April 2024 arXiv papers — page 127

Shrey Gupta, Yongbee Park, Jianzhao Bi, Suyash Gupta

Air pollution, especially particulate matter 2.5 (PM2.5), is a pressing concern for public health and is difficult to estimate in developing countries (data-poor regions) due to a lack of ground sensors. Transfer learning models can be leveraged to solve this problem, as they use alternate data sources to gain knowledge (i.e., data from data-rich regions). H

Valdemar Melin, Yuta Sekiguchi, Paul Wiegmann, Konstantin Zarembo

The two-dimensional Gross-Neveu model is anticipated to undergo a crystalline phase transition at high baryon charge densities. This conclusion is drawn from the mean-field approximation, which closely resembles models of Peierls instability. We demonstrate that this transition indeed occurs when both the rank of the symmetry group and the dimension of the p

Rohan Reddy Mekala, Elias Garratt, Matthias Muehle, Arjun Srinivasan

From a process development perspective, diamond growth via chemical vapor deposition has made significant strides. However, challenges persist in achieving high quality and large-area material production. These difficulties include controlling conditions to maintain uniform growth rates for the entire growth surface. As growth progresses, various factors or

Sam Spiro

Given a digraph $D$, we say that a set of vertices $Q\subseteq V(D)$ is a $q$-kernel if $Q$ is an independent set and if every vertex of $D$ can be reached from $Q$ by a path of length at most $q$. In this paper, we initiate the study of several extremal problems for $q$-kernels. For example, we introduce and make progress on (what turns out to be) a weak ve

Aarohi Srivastava, David Chiang

We present a suite of experiments that allow us to understand the underlying challenges of language model adaptation to nonstandard text. We do so by designing interventions that approximate core features of user-generated text and their interactions with existing biases of language models. Applying our interventions during language model adaptation to nonst

Hari Krovi

Simulation of realistic classical mechanical systems is of great importance to many areas of engineering such as robotics, dynamics of rotating machinery and control theory. In this work, we develop quantum algorithms to estimate quantities of interest such as the kinetic energy in a given classical mechanical system in the presence of friction or damping as

Colton Hill, Philip N. Brown

Self-interested routing polices from individual users in a system can collectively lead to poor aggregate congestion in routing networks. The introduction of altruistic agents, whose goal is to benefit other agents in the system, can seemingly improve aggregate congestion. However, it is known in that in some network routing problems, altruistic agents can a

Patrick Hennebelle, Michael Y. Grudić

Stars are amongst the most fundamental structures of our Universe. They comprise most of the baryonic and luminous mass of galaxies, synthethise heavy elements, and injec\ t mass, momentum, and energy into the interstellar medium. They are also home to the planets. Since stellar properties are primarily decided by their mass, the so-called \ stellar initial

Alyssa Mock, Steffen Richter, Alexis Papamichail, Vallery Stanishev

Monoclinic $\beta$-Ga$_2$O$_3$ films grown on $c$-plane sapphire have been shown to exhibit six $(\bar{2}01)$-plane oriented domains, which are equally-spaced-by-rotation around the surface normal and equally-sized-by-volume that render the film optical response effectively uniaxial. We derive and discuss an optical model suitable for ellipsometry data analy

David A. Neufeld, P. Manoj, Himanshu Tyagi, Mayank Narang

Using the MIRI/MRS spectrometer on JWST, we have detected pure rotational, suprathermal OH emissions from the vicinity of the intermediate-mass protostar HOPS 370 (OMC2/FIR3). These emissions are observed from shocked knots in a jet/outflow, and originate in states of rotational quantum number as high as 46 that possess excitation energies as large as $E_U/k

Dayu Yang

Merger and Acquisition (M&A) activities play a vital role in market consolidation and restructuring. For acquiring companies, M&A serves as a key investment strategy, with one primary goal being to attain complementarities that enhance market power in competitive industries. In addition to intrinsic factors, a M&A behavior of a firm is influenced by the M&A

H. Ananthnarayan, Omkar Javadekar, Rajiv Kumar

Let $R$ be a fibre product of standard graded algebras over a field. We study the structure of syzygies of finitely generated graded $R$-modules. As an application of this, we show that the existence of an $R$-module of finite regularity and infinite projective dimension forces $R$ to be Koszul. We also look at the extremal rays of the Betti cone of finitely

Bob Knighton, Vit Sriprachyakul

We study correlation functions of spectrally-flowed vertex operators in bosonic string theory on $\text{AdS}_3\times X$ in the path integral formalism. By restricting the path integral to only include worldsheets which live near the asymptotic boundary, we compute correlation functions of spectrally-flowed vertex operators and find a precise agreement with t

