultralight bosons, is an intriguing alternative to Cold Dark Matter. Numerical simulations solving the Schr\"odinger-Poisson (SP) equation, which governs FDM dynamics, show that FDM halos consist of a central solitonic core (representing the ground state of the SP equation), surrounded by a large envelope of excited sta

Emanuele Panella, Andrew Svesko

We use braneworld holography to construct a three-dimensional quantum-corrected Kerr-de Sitter black hole, exactly accounting for semi-classical backreaction effects due to a holographic conformal field theory. By contrast, classically there are no de Sitter black holes in three-dimensions, only geometries with a single cosmological horizon. The quantum Kerr

Liangdong Hu, Yin-Chen He, W. Zhu

Conformal field theory (CFT) is the key to various critical phenomena. So far, most of studies focus on the critical exponents of various universalities, corresponding to conformal dimensions of CFT primary fields. However, other important yet intricate data such as the operator product expansion (OPE) coefficients governing the fusion of two primary fields,

Anirban Das, Subhajit Ghosh

We revisit the cosmology of neutrino self-interaction and use the latest cosmic microwave background data from the Atacama Cosmology Telescope (ACT) and the Planck experiment to constrain the interaction strength. In both flavor-universal and nonuniversal coupling scenarios, we find that the ACT data prefers strong neutrino self-interaction that delays neutr

L. Hernández-García, F. Panessa, G. Bruni, L. Bassani

PBC J2333.9-2343 is a giant radio galaxy at z = 0.047 with a bright central core associated to a blazar nucleus. If the nuclear blazar jet is a new phase of the jet activity, then the small orientation angle suggest a dramatic change of the jet direction. We present observations obtained between September 2018 and January 2019 (cadence larger than three days

M. Laurenti, F. Tombesi, F. Vagnetti, E. Piconcelli

The bulk of X-ray spectroscopic studies of active galactic nuclei (AGN) are focused on local ($z < 0.1$) sources with low-to-moderate ($< 0.3$) Eddington ratio ($\lambda_\mathrm{Edd}$). It is then mandatory to overcome this limitation and improve our understanding of highly accreting AGN. In this work we present the preliminary results from the analysis of a

Stefan Meingast, Hervé Bouy, Verena Fürnkranz, David Hernandez

The VISIONS public survey provides large-scale, multiepoch imaging of five nearby star-forming regions at subarcsecond resolution in the near-infrared. All data collected within the program and provided by the European Southern Observatory (ESO) science archive are processed with a custom end-to-end pipeline infrastructure to provide science-ready images and

Piotr Tourkine, Alexander Zhiboedov

We present and numerically implement a computational method to construct relativistic scattering amplitudes that obey analyticity, crossing, elastic and inelastic unitarity in three and four spacetime dimensions. The algorithm is based on the Mandelstam representation of the amplitude and iterations of unitarity. The input for the iterative procedure is give

Michele De Leo, Justin I. Read, Noelia E. D. Noel, Denis Erkal

We use spectroscopic data for ${\sim}6,000$ Red Giant Branch (RGB) stars in the Small Magellanic Cloud (SMC), together with proper motion data from \textit{Gaia} Early Data Release 3 (EDR3), to build a mass model of the SMC. We test our Jeans mass modelling method (\textsc{Binulator}+\textsc{GravSphere}) on mock data for an SMC-like dwarf undergoing severe t

J. Sánchez-Sierras, T. Muñoz-Darias, J. Casares, G. Panizo-Espinar

We present simultaneous optical and near-infrared spectra obtained during the 2021 outburst of the black hole transient 4U 1543-47. The X-ray hardness-intensity diagram and the comparison with similar systems reveal a luminous outburst, probably reaching the Eddington luminosity, as well as a long-lasting excursion to the so-called ultra-luminous state. VLT/

T. Panurach, R. Urquhart, J. Strader, L. Chomiuk

The conditions under which accreting neutron stars launch radio-emitting jets and/or outflows are still poorly understood. The ultracompact X-ray binary X1850--087, located in the globular cluster NGC 6712, is a persistent atoll-type X-ray source that has previously shown unusual radio continuum variability. Here we present the results of a pilot radio monit

