April 2024 arXiv papers — page 186

J. B. Bell, A. Nonaka, A. L. Garcia

We simulate phase separated fluids using the Cahn-Hillard fluctuating hydrodynamic (CH-FHD) model and measure the statistical properties of capillary waves generated by thermal fluctuations. Our measurements are in good agreement with stochastic lubrication theory and molecular dynamics simulations but differ significantly from recent CH-FHD results by Zhang

Phillip Schneider, Tim Schopf, Juraj Vladika, Florian Matthes

Knowledge management is a critical challenge for enterprises in today's digital world, as the volume and complexity of data being generated and collected continue to grow incessantly. Knowledge graphs (KG) emerged as a promising solution to this problem by providing a flexible, scalable, and semantically rich way to organize and make sense of data. This pape

Eric O. D. Andriantiana, Valisoa R. M. Rakotonarivo

We study the Sombor index of trees with various degree restrictions. In addition to rediscovering that among all trees with a given degree sequence, the greedy tree minimises the Sombor index and the alternating greedy tree maximises it, we also provide a full characterisation of all trees that have those maximum or minimum values. Moreover, we compare trees

Sima Ghafoori, Ali Rabiee, Maryam Norouzi, Musa Jouaneh

Rehabilitation robotics continues to confront substantial challenges, particularly in achieving smooth, safe, and intuitive human-robot interactions for upper limb motor training. Many current systems depend on complex mechanical designs, direct physical contact, and multiple sensors, which not only elevate costs but also reduce accessibility. Additionally,

Yijia Weng, Bowen Wen, Jonathan Tremblay, Valts Blukis

We address the problem of building digital twins of unknown articulated objects from two RGBD scans of the object at different articulation states. We decompose the problem into two stages, each addressing distinct aspects. Our method first reconstructs object-level shape at each state, then recovers the underlying articulation model including part segmentat

Milagros Fernández-Gavilanes, Jonathan Juncal-Martínez, Silvia García-Méndez, Enrique Costa-Montenegro

Online media, such as blogs and social networking sites, generate massive volumes of unstructured data of great interest to analyze the opinions and sentiments of individuals and organizations. Novel approaches beyond Natural Language Processing are necessary to quantify these opinions with polarity metrics. So far, the sentiment expressed by emojis has rece

Shahzeb Naeem, Muhammad Riyyan Khan, Usman Tariq, Abhinav Dhall

This research explores the positive application of deepfake technology for upper body generation, specifically sign language for the Deaf and Hard of Hearing (DHoH) community. Given the complexity of sign language and the scarcity of experts, the generated videos are vetted by a sign language expert for accuracy. We construct a reliable deepfake dataset, eva

Florian Kraus, Nicolas Scheiner, Werner Ritter, Klaus Dietmayer

Radar sensors have a long tradition in advanced driver assistance systems (ADAS) and also play a major role in current concepts for autonomous vehicles. Their importance is reasoned by their high robustness against meteorological effects, such as rain, snow, or fog, and the radar's ability to measure relative radial velocity differences via the Doppler effec

Qi Zhang, Yi Zhou, Shaofeng Zou

This paper provides the first tight convergence analyses for RMSProp and Adam in non-convex optimization under the most relaxed assumptions of coordinate-wise generalized smoothness and affine noise variance. We first analyze RMSProp, which is a special case of Adam with adaptive learning rates but without first-order momentum. Specifically, to solve the cha

Lena Komarova, M. S. Oey, Svea Hernandez, Angela Adamo

As the nearest confirmed Lyman continuum (LyC) emitter, Haro 11 is an exceptional laboratory for studying LyC escape processes crucial to cosmic reionization. Our new HST/COS G130M/1055 observations of its three star-forming knots now reveal that the observed LyC originates in Knots B and C, with $903 - 912~\r{A}$ luminosities of $1.9\pm1.5 \times 10^{40}~\r

Simon A. Willis, Wyatt A. Curtis, David J. Flannigan

We tested and compared the stability and usability of three different cathode materials and configurations in a thermionic-based ultrafast electron microscope: (1) on-axis thermionic and photoemission from a 0.1-mm diameter LaB6 source with graphite guard ring, (2) off-axis photoemission from the Ni aperture surface of the Wehnelt electrode, and (3) on-axis

Oleg Asipchuk, Christopher Leonard, Shijun Zheng

We show the existence and stability of ground state solutions (g.s.s.) for $L^2$-critical magnetic nonlinear Schr\"odinger equations (mNLS) for a class of unbounded electromagnetic potentials. We then give non-existence result by constructing a sequence of vortex type functions in the setting of RNLS with an anisotropic harmonic potential. These generalize t

