April 2024 arXiv papers — page 99

Hanjing Wang, Qiang Ji

Epistemic uncertainty quantification (UQ) identifies where models lack knowledge. Traditional UQ methods, often based on Bayesian neural networks, are not suitable for pre-trained non-Bayesian models. Our study addresses quantifying epistemic uncertainty for any pre-trained model, which does not need the original training data or model modifications and can

Raj Narayan Dhara, Krzysztof E. Rutkowski, Katarzyna Szulc

The problem of partially hinged and partially free rectangular plate that aims to represent a suspension bridge subject to some external forces (for example the wind) is considered in order to model and simulate the unstable end behavior. Such a problem can be modeled by a plate evolution equation, which is nonlinear with a nonlocal stretching effect in the

Dylan J. Foster, Yanjun Han, Jian Qian, Alexander Rakhlin

$ $The classical theory of statistical estimation aims to estimate a parameter of interest under data generated from a fixed design ("offline estimation"), while the contemporary theory of online learning provides algorithms for estimation under adaptively chosen covariates ("online estimation"). Motivated by connections between estimation and interactive de

Bryce Morsky, Joshua B. Plotkin, Erol Akçay

Previous research has shown how indirect reciprocity can promote cooperation through evolutionary game theoretic models. Most work in this field assumes a separation of time-scales: individuals' reputations equilibrate at a fast time scale for given frequencies of strategies while the strategies change slowly according to the replicator dynamics. Much of the

Shahzeb Raja Noureen, Richard L. Mort, Christian A. Yates

Adhesion between cells plays an important role in many biological processes such as tissue morphogenesis and homeostasis, wound healing and cancer cell metastasis. From a mathematical perspective, adhesion between multiple cell types has been previously analysed using discrete and continuum models including the Cellular Potts models and partial differential

Joshua Eglinton, Federico Carollo, Igor Lesanovsky, Kay Brandner

Microscopic thermal machines promise to play an important role in future quantum technologies. Making such devices widely applicable will require effective strategies to channel their output into easily accessible storage systems like classical degrees of freedom. Here, we develop a self-consistent theoretical framework that makes it possible to model such q

A. Sommariva, M. Vianello

We prove that interpolation matrices for Generalized MultiQuadrics (GMQ) of order greater than one are almost surely nonsingular without polynomial addition, in any dimension and with any continuous random distribution of sampling points. We also include a new class of generalized MultiQuadrics recently proposed by Buhmann and Ortmann.

Timothy H. Boyer

A derivation of the Planck spectrum for thermal radiation is given based upon wave fluctuations within relativistic classical physics. The derivation depends crucially on thermal fluctuations existing above the fundamental inertial-frame-independent fluctuations of classical zero-point radiation. Such frame-independent zero-point fluctuations exist only in a

Fanny Lehmann, Filippo Gatti, Didier Clouteau

Numerical simulations are essential tools to evaluate the solution of the wave equation in complex settings, such as three-dimensional (3D) domains with heterogeneous properties. However, their application is limited by high computational costs and existing surrogate models lack the flexibility of numerical solvers. This work introduces the Multiple-Input Fo

Jimena Stephenson, Aldo Rodriguez-Puebla, S. M. Faber, Joel R. Primack

We investigate the relation between galaxy structure and star formation rate (SFR) in a sample of $\sim2.9\times10^{4}$ central galaxies with $z<0.0674$ and axial ratios $b/a>0.5$. The star-forming main sequence (SFMS) shows a bend around the stellar mass of $M_\ast\leq{}M_c=2\times10^{10}{}M_{\odot}$. At $M_\ast\leq{}M_c$ the SFMS follows a power-law $\text

Leo C. Stein

In this short Note, I answer the titular question: Yes, a radiation gauge can be horizon-locking. Radiation gauges are very common in black hole perturbation theory. It's also very convenient if a gauge choice is horizon-locking, i.e. the location of the horizon is not moved by a linear metric perturbation. Therefore it is doubly convenient that a radiation