Stéphane Ouvry, Alexios P. Polychronakos

We propose a new type of quantum statistics, which we call inclusion statistics, in which particles tend to coalesce more than ordinary bosons. Inclusion statistics is defined in analogy with exclusion statistics, in which statistical exclusion is stronger than in Fermi statistics, but now extrapolating beyond Bose statistics, resulting in statistical inclus

Luis F. Alday, Tobias Hansen, Joao A. Silva

We study short operators in planar $\mathcal{N}=4$ SYM at strong coupling, for general spin and $SO(6)$ symmetric traceless representations. At strong coupling their dimension grows like $\Delta \sim 2\sqrt{\delta} \lambda^{1/4}$ and their spectrum of degeneracies can be analysed by considering the massive spectrum of type II strings in flat space-time. We f

Gerrit Schellenberger, Ewan O'Sullivan, Simona Giacintucci, Jan Vrtilek

The galaxy group NGC6338 is one of the most violent group-group mergers known to date. While the central dominant galaxies rush at each other at 1400km/s along the line of sight, with dramatic gas heating and shock fronts detected, the central gas in the BCGs remains cool. There are also indications of feedback from active galactic nuclei (AGNs), and neither

Guillaume Cecile, Jacopo De Nardis, Enej Ilievski

It is widely accepted that local subsystems in isolated integrable quantum systems equilibrate to generalized Gibbs ensembles. Here, we demonstrate the failure of canonical generalized thermalization for a particular class of initial states in certain types of interacting integrable models. Particularly, we show that in the easy-axis regime of the quantum XX

Stefan Meingast, João Alves, Hervé Bouy, Monika G. Petr-Gotzens

VISIONS is an ESO public survey of five nearby (d < 500 pc) star-forming molecular cloud complexes that are canonically associated with the constellations of Chamaeleon, Corona Australis, Lupus, Ophiuchus, and Orion. The survey was carried out with VISTA, using VIRCAM, and collected data in the near-infrared passbands J, H, and Ks. With a total on-sky exposu

Luke G. Bouma, Elsa K. Palumbo, Lynne A. Hillenbrand

The promise of gyrochronology is that given a star's rotation period and mass, its age can be inferred. The reality of gyrochronology is complicated by effects other than ordinary magnetized braking that alter stellar rotation periods. In this work, we present an interpolation-based gyrochronology framework that reproduces the time- and mass-dependent spin-d

Hector Bombin, Daniel Litinski, Naomi Nickerson, Fernando Pastawski

There are several models of quantum computation which exhibit shared fundamental fault-tolerance properties. This article makes commonalities explicit by presenting these different models in a unifying framework based on the ZX calculus. We focus on models of topological fault tolerance - specifically surface codes - including circuit-based, measurement-base

Oliver H. E. Philcox

We derive optimal estimators for the two-, three-, and four-point correlators of statistically isotropic scalar fields defined on the sphere, such as the Cosmic Microwave Background temperature fluctuations, allowing for arbitrary (linear) masking and inpainting schemes. In each case, we give the optimal unwindowed estimator (obtained via a maximum-likelihoo

Michalis Kourniotis, Richard Wünsch, Sergio Martínez-González, Jan Palouš

We present a one-dimensional radiation-hydrodynamic model of a spherically symmetric cloud evolving under the influence of the self-gravity and the feedback from a star cluster forming in its centre. On one hand, the model is simple due to its 1D geometry, on the other hand, the feedback includes the ionising radiation, stellar winds and the radiation pressu

Sucheng Ren, Fangyun Wei, Samuel Albanie, Zheng Zhang

Deep supervision, which involves extra supervisions to the intermediate features of a neural network, was widely used in image classification in the early deep learning era since it significantly reduces the training difficulty and eases the optimization like avoiding gradient vanish over the vanilla training. Nevertheless, with the emergence of normalizatio

Yue Wu, Tao Jin, Hao Lou, Farzad Farnoud

Dueling bandits are widely used to model preferential feedback prevalent in many applications such as recommendation systems and ranking. In this paper, we study the Borda regret minimization problem for dueling bandits, which aims to identify the item with the highest Borda score while minimizing the cumulative regret. We propose a rich class of generalized

