March 2023 arXiv papers — page 63

A. Ersin Ureyen

For $\alpha>-1$ and $0<p<\infty$, we study weighted Bergman spaces $\mathcal B^p_\alpha$ of harmonic functions on the real hyperbolic ball and obtain an atomic decomposition of these spaces in terms of reproducing kernels. We show that an $r$-separated sequence $\{a_m\}$ with sufficiently large $r$ is an interpolating sequence for $\mathcal B^p_\alpha$. Usin

Dusan Gostimirovic, Yuri Grinberg, Dan-Xia Xu, Odile Liboiron-Ladouceur

Next-generation integrated nanophotonic device designs leverage advanced optimization techniques such as inverse design and topology optimization which achieve high performance and extreme miniaturization by optimizing a massively complex design space enabled by small feature sizes. However, unless the optimization is heavily constrained, the generated small

Xin Jin, Yuchen Wang

The growth of pending legal cases in populous countries, such as India, has become a major issue. Developing effective techniques to process and understand legal documents is extremely useful in resolving this problem. In this paper, we present our systems for SemEval-2023 Task 6: understanding legal texts (Modi et al., 2023). Specifically, we first develop

Diana Wofk, René Ranftl, Matthias Müller, Vladlen Koltun

We present a visual-inertial depth estimation pipeline that integrates monocular depth estimation and visual-inertial odometry to produce dense depth estimates with metric scale. Our approach performs global scale and shift alignment against sparse metric depth, followed by learning-based dense alignment. We evaluate on the TartanAir and VOID datasets, obser

Michael Lindsey

We develop a practical approach to semidefinite programming (SDP) that includes the von Neumann entropy, or an appropriate variant, as a regularization term. In particular we solve the dual of the regularized program, demonstrating how a carefully chosen randomized trace estimator can be used to estimate dual gradients effectively. We also introduce speciali

Andrei Kucharavy, Zachary Schillaci, Loïc Maréchal, Maxime Würsch

Generative Language Models gained significant attention in late 2022 / early 2023, notably with the introduction of models refined to act consistently with users' expectations of interactions with AI (conversational models). Arguably the focal point of public attention has been such a refinement of the GPT3 model -- the ChatGPT and its subsequent integration

Ben Dudson, Mike Kryjak, Hasan Muhammed, Peter Hill

A new open source tool for fluid simulation of multi-component plasmas is presented, based on a flexible software design that is applicable to scientific simulations in a wide range of fields. This design enables the same code to be configured at run-time to solve systems of partial differential equations in 1D, 2D or 3D, either for transport (steady-state)

Vitaliy Kinakh, Mariia Drozdova, Slava Voloshynovskiy

We present a new method of self-supervised learning and knowledge distillation based on the multi-views and multi-representations (MV-MR). The MV-MR is based on the maximization of dependence between learnable embeddings from augmented and non-augmented views, jointly with the maximization of dependence between learnable embeddings from augmented view and mu

Yang Bai, Sida Lu, Nicholas Orlofsky

The prevailing assumption is that all exoplanets are made of ordinary matter. However, we propose an unconventional possibility that some exoplanets could be made of dark matter, which we name "dark exoplanets." In this paper, we explore methods to search for dark exoplanets, including the mass-radius relation, spectroscopy, missing transit, and transit ligh

Jia-Hui Su, Chen-Hua Lu, Jenq Kuen Lee, Andrea Coluccio

Nowadays, various memory-hungry applications like machine learning algorithms are knocking "the memory wall". Toward this, emerging memories featuring computational capacity are foreseen as a promising solution that performs data process inside the memory itself, so-called computation-in-memory, while eliminating the need for costly data movement. Recent res

Mohammad Sohail, Usman Nazir, Jawairia Ahmad, Abubakr Muhammad

While the world's attention is focused on immediate relief and rescue operations for the affectees of the current floods in Pakistan, knock-on effects are expected to play further havoc with the country's economy and food security in the coming months. Significant crop yield losses had already occurred for Winter (Rabi) 2021-22 due to a heatwave earlier in t

Siddharth H. Nair, Francesco Borrelli

We propose an iterative approach for designing Robust Learning Model Predictive Control (LMPC) policies for a class of nonlinear systems with additive, unmodelled dynamics. The nominal dynamics are assumed to be difference flat, i.e., the state and input can be reconstructed using flat output sequences. For the considered class of systems, we synthesize Robu

Jascha Achterberg, Danyal Akarca, Moataz Assem, Moritz Heimbach

There is a concerted effort to build domain-general artificial intelligence in the form of universal neural network models with sufficient computational flexibility to solve a wide variety of cognitive tasks but without requiring fine-tuning on individual problem spaces and domains. To do this, models need appropriate priors and inductive biases, such that t