Zofia Malisz, Jan Foremski, Małgorzata Kul

We present a speech database and a phoneme-level language model of Polish. The database and model are designed for the analysis of prosodic and discourse factors and their impact on acoustic parameters in interaction with predictability effects. The database is also the first large, publicly available Polish speech corpus of excellent acoustic quality that c

Sendhil Mullainathan, Ashesh Rambachan

How can we extract theoretical insights from machine learning algorithms? We take a familiar lesson: researchers often turn their intuitions into theoretical insights by constructing "anomalies" -- specific examples highlighting hypothesized flaws in a theory, such as the Allais paradox and the Kahneman-Tversky choice experiments for expected utility. We dev

Chong Yu, Shuaiqi Shen, Shiqiang Wang, Kuan Zhang

E-health allows smart devices and medical institutions to collaboratively collect patients' data, which is trained by Artificial Intelligence (AI) technologies to help doctors make diagnosis. By allowing multiple devices to train models collaboratively, federated learning is a promising solution to address the communication and privacy issues in e-health. Ho

A. N. Vantyghem, T. J. Galvin, B. Sebastian, C. P. O'Dea

Modern wide field radio surveys typically detect millions of objects. Techniques based on machine learning are proving to be useful for classifying large numbers of objects. The self-organizing map (SOM) is an unsupervised machine learning algorithm that projects a many-dimensional dataset onto a two- or three-dimensional lattice of neurons. This dimensional

Wenwen Li, Chia-Yu Hsu, Sizhe Wang, Peter Kedron

GeoAI has emerged as an exciting interdisciplinary research area that combines spatial theories and data with cutting-edge AI models to address geospatial problems in a novel, data-driven manner. While GeoAI research has flourished in the GIScience literature, its reproducibility and replicability (R&R), fundamental principles that determine the reusability,

Omkar Patil, Aarya Shirbhate

This report details the development of a networked distributed system named Group Communication System (GCS), implemented in Java to exemplify socket programming and communication protocols. GCS facilitates group-based client-server communication through a command-line interface (CLI), enabling seamless group interaction and management. The project emphasize

Elena Magnanini, Giacomo Passuello

We consider the edge-triangle model (or Strauss model), and focus on the asymptotic behavior of the triangle density when the size of the graph increases to infinity. This random graph belongs to the class of exponential random graphs, which follows the statistical mechanics approach of introducing a Hamiltonian to weigh the probability measure on the state

Ligia Fonseca Coelho, Lisa Kaltenegger, Stephen Zinder, William Philpot

With more than 5500 detected exoplanets, the search for life is entering a new era. Using life on Earth as our guide, we look beyond green landscapes to expand our ability to detect signs of surface life on other worlds. While oxygenic photosynthesis gives rise to modern green landscapes, bacteriochlorophyll-based anoxygenic phototrophs can also colour their

Sean P. Bartz, Robert C. Meadows, Glenn Brock

The chiral phase boundary of nuclear matter is expected to have a critical point where the rapid crossover of lattice methods at zero chemical potential becomes a first-order phase transition. Phenomenological models based on the AdS/CFT correspondence, known as AdS/ QCD, have succeeded in capturing many features of nuclear matter, with recent progress in pr

Jack Morgan, Eric Ghysels, Hamed Mohammadbagherpoor

We present a classical enhancement to improve the accuracy of the Hybrid variant (Hybrid HHL) of the quantum algorithm for solving linear systems of equations proposed by Harrow, Hassidim, and Lloyd (HHL). We achieve this by using higher precision quantum estimates of the eigenvalues relevant to the linear system, and a new classical step to guide the eigenv

Amit Karanth Gurpur, Janani S, Ajeetha B, Brintha Therese A

Manual identification and classification of pneumonia and COVID-19 infection is a cumbersome process that, if delayed can cause irreversible damage to the patient. We have compiled CT scan images from various sources, namely, from the China Consortium of Chest CT Image Investigation (CC-CCII), the Negin Radiology located at Sari in Iran, an open access COVID