Bencheng Liao, Shaoyu Chen, Bo Jiang, Tianheng Cheng

Online lane graph construction is a promising but challenging task in autonomous driving. Previous methods usually model the lane graph at the pixel or piece level, and recover the lane graph by pixel-wise or piece-wise connection, which breaks down the continuity of the lane and results in suboptimal performance. Human drivers focus on and drive along the c

Zihao Wu, Ming-Ming Long

We studied the two-loop non-factorizable Feynman diagrams for the $t$-channel single-top production process in quantum chromodynamics. We present a systematic computation of master integrals of the two-loop Feynman diagrams with one internal massive propagator in which a complete uniform transcendental basis can be built. The master integrals are derived by

Christopher M. Carroll, Tonima T. Ananna, Ryan C. Hickox, Alberto Masini

We present new estimates on the fraction of heavily X-ray obscured, Compton-thick (CT) active galactic nuclei (AGNs) out to a redshift of $z \leq$ 0.8. From a sample of 540 AGNs selected by mid-IR (MIR) properties in observed X-ray survey fields, we forward model the observed-to-intrinsic X-ray luminosity ratio ($R_{L_{\text{X}}}$) with a Markov chain Monte

Felix J. Yu, Jeffrey Lazar, Carlos A. Argüelles

Convolutional neural networks (CNNs) have seen extensive applications in scientific data analysis, including in neutrino telescopes. However, the data from these experiments present numerous challenges to CNNs, such as non-regular geometry, sparsity, and high dimensionality. Consequently, CNNs are highly inefficient on neutrino telescope data, and require si

Mehdi Azabou, Michael Mendelson, Nauman Ahad, Maks Sorokin

Natural behavior consists of dynamics that are complex and unpredictable, especially when trying to predict many steps into the future. While some success has been found in building representations of behavior under constrained or simplified task-based conditions, many of these models cannot be applied to free and naturalistic settings where behavior becomes

Lei Zhu, Xinjiang Wang, Zhanghan Ke, Wayne Zhang

As the core building block of vision transformers, attention is a powerful tool to capture long-range dependency. However, such power comes at a cost: it incurs a huge computation burden and heavy memory footprint as pairwise token interaction across all spatial locations is computed. A series of works attempt to alleviate this problem by introducing handcra

Yuan Tseng, Cheng-I Lai, Hung-yi Lee

Past work on unsupervised parsing is constrained to written form. In this paper, we present the first study on unsupervised spoken constituency parsing given unlabeled spoken sentences and unpaired textual data. The goal is to determine the spoken sentences' hierarchical syntactic structure in the form of constituency parse trees, such that each node is a sp

Rohit Jena, Pratik Chaudhari, James Gee, Ganesh Iyer

Human reconstruction and synthesis from monocular RGB videos is a challenging problem due to clothing, occlusion, texture discontinuities and sharpness, and framespecific pose changes. Many methods employ deferred rendering, NeRFs and implicit methods to represent clothed humans, on the premise that mesh-based representations cannot capture complex clothing

Wojciech Kryński, Omid Makhmali

Given a 3-dimensional (para-)CR structure, its family of chains define a 3-dimensional path geometry. We provide necessary and sufficient conditions that determine whether a path geometry in dimension three arises from chains of a CR or para-CR 3-manifold. We demonstrate how our characterization can be verified computationally for a given 3-dimensional path

Gianluigi Lopardo, Frederic Precioso, Damien Garreau

In many scenarios, the interpretability of machine learning models is a highly required but difficult task. To explain the individual predictions of such models, local model-agnostic approaches have been proposed. However, the process generating the explanations can be, for a user, as mysterious as the prediction to be explained. Furthermore, interpretabilit

Jacob A. Hines, Shankari V. Rajagopal, Gabriel L. Moreau, Michael D. Wahrman

We report on the creation of an array of spin-squeezed ensembles of cesium atoms via Rydberg dressing, a technique that offers optical control over local interactions between neutral atoms. We optimize the coherence of the interactions by a stroboscopic dressing sequence that suppresses super-Poissonian loss. We thereby prepare squeezed states of $N=200$ ato