Huizhong Ren, Georgios G. Pyrialakos, Fan O. Wu, Pawel S. Jung

The theory of optical thermodynamics provides a comprehensive framework that enables a self-consistent description of the intricate dynamics of nonlinear multimoded photonic systems. This theory, among others, predicts a pressure-like intensive quantity ($\hat{p}$) that is conjugate to the system's total number of modes ($M$) - its corresponding extensive va

Huizhong Ren, Haokun Luo, Mahmoud A. Selim, Georgios G. Pyrialakos

Optical forces in dielectric structures are typically analyzed by utilizing either the Maxwell stress tensor or energy-based methods from which they can be derived by means of the eigenfrequencies and the effective refractive indices involved. While the equivalence of these two methods has been discussed in several studies, it would seem that a general elect

Ruijiao Sun, Rohith Reddy, David Mayerich

Several emerging microscopy imaging methods rely on complex interactions between the incident light and the sample. These include interferometry, spectroscopy, and nonlinear optics. Reconstructing a sample from the measured scattered field relies on fast and accurate optical models. Fast approaches like ray tracing and the Born approximation have limitations

Jinyang Liu, Wondmgezahu Teshome, Sandesh Ghimire, Mario Sznaier

Solving image and video jigsaw puzzles poses the challenging task of rearranging image fragments or video frames from unordered sequences to restore meaningful images and video sequences. Existing approaches often hinge on discriminative models tasked with predicting either the absolute positions of puzzle elements or the permutation actions applied to the o

Qian Lei, Boris Khusid, Lou Kondic, Paul M. Chaikin

Here we report the results of microgravity experiments performed on the International Space Station (ISS) to study crystallized, metastable colloidal liquids in the region of the hard sphere phase diagram that has been found to be glassy on Earth. Using confocal microscopy, we observed the self-assembly of high density, three-dimensional colloidal crystals f

Ivri Nagar, Amit Sever, De-liang Zhong

We study a class of renormalization group flows on line defects that can be described by a generalized free field with ordered planar contractions on the line. They are realized, for example, in large $N$ gauge theories with matter in the fundamental representation and arise generically in non-relativistic CFTs. We analyze the flow exactly and compute the ch

Rohan S. Adhikari, Dilipkumar N. Asthagiri, Walter G. Chapman

Atomistic force fields that are tuned to describe folded proteins predict overly compact structures for intrinsically disordered proteins (IDPs). To correct this, improvements in force fields to better model IDPs are usually paired with scattering models for validation against experiments. For scattering calculations, protein configurations from all-atom sim

Dongdong Ren, Wenbin Li, Tianyu Ding, Lei Wang

Recent advancements in model pruning have focused on developing new algorithms and improving upon benchmarks. However, the practical application of these algorithms across various models and platforms remains a significant challenge. To address this challenge, we propose ONNXPruner, a versatile pruning adapter designed for the ONNX format models. ONNXPruner

Renzo Bruera, Robert Cardona, Eva Miranda, Daniel Peralta-Salas

We explore the relationship between Turing completeness and topological entropy of dynamical systems. We first prove that a natural class of Turing machines that we call "branching Turing machines" (which includes most of the known examples of universal Turing machines) has positive topological entropy. Motivated by the recent construction of Turing complete

Cheol-Hui Lee, Hakseung Kim, Hyun-jee Han, Min-Kyung Jung

The classification of sleep stages is a pivotal aspect of diagnosing sleep disorders and evaluating sleep quality. However, the conventional manual scoring process, conducted by clinicians, is time-consuming and prone to human bias. Recent advancements in deep learning have substantially propelled the automation of sleep stage classification. Nevertheless, c

Victor Hugo Pereira Rodrigues, Tiago Roux Oliveira, Miroslav Krstić, Tamer Başar

This paper proposes a novel approach for locally stable convergence to Nash equilibrium in duopoly noncooperative games based on a distributed event-triggered control scheme. The proposed approach employs extremum seeking, with sinusoidal perturbation signals applied to estimate the Gradient (first derivative) of unknown quadratic payoff functions. This is t

D. Kislov, P. Voroshilov, A. Kadochkin, A. Veniaminov

Flexible transparent electrodes, encompassing the combination of optical transparency and electrical conductivity, empower numerous optoelectronic applications. While the main efforts nowadays concentrate on developing wire meshes and conductive oxides, those technologies are still in a quest to find a balance between price, performance, and versatility. Her