Tamay Besiroglu, Ege Erdil, Matthew Barnett, Josh You

Hoffmann et al. (2022) propose three methods for estimating a compute-optimal scaling law. We attempt to replicate their third estimation procedure, which involves fitting a parametric loss function to a reconstruction of data from their plots. We find that the reported estimates are inconsistent with their first two estimation methods, fail at fitting the e

Alessandra Rizzo, Pierandrea Vergallo

We prove that linear degeneracy is a necessary conditions for systems in Jordan-block form to admit a compatible quasilinear differential constraint. Such condition is also sufficient for 2x2 systems and turns out to be equivalent to possess the Hamiltonian property. Some explicit solutions of parabolic systems are herein given: two principal hierarchies ari

Sarah Fakhoury, Aaditya Naik, Georgios Sakkas, Saikat Chakraborty

Large language models (LLMs) have shown great potential in automating significant aspects of coding by producing natural code from informal natural language (NL) intent. However, given NL is informal, it does not lend easily to checking that the generated code correctly satisfies the user intent. In this paper, we propose a novel interactive workflow TiCoder

Immanuel Bomze, Federico D'Onofrio, Laura Palagi, Bo Peng

In this paper, we study the embedded feature selection problem in linear Support Vector Machines (SVMs), in which a cardinality constraint is employed, leading to an interpretable classification model. The problem is NP-hard due to the presence of the cardinality constraint, even though the original linear SVM amounts to a problem solvable in polynomial time

Yuri Malykhin, Konstantin Ryutin

We prove that any unconditional set in $\mathbb{R}^N$ that is invariant under cyclic shifts of coordinates is rigid in $\ell_q^N$, $1\le q\le 2$, i.e. it can not be well approximated by linear spaces of dimension essentially smaller than $N$. We apply the approach of E.D.~Gluskin to the setting of averaged Kolmogorov widths of unconditional random vectors or

Richard A Zalik

Using properties of the Fourier transform we prove that if a Hartree-Fock molecular spatial orbital is in $L_1(\mathbb{R}^3)$, then it decays to zero as its argument diverges to infinity. The proof is rigorous, elementary, and short. Our result implies that occupied orbitals with positive eigenvalues will decay to zero provided they are in $L_1$.

Amit Tewari

A contract is a type of legal document commonly used in organizations. Contract review is an integral and repetitive process to avoid business risk and liability. Contract analysis requires the identification and classification of key provisions and paragraphs within an agreement. Identification and validation of contract clauses can be a time-consuming and

Daniel Lu

This paper is an original attempt to understand the foundations of economic reasoning. It endeavors to rigorously define the relationship between subjective interpretations and objective valuations of such interpretations in the context of theoretical economics. This analysis is substantially expanded through a dynamic approach, where the truth of a valuatio

Yiqiao Yin

Recent advancements in sequence prediction have significantly improved the accuracy of video data interpretation; however, existing models often overlook the potential of attention-based mechanisms for next-frame prediction. This study introduces the Vision Augmentation Prediction Autoencoder with Attention Design (VAPAAD), an innovative approach that integr

Cynthia Dwork, Kristjan Greenewald, Manish Raghavan

The US Decennial Census provides valuable data for both research and policy purposes. Census data are subject to a variety of disclosure avoidance techniques prior to release in order to preserve respondent confidentiality. While many are interested in studying the impacts of disclosure avoidance methods on downstream analyses, particularly with the introduc

Michał Koziarski, Mohammed Abukalam, Vedant Shah, Louis Vaillancourt

DNA-encoded libraries (DELs) are a powerful approach for rapidly screening large numbers of diverse compounds. One of the key challenges in using DELs is library design, which involves choosing the building blocks that will be combinatorially combined to produce the final library. In this paper we consider the task of protein-protein interaction (PPI) biased

Zhi-Feng Huang, Michael te Vrugt, Jonas Mayer Martins, Raphael Wittkowski

Nonreciprocal interactions violating Newton's third law are common in a plethora of nonequilibrium situations ranging from predator-prey systems to the swarming of birds and effective colloidal interactions under flow. While many recent studies have focused on two species with nonreciprocal coupling, less is examined for the basic single-component system bre