Sarah McMullan, Denis Vida, Hadrien A. R. Devillepoix, Jim Rowe

On February 28, 2021, a fireball dropped $\sim0.6$ kg of recovered CM2 carbonaceous chondrite meteorites in South-West England near the town of Winchcombe. We reconstruct the fireball's atmospheric trajectory, light curve, fragmentation behaviour, and pre-atmospheric orbit from optical records contributed by five networks. The progenitor meteoroid was three

Anthony K. C. Tan, Hariom Jani, Michael Högen, Lucio Stefan

Whirling topological textures play a key role in exotic phases of magnetic materials and offer promise for logic and memory applications. In antiferromagnets, these textures exhibit enhanced stability and faster dynamics with respect to ferromagnetic counterparts, but they are also difficult to study due to their vanishing net magnetic moment. One technique

Francesco Gallinaro, Stefano Mereta

We prove a fundamental theorem for tropical partial differential equations, analogous to the fundamental theorem of tropical geometry in this context. We extend results from Aroca et al., Falkensteiner et al. and from Fink and Toghani for the case of trivial valuation as introduced by Grigoriev to differential equations with power series coefficients over an

Weinan Song, Haoxin Zheng, Dezhan Tu, Chengwen Liang

3D reconstruction of medical imaging from 2D images has become an increasingly interesting topic with the development of deep learning models in recent years. Previous studies in 3D reconstruction from limited X-ray images mainly rely on learning from paired 2D and 3D images, where the reconstruction quality relies on the scale and variation of collected dat

Aurelie Champagne, Jonah B. Haber, Supavit Pokawanvit, Diana Y. Qiu

The intrinsic weak and highly non-local dielectric screening of two-dimensional materials is well known to lead to high sensitivity of their optoelectronic properties to environment. Less studied theoretically is the role of free carriers on those properties. Here, we use ab initio GW and Bethe-Salpeter equation calculations, with a rigorous treatment of dyn

Shivani Choudhary, Sudipta Mondal, Daniele Margarone, Subhendu Kahaly

We investigate the different facets of ion acceleration by a relativistically intense circularly polarized laser pulse interacting with thin near-critical density plasma targets. Our simulations establish that plasma density gradient and laser frequency chirp can be controlled to switch the interaction from the transparent to the opaque regimes of operation.

Sara Murciano, Pasquale Calabrese, Vincenzo Alba

We investigate symmetry-resolved entanglement in out-of-equilibrium fermionic systems subject to gain and loss dissipation, which preserves the block-diagonal structure of the reduced density matrix. We derive a hydrodynamic description of the dynamics of several entanglement-related quantities, such as the symmetry-resolved von Neumann entropy and the charg

Johannes Hamre Isaksen, Konrad Tywoniuk

We study jet fragmentation via final-state parton splittings in the medium. These processes are usually calculated theoretically by invoking the large-$N_c$ limit. In this paper we perform the first computation of a $1\to2$ parton splitting in a thermal medium at finite numbers of colors $N_c$, for arbitrary momentum-sharing fraction $z$ and with full transv

K. J. Kevin Feng, Nick Ritchie, Pia Blumenthal, Andy Parsons

In recent years, industry leaders and researchers have proposed to use technical provenance standards to address visual misinformation spread through digitally altered media. By adding immutable and secure provenance information such as authorship and edit date to media metadata, social media users could potentially better assess the validity of the media th

Rahul Nellikkath, Andreas Venzke, Mohammad Kazem Bakhshizadeh, Ilgiz Murzakhanov

A significant increase in renewable energy production is necessary to achieve the UN's net-zero emission targets for 2050. Using power-electronic controllers, such as Phase Locked Loops (PLLs), to keep grid-tied renewable resources in synchronism with the grid can cause fast transient behavior during grid faults leading to instability. However, assessing all

Corrado Monti, Matteo Cinelli, Carlo Valensise, Walter Quattrociocchi

Online social media foster the creation of active communities around shared narratives. Such communities may turn into incubators for conspiracy theories -- some spreading violent messages that could sharpen the debate and potentially harm society. To face these phenomena, most social media platforms implemented moderation policies, ranging from posting warn

Ashish S. Nair, Justin Sirignano, Marco Panesi, Jonathan F. MacArt

The predictive accuracy of the Navier-Stokes equations is known to degrade at the limits of the continuum assumption, thereby necessitating expensive and often highly approximate solutions to the Boltzmann equation. While tractable in one spatial dimension, their high dimensionality makes multi-dimensional Boltzmann calculations impractical for all but canon