Joseph Briggs, Alex Parker, Coy Schwieder, Chris Wells

Write $W^{(n)}$ to mean the $n$-letter word obtained by repeating a fixed word $W$ and let $R_n$ denote a uniformly random $n$-letter word sampled from the same alphabet as $W$. We are interested in the average length of the longest common subsequence between $W^{(n)}$ and $R_n$, which is known to be $\gamma(W)\cdot n+o(n)$ for some constant $\gamma(W)$. Buk

Alfonso Romero, Miguel Sánchez

A new curvature obstruction to the existence of a timelike (resp. causal) Killing or homothetic vector field $X$ on an even-dimensional (odd-dimensional) Lorentzian manifold, in terms of its timelike (resp. null) sectional curvature is given. As a consequence for the compact case, the well-known Gauss-Bonnet-Chern obstruction to the existence of semi-Riemann

Y. Lai, C. Howlett, M. Maus, H. Gil-Marín

DESI aims to provide one of the tightest constraints on cosmological parameters by analysing the clustering of more than thirty million galaxies. However, obtaining such constraints requires special care in validating the methodology and efforts to reduce the computational time required through data compression and emulation techniques. In this work, we perf

U. Andrade, J. Mena-Fernández, H. Awan, A. J. Ross

In the era of precision cosmology, ensuring the integrity of data analysis through blinding techniques is paramount -- a challenge particularly relevant for the Dark Energy Spectroscopic Instrument (DESI). DESI represents a monumental effort to map the cosmic web, with the goal to measure the redshifts of tens of millions of galaxies and quasars. Given the d

Hsin-Yuan Huang, John Preskill, Mehdi Soleimanifar

Certifying that an n-qubit state synthesized in the lab is close to the target state is a fundamental task in quantum information science. However, existing rigorous protocols either require deep quantum circuits or exponentially many single-qubit measurements. In this work, we prove that almost all n-qubit target states, including those with exponential cir

Joseph McDonough, Pavlo Pylyavskyy, Shiyun Wang

A natural unit interval order is a naturally labelled partially ordered set that avoids patterns ${\bf 3} + {\bf 1}$ and $\bf 2 + 2$. To each natural unit interval order one can associate a symmetric function. The Stanley-Stembridge conjecture states that each such symmetric function is positive in the basis of complete homogenous symmetric functions. This c

Emilio Vilches

In this paper, we study the well-posedness of integro-differential sweeping processes of Volterra type. Using new enhanced versions of Gronwall's inequality, a reparametrization technique, and a fixed point argument for history-dependent operators, we obtain the existence of solutions and provide a fully continuous dependence result for the integro-different

Samuel Tovey, Tobias Fellner, Christian Holm, Michael Spannowsky

We demonstrate a novel approach to reservoir computation measurements using random matrices. We do so to motivate how atomic-scale devices could be used for real-world computational applications. Our approach uses random matrices to construct reservoir measurements, introducing a simple, scalable means of generating state representations. In our studies, two

Evan Peters

Information theory provides tools to predict the performance of a learning algorithm on a given dataset. For instance, the accuracy of learning an unknown parameter can be upper bounded by reducing the learning task to hypothesis testing for a discrete random variable, with Fano's inequality then stating that a small conditional entropy between a learner's o

Tom Hutchcroft

In long-range percolation on $\mathbb{Z}^d$, we connect each pair of distinct points $x$ and $y$ by an edge independently at random with probability $1-\exp(-\beta\|x-y\|^{-d-\alpha})$, where $\alpha>0$ is fixed and $\beta\geq 0$ is a parameter. In a previous paper, we proved that if $0<\alpha<d$ then the critical two-point function satisfies the spatially a

Seyed Mahed Mousavi, Simone Alghisi, Giuseppe Riccardi

LLMs acquire knowledge from massive data snapshots collected at different timestamps. Their knowledge is then commonly evaluated using static benchmarks. However, factual knowledge is generally subject to time-sensitive changes, and static benchmarks cannot address those cases. We present an approach to dynamically evaluate the knowledge in LLMs and their ti

Pierre Houdouin, Manuel Ruiz, Patrick Panciatici

The fast growth of renewable energies increases the power congestion risk. To address this issue, the French Transmission System Operator (RTE) has developed closed-loop controllers to handle congestion. RTE wishes to estimate the probability that the controllers ensure the equipment's safety to guarantee their proper functioning. The naive approach to estim

Parthapratim Pradhan

We derive the entropy product rule for Taub-NUT~(Newman-Unti-Tamburino)-de~Sitter black hole~(BH) and Taub-NUT--Anti-de~Sitter BH. We show that the entropy products in terms of both the physical horizons are \emph{mass-independent}. Both \emph{perturbative} approximation and \emph{direct} method have been considered. By introducing the cosmological horizon w