Danh-Phuong Nguyen, Geva Arwas, Zuzhang Lin, Wang Yao

We explore theoretically how the topological properties of 2D materials can be manipulated by cavity quantum electromagnetic fields for both resonant and off-resonant electron-photon coupling, with a focus on van der Waals moir\'e superlattices. We investigate an electron-photon topological Chern number for the cavity-dressed energy minibands that is well de

Logan Ward, J. Gregory Pauloski, Valerie Hayot-Sasson, Ryan Chard

Applications that fuse machine learning and simulation can benefit from the use of multiple computing resources, with, for example, simulation codes running on highly parallel supercomputers and AI training and inference tasks on specialized accelerators. Here, we present our experiences deploying two AI-guided simulation workflows across such heterogeneous

Jean-Luc Lehners

When the universe is treated as a quantum system, it is described by a wave function. This wave function is a function not only of the matter fields, but also of spacetime. The no-boundary proposal is the idea that the wave function should be calculated by summing over geometries that have no boundary to the past, and over regular matter configurations on th

Myeonghyeon Kim, Dong-Hee Kim

We present a perturbation method to compute the out-of-time-ordered correlator in the strongly disordered Heisenberg XXZ model in the deep many-body localized regime. We characterize the discrete structure of the information propagation across the eigenstates, revealing a highly structured light cone confined by the strictly logarithmic upper and lower bound

Navnath Daundkar, Saikat Panja, Sachchidanand Prasad

In this article, we introduce the notion of a wedge of graphs and provide detailed computations for the independence complex of a wedge of path and cycle graphs. In particular, we show that these complexes are either contractible or wedges of spheres.

Riasat Ali, Muhammad Asgher, P. K. Sahoo

The Newman-Janis technique and the semi-classical Hamilton-Jacobi approach are two distinct phenomena that we apply in this paper to examine the Hawking temperature $(T_{H})$ for $4$-dimensional gauge super gravity like black hole with rotation parameters. First, using the Newman-Janis algorithmic approach, we compute the gauge super gravity like black holes

Brando Miranda, Avi Shinnar, Vasily Pestun, Barry Trager

Despite a growing body of work at the intersection of deep learning and formal languages, there has been relatively little systematic exploration of transformer models for reasoning about typed lambda calculi. This is an interesting area of inquiry for two reasons. First, typed lambda calculi are the lingua franc of programming languages. A set of heuristics

Michael S. Albergo, Nicholas M. Boffi, Eric Vanden-Eijnden

A class of generative models that unifies flow-based and diffusion-based methods is introduced. These models extend the framework proposed in Albergo and Vanden-Eijnden (2023), enabling the use of a broad class of continuous-time stochastic processes called stochastic interpolants to bridge any two probability density functions exactly in finite time. These

A. Salch

In the 2000s, Sadofsky constructed a spectral sequence which converges to the mod $p$ homology groups of a homotopy limit of a sequence of spectra. The input for this spectral sequence is the derived functors of sequential limit in the category of graded comodules over the dual Steenrod algebra. Since then, there has not been an identification of those deriv

Liam Zuckerman, Kishalay De, Anna-Christina Eilers, Aaron M. Meisner

The Galactic nova rate is intimately linked to our understanding of its chemical enrichment and progenitor channels of Type Ia supernovae. Yet past estimates have varied by more than an order of magnitude ($\approx10-300$ yr$^{-1}$) owing to limitations in both discovery methods as well as assumptions regarding the Galactic dust distribution and extragalacti

Alessio Di Prisa, Giovanni Framba

We study the equivariant concordance classes of two-bridge knots, providing an easy formula to compute their butterfly polynomial, and we give two different proofs that no two-bridge knot is equivariantly slice. Finally, we introduce a new invariant of equivariant concordance for strongly invertible knots. Using this invariant as an obstruction we strengthen

F. Rajabi, M. Houde, G. C. MacLeod, S. Goedhart

We present detailed modeling of periodic flaring events in the 6.7 GHz and 12.2 GHz methanol lines as well as the OH 1665 MHz and 1667 MHz transitions observed in the G9.62+0.20E star-forming region. Our analysis is performed within the framework of the one-dimensional Maxwell-Bloch equations, which intrinsically cover the complementary quasi-steady state ma