David Sharp, Christopher Flower, Mahmoud Jalali Mehrabad, Arnab Manna

Demonstrations of topological photonics have so far largely been confined to infrared wavelengths where imaging technology and access to low-dimensional quantum materials are both limited. Here, we designed and fabricated silicon nitride ring-resonator arrays to demonstrate photonic topological edge states at ~780 nm. We observed edge states corresponding to

Guanyang Wang, Jose Blanchet, Peter W. Glynn

Due to the potential benefits of parallelization, designing unbiased Monte Carlo estimators, primarily in the setting of randomized multilevel Monte Carlo, has recently become very popular in operations research and computational statistics. However, existing work primarily substantiates the benefits of unbiased estimators at an intuitive level or using empi

Zheng Zhang, Fan Yang, Ziyan Jiang, Zheng Chen

Recent advances in large language models (LLMs) have enhanced their ability to process long input contexts. This development is particularly crucial for tasks that involve retrieving knowledge from an external datastore, which can result in long inputs. However, recent studies show a positional bias in LLMs, demonstrating varying performance depending on the

Julia S. Meyer, Manuel Houzet

When time-reversal and inversion symmetry are broken, superconducting circuits may exhibit a so-called diode effect, where the critical currents for opposite directions of the current flow differ. In recent years, this effect has been observed in a multitude of systems and the different physical ingredients that may yield such an effect are well understood.

Kaustubh Rajesh Gupta, Arka Banerjee

We present a framework to quantify the clustering of gravitational wave (GW) transient sources and measure their spatial cross-correlation with the large-scale structure (LSS) of the universe using the $k$-nearest neighbour ($k$NN) formalism. As a first application, we measure the nearest-neighbour distributions of 53 suitably selected Binary Black Hole (BBH

Takashi Yamamoto, Daisuke Iono, Toshiki Saito, Nario Kuno

We present a quantitative and statistical analysis of the molecular gas morphology in 73 nearby galaxies using high spatial resolution CO ($J$ = 2-1) data obtained from the Atacama Large Millimeter/submillimeter Array (ALMA) by the PHANGS large program. We applied three model-independent parameters: Concentration ($C$), Asymmetry ($A$), and Clumpiness ($S$)

Yinzi Xin, Daniel Echeverri, Nemanja Jovanovic, Dimitri Mawet

Photonic lantern nulling (PLN) is a method for enabling the detection and characterization of close-in exoplanets by exploiting the symmetries of the ports of a mode-selective photonic lantern (MSPL) to cancel out starlight. A six-port MSPL provides four ports where on-axis starlight is suppressed, while off-axis planet light is coupled with efficiencies tha

Harry Li, Gabriel Appleby, Ashley Suh

We present a mixed-methods study to explore how large language models (LLMs) can assist users in the visual exploration and analysis of knowledge graphs (KGs). We surveyed and interviewed 20 professionals from industry, government laboratories, and academia who regularly work with KGs and LLMs, either collaboratively or concurrently. Our findings show that p

Yixuan Zhu, Ao Li, Yansong Tang, Wenliang Zhao

The recovery of occluded human meshes presents challenges for current methods due to the difficulty in extracting effective image features under severe occlusion. In this paper, we introduce DPMesh, an innovative framework for occluded human mesh recovery that capitalizes on the profound diffusion prior about object structure and spatial relationships embedd

Samantha Gilbert-Janizek, Victoria S. Meadows, Jacob Lustig-Yaeger

Future astrophysics missions will seek extraterrestrial life via transmission and direct imaging observations. To assess habitability and biosignatures, we need robust retrieval tools to analyze observed spectra, and infer surface and atmospheric properties with their uncertainties. We use a novel retrieval tool to assess accuracy in characterizing near-surf

Tim Möbus

The Trotter product formula and the quantum Zeno effect are both indispensable tools for constructing time-evolutions using experimentally feasible building blocks. In this work, we discuss assumptions under which quantitative bounds can be proven in the strong operator topology on Banach spaces and provide natural bosonic examples. Specially, we assume the

Ashutosh Dwibedi, Nandita Padhan, Arghya Chatterjee, Sabyasachi Ghosh

The present review article has attempted a compact formalism description of transport coefficient calculations for relativistic fluid, which is expected in heavy ion collision experiments. Here, we first address the macroscopic description of relativistic fluid dynamics and then its microscopic description based on the kinetic theory framework. We also addre

Christopher Sneden, George W. Preston

We have investigated the absorption shapes of atomic lines and H{\alpha} in RR Lyrae stars. We used the database of high resolution spectra gathered with the Las Campanas Observatory du Pont Telescope, analyzing a set of about 2700 short exposure spectra of 17 RRab and 5 RRc variables. To increase the signal-to-noise of the spectra for each star, we first co

Stephen Dilworth, Denka Kutzarova, Pavlos Motakis

A reflexive Banach space with an unconditional basis admits an equivalent $1$-unconditional $2R$ norm and embeds into a reflexive space with a $1$-symmetric $2R$ norm. Partial results on $1$-symmetric $2R$ renormings of spaces with a symmetric basis are obtained.