Ming Xiang, Stratis Ioannidis, Edmund Yeh, Carlee Joe-Wong

Federated learning is a popular distributed learning approach for training a machine learning model without disclosing raw data. It consists of a parameter server and a possibly large collection of clients (e.g., in cross-device federated learning) that may operate in congested and changing environments. In this paper, we study federated learning in the pres

Francesco Lancia, Alessia Russo, Tim Worrall

How should successive generations insure each other when the young can default on previously promised transfers to the old? This paper studies intergenerational insurance that maximizes the expected discounted utility of all generations subject to participation constraints for each generation. If complete insurance is unattainable, the optimal intergeneratio

Ashley Ge Zhang, Xiaohang Tang, Steve Oney, Yan Chen

The high demand for computer science education has led to high enrollments, with thousands of students in many introductory courses. In such large courses, it can be overwhelmingly difficult for instructors to understand class-wide problem-solving patterns or issues, which is crucial for improving instruction and addressing important pedagogical challenges.

Nikitas Stamatopoulos, B. David Clader, Stefan Woerner, William J. Zeng

We introduce two quantum algorithms to compute the Value at Risk (VaR) and Conditional Value at Risk (CVaR) of financial derivatives using quantum computers: the first by applying existing ideas from quantum risk analysis to derivative pricing, and the second based on a novel approach using Quantum Signal Processing (QSP). Previous work in the literature has

Zixuan Li, Mingxing Duan, Huizhang Luo, Wangdong Yang

Sparse tensors are prevalent in real-world applications, often characterized by their large-scale, high-order, and high-dimensional nature. Directly handling raw tensors is impractical due to the significant memory and computational overhead involved. The current mainstream approach involves compressing or decomposing the original tensor. One popular tensor

Sai Teja Gajjala, Devi Deepak Manchala, Bhargav Gummadelly, Naga Sailaja K

This project proposes the development of an advanced admin dashboard tailored for enterprise development, leveraging the Refine framework, Ant Design, and GraphQL API. It promises heightened operational efficiency by optimizing backend integration and employing GraphQL's dynamic data subscription for real-time insights. With an emphasis on modern aesthetics

Oscar López, Richard Lehoucq, Carlos Llosa-Vite, Arvind Prasadan

We introduce a new tensor norm, the average spectrum norm, to study sample complexity of tensor completion problems based on the canonical polyadic decomposition (CPD). Properties of the average spectrum norm and its dual norm are investigated, demonstrating their utility for low-rank tensor recovery analysis. Our novel approach significantly reduces the pro

Gregory Eyink

Lars Onsager in 1945-1949 made an exact analysis of the high Reynolds-number limit for individual turbulent flow realizations modeled by incompressible Navier-Stokes equations, motivated by experimental observations that dissipation of kinetic energy does not vanish. I review here developments spurred by his key idea, that such flows are well-described by di

Rodrigo Panosso Macedo, Patrick Bourg, Adam Pound, Samuel D. Upton

Second-order self-force calculations will be critical for modelling extreme-mass-ratio inspirals, and they are now known to have high accuracy even for binaries with mass ratios $\sim 1:10$. Many of the challenges facing these calculations are related to slow convergence of spherical-harmonic (or spheroidal harmonic) mode sums in a region containing the smal

Patrick Bourg, Adam Pound, Samuel D. Upton, Rodrigo Panosso Macedo

Most self-force calculations rely, in one way or another, on representations of a particle's Detweiler- Whiting singular field. We present a simple method of calculating the singular field to high order in a local expansion in powers of distance from the particle. As a demonstration, we compute the singular field to 14th order in distance, 10 orders beyond t

Kagan Ucak, Faruk Karatas, Emre Cetinkaya, Kerem Pekkan

A blood turbine-pump system (iATVA), resembling a turbocharger was proposed as a mechanical right-heart assist device without external drive power. In this study, the iATVA system is investigated with particular emphasis on the blood turbine flow dynamics. A time-resolved 2D particle image velocimetry (PIV) set-up equipped with a beam splitter and two high s