Amar Hadzihasanovic

This is a book on higher-categorical diagrams, including pasting diagrams. It aims to provide a thorough and modern reference on the subject, collecting, revisiting and expanding results scattered across the literature, informed by recent advances and practical experience with higher-dimensional diagram rewriting. We approach the subject as a kind of directe

M. Maus, Y. Lai, H. E. Noriega, S. Ramirez-Solano

In preparation for the next generation of galaxy redshift surveys, and in particular the year-one data release from the Dark Energy Spectroscopic Instrument (DESI), we investigate the consistency of a variety of effective field theory models that describe the galaxy-galaxy power spectra in redshift space into the quasi-linear regime using 1-loop perturbation

Nikhil Sarin, Stephan Rosswog

A major ingredient for kilonova lightcurves is the radioactive heating rate and its dependence on the electron fraction and velocity of the ejecta and, in principle, on the nuclear mass formula. Heating-rate formulae commonly used as the basis for kilonova models previously employed in the literature produce substantially different outputs for high electron

Arazi Pinhas, Zbyszek Krzeminski, Denis Vida, Peter Brown

Physical properties of ten millimeter-sized meteoroids from the Southern Delta Aquariids (SDA) shower are derived using optical observations from the Canadian Automated Meteor Observatory between 2020 and 2023. The meteors are found to ablate in two distinct erosion stages, the second stage showing a single, bright leading fragment. Our modelling interprets

H. E. Noriega, A. Aviles, H. Gil-Marín, S. Ramirez-Solano

The Dark Energy Spectroscopic Instrument (DESI) will provide unprecedented information about the large-scale structure of our Universe. In this work, we study the robustness of the theoretical modelling of the power spectrum of FOLPS, a novel effective field theory-based package for evaluating the redshift space power spectrum in the presence of massive neut

S. Ramirez-Solano, M. Icaza-Lizaola, H. E. Noriega, M. Vargas-Magaña

In the contemporary era of high-precision spectroscopic surveys, led by projects like DESI, there is an increasing demand for optimizing the extraction of cosmological information from clustering data. This work conducts a thorough comparison of various methodologies for modeling the full shape of the two-point statistics in configuration space. We investiga

Mohsen Amiri, Mehdi Hosseinzadeh

The growing potential of quadcopters in various domains, such as aerial photography, search and rescue, and infrastructure inspection, underscores the need for real-time control under strict safety and operational constraints. This challenge is compounded by the inherent nonlinear dynamics of quadcopters and the on-board computational limitations they face.

Vahid Balazadeh, Keertana Chidambaram, Viet Nguyen, Rahul G. Krishnan

We study the problem of online sequential decision-making given auxiliary demonstrations from experts who made their decisions based on unobserved contextual information. These demonstrations can be viewed as solving related but slightly different problems than what the learner faces. This setting arises in many application domains, such as self-driving cars

David G. Rea, Jacob B. Simon, Daniel Carrera, Geoffroy Lesur

Given the important role turbulence plays in the settling and growth of dust grains in protoplanetary disks, it is crucial that we determine whether these disks are turbulent and to what extent. Protoplanetary disks are weakly ionized near the mid-plane, which has led to a paradigm in which largely laminar magnetic field structures prevail deeper in the disk

Hareesh Gautham Bhaskar, Hagai Perets

Multiple analytical and empirical stability criteria have been derived in the literature for two planet systems. But, the dependence of the stability limit on the initial mutual inclination between the inner and outer orbits is not well modeled by previous stability criteria. Here, we derive a semi-analytical stability criteria for two planet systems, at arb

Sun Woo P. Kim, Austen Lamacraft

We introduce and study the planted directed polymer, in which the path of a random walker is inferred from noisy 'images' accumulated at each timestep. Formulated as a nonlinear problem of Bayesian inference for a hidden Markov model, this problem is a generalization of the directed polymer problem of statistical physics, coinciding with it in the limit of z

Teruyuki Hirano, Eric Gaidos, Hiroki Harakawa, Klaus W. Hodapp

Exoplanets in their infancy are ideal targets to probe the formation and evolution history of planetary systems, including the planet migration and atmospheric evolution and dissipation. In this paper, we present spectroscopic observations and analyses of two planetary transits of K2-33b, which is known to be one of the youngest transiting planets (age $\app

Zhengzhi Wu, Jing-yun Zhang, Hong Yao

The non-integrable higher spin Kitaev honeycomb model has an exact $\mathbb{Z}_2$ gauge structure, which exclusively identifies quantum spin liquid (QSL) in the half-integer spin Kitaev model. But its constraints for the integer-spin Kitaev model are much limited, and even trivially gapped insulators cannot be excluded. The physical implications of exact $\m