Olli Niinivaara

Knowledge sharing is an important aspect in most meetings. Personal characteristics of some participants, such as their (in)ability or (un)willingness to take the floor, may have a negative effect on the quality of knowledge sharing; some people tend to talk too much, while others have difficulties in making themselves heard. A robotic facilitator can be use

Sara Sarto, Manuele Barraco, Marcella Cornia, Lorenzo Baraldi

The CLIP model has been recently proven to be very effective for a variety of cross-modal tasks, including the evaluation of captions generated from vision-and-language architectures. In this paper, we propose a new recipe for a contrastive-based evaluation metric for image captioning, namely Positive-Augmented Contrastive learning Score (PAC-S), that in a n

Yunzhao Wang, Kyrylo Snizhko, Alessandro Romito, Yuval Gefen

We present and analyze a protocol for driven-dissipatively preparing and stabilizing a manifold of quantum manybody entangled states with symmetry-protected topological order. Specifically, we consider the experimental platform consisting of superconducting transmon circuits and linear microwave resonators. We perform theoretical modeling of this platform vi

David Blánquez-Sesé, C. Gómez-Guijarro, G. E. Magdis, B. Magnelli

We present a 1.1mm stacking analysis of moderately massive (log($M_{*}$/$M_{\odot}$) = 10.7 $\pm$ 0.2) quiescent galaxies (QGs) at $\langle z\rangle \sim1.5$, searching for cold dust continuum emission, an excellent tracer of dust and gas mass. Using both the recent GOODS-ALMA survey as well as the full suite of ALMA Band-6 ancillary data in the GOODS-S fiel

W. Hon, M. Berton, E. Sani, R. Webster

PKS 2004-447 is a narrow-line Seyfert 1 (NLS1) harbouring a relativistic jet with gamma-ray emission. On 2019-10-25, the Fermi-Large Area Telescope captured a $\gamma$-ray flare from this source, offering a chance to study the broad-line region (BLR) and jet during such violent events. This can provide insights to the BLR structure and jet interactions, whic

Jin Koda, Akihiko Hirota, Fumi Egusa, Kazushi Sakamoto

We present high-fidelity CO(1-0) imaging of molecular gas across the full star-forming disk of M83, using ALMA's 12m, 7m, and TP arrays and the MIRIAD package. The data have a mass sensitivity and resolution of 10^4Msun and 40 pc. The full disk coverage shows that the characteristics of molecular gas change radially from the center to outer disk. The molecul

Shyam Balaji, Divya Sachdeva, Filippo Sala, Joseph Silk

We use H.E.S.S. $\gamma$-ray observations of Sgr A* to derive novel limits on the Dark Matter (DM) annihilation cross-section. We quantify their dependence on uncertainties i) in the DM halo profile, which we vary from peaked to cored, and ii) in the shape of the DM spike around Sgr A*, dynamically heated by the nuclear star cluster. For peaked halo profiles

Oliver H. E. Philcox

Observations of the Cosmic Microwave Background (CMB) have cemented the notion that the large-scale Universe is both statistically homogeneous and isotropic. But is it invariant also under reflections? To probe this we require parity-sensitive statistics: for scalar observables, the simplest is the trispectrum. We make the first measurements of the parity-od

Aman Srivastava, Shantanu Desai, Neel Kolhe, Mayuresh Surnis

The Indian Pulsar Timing Array (InPTA) collaboration has recently made its first official data release (DR1) for a sample of 14 pulsars using 3.5 years of uGMRT observations. We present the results of single-pulsar noise analysis for each of these 14 pulsars using the InPTA DR1. For this purpose, we consider white noise, achromatic red noise, dispersion meas

Chun-Hao To, Joseph DeRose, Risa H. Wechsler, Eli Rykoff

We present the Cardinal mock galaxy catalogs, a new version of the Buzzard simulation that has been updated to support ongoing and future cosmological surveys, including DES, DESI, and LSST. These catalogs are based on a one-quarter sky simulation populated with galaxies out to a redshift of $z=2.35$ to a depth of $m_{\rm{r}}=27$. Compared to the Buzzard moc

Tom Rudelius

The Distance Conjecture of Ooguri and Vafa holds that any infinite-distance limit in the moduli space of a quantum gravity theory must be accompanied by a tower of exponentially light particles, which places tight constraints on the low-energy effective field theories in these limits. One attempt to extend these constraints to the interior of moduli space is