Lei You, Yu-Hang Feng, Rui-Bo Wang, Jian-Bo Deng

The combination of Loop Quantum Gravity theory with the classical gravitational collapse model has effectively addressed the singularity problem of black holes and predicted the emergence of white holes in the late stages of collapse. The quantum extension of Kruskal spacetime suggests that the appearance of white holes may carry information from companion b

Susmita Chowdhury, Niraj Kumar Singh, Sanath Kumar Honnali, Grzegorz Greczynski

The electronic structure of Sc1-xVxNy epitaxial films with different alloying concentrations of V are investigated with respect to effects on thermoelectric properties. Band structure calculations on Sc0.75V0.25N indicate that V 3d states lie in the band gap of the parent ScN compound in the vicinity of the Fermi level. Thus, theoretically the presence of li

Banani Biswas, Pavel Naumov, Federico Motti, Patrick Hautle

In orthoferrites the rare-earth (R) ion has a big impact on structural and magnetic properties in particular the ionic size influences the octahedral tilt and the R3+- Fe3+ interaction modifies properties like the spin reorientation. Growth induced strain in thin films is another means to modify materials properties since the sign of strain affects the bond

Junyi Wu, Weitai Kang, Hao Tang, Yuan Hong

To interpret Vision Transformers, post-hoc explanations assign salience scores to input pixels, providing human-understandable heatmaps. However, whether these interpretations reflect true rationales behind the model's output is still underexplored. To address this gap, we study the faithfulness criterion of explanations: the assigned salience scores should

Bartu Bingol

We study obstructed deformation problems for two-dimensional residual Galois representations arising from weight~$2$ newforms of level~$N$. Using Poitou-Tate duality, we isolate local and global sources of obstructions and give concrete criteria for when they occur. In several cases we also describe the resulting universal deformation ring explicitly.

Matthias Gerstgrasser, Rylan Schaeffer, Apratim Dey, Rafael Rafailov

The proliferation of generative models, combined with pretraining on web-scale data, raises a timely question: what happens when these models are trained on their own generated outputs? Recent investigations into model-data feedback loops proposed that such loops would lead to a phenomenon termed model collapse, under which performance progressively degrades

Filip B. Maciejewski, Jacob Biamonte, Stuart Hadfield, Davide Venturelli

We present Noise-Directed Adaptive Remapping (NDAR), a heuristic algorithm for approximately solving binary optimization problems by leveraging certain types of noise. We consider access to a noisy quantum processor with dynamics that features a global attractor state. In a standard setting, such noise can be detrimental to the quantum optimization performan

Jin Heo

A geometric figure is a reptile if it can be dissected into at least two similar copies congruent to each other. We prove that if a trapezoid is a reptile and not a parallelogram, then the length of each base is a linear combination of the lengths of its legs with rational coefficients. We then rule out isosceles trapezoids and right trapezoids which are not

Davide Neri

After Galileo's publication of the Sidereus Nuncius in 1610, Giovanni Battista Agucchi obtained in 1611 an estimate of the orbital periods of the Galilean satellites of Jupiter using the figures published in the book. The article shows how to repeat these measurements in a teaching context for high school students.

Xiongwei Wu, Sicheng Yu, Ee-Peng Lim, Chong-Wah Ngo

In the realm of food computing, segmenting ingredients from images poses substantial challenges due to the large intra-class variance among the same ingredients, the emergence of new ingredients, and the high annotation costs associated with large food segmentation datasets. Existing approaches primarily utilize a closed-vocabulary and static text embeddings

Alia Hamdan, Ash Bista, Dina Newman, Scott Franklin

This study investigates how faculty acquire contextual information about students, examining mechanisms and motivations used when sharing their identity to facilitate empathy. Empathy is "the ability and tendency to share and understand others' internal state" (Zaki and Ochsner, 2012), and is a critical factor in both motivating faculty to enact large scale

Feng Wang, Kurt Webber, David Radford, Luca di Mare

This paper develops a numerical procedure to accelerate the convergence of the Favre-averaged Non-Linear Harmonic (FNLH) method. The scheme provides a unified mathematical framework for solving the sparse linear systems formed by the mean flow and the time-linearized harmonic flows of FNLH in an explicit or implicit fashion. The approach explores the similar