Dominik Neuenfeld, Andrew Svesko, Watse Sybesma

We study shape deformations of two-dimensional end-of-the-world (ETW) branes, such as those in bottom-up models of two-dimensional holographic boundary conformal field theories (BCFT), and derive an action for the theory of brane deformations in any bulk three-dimensional maximally symmetric spacetime. In the case of a bulk anti-de Sitter (AdS) spacetime, at

Rachel K. Friesen, Emma Jarvis

Most stars form in clusters and groups rather than in isolation. We present $\lesssim 5^{\prime\prime}$ angular resolution ($\sim 2000$ au, or 0.01 pc) Very Large Array NH$_3$ (1,1), (2,2), and (3,3) and 1.3 cm continuum emission observations of the dense gas within the Serpens South protocluster and extended filaments to the north and south. We identify 94

Gregor Kasieczka, John Andrew Raine, David Shih, Aman Upadhyay

We propose the first-ever complete, model-agnostic search strategy based on the optimal anomaly score, for new physics on the tails of distributions. Signal sensitivity is achieved via a classifier trained on auxiliary features in a weakly-supervised fashion, and backgrounds are predicted using the ABCD method in the classifier output and the primary tail fe

Nuno M. Santos, Carolina L. Benone, Carlos A. R. Herdeiro

We study radial perturbations of spherically symmetric spin-$0$ and spin-$1$ bosonic stars, computing numerically the squared frequency of the fundamental mode. We find that not all critical points $-$ where the Arnowitt-Deser-Misner mass attains an extremum $-$ correspond to zero modes. Thus, radial stability does not $\textit{always}$ change at such critic

Mathias Garny, Florian Niedermann, Henrique Rubira, Martin S. Sloth

We propose a simple model that can alleviate the $H_0$ tension while remaining consistent with big bang nucleosynthesis (BBN). It is based on a dark sector described by a standard Lagrangian featuring a $SU(N)$ gauge symmetry with $N\geq3$ and a massive scalar field with a quartic coupling. The scalar acts as dark Higgs leading to spontaneous symmetry breaki

Betty X. Hu, Avi Loeb

The strong tidal force in a supermassive black hole's (SMBH) vicinity, coupled with a higher stellar density at the center of a galaxy, make it an ideal location to study the interaction between stars and black holes. Two stars moving near the SMBH could collide at a very high speed, which can result in a high energy flare. The resulting debris can then accr

Pedro Bittar, Sylvain Fichet, Lucas de Souza

We compute the four-photon ($F^4$) operators generated by loops of charged particles of spin $0$, $\frac{1}{2}$, $1$ in the presence of gravity and in any spacetime dimension $d$. To this end, we expand the one-loop effective action via the heat kernel coefficients, which capture both the gravity-induced renormalization of the $F^4$ operators and the low-ene

Jonah Herzog-Arbeitman, Jiabin Yu, Dumitru Călugăru, Haoyu Hu

We propose a general principle for the low-energy theory of narrow bands with concentrated Berry curvature and Fubini-Study metric in the form of a map to Anderson-"+" models composed of heavy fermions hybridizing and interacting with semi-metallic modes. This map resolves the obstruction preventing topological bands from being realized in a local Hamiltonia

Lucie Scharré, Daniele Sorini, Romeel Davé

Using several variants of the cosmological Simba simulations, we investigate the impact of different feedback prescriptions on the cosmic star formation history. Adopting a global-to-local approach, we link signatures seen in global observables, such as the star formation rate density (SFRD) and the galaxy stellar mass function (GSMF), to feedback effects in

Shengqi Sang, Timothy H. Hsieh

For quantum phases of Hamiltonian ground states, the energy gap plays a central role in ensuring the stability of the phase as long as the gap remains finite. We propose Markov length, the length scale at which the quantum conditional mutual information (CMI) decays exponentially, as an equally essential quantity characterizing mixed-state phases and transit

Julian B. Muñoz, Jordan Mirocha, John Chisholm, Steven R. Furlanetto

New James Webb Space Telescope (JWST) observations are revealing the first galaxies to be prolific producers of ionizing photons, which we argue gives rise to a tension between different probes of reionization. Over the last two decades a consensus has emerged where star-forming galaxies are able to generate enough photons to drive reionization, given reason

Oliver H. E. Philcox, Thomas Flöss

By measuring, modeling and interpreting cosmological datasets, one can place strong constraints on models of the Universe. Central to this effort are summary statistics such as power spectra and bispectra, which condense the high-dimensional data into low-dimensional representations. In this work, we introduce a modern set of estimators for computing such st