Kazem Taghandiki

Today, people use email services such as Gmail, Outlook, AOL Mail, etc. to communicate with each other as quickly as possible to send information and official letters. Spam or junk mail is a major challenge to this type of communication, usually sent by botnets with the aim of advertising, harming and stealing information in bulk to different people. Receivi

Alessandra Milloch, Umberto Filippi, Paolo Franceschini, Michele Galvani

The development of Quantum Simulators, artificial platforms where the predictions of many-body theories of correlated quantum materials can be tested in a controllable and tunable way, is one of the main challenges of condensed matter physics. Here we introduce artificial lattices made of lead halide perovskite nanocubes as a new platform to simulate and inv

Ambarish Chattopadhyay, Noah Greifer, Jose R. Zubizarreta

The linear regression model is widely used in the biomedical and social sciences as well as in policy and business research to adjust for covariates and estimate the average effects of treatments. Behind every causal inference endeavor there is a hypothetical randomized experiment. However, in routine regression analyses in observational studies, it is uncle

Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri

A rich representation is key to general robotic manipulation, but existing approaches to representation learning require large amounts of multimodal demonstrations. In this work we propose PLEX, a transformer-based architecture that learns from a small amount of task-agnostic visuomotor trajectories and a much larger amount of task-conditioned object manipul

Claudio Macci, Barbara Pacchiarotti

We prove large and moderate deviation results for sequences of compound sums, where the summands are i.i.d. random variables taking values in a separable Banach space. We establish that the results hold by proving that we are dealing with exponentially tight sequences. We present two moderate deviation results: in the first one the summands are centered, in

Mikhail Alfimov, Andrey Kurakin

We present the way to continue the bosonic Thirring model or $\beta\gamma$-system with quartic interaction to Minkowski signature, based on the symmetries of this model. It is shown that the considered Minkowski version of the model is one-loop renormalizable. Based on this, we find the amplitudes of the scattering of the excitations corresponding to the $\g

Tianyi Li, Minping Wan, Shiyi Chen

Localized turbulence is common in geophysical flows, where the roles of rotation and stratification are paramount. In this study, we investigate the evolution of a stratified turbulent cloud under rotation. Recognizing that a turbulent cloud is composed of vortices of varying scales and shapes, we start our investigation with a single eddy using analytical s

Pham Duy Khanh, Boris S. Mordukhovich, Dat Ba Tran

The paper proposes and develops a novel inexact gradient method (IGD) for minimizing C1-smooth functions with Lipschitzian gradients, i.e., for problems of C1,1 optimization. We show that the sequence of gradients generated by IGD converges to zero. The convergence of iterates to stationary points is guaranteed under the Kurdyka- Lojasiewicz (KL) property of

Wei Jiang, Hans Schotten

Intelligent reflecting surface (IRS) is envisioned to become a key technology for the upcoming six-generation (6G) wireless system due to its potential of reaping high performance in a power-efficient and cost-efficient way. With its disruptive capability and hardware constraint, the integration of IRS imposes some fundamental particularities on the coordina

Aditay Tripathi, Anand Mishra, Anirban Chakraborty

In this work, we investigate the problem of sketch-based object localization on natural images, where given a crude hand-drawn sketch of an object, the goal is to localize all the instances of the same object on the target image. This problem proves difficult due to the abstract nature of hand-drawn sketches, variations in the style and quality of sketches,

R. J. P. T. de Keijzer, O. Tse, S. J. J. M. F. Kokkelmans

In a neutral atom quantum computer, the qubits are individual neutral atoms trapped in optical tweezers. Excitations to Rydberg states form the basis for the entanglement procedure that is at the basis of multi-qubit quantum gates. However, these Rydberg atoms are often anti-trapped, leading to decoherence and atom loss. In this work, we give a quantum mecha

Obinna Umeh

There is no source for cosmic vorticity within the cold dark matter cosmology. However, vorticity has been observed in the universe, especially on the scales of clusters, filaments, galaxies, etc. Recent results from high-resolution general relativistic N-body simulation show that the vorticity power spectrum dominates over the power spectrum of the divergen

Samay Kothari, Abhishek Deshpande

We show that there exists endotactic and strongly endotactic dynamical systems that are not weakly reversible and possess infinitely many steady states. We provide a few examples in two dimensions and an example in three dimensions that satisfy this property. In addition, we prove for some of these systems that there exist no weakly reversible mass-action sy