Colin Orion Chandler, William J. Oldroyd, Henry H. Hsieh, Chadwick A. Trujillo

We announce the discovery of a main-belt comet (MBC), 2010 LH15 (alternately designated 2010 TJ175). MBCs are a rare type of main-belt asteroid that display comet-like activity, such as tails or comae, caused by sublimation. Consequently, MBCs help us map the location of solar system volatiles, providing insight into the origins of material prerequisite for

Fabian Scheuermann, Kathryn Kreckel, Ashley T. Barnes, Francesco Belfiore

Connecting the gas in HII regions to the underlying source of the ionizing radiation can help us constrain the physical processes of stellar feedback and how HII regions evolve over time. With PHANGS$\unicode{x2013}$MUSE we detect nearly 24,000 HII regions across 19 galaxies and measure the physical properties of the ionized gas (e.g. metallicity, ionization

Kazutaka Kimura, Takashi Hosokawa, Kazuyuki Sugimura, Hajime Fukushima

Direct collapse of supermassive stars is a possible pathway to form supermassive black hole seeds at high redshifts. Whereas previous three-dimensional (3D) simulations demonstrate that supermassive stars form via rapid mass accretion, those resolving the stellar interior have been limited. We here report 3D radiation-hydrodynamic (RHD) simulations following

Evan H. Anders, May G. Pedersen

The convective envelopes of solar-type stars and the convective cores of intermediate- and high-mass stars share boundaries with stable radiative zones. Through a host of processes we collectively refer to as "convective boundary mixing" (CBM), convection can drive efficient mixing in these nominally stable regions. In this review, we discuss the current sta

Ronglai Zuo, Fangyun Wei, Brian Mak

Sign languages are visual languages which convey information by signers' handshape, facial expression, body movement, and so forth. Due to the inherent restriction of combinations of these visual ingredients, there exist a significant number of visually indistinguishable signs (VISigns) in sign languages, which limits the recognition capacity of vision neura

Junke Wang, Zuxuan Wu, Dongdong Chen, Chong Luo

Visual Object Tracking (VOT) aims to estimate the positions of target objects in a video sequence, which is an important vision task with various real-world applications. Depending on whether the initial states of target objects are specified by provided annotations in the first frame or the categories, VOT could be classified as instance tracking (e.g., SOT

Kun Yan, Xiao Li, Fangyun Wei, Jinglu Wang

Previous works on video object segmentation (VOS) are trained on densely annotated videos. Nevertheless, acquiring annotations in pixel level is expensive and time-consuming. In this work, we demonstrate the feasibility of training a satisfactory VOS model on sparsely annotated videos-we merely require two labeled frames per training video while the performa

Bo Jiang, Shaoyu Chen, Qing Xu, Bencheng Liao

Autonomous driving requires a comprehensive understanding of the surrounding environment for reliable trajectory planning. Previous works rely on dense rasterized scene representation (e.g., agent occupancy and semantic map) to perform planning, which is computationally intensive and misses the instance-level structure information. In this paper, we propose

Irmak Guzey, Ben Evans, Soumith Chintala, Lerrel Pinto

Teaching dexterity to multi-fingered robots has been a longstanding challenge in robotics. Most prominent work in this area focuses on learning controllers or policies that either operate on visual observations or state estimates derived from vision. However, such methods perform poorly on fine-grained manipulation tasks that require reasoning about contact

Yufei Ye, Xueting Li, Abhinav Gupta, Shalini De Mello

Recent successes in image synthesis are powered by large-scale diffusion models. However, most methods are currently limited to either text- or image-conditioned generation for synthesizing an entire image, texture transfer or inserting objects into a user-specified region. In contrast, in this work we focus on synthesizing complex interactions (ie, an artic

Manuel Moriche, Daniel Hettmann, Manuel García-Villalba, Markus Uhlmann

We have performed particle-resolved direct numerical simulations of many heavy non-spherical particles settling under gravity in the dilute regime. The particles are oblate spheroids of aspect ratio 1.5 and density ratio 1.5. Two Galileo numbers are considered, namely 111 and 152, for which a single oblate spheroid follows a steady vertical and a steady obli

Sherwin Bahmani, Jeong Joon Park, Despoina Paschalidou, Xingguang Yan

In this work, we introduce CC3D, a conditional generative model that synthesizes complex 3D scenes conditioned on 2D semantic scene layouts, trained using single-view images. Different from most existing 3D GANs that limit their applicability to aligned single objects, we focus on generating complex scenes with multiple objects, by modeling the compositional

Omkar Thawakar, Rao Muhammad Anwer, Jorma Laaksonen, Orly Reiner

Accurate 3D mitochondria instance segmentation in electron microscopy (EM) is a challenging problem and serves as a prerequisite to empirically analyze their distributions and morphology. Most existing approaches employ 3D convolutions to obtain representative features. However, these convolution-based approaches struggle to effectively capture long-range de