Zewei Zhang, Huan Liu, Jun Chen, Xiangyu Xu

In this paper, we introduce GoodDrag, a novel approach to improve the stability and image quality of drag editing. Unlike existing methods that struggle with accumulated perturbations and often result in distortions, GoodDrag introduces an AlDD framework that alternates between drag and denoising operations within the diffusion process, effectively improving

Bartolomeo Trefoloni, Elisabeta Lusso, Emanuele Nardini, Guido Risaliti

A sample of quasars has been recently assembled to investigate the non-linear relation between their monochromatic luminosities at 2500{\AA}, and 2 keV and to exploit quasars as a new class of standardized candles. The use of this technique for cosmological purposes relies on the non-evolution with redshift of the UV-optical spectral properties of quasars, a

Oğuzhan Fatih Kar, Alessio Tonioni, Petra Poklukar, Achin Kulshrestha

Vision-language models (VLMs) are typically composed of a vision encoder, e.g. CLIP, and a language model (LM) that interprets the encoded features to solve downstream tasks. Despite remarkable progress, VLMs are subject to several shortcomings due to the limited capabilities of vision encoders, e.g. "blindness" to certain image features, visual hallucinatio

Wuhyun Sohn, Dong-Gang Wang, James R. Fergusson, E. P. S. Shellard

In this paper, we present the first comprehensive CMB data analysis of cosmological collider physics. New heavy particles during inflation can leave imprints in the primordial correlators which are observable in today's cosmological surveys. This remarkable detection channel provides an unsurpassed opportunity to probe new physics at extremely high energies.

Weihao Xia, Raoul de Charette, Cengiz Öztireli, Jing-Hao Xue

We address prevailing challenges of the brain-powered research, departing from the observation that the literature hardly recover accurate spatial information and require subject-specific models. To address these challenges, we propose UMBRAE, a unified multimodal decoding of brain signals. First, to extract instance-level conceptual and spatial details from

Eduardo Camps-Moreno, Gretchen L. Matthews, Welington Santos

In this paper, we study algebraic geometry codes from curves over $\mathbb{F}_{q^\ell}$ through their virtual projections which are algebraic geometric codes over $\mathbb{F}_q$. We use the virtual projections to provide fractional decoding algorithms for the codes over $\mathbb{F}_{q^\ell}$. Fractional decoding seeks to perform error correction using a smal

Shaoxiang Qin, Fuyuan Lyu, Wenhui Peng, Dingyang Geng

In solving partial differential equations (PDEs), Fourier Neural Operators (FNOs) have exhibited notable effectiveness. However, FNO is observed to be ineffective with large Fourier kernels that parameterize more frequencies. Current solutions rely on setting small kernels, restricting FNO's ability to capture complex PDE data in real-world applications. Thi

Jaidev Shriram, Alex Trevithick, Lingjie Liu, Ravi Ramamoorthi

We introduce RealmDreamer, a technique for generating forward-facing 3D scenes from text descriptions. Our method optimizes a 3D Gaussian Splatting representation to match complex text prompts using pretrained diffusion models. Our key insight is to leverage 2D inpainting diffusion models conditioned on an initial scene estimate to provide low variance super

Abhishek Moitra, Abhiroop Bhattacharjee, Priyadarshini Panda

The attention module in vision transformers(ViTs) performs intricate spatial correlations, contributing significantly to accuracy and delay. It is thereby important to modulate the number of attentions according to the input feature complexity for optimal delay-accuracy tradeoffs. To this end, we propose PIVOT - a co-optimization framework which selectively

Mikhail Galkin, Jincheng Zhou, Bruno Ribeiro, Jian Tang

Complex logical query answering (CLQA) in knowledge graphs (KGs) goes beyond simple KG completion and aims at answering compositional queries comprised of multiple projections and logical operations. Existing CLQA methods that learn parameters bound to certain entity or relation vocabularies can only be applied to the graph they are trained on which requires

Francisco Pipa

I present and defend a new ontology for quantum theories (or ``interpretations'' of quantum theory) called Generative Quantum Theory (GQT). GQT postulates different sets of features, and the combination of these different features can help generate different quantum theories. Furthermore, this ontology makes quantum indeterminacy and determinacy play an impo

Guillermo Ballesteros, Jesús Gambín Egea

We apply the in-in formalism to address the question of whether the size of the one-loop spectrum of curvature fluctuations in ultra-slow-roll inflation models designed for producing a large population of primordial black holes implies a breakdown of perturbation theory. We consider a simplified piece-wise description of inflation, in which the ultra-slow-ro