Tania E. Medina-Torrejón, Elisabete M. de Gouveia Dal Pino, Grzegorz Kowal

Several MHD works and, in particular, the recent one by Medina-Torrejon et al. (2021) based on three-dimensional MHD simulations of relativistic jets, have evidenced that particle acceleration by magnetic reconnection driven by the turbulence in the flow occurs from the resistive up to the large injection scale of the turbulence. Particles experience Fermi-t

Federico Paredes-Vallés, Jesse Hagenaars, Julien Dupeyroux, Stein Stroobants

Biological sensing and processing is asynchronous and sparse, leading to low-latency and energy-efficient perception and action. In robotics, neuromorphic hardware for event-based vision and spiking neural networks promises to exhibit similar characteristics. However, robotic implementations have been limited to basic tasks with low-dimensional sensory input

Tomasz Bartnicki, Sebastian Czerwiński, Jarosław Grytczuk, Zofia Miechowicz

Let $M_1,M_2,\ldots,M_k$ be a collection of matroids on the same ground set $E$. A coloring $c:E \rightarrow \{1,2,\ldots,k\}$ is called \emph{cooperative} if for every color $j$, the set of elements in color $j$ is independent in $M_j$. We prove that such coloring always exists provided that every matroid $M_j$ is itself $k$-colorable (the set $E$ can be sp

OpenAI, Josh Achiam, Steven Adler, Sandhini Agarwal

We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs. While less capable than humans in many real-world scenarios, GPT-4 exhibits human-level performance on various professional and academic benchmarks, including passing a simulated bar exam with a score around the top 10% of test

Junyan Cao, Patrick Graf, Philipp Naumann, Mihai Paun

In this article we pursue the following main goals. In the first place, we establish the existence of "estimable" Hermite--Einstein metrics for stable reflexive coherent sheaves on compact normal K\"ahler spaces. If moreover the background variety has klt singularities, we obtain a much more precise result.

Jean-Baptiste Monteil, George Iosifidis, Ivana Dusparic

The virtualization of wireless networks enables new services to access network resources made available by the Network Operator (NO) through a Network Slicing market. The different service providers (SPs) have the opportunity to lease the network resources from the NO to constitute slices that address the demand of their specific network service. The goal of

Tomasz Bartnicki, Sebastian Czerwiński, Jarosław Grytczuk, Zofia Miechowicz

An edge coloring of a graph $G$ is \emph{woody} if no cycle is monochromatic. The \emph{arboricity} of a graph $G$, denoted by $\arb (G)$, is the least number of colors needed for a woody coloring of $G$. A coloring of $G$ is \emph{strongly woody} if after contraction of any single edge it is still woody. In other words, not only any cycle in $G$ can be mono

Elena Gati, Burkhard Schmidt, Sergey L. Bud'ko, Andrew P. Mackenzie

YbPtBi is one of the heavy-fermion systems with largest Sommerfeld coefficient $\gamma$ and is thus classified as a `super'-heavy fermion material. In this work, we resolve the long-debated question about the hierarchy of relevant energy scales, such as crystal-electric field (CEF) levels, Kondo and magnetic ordering temperature, in YbPtBi. Through measureme

Inhwa Han, Serin Yang, Taesung Kwon, Jong Chul Ye

Diffusion models have shown superior performance in image generation and manipulation, but the inherent stochasticity presents challenges in preserving and manipulating image content and identity. While previous approaches like DreamBooth and Textual Inversion have proposed model or latent representation personalization to maintain the content, their relianc

Alena Bakalová, Jakub Vícha, Petr Trávníček

The direction and magnitude of the dipole anisotropy of ultra-high-energy cosmic rays with energies above 8 EeV observed by the Pierre Auger Observatory indicate their extragalactic origin. The observed dipole on Earth does not necessarily need to correspond to the anisotropy of the extragalactic cosmic-ray flux due to the effects of propagation in the Galac