Gabriel Goren-Roig, Joshua Meyers, Emilio Minichiello

Motivated by problems in categorical database theory, we introduce and compare two notions of presentation for profunctors, uncurried and curried, which arise intuitively from thinking of profunctors either as functors C^op x D -> Set or C^op -> Set^D. Although the Cartesian closure of Cat means these two perspectives can be used interchangeably at the seman

Daniela Bubboloni, Michele Gori, Claudia Meo

We focus on the one-to-one two-sided matching model with two disjoint sets of agents of equal size, where each agent in a set has preferences on the agents in the other set modeled by a linear order. A matching mechanism associates a set of matchings to each preference profile; resoluteness, that is the capability to select a unique matching, and stability a

David Josef Herzog, Nitsa Judith Herzog

Industrial Revolution 4.0 transforms healthcare systems. The first three technological revolutions changed the relationship between human and machine interaction due to the exponential growth of machine numbers. The fourth revolution put humans into a situation where heterogeneous data is produced with unmatched quantity and quality not only by traditional m

Zixi Wang, Zeyi Liu, Nicolas Ouporov, Shuran Song

Robot-to-human object handover is an important step in many human robot collaboration tasks. A successful handover requires the robot to maintain a stable grasp on the object while making sure the human receives the object in a natural and easy-to-use manner. We propose ContactHandover, a robot to human handover system that consists of two phases: a contact-

Raz Rivlis, Andrei Zadorozhnyi, Yuri Dahnovsky

We study magnetotransport in conical helimagnet crystals. Spin dependent magnetoresistance exhibits dramatic properties for high and low electron concentrations at different temperatures. For spin up electrons we find negative magnetoresistance despite only considering a single carrier type. For spin down electrons we observe giant magnetoresistance due to d

Juyeop Han, Lukas Lao Beyer, Guilherme V. Cavalheiro, Sertac Karaman

In recent years, Neural Radiance Fields (NeRF) have emerged as a powerful tool for 3D reconstruction and novel view synthesis. However, the computational cost of NeRF rendering and degradation in quality due to the presence of artifacts pose significant challenges for its application in real-time and robust robotic tasks, especially on embedded systems. This

Shaina Raza, Oluwanifemi Bamgbose, Shardul Ghuge, Fatemeh Tavakol

Large Language Models (LLMs) have advanced various Natural Language Processing (NLP) tasks, such as text generation and translation, among others. However, these models often generate texts that can perpetuate biases. Existing approaches to mitigate these biases usually compromise knowledge retention. This study explores whether LLMs can produce safe, unbias

Chen Liang, Matvei Libine

We extend constructions of classical Clifford analysis to the case of indefinite non-degenerate quadratic forms. Clifford analogues of complex holomorphic functions - called monogenic functions - are defined by means of the Dirac operators that factor a certain wave operator. One of the fundamental features of quaternionic analysis is the invariance of quate

Umberto Michieli, Jijoong Moon, Daehyun Kim, Mete Ozay

Nowadays, users demand for increased personalization of vision systems to localize and identify personal instances of objects (e.g., my dog rather than dog) from a few-shot dataset only. Despite outstanding results of deep networks on classical label-abundant benchmarks (e.g., those of the latest YOLOv8 model for standard object detection), they struggle to

Sean Greenaway, William Pol, Sukin Sim

In recent years, quantum algorithms have been proposed which use quantum phase estimation (QPE) coherently as a subroutine without measurement. In order to do this effectively, the routine must be able to distinguish eigenstates with success probability close to unity. In this paper, we provide the first systematic comparison between two approaches towards m

Raimon Luna, Miquel Llorens-Monteagudo, Ana Lorenzo-Medina, Juan Calderón Bustillo

We present several high-accuracy surrogate models for gravitational-wave signals from equal-mass head-on mergers of Proca stars, computed through the Newman-Penrose scalar $\psi_4$. We also discuss the current state of the model extensions to mergers of Proca stars with different masses, and the particular challenges that these present. The models are divide

Anupam Bhardwaj, Marina Rejkuba, Chow-Choong Ngeow, Marcella Marconi

Draco dwarf Spheroidal galaxy (dSph) is one of the nearest and the most dark matter dominated satellites of the Milky Way. We obtained multi-epoch near-infrared (NIR, $JHK_s$) observations of the central region of Draco dSph covering a sky area of $\sim 21'\times21'$ using the WIRCam instrument at the 3.6-m Canada-France-Hawaii Telescope. Homogeneous $JHK_s$