Naser Ahmadiniaz, Cristhiam Lopez-Arcos, Misha A. Lopez-Lopez, Christian Schubert

This is the second one of a series of four papers devoted to a first calculation of the scalar and spinor QED four-photon amplitudes completely off-shell. We use the worldline formalism which provides a gauge-invariant decomposition for these amplitudes as well as compact integral representations. It also makes it straightforward to integrate out any given p

Xishun Wang, Tong Su, Fang Da, Xiaodong Yang

Motion forecasting is a key module in an autonomous driving system. Due to the heterogeneous nature of multi-sourced input, multimodality in agent behavior, and low latency required by onboard deployment, this task is notoriously challenging. To cope with these difficulties, this paper proposes a novel agent-centric model with anchor-informed proposals for e

Nidhi Pashine, Dong Wang, Jerry Zhang, Sree Kalyan Patiballa

Most granular packings possess shear moduli ($G$) that increase with the applied external pressure, and bulk moduli ($B$) that increase or remain constant with pressure. This paper presents "tessellated" granular metamaterials for which both $G$ and the ratio $G/B$ decrease with increasing pressure. The granular metamaterials are made from flexible tessellat

Mitchell Dennis, Jeremy Sakstein

A method for investigating the sensitivity of the tip of the red giant branch (TRGB) I band magnitude $M_I$ to stellar input physics is presented.~We compute a grid of $\sim$125,000 theoretical stellar models with varying mass, initial helium abundance, and initial metallicity, and train a machine learning emulator to predict $M_I$ as a function of these par

Robin Courant, Maika Edberg, Nicolas Dufour, Vicky Kalogeiton

Transformers were initially introduced for natural language processing (NLP) tasks, but fast they were adopted by most deep learning fields, including computer vision. They measure the relationships between pairs of input tokens (words in the case of text strings, parts of images for visual Transformers), termed attention. The cost is exponential with the nu

Gabriel Cardoso

By the adiabatic theorem, the probability of non-adiabatic transitions in a time-dependent quantum system vanishes in the adiabatic limit. The Landau-Zener (LZ) formula gives the leading functional behavior of the probability close to this limit. On the other hand, in counterdiabatic dynamics, one achieves effectively adiabatic evolution at finite driving sp

Mosima P. Masipa, Sultan Hassan, Mario G. Santos, Gabriella Contardo

Semi-numerical simulations are the leading candidates for evolving reionization on cosmological scales. These semi-numerical models are efficient in generating large-scale maps of the 21cm signal, but they are too slow to enable inference at the field level. We present different strategies to train a U-Net to accelerate these simulations. We derive the ioniz

Riikka Korte, Timo Takala

The John-Nirenberg spaces $JN_p$ are generalizations of the space of bounded mean oscillation $BMO$ with $JN_{\infty}=BMO$. Their vanishing subspaces $VJN_p$ and $CJN_p$ are defined in similar ways as $VMO$ and $CMO$, which are subspaces of $BMO$. As our main result, we prove that $VJN_p$ and $CJN_p$ coincide by showing that certain Morrey type integrals of

Sabarnya Mitra

The recently introduced unbiased exponential resummation at finite chemical potential has become an important approach which promises to capture reliably the behaviour of higher order conserved charge cumulants appearing otherwise in the finite-density QCD Taylor series of thermodynamic observables. In this paper, we present a thorough analysis of the estima

Julien Moatti

We introduce a nonlinear structure preserving high-order scheme for anisotropic advection-diffusion equations. This scheme, based on Hybrid High-Order methods, can handle general meshes. It also has an entropy structure, and preserves the positivity of the solution. We present some numerical simulations showing that the scheme converges at the expected order

Samyak Jain, Rickmoy Samanta

We construct viscous fluid flow sourced by a force dipole embedded in a cylindrical fluid membrane, coupled to external embedding fluids. We find analytic expressions for the flow, in the limit of infinitely long and thin tubular membranes. We utilize this solution to formulate the in-plane dynamics of a pair of pusher-type dipoles along the cylinder surface

Jingyang Lin, Hang Hua, Ming Chen, Yikang Li

Video summarization aims to distill the most important information from a source video to produce either an abridged clip or a textual narrative. Traditionally, different methods have been proposed depending on whether the output is a video or text, thus ignoring the correlation between the two semantically related tasks of visual summarization and textual s