Juan Andres Espinosa-Torres, Jaime Ramirez-Cuellar

We explore firm-level markup and profit rates during the COVID-19 pandemic for a panel of 3,611 publicly traded firms in Compustat and find increases for the average firm. We offer conditions to give markups and profit rate forecasts a causal interpretation of what would have happened had the pandemic not happened. Our estimations suggest that had the pandem

Robert Fleischer, Eleftheria Malami, Anders Rehult, K. Keri Vos

Intriguing results for tests of the universality of electrons and muons through measurements of rates of $B\to K \ell^+ \ell^-$ and similar decays have been in the spotlight for years. The LHCb collaboration has recently reported new results which are in agreement with Lepton Flavour Universality, while the individual decay rates are found below their Standa

Thomas Christiansen, Katrin Grunert, Anders Nordli, Susanne Solem

A convergent numerical method for $\alpha$-dissipative solutions of the Hunter-Saxton equation is derived. The method is based on applying a tailor-made projection operator to the initial data, and then solving exactly using the generalized method of characteristics. The projection step is the only step that introduces any approximation error. It is therefor

G. P. Mikitik, Yu. V. Sharlai

In the recent paper [1], a new method based on measuring a temperature correction to a quantum-oscillation frequency was proposed to study an energy-band dispersion of charge carriers in small Fermi surface (FS) pockets of crystals. To illustrate their approach, Guo et al. [1] applied it to a number of materials and, in particular, to the multiband metal LaR

Mamta Jotkar, Pietro de Anna, Marco Dentz, Luis Cueto-Felgueroso

In this letter, we show that pore-scale diffusiophoresis of colloidal particles along local salt gradients manifests in the macroscopic dispersion of particles in a porous medium. Despite is transient character, this microscopic phenomenon controls large-scale particle transport by altering their partitioning between transmitting and dead-end pores. It deter

Young Shin Kim, Hyangju Kim, Jaehyung Choi

This paper explores Artificial Neural Network (ANN) as a model-free solution for a calibration algorithm of option pricing models. We construct ANNs to calibrate parameters for two well-known GARCH-type option pricing models: Duan's GARCH and the classical tempered stable GARCH that significantly improve upon the limitation of the Black-Scholes model but hav

Xue Ming, Ying-Jie Zhang, Xiyu Zhu, Qing Li

Recently near-ambient superconductivity was claimed in N-doped lutetium hydride (ref. 1). This induces a worldwide fanaticism about the dream of room temperature superconductivity under low pressures. By using a high pressure and high temperature synthesis technique, we have successfully obtained the nitrogen doped lutetium hydride (LuH$_{2\pm\text{x}}$N$_y$

Giorgio Gonnella

The number of available genomes of prokaryotic organisms is rapidly growing enabling comparative genomics studies. The comparison of genomes of organisms with a common phenotype, habitat or phylogeny often shows that these genomes share some common contents. Collecting rules expressing common genome traits depending on given factors is useful, as such rules

Luca Tomasetti, Kjersti Engan, Liv Jorunn Høllesli, Kathinka Dæhli Kurz

Precise and fast prediction methods for ischemic areas comprised of dead tissue, core, and salvageable tissue, penumbra, in acute ischemic stroke (AIS) patients are of significant clinical interest. They play an essential role in improving diagnosis and treatment planning. Computed Tomography (CT) scan is one of the primary modalities for early assessment in

Liran Shaul

For a ring $A$, we consider the question whether every bounded above cochain complex of injective $A$-modules which is acyclic is null-homotopic. We show that if $A$ is left and right noetherian and has a dualizing complex, then this implies that the finitistic dimension of $A$ is finite. In the appendix, Nakamura and Thompson show that the opposite holds ov

Federico Cerisola, Franco Mayo, Augusto J. Roncaglia

In this article we introduce a quasiprobability distribution of work that is based on the Wigner function. This construction rests on the idea that the work done on an isolated system can be coherently measured by coupling the system to a quantum measurement apparatus. In this way, a quasiprobability distribution of work can be defined in terms of the Wigner

Eliana Duarte, Benjamin Hollering, Maximilian Wiesmann

An important challenge in Geometric Modeling is to classify polytopes with rational linear precision. Equivalently, in Algebraic Statistics one is interested in classifying scaled toric varieties, also known as discrete exponential families, for which the maximum likelihood estimator can be written in closed form as a rational function of the data (rational