Mir Afrasiar, Jaydeep Kumar Basak, Dimitrios Giataganas

We propose a holographic formalism for a timelike entanglement entropy in non-conformal theories. This pseudoentropy is a complex-valued measure of information, which, in holographic non-conformal theories, receives contributions from a set of spacelike surfaces and a finite timelike bulk surface with mirror symmetry. We suggest a method of merging the surfa

Vishal Singh, Mark M. Wilde

The heralded exact one-way distillable secret key is equal to the largest expected rate at which perfect secret key bits can be probabilistically distilled from a bipartite state by means of local operations and one-way classical communication. Here we define the set of super two-extendible states and prove that an arbitrary state in this set cannot be used

Tyler Trent, Karin Roley, Matthew Golden, Dimitrios Psaltis

Low density plasmas in curved spacetimes, such as those found in accretion flows around black holes, are challenging to model from first principles, owing to the large scale separation between the characteristic scales of the microscopic processes and large mean-free-paths comparable to the system sizes. Kinetic approaches become necessary to capture the rel

Gabriel Ponte, Marcia Fampa, Jon Lee

The generalized maximum-entropy sampling problem (GMESP) is to select an order-$s$ principal submatrix from an order-$n$ covariance matrix, to maximize the product of its $t$ greatest eigenvalues, $0<t\leq s <n$. Introduced more than 25 years ago, GMESP is a natural generalization of two fundamental problems in statistical design theory: (i) maximum-entropy

Fangze Liu, Xu-Xin Huang, Edwin W. Huang, Brian Moritz

Motivated by the pair-density-wave (PDW) state found in the one-dimensional Kondo-Heisenberg chain, we report on a determinant quantum Monte Carlo DQMC study of pair-fields for a two-dimensional half-filled Hubbard layer coupled to an itinerant, non-interacting layer with one electron per site. In a specific range of interlayer hopping, the pairing vertex as

Ritesh Ghosh, Igor A. Shovkovy

We employ first-principles quantum field theoretical methods to investigate the longitudinal and transverse electrical conductivities of a strongly magnetized hot quantum electrodynamics (QED) plasma at the leading order in coupling. The analysis employs the fermion damping rate in the Landau-level representation, calculated with full kinematics and exact am

Ezequiel Alvarez, Yuling Yao

Multijet events with heavy-flavors are of central importance at the LHC since many relevant processes -- such as $t\bar t$, $hh$, $t\bar t h$ and others -- have a preferred branching ratio for this final state. Current techniques for tackling these processes use hard-assignment selections through $b$-tagging working points, and suffer from systematic uncerta

Minwoo Suh

Following the work of [1], we consider six- and seven-dimensional gauged supergravity coupled to a vector multiplet on an ansatz of $AdS_{4,5}\times{M}_2$, respectively, where $M_2$ is a two-dimensional surface with a Killing vector. We construct equivariantly closed forms from spinor bilinears of Killing spinors. From the integration of equivariantly closed

Aritra Banerjee, Ritankar Chatterjee, Priyadarshini Pandit

We investigate tensionless (or null) bosonic string theory with a Kalb-Ramond background turned on. In analogy with the tensile case, we find that the Kalb-Ramond field has a non-trivial effect on the spectrum only when the theory is compactified on an (\left(S^1\right)^{\otimes d}) background with (d\geq 2). We discuss the effect of this background field on

Mor Rozner, Hagai B. Perets

Binaries in dense environments are traditionally classified as soft or hard based on their binding energy relative to the kinetic energy of surrounding stars. Heggie's law suggests that stellar encounters tend to soften soft binaries and harden hard binaries, altering their separations. However, interactions with gas in such environments can significantly mo

Antonio Ragagnin, Massimo Meneghetti, Francesco Calura, Giulia Despali

This work aims at assessing the impact of DM self-interactions on the properties of galaxy clusters. In particular, the goal is to study the angular dependence of the cross section by testing rare (large angle scattering) and frequent (small angle scattering) SIDM models with velocity-dependent cross sections. We re-simulate six galaxy cluster zoom-in initia

Ava Polzin, Laura Newburgh, Priyamvada Natarajan, Hsiao-Wen Chen

The Canadian Hydrogen Intensity Mapping Experiment (CHIME) is a drift-scan interferometer designed to map the entire northern sky every 24 hours. The all-sky coverage and sensitivity to neutral hydrogen flux at intermediate redshifts makes the instrument a resource for other exciting science in addition to cosmology for which it was originally designed. Char

Alberto Cobos Rabano, Cristina Manolache, Qaasim Shafi

We study the relationship between the enumerative geometry of rational curves in local geometries and various versions of maximal contact logarithmic curve counts. Our approach is via quasimap theory, and we show versions of the arXiv:1712.05210 local/logarithmic correspondence for quasimaps, and in particular for normal crossings settings, where the Gromov-