Akshay Paruchuri, Xin Liu, Yulu Pan, Shwetak Patel

Machine learning models for camera-based physiological measurement can have weak generalization due to a lack of representative training data. Body motion is one of the most significant sources of noise when attempting to recover the subtle cardiac pulse from a video. We explore motion transfer as a form of data augmentation to introduce motion variation whi

Jane Ivy Coons, Benjamin Hollering

Identifiability of the discrete tree parameter is a key property for phylogenetic models since it is necessary for statistically consistent estimation of the tree from sequence data. Algebraic methods have proven to be very effective at showing that tree and network parameters of phylogenetic models are identifiable, especially when the underlying models are

Patrick Y. Wu, Jonathan Nagler, Joshua A. Tucker, Solomon Messing

Existing approaches to estimating politicians' latent positions along specific dimensions often fail when relevant data is limited. We leverage the embedded knowledge in generative large language models (LLMs) to address this challenge and measure lawmakers' positions along specific political or policy dimensions. We prompt an instruction/dialogue-tuned LLM

Nikita Medvedev

This proceeding discusses the impact of XUV/X-ray irradiation on materials, and how their response is affected by temperature, size, and structure. When materials are exposed to intense XUV/X-ray irradiation, they undergo a series of processes ultimately leading to observable structure modification and damage. These effects were studied with a hybrid simulat

Project 8 Collaboration, A. Ashtari Esfahani, S. Böser, N. Buzinsky

Project 8 has developed a novel technique, Cyclotron Radiation Emission Spectroscopy (CRES), for direct neutrino mass measurements. A CRES-based experiment on the beta spectrum of tritium has been carried out in a small-volume apparatus. We provide a detailed account of the experiment, focusing on systematic effects and analysis techniques. In a Bayesian (fr

Haoheng Lan, Jindong Gu, Philip Torr, Hengshuang Zhao

When a small number of poisoned samples are injected into the training dataset of a deep neural network, the network can be induced to exhibit malicious behavior during inferences, which poses potential threats to real-world applications. While they have been intensively studied in classification, backdoor attacks on semantic segmentation have been largely o

Jyun-Yu Wu, Yung-Ting Lee, Guan-Hao Chen, Zheng-Hong Li

Charge density wave (CDW) resulted from a small distortion in the lattice is able to create new orders beyond the original lattice. In 2H-NbSe2, one of the layered transition metal dichalcogenides (TMD), the 3x3 charge order appears in two-dimensional (2D) layers. Although CDW is usually described by a sine wave, the spatial distribution within a 2D layer ha

E. Kryshen, M. Strikman, M. Zhalov

We present predictions for the cross sections of the coherent and incoherent $J/\psi$ photoproduction in ultra-peripheral collisions at RHIC and at the LHC calculated for different classes of events depending on the presence of neutrons emitted by colliding nuclei. Since strong nucleus-nucleus interactions in UPCs are suppressed, it is usually assumed that n

Duc Nguyen, Anderson Ye Zhang

Permutation synchronization is an important problem in computer science that constitutes the key step of many computer vision tasks. The goal is to recover $n$ latent permutations from their noisy and incomplete pairwise measurements. In recent years, spectral methods have gained increasing popularity thanks to their simplicity and computational efficiency.

Colton Stearns, Davis Rempe, Jiateng Liu, Alex Fu

Modern depth sensors such as LiDAR operate by sweeping laser-beams across the scene, resulting in a point cloud with notable 1D curve-like structures. In this work, we introduce a new point cloud processing scheme and backbone, called CurveCloudNet, which takes advantage of the curve-like structure inherent to these sensors. While existing backbones discard

L. Buffarini, H. J. Rabal, N. L. Cap, E. E. Grumel

We carried out an experimental set-up for reading a hidden drawing under papyrus using an optical technique based on the speckle phenomenon that is observed when a rough surface is illuminated by laser light. We propose the use of several wavelengths of light illumination and adaptive algorithms to process the speckle images. We employ a set of filters to pr

Gábor B. Kovács, Róbert Szabó, János Nuspl

Despite the appearance of two- and three-dimensional models thanks to the rapid growth of computing performance, numerical hydrocodes used to model radial stellar pulsations still apply a one-dimensional stellar envelope model without any realistic atmosphere, in which a significant improvement was the inclusion of turbulent convection. However, turbulent co

Etai Sella, Gal Fiebelman, Peter Hedman, Hadar Averbuch-Elor

Large scale text-guided diffusion models have garnered significant attention due to their ability to synthesize diverse images that convey complex visual concepts. This generative power has more recently been leveraged to perform text-to-3D synthesis. In this work, we present a technique that harnesses the power of latent diffusion models for editing existin