Marika Asgari, Alexander J. Mead, Catherine Heymans

We present a pedagogical review of the halo model, a flexible framework that can describe the distribution of matter and its tracers on non-linear scales for both conventional and exotic cosmological models. We start with the premise that the complex structure of the cosmic web can be described by the sum of its individual components: dark matter, gas, and g

Corentin Charlo, Stéphane Méric, François Sarrazin, Elodie Richalot

Reverberation chambers (RCs) were recently reported as a low-cost alternative to anechoic chambers (ACs) to perform radar cross-section (RCS) pattern measurements. The method consists of using transmitting and receiving antennas pointing towards a target under test placed on a rotating mast. As a classical RCS characterization, the echo signal is analysed ba

Masaya Yamamoto, Katherine Laliotis, Emily Macbeth, Tianqing Zhang

One challenge for applying current weak lensing analysis tools to the Nancy Grace Roman Space Telescope is that individual images will be undersampled. Our companion paper presented an initial application of Imcom - an algorithm that builds an optimal mapping from input to output pixels to reconstruct a fully sampled combined image - on the Roman image simul

Christopher M. Hirata, Masaya Yamamoto, Katherine Laliotis, Emily Macbeth

The upcoming Nancy Grace Roman Space Telescope will carry out a wide-area survey in the near infrared. A key science objective is the measurement of cosmic structure via weak gravitational lensing. Roman data will be undersampled, which introduces new challenges in the measurement of source galaxy shapes; a potential solution is to use linear algebra-based c

Akhil Meethal, Eric Granger, Marco Pedersoli

Detecting objects in aerial images is challenging because they are typically composed of crowded small objects distributed non-uniformly over high-resolution images. Density cropping is a widely used method to improve this small object detection where the crowded small object regions are extracted and processed in high resolution. However, this is typically

Mohammed Abouheaf, Derek Boase, Wail Gueaieb, Davide Spinello

The paper introduces an interactive machine learning mechanism to process the measurements of an uncertain, nonlinear dynamic process and hence advise an actuation strategy in real-time. For concept demonstration, a trajectory-following optimization problem of a Kinova robotic arm is solved using an integral reinforcement learning approach with guaranteed st

Simon Bilik, Daniel Batrakhanov, Tuomas Eerola, Lumi Haraguchi

Phytoplankton parasites are largely understudied microbial components with a potentially significant ecological impact on phytoplankton bloom dynamics. To better understand their impact, we need improved detection methods to integrate phytoplankton parasite interactions in monitoring aquatic ecosystems. Automated imaging devices usually produce high amount o

Wentao Ma, Xuning Zhao, Shafquat Islam, Aditya Narkhede

When solving compressible multi-material flow problems, an unresolved challenge is the computation of advective fluxes across material interfaces that separate drastically different thermodynamic states and relations. A popular idea in this regard is to locally construct bimaterial Riemann problems, and to apply their exact solutions in flux computation. For

Joy Morris

A Cayley graph Cay$(G;S)$ has the CI (Cayley Isomorphism) property if for every isomorphic graph Cay$(G;T)$, there is a group automorphism $\alpha$ of $G$ such that $S^\alpha=T$. The DCI (Directed Cayley Isomorphism) property is defined analogously on digraphs. A group $G$ is a CI-group if every Cayley graph on $G$ has the CI property, and is a DCI-group if

Andria Agadjanov, Dalibor Djukanovic, Georg von Hippel, Harvey B. Meyer

We present a lattice-QCD based analysis of the nucleon sigma terms using gauge ensembles with $N_f = 2 + 1$ flavors of ${\cal O}(a)$-improved Wilson fermions, with a complete error budget concerning excited-state contaminations, the chiral interpolation as well as finite-size and lattice spacing effects. We compute the sigma terms determined directly from th

Fares Bougourzi, Fadi Dornaika, Amir Nakib, Cosimo Distante

Since the appearance of Covid-19 in late 2019, Covid-19 has become an active research topic for the artificial intelligence (AI) community. One of the most interesting AI topics is Covid-19 analysis of medical imaging. CT-scan imaging is the most informative tool about this disease. This work is part of the 3nd COV19D competition for Covid-19 Severity Predic