Indranil Halder, Cumrun Vafa, Kai Xu

Microscopic black hole entropy calculations in string theory usually proceeds through identifying them as wrapped strings in one higher dimension. For M-theory on elliptic Calabi-Yau threefolds this proceeds via its relation to F-theory in one higher dimension. Here we show how this method can be extended to M-theory on non-elliptic Calabi-Yau threefolds suc

Haining Pan, Sankar Das Sarma

The interplay of disorder and short finite wire length is the crucial physics hindering progress in the semiconductor-superconductor nanowire platform for realizing non-Abelian Majorana zero modes (MZM). Disorder effectively segments the nanowire into isolated patches of quantum dots (QD) which act as subgap Andreev bound states often mimicking MZMs. In this

Peter W. Graham, Harikrishnan Ramani

There is a large and growing interest in observations of small-scale structure in dark matter. We propose a new way to probe dark matter structures in the $\sim 10 - 10^8 \, M_\odot$ range. This allows us to constrain the primordial power spectrum over shorter distances scales than possible with direct observations from the CMB. For $k$ in the range $\sim 10

Zheng Zhou, Junjie Mao, Taotao Fang, Yijun Wang

We conduct an in-depth spectral analysis of $\sim1{\rm ~Ms}$ XMM-Newton data of the narrow line Seyfert 1 galaxy RE J1034+396. The long exposure ensures high spectral quality and provides us with a detailed look at the intrinsic absorption and emission features toward this target. Two warm-absorber (WA) components with different ionization states ($\log (\xi

Pablo A. Cano

We show that there is a fundamental flaw in the application of modified gravity theories in cosmology, taking $f(R)$ gravity as a paradigmatic example. This theory contains a scalar degree of freedom that couples to the matter stress-energy tensor but not to gravitational energy. However, when applied to cosmology this theory is unable to distinguish between

Sally Dawson, Matthew Forslund, Marvin Schnubel

Heavy neutral gauge bosons arise in many motivated models of Beyond the Standard Model Physics. Experimental searches require that such gauge bosons are above the TeV scale in most models which means that the tools of effective field theories, in particular the Standard Model Effective Field Theory (SMEFT), are useful. We match the SMEFT to models with heavy

Vitor Cardoso, Shilpa Kastha, Rodrigo Panosso Macedo

It has been shown, via specific examples and a pseudospectrum analysis, that the black hole quasinormal spectra are unstable. The implication of such a result for gravitational-wave physics and of our understanding of black holes is, still, unclear. The purpose of this work is twofold: (i) we show that some of the setups leading to instabilities are unphysic

Morten Amundsen, Vladimir Juričić, Jabir Ali Ouassou

The Josephson effect is a hallmark signature of the superconducting state, which, however, has been sparsely explored in non-crystalline superconducting materials. Motivated by this, we consider a Josephson junction consisting of two superconductors with a fractal metallic interlayer, which is patterned as a Sierpi\'nski carpet by removing atomic sites in a

Yonglong Xie, Andrew T. Pierce, Jeong Min Park, Daniel E. Parker

In multilayer moir\'e heterostructures, the interference of multiple twist angles ubiquitously leads to tunable ultra-long-wavelength patterns known as supermoir\'e lattices. However, their impact on the system's many-body electronic phase diagram remains largely unexplored. We present local compressibility measurements revealing numerous incompressible stat

Ralph Blumenhagen, Niccolò Cribiori, Aleksandar Gligovic, Antonia Paraskevopoulou

It has been recently suggested that the strong Emergence Proposal is realized in M-theory limits by integrating out all light towers of states with a typical mass scale not larger than the species scale, i.e. the eleventh dimensional Planck mass. Within the BPS sector, these are transverse $M2$- and $M5$-branes, that can be wrapped and particle-like, carryin

Rahul Ramesh, Dylan Nelson, Drummond Fielding, Marcus Brüggen

We use a cosmological zoom-in simulation of a Milky Way-like galaxy to study and quantify the topology of magnetic field lines around cold gas clouds in the circumgalactic medium (CGM). This simulation is a new addition to Project GIBLE, a suite of cosmological magnetohydrodynamical simulations of galaxy formation with preferential super-Lagrangian refinemen

Sahand Seifnashri, Shu-Heng Shao

We show that the standard 1+1d $\mathbb{Z}_2\times \mathbb{Z}_2$ cluster model has a non-invertible global symmetry, described by the fusion category Rep(D$_8$). Therefore, the cluster state is not only a $\mathbb{Z}_2\times \mathbb{Z}_2$ symmetry protected topological (SPT) phase, but also a non-invertible SPT phase. We further find two new commuting Pauli