László Lempert

Let $S$ be a compact Hausdorff space and $X$ a complex manifold. We consider the space $C(S,X)$ of continuous maps $S\to X$, and prove that any bounded holomorphic function on this space can be continued to a holomorphic function, possibly multivalued, on a larger space $B(S,X)$ of Borel maps. As an application we prove two theorems about bounded holomorphic

Sahar Diskin, Ilay Hoshen, Maksim Zhukovskii

For graphs $G$ and $F$, the saturation number $\textit{sat}(G,F)$ is the minimum number of edges in an inclusion-maximal $F$-free subgraph of $G$. In 2017, Kor\'andi and Sudakov initiated the study of saturation in random graphs. They showed that for constant $p\in (0,1)$, whp $\textit{sat}\left(G(n,p),K_s\right)=\left(1+o(1)\right)n\log_{\frac{1}{1-p}}n$. W

Chris Emezue, Hellina Nigatu, Cynthia Thinwa, Helper Zhou

Stopwords are fundamental in Natural Language Processing (NLP) techniques for information retrieval. One of the common tasks in preprocessing of text data is the removal of stopwords. Currently, while high-resource languages like English benefit from the availability of several stopwords, low-resource languages, such as those found in the African continent,

Morris Alper, Michael Fiman, Hadar Averbuch-Elor

Most humans use visual imagination to understand and reason about language, but models such as BERT reason about language using knowledge acquired during text-only pretraining. In this work, we investigate whether vision-and-language pretraining can improve performance on text-only tasks that involve implicit visual reasoning, focusing primarily on zero-shot

Rodrigo C. V. Coelho, Hanqing Zhao, Mykola Tasinkevych, Ivan I. Smalyukh

We investigate, using experiments and numerical simulations, the distortions and the alignment of skyrmions in the liquid crystal under external flows for a range of average flow velocities. The simulations are based on the Landau-de Gennes $Q$ tensor theory both for isolated as well as for systems with many skyrmions. We found striking flow-driven elongatio

Chaoda Zheng, Xu Yan, Haiming Zhang, Baoyuan Wang

3D single object tracking in LiDAR point clouds (LiDAR SOT) plays a crucial role in autonomous driving. Current approaches all follow the Siamese paradigm based on appearance matching. However, LiDAR point clouds are usually textureless and incomplete, which hinders effective appearance matching. Besides, previous methods greatly overlook the critical motion

Stephen Gustafson, Evan Miller, Tai-Peng Tsai

We consider axisymmetric, swirl-free solutions of the Euler equations in three and higher dimensions, of generalized anti-parallel-vortex-tube-pair-type: the initial scalar vorticity has a sign in the half-space, is odd under reflection across the plane, is bounded and decays sufficiently rapidly at the axis and at spatial infinity. We prove lower bounds on

Ambrose D. Law, Matthew C. Lettington, Karl Michael Schmidt

We consider a joint ordered multifactorisation for a given positive integer $n\geq 2$ into $m$ parts, where $n=n_1~\times~\ldots~\times~n_m$, and each part $n_j$ is split into one or more component factors. Our central result gives an enumeration formula for all such joint ordered multifactorisations $\mathcal{N}_m(n)$. As an illustrative application, we sho

Andrei Neguţ

We develop the connection between the preprojective $K$-theoretic Hall algebra of a quiver $Q$ and the quantum loop group associated to $Q$ via stable envelopes of Nakajima quiver varieties.

Mark Stefik

The vision of AI collaborators is a staple of mythology and science fiction, where artificial agents with special talents assist human partners and teams. In this dream, sophisticated AIs understand nuances of collaboration and human communication. The AI as collaborator dream is different from computer tools that augment human intelligence (IA) or intermedi

C. Piquard, P. Glidic, C. Han, A. Aassime

The Kondo effect, deriving from a local magnetic impurity mediating electron-electron interactions, constitutes a flourishing basis for understanding a large variety of intricate many-body problems. Its experimental implementation in tunable circuits has made possible important advances through well-controlled investigations. However, these have mostly conce

Jonathon Mellor, Christopher E Overton, Martyn Fyles, Liam Chawner

Following the UK Government's Living with COVID-19 Strategy and the end of universal testing, hospital admissions are an increasingly important measure of COVID-19 pandemic pressure. Understanding leading indicators of admissions at National Health Service (NHS) Trust, regional and national geographies help health services plan capacity needs and prepare for

Jiawang Nie, Defeng Sun, Xindong Tang, Min Zhang

In this paper, we study variational inequality problems (VIPs) with involved mappings and feasible sets characterized by polynomial functions (namely, polynomial VIPs). We propose a numerical algorithm for computing solutions to polynomial VIPs based on Lagrange multiplier expressions and the Moment-SOS hierarchy of semidefinite relaxations. We also extend o