Marco Rupp, Karen Schwarzkopf, Markus Doering, Shuichiro Hayashi

Spatially selective melting of metal materials by laser irradiation allows for the precise welding as well as the 3D printing of complex metal parts. However, the simple scanning of a conventional Gaussian beam typically results in a melt track with randomly distributed surface features due to the complex and dynamic behavior of the melt pool. In this study,

Florian Sestak, Lisa Schneckenreiter, Johannes Brandstetter, Sepp Hochreiter

Being able to identify regions within or around proteins, to which ligands can potentially bind, is an essential step to develop new drugs. Binding site identification methods can now profit from the availability of large amounts of 3D structures in protein structure databases or from AlphaFold predictions. Current binding site identification methods heavily

Oleksandr Pryshliak, Karolina Haieva

To investigate the topological structure of planar polygon decomposition on trapezoids, which is formed by height functions. We use the oriented Reeb graph of the function with a marked vertex. We describe all possible optimal Reeb graphs in the case of polygon in general position with one local minimum and one local maximum. By optimal Reeb graph we mean Re

Yiji Feng, Hao Ma, Robert B. Mann, Yesheng Xue

Within the framework of braneworld holography, we construct a quantum charged black hole localized on a three-dimensional anti-de Sitter (AdS) brane that intersects the asymptotic boundary of the four-dimensional AdS spacetime at the conformal defects and incorporates quantum backreaction effects from the conformal field theory (CFT) on the brane. This quant

Jiale Xu, Weihao Cheng, Yiming Gao, Xintao Wang

We present InstantMesh, a feed-forward framework for instant 3D mesh generation from a single image, featuring state-of-the-art generation quality and significant training scalability. By synergizing the strengths of an off-the-shelf multiview diffusion model and a sparse-view reconstruction model based on the LRM architecture, InstantMesh is able to create

Debsoumya Chakraborti, Oliver Janzer, Abhishek Methuku, Richard Montgomery

In 1975, Erd\H{o}s asked for the maximum number of edges that an $n$-vertex graph can have if it does not contain two edge-disjoint cycles on the same vertex set. It is known that Tur\'an-type results can be used to prove an upper bound of $n^{3/2+o(1)}$. However, this approach cannot give an upper bound better than $\Omega(n^{3/2})$. We show that, for any $

Shahin Rahimi, Ashkan Nikseresht

Let $R$ be a finite ring with identity. The unit graph (unitary Cayley graph) of $R$ is the graph with vertex set $R$, where two distinct vertices $x$ and $y$ are adjacent exactly whenever $x+y$ is a unit in $R$ ($x-y$ is a unit in $R$). Here, we study independent sets of unit graphs of matrix rings over finite fields and use them to characterize all finite

Bingyi Zhang, Rajgopal Kannan, Carl Busart, Viktor Prasanna

Graph neural networks (GNNs) have recently empowered various novel computer vision (CV) tasks. In GNN-based CV tasks, a combination of CNN layers and GNN layers or only GNN layers are employed. This paper introduces GCV-Turbo, a domain-specific accelerator on FPGA for end-to-end acceleration of GNN-based CV tasks. GCV-Turbo consists of two key components: (1

Chih-Ting Lu, Arvind Kumar Mishra, Lei Wu

Dark matter (DM) may be captured around a neutron star (NS) through DM-nucleon interactions. We observe that the enhancement of such capturing is particularly significant when the DM velocity and/or momentum transfer depend on the DM-nucleon scattering cross-section. This could potentially lead to the formation of a black hole within the typical lifetime of

Martin Pijnenburg, Giulia Cusin, Cyril Pitrou, Jean-Philippe Uzan

We study lensing of gravitational waves by a black hole in the deep wave optics regime, i.e. when the wavelength is much larger than the black hole Schwarzschild radius. We apply it to triple systems, with a binary of stellar mass objects in the inspiraling phase orbiting around a central massive black hole. We describe the full polarisation structure of the

Zohre Karimi, Shing-Hei Ho, Bao Thach, Alan Kuntz

Automating robotic surgery via learning from demonstration (LfD) techniques is extremely challenging. This is because surgical tasks often involve sequential decision-making processes with complex interactions of physical objects and have low tolerance for mistakes. Prior works assume that all demonstrations are fully observable and optimal, which might not

Zoe Cooperband, Allan McRobie, Cameron Millar, Bernd Schulze

Using homological techniques we show that a pin-anchored frame that involves only moments and shears provides a conceptual bridge between the statics of moment frames and the kinematics of pin-jointed trusses. One immediate result is a long exact sequence whose alternating sum of dimensions gives a novel counting rule for self-stresses and mechanisms. This c