Lucas M. Valenzuela, Rhea-Silvia Remus, Klaus Dolag, Benjamin A. Seidel

Despite being a fundamental property of galaxies that dictates the form of the potential, the 3D shape is intrinsically difficult to determine from observations. The improving quality of triaxial modeling methods in recent years has made it possible to measure these shapes more accurately. This study provides a comprehensive understanding of the stellar and

Muhammad Zubair Irshad, Sergey Zakharov, Vitor Guizilini, Adrien Gaidon

Neural fields excel in computer vision and robotics due to their ability to understand the 3D visual world such as inferring semantics, geometry, and dynamics. Given the capabilities of neural fields in densely representing a 3D scene from 2D images, we ask the question: Can we scale their self-supervised pretraining, specifically using masked autoencoders,

Ruiming Cao, Dekel Galor, Amit Kohli, Jacob L Yates

Event cameras, also known as dynamic vision sensors, are an emerging modality for measuring fast dynamics asynchronously. Event cameras capture changes of log-intensity over time as a stream of 'events' and generally cannot measure intensity itself; hence, they are only used for imaging dynamic scenes. However, fluctuations due to random photon arrival inevi

Kangfu Mei, Zhengzhong Tu, Mauricio Delbracio, Hossein Talebi

We study the scaling properties of latent diffusion models (LDMs) with an emphasis on their sampling efficiency. While improved network architecture and inference algorithms have shown to effectively boost sampling efficiency of diffusion models, the role of model size -- a critical determinant of sampling efficiency -- has not been thoroughly examined. Thro

Xingyi Zhou, Anurag Arnab, Shyamal Buch, Shen Yan

An ideal model for dense video captioning -- predicting captions localized temporally in a video -- should be able to handle long input videos, predict rich, detailed textual descriptions, and be able to produce outputs before processing the entire video. Current state-of-the-art models, however, process a fixed number of downsampled frames, and make a singl

Armand Comas-Massagué, Di Qiu, Menglei Chai, Marcel Bühler

We introduce a novel framework for 3D human avatar generation and personalization, leveraging text prompts to enhance user engagement and customization. Central to our approach are key innovations aimed at overcoming the challenges in photo-realistic avatar synthesis. Firstly, we utilize a conditional Neural Radiance Fields (NeRF) model, trained on a large-s

Yi-Lin Tuan, Xilun Chen, Eric Michael Smith, Louis Martin

As large language models (LLMs) become easily accessible nowadays, the trade-off between safety and helpfulness can significantly impact user experience. A model that prioritizes safety will cause users to feel less engaged and assisted while prioritizing helpfulness will potentially cause harm. Possible harms include teaching people how to build a bomb, exp

Shikai Li, Jianglin Fu, Kaiyuan Liu, Wentao Wang

We present CosmicMan, a text-to-image foundation model specialized for generating high-fidelity human images. Unlike current general-purpose foundation models that are stuck in the dilemma of inferior quality and text-image misalignment for humans, CosmicMan enables generating photo-realistic human images with meticulous appearance, reasonable structure, and

Gowthami Somepalli, Anubhav Gupta, Kamal Gupta, Shramay Palta

Generative models are now widely used by graphic designers and artists. Prior works have shown that these models remember and often replicate content from their training data during generation. Hence as their proliferation increases, it has become important to perform a database search to determine whether the properties of the image are attributable to spec

Zhiqiu Lin, Deepak Pathak, Baiqi Li, Jiayao Li

Despite significant progress in generative AI, comprehensive evaluation remains challenging because of the lack of effective metrics and standardized benchmarks. For instance, the widely-used CLIPScore measures the alignment between a (generated) image and text prompt, but it fails to produce reliable scores for complex prompts involving compositions of obje

A. Carvunis, F. Mahmoudi, Y. Monceaux

This work addresses the calculation of local form factors involved in the theoretical predictions of semileptonic $B$-meson decays at low $q^2$. We present a new approach to the method of QCD light-cone sum rule with $B$-meson light-cone distribution amplitudes. In our strategy, we bypass the semiglobal quark-hadron duality (QHD) approximation which usually

A. Andrade, I. Saviane, L. Monaco, I. Yegorova

We study the role of galaxy clusters in the mass-metallicity relation by using a sample of galaxies belonging to the AC114 (z=0.317) galaxy cluster. The data was taken from archival VIMOS-MOS spectroscopy to estimate gas-phase metallicities by using strong-line methods. On the other hand, the data obtained from DECaLS DR10 and VIKING DR4 ESO surveys were use