J. Fekete, P. Joshi, T. J. Barrett, T. M. James

Electrically percolating nanowire networks are amongst the most promising candidates for next-generation transparent electrodes. Scientific interest in these materials stems from their intrinsic current distribution heterogeneity, leading to phenomena like percolating pathway re-routing and localized self-heating, which can cause irreversible damage. Without

Jakub Podgorny, Lorenzo Marra, Fabio Muleri, Nicole Rodriguez Cavero

We report on an X-ray polarimetric observation of the high-mass X-ray binary LMC X-1 in the high/soft state, obtained by the Imaging X-ray Polarimetry Explorer (IXPE) in October 2022. The measured polarization is below the minimum detectable polarization of 1.1 per cent (at the 99 per cent confidence level). Simultaneously, the source was observed with the N

Guilherme S. Couto, Thaisa Storchi-Bergmann

Radio activity in AGN (Active Galactic Nuclei) produce feedback on the host galaxy via the impact of the relativistic jets on the circumnuclear gas. Although radio jets can reach up to several times the optical radius of the host galaxy, in this review we focus on the observation of the feedback deposited locally in the central region of the host galaxies, i

Eamon Duede

This paper aims to clarify the representational status of Deep Learning Models (DLMs). While commonly referred to as 'representations', what this entails is ambiguous due to a conflation of functional and relational conceptions of representation. This paper argues that while DLMs represent their targets in a relational sense, in general, we have no good reas

Matthias Keicher, Matan Atad, David Schinz, Alexandra S. Gersing

Vertebral fractures are a consequence of osteoporosis, with significant health implications for affected patients. Unfortunately, grading their severity using CT exams is hard and subjective, motivating automated grading methods. However, current approaches are hindered by imbalance and scarcity of data and a lack of interpretability. To address these challe

Markus J. Bonse, Emily O. Garvin, Timothy D. Gebhard, Felix A. Dannert

Over the past decade, hundreds of nights have been spent on the worlds largest telescopes to search for and directly detect new exoplanets using high-contrast imaging (HCI). Thereby, two scientific goals are of central interest: First, to study the characteristics of the underlying planet population and distinguish between different planet formation and evol

Hong Zhang, Haewoon Kwak, Wei Gao, Jisun An

People who share similar opinions towards controversial topics could form an echo chamber and may share similar political views toward other topics as well. The existence of such connections, which we call connected behavior, gives researchers a unique opportunity to predict how one would behave for a future event given their past behaviors. In this work, we

Junchen Rong

We discuss scalar conformal field theories (CFTs) that can be realized in structural phase transitions. The Landau condition and Lifshitz condition are reviewed, which are necessary conditions for a structural phase transition to be second order. We also review the perturbative analysis in $4-\epsilon$ expansion of the corresponding Landau actions, which wer

Li Zhou, Zikun Zhou, Kaige Mao, Zhenyu He

Tracking by natural language specification aims to locate the referred target in a sequence based on the natural language description. Existing algorithms solve this issue in two steps, visual grounding and tracking, and accordingly deploy the separated grounding model and tracking model to implement these two steps, respectively. Such a separated framework

Hassan Firouzjahi

We revisit the one-loop correction in curvature perturbation power spectrum in models of single field inflation which undergo a phase of ultra slow-roll (USR) inflation. We include the contributions from both the cubic and quartic interaction Hamiltonians and calculate the one-loop corrections on the spectrum of the CMB scale modes from the small scale modes

Anirudh S Sundar, Larry Heck

Optimizing accuracy and performance while eliminating hallucinations of open-domain conversational large language models (LLMs) is an open research challenge. A particularly promising direction is to augment and ground LLMs with information from structured sources. This paper introduces Conversational Tables (cTBLS), a three-step architecture to retrieve and

Zonglin Yang, Xinya Du, Rui Mao, Jinjie Ni

Logical reasoning is central to human cognition and intelligence. It includes deductive, inductive, and abductive reasoning. Past research of logical reasoning within AI uses formal language as knowledge representation and symbolic reasoners. However, reasoning with formal language has proved challenging (e.g., brittleness and knowledge-acquisition bottlenec

N. V. Peskov, M. M. Slinko

Self-oscillations in some oxidation reactions on metal catalysts are associated with periodic oxidation/reduction of the catalyst surface. If the reaction proceeds in a flow reactor at atmospheric pressure, then the reaction dynamics is complicated by the mass transfer in the gas phase. In this paper, the reaction in a flow reactor is described by an 1D syst