Björn H. Wehlin

We present a computational framework for piecewise constant functions (PCFs) and use this for several types of computations that are useful in statistics, e.g., averages, similarity matrices, and so on. We give a linear-time, allocation-free algorithm for working with pairs of PCFs at machine precision. From this, we derive algorithms for computing reduction

Denitsa Staicova

In this proceeding we review and expand on our recent work investigating the constancy of the absolute magnitude $M_B$ of Type Ia supernovae. In it, we used baryonic acoustic oscillations (BAO) to calibrate the supernova data and to check whether the resulting $M_B$ is constant. We used non-parametric methods like Gaussian processes and artificial neural net

Sheng Gong, Yumin Zhang, Zhenliang Mu, Zhichen Pu

Despite the widespread applications of machine learning force fields (MLFF) in solids and small molecules, there is a notable gap in applying MLFF to simulate liquid electrolyte, a critical component of the current commercial lithium-ion battery. In this work, we introduce BAMBOO (\textbf{B}yteDance \textbf{A}I \textbf{M}olecular Simulation \textbf{Boo}ster)

Luka Milićević

A skew corner is a triple of points in $\mathbb{Z} \times \mathbb{Z}$ of the form $(x,y), (x, y + a)$ and $(x + a, y')$. Pratt posed the following question: how large can a set $A \subseteq [n] \times [n]$ be, provided it contains no non-trivial skew corner (i.e. one for which $a\not=0$)? We prove that $|A| \leq \exp(- c\log^c n) n^2$, for an absolute consta

Giambattista Albora, Matteo Straccamore, Andrea Zaccaria

Defining and finalizing Mergers and Acquisitions (M&A) requires complex human skills, which makes it very hard to automatically find the best partner or predict which firms will make a deal. In this work, we propose the MASS algorithm, a specifically designed measure of similarity between companies and we apply it to patenting activity data to forecast M&A d

Xin Liu, Xingchen Liu, Paul Witherell

Laser Powder Bed Fusion (LPBF) additive manufacturing has revolutionized industries with its capability to create intricate and customized components. The LPBF process uses moving heat sources to melt and solidify metal powders. The fast melting and cooling leads to residual stress, which critically affects the part quality. Currently, the computational inte

Jiawei Ren, Mengmeng Xu, Jui-Chieh Wu, Ziwei Liu

Diffusion models generate images with an unprecedented level of quality, but how can we freely rearrange image layouts? Recent works generate controllable scenes via learning spatially disentangled latent codes, but these methods do not apply to diffusion models due to their fixed forward process. In this work, we propose SceneDiffusion to optimize a layered

Sachin Goyal, Pratyush Maini, Zachary C. Lipton, Aditi Raghunathan

Vision-language models (VLMs) are trained for thousands of GPU hours on carefully curated web datasets. In recent times, data curation has gained prominence with several works developing strategies to retain 'high-quality' subsets of 'raw' scraped data. For instance, the LAION public dataset retained only 10% of the total crawled data. However, these strateg

Zhengyang Lu, Ying Chen

Monocular depth estimation from a single image is an ill-posed problem for computer vision due to insufficient reliable cues as the prior knowledge. Besides the inter-frame supervision, namely stereo and adjacent frames, extensive prior information is available in the same frame. Reflections from specular surfaces, informative intra-frame priors, enable us t

Donghao Chen, Binkun Liu

Temperature fluctuations significantly affect microorganism growth and pest activities in grain pile, precise monitoring and forecasting temperature of stored grain are essential for maintaining the quality and safety of grain storage. This paper proposes a multi-model fusion approach to predict grain temperature using historical temperature data of stored g

Edoardo Colombo, Seyed Morteza Hosseini, Dario Martelli, Antonio Pittelli

We provide a first principles derivation of the microscopic entropy of a very general class of supersymmetric, rotating and accelerating black holes in AdS$_4$. This is achieved by analysing the large-$N$ limit of the spindle index and completes the construction of the first example of a holographic duality involving supersymmetric field theories defined on

Neel Mishra, Bamdev Mishra, Pratik Jawanpuria, Pawan Kumar

A novel first-order method is proposed for training generative adversarial networks (GANs). It modifies the Gauss-Newton method to approximate the min-max Hessian and uses the Sherman-Morrison inversion formula to calculate the inverse. The method corresponds to a fixed-point method that ensures necessary contraction. To evaluate its effectiveness, numerical

Andreas Sturm, Bharadwaj Mummaneni, Leon Rullkötter

The major advances in quantum computing over the last few decades have sparked great interest in applying it to solve the most challenging computational problems in a wide variety of areas. One of the most pronounced domains here are optimization problems and a number of algorithmic approaches have been proposed for their solution. For the current noisy inte