Serhat Bakirtas, Elza Erkip

Database de-anonymization typically involves matching an anonymized database with correlated publicly available data. Existing research focuses either on practical aspects without requiring knowledge of the data distribution yet provides limited guarantees, or on theoretical aspects assuming known distributions. This paper aims to bridge these two approaches

Hongli Zhan, Allen Zheng, Yoon Kyung Lee, Jina Suh

Large language models (LLMs) have offered new opportunities for emotional support, and recent work has shown that they can produce empathic responses to people in distress. However, long-term mental well-being requires emotional self-regulation, where a one-time empathic response falls short. This work takes a first step by engaging with cognitive reappraisa

Moritz Cygorek, Erik M. Gauger

Process tensor matrix product operators (PT-MPOs) enable numerically exact simulations for an unprecedentedly broad range of open quantum systems. By representing environment influences in MPO form, they can be efficiently compressed using established algorithms. The dimensions of inner bonds of the compressed PT-MPO may be viewed as an indicator of the comp

Adrianne Zhong, Michael R. DeWeese

A fundamental result of thermodynamic geometry is that the optimal, minimal-work protocol that drives a nonequilibrium system between two thermodynamic states in the slow-driving limit is given by a geodesic of the friction tensor, a Riemannian metric defined on control space. For overdamped dynamics in arbitrary dimensions, we demonstrate that thermodynamic

Aritra Ghosh, Sushanta Dattagupta

The quantum Langevin equation as obtained from the independent-oscillator model describes a strong-coupling situation, devoid of the Born-Markov approximation that is employed in the context of the Gorini-Kossakowski-Sudarshan-Lindblad equation. The question we address is what happens when we implement such 'Born-Markov'-like approximations at the level of t

Harry Dong, Beidi Chen, Yuejie Chi

With the development of transformer-based large language models (LLMs), they have been applied to many fields due to their remarkable utility, but this comes at a considerable computational cost at deployment. Fortunately, some methods such as pruning or constructing a mixture of experts (MoE) aim at exploiting sparsity in transformer feedforward (FF) blocks

Mingyuan Zhang, Daisheng Jin, Chenyang Gu, Fangzhou Hong

Human motion generation, a cornerstone technique in animation and video production, has widespread applications in various tasks like text-to-motion and music-to-dance. Previous works focus on developing specialist models tailored for each task without scalability. In this work, we present Large Motion Model (LMM), a motion-centric, multi-modal framework tha

Maxwell Prybylo, Sara Haghighi, Sai Teja Peddinti, Sepideh Ghanavati

With the increase in the number of privacy regulations, small development teams are forced to make privacy decisions on their own. In this paper, we conduct a mixed-method survey study, including statistical and qualitative analysis, to evaluate the privacy perceptions, practices, and knowledge of members involved in various phases of the Software Developmen

Akshita Gupta, Gaurav Mittal, Ahmed Magooda, Ye Yu

Temporal Action Localization (TAL) involves localizing and classifying action snippets in an untrimmed video. The emergence of large video foundation models has led RGB-only video backbones to outperform previous methods needing both RGB and optical flow modalities. Leveraging these large models is often limited to training only the TAL head due to the prohi

Nathanael Arkor, Dylan McDermott

A fundamental result in the theory of monads is the characterisation of the category of algebras for a monad in terms of a pullback of the category of presheaves on the category of free algebras: intuitively, this expresses that every algebra is a colimit of free algebras. We establish an analogous result for enriched relative monads with dense roots, and ex

P. R. S. Carvalho

In this Letter we introduce some field-theoretic approach for computing the critical properties of $\gamma_{KLS}$-generalized systems undergoing continuous phase transitions, namely $\gamma_{KLS}$-statistical field theory. From this new approach emerges the new generalized O($N$)$_{\gamma_{KLS}}$ universality class, which is capable of encompassing nonconven

Matthew Ellison

Let $\mathcal{K}$ be a finite pure simplicial $d$-complex, with oriented facets $\{F_i\}$, which is boundaryless in the sense that $\sum\partial F_i=0$. We call such a $\mathcal{K}$ an \textit{admissible $d$-complex}. Given an admissible $d$-complex, one can ask for the smallest collection $\{T_i\}$ of oriented $(d+1)$-simplices on the vertices of $\mathcal{

Edwin Vargas, Claudia Correa, Carlos Hinojosa, Henry Arguello

Quantized neural networks employ reduced precision representations for both weights and activations. This quantization process significantly reduces the memory requirements and computational complexity of the network. Binary Neural Networks (BNNs) are the extreme quantization case, representing values with just one bit. Since the sign function is typically u