Stephen H. Lubow, Anna C. Childs, Rebecca G. Martin

We analyze a tilt instability of the orbit of an outer planet in a two planet circumbinary system that we recently reported. The binary is on an eccentric orbit and the inner circumbinary planet is on a circular polar orbit that causes the the binary to undergo apsidal precession. The outer circumbinary planet is initially on a circular or eccentric orbit th

Lorenzo Sillari

We prove that, on a compact almost complex manifold, the space of almost complex structures whose Nijenhuis tensor has rank at least $k$ at every point is either empty or dense in each path-connected component of the space of almost complex structures. In particular, this applies to maximally non-integrable almost complex structures.

Dai Quoc Tran, Armstrong Aboah, Yuntae Jeon, Maged Shoman

This study addresses the evolving challenges in urban traffic monitoring detection systems based on fisheye lens cameras by proposing a framework that improves the efficacy and accuracy of these systems. In the context of urban infrastructure and transportation management, advanced traffic monitoring systems have become critical for managing the complexities

Dilip Kumar Ghosh, Purusottam Ghosh, Sk Jeesun, Rahul Srivastava

The relativistic degrees of freedom ($N_{\rm eff}$) is one of the crucial cosmological parameters. The precise measurement of $N_{\rm eff}$ at the time of cosmic microwave background formation, by Planck 2018 can be used to understand the new fundamental interactions, in particular involving light mediators. Presence of any new particle with sufficient energ

Andrew Boutros, Aman Arora, Vaughn Betz

Deep learning (DL) is becoming the cornerstone of numerous applications both in datacenters and at the edge. Specialized hardware is often necessary to meet the performance requirements of state-of-the-art DL models, but the rapid pace of change in DL models and the wide variety of systems integrating DL make it impossible to create custom computer chips for

Lillian B. Hughes, Simon A. Meynell, Weijie Wu, Shreyas Parthasarathy

Systems of spins with strong dipolar interactions and controlled dimensionality enable new explorations in quantum sensing and simulation. In this work, we investigate the creation of strong dipolar interactions in a two-dimensional ensemble of nitrogen-vacancy (NV) centers generated via plasma-enhanced chemical vapor deposition (PECVD) on (111)-oriented dia

Moallison F. Cavalcante, Marcus V. S. Bonança, Eduardo Miranda, Sebastian Deffner

We consider the optimal control of switching on a coupling term between two quantum many-body systems. Specifically, we (i) quantify the energetic cost of establishing a weak junction between two quantum spin-$1/2$ chains in finite time $\tau$ and (ii) identify the energetically optimal protocol to realize it. For linear driving protocols, we find that for l

Aswini Kumar Patra, Lingaraj Sahoo

Early identification of drought stress in crops is vital for implementing effective mitigation measures and reducing yield loss. Non-invasive imaging techniques hold immense potential by capturing subtle physiological changes in plants under water deficit. Sensor based imaging data serves as a rich source of information for machine learning and deep learning

Mody Sy, Raymond Knopp

This paper presents low-complexity block-based encoding and decoding algorithms for short block length channels. In terms of the precise use-case, we are primarily concerned with the baseline 3GPP Short block transmissions in which payloads are encoded by Reed-Muller codes and paired with orthogonal DMRS. In contemporary communication systems, the short bloc

Abeba Birhane, Jelle van Dijk, Frank Pasquale

In this work we challenge arguments for robot rights on metaphysical, ethical and legal grounds. Metaphysically, we argue that machines are not the kinds of things that may be denied or granted rights. Building on theories of phenomenology and post-Cartesian approaches to cognitive science, we ground our position in the lived reality of actual humans in an i

Roger Domingo-Enrich, Xiuqiang He, Verena Häberle, Florian Dörfler

Complex droop control, alternatively known as dispatchable virtual oscillator control (dVOC), stands out for its unique capabilities in synchronization and voltage stabilization among existing control strategies for grid-forming converters. Complex droop control leverages the novel concept of ``complex frequency'', thereby establishing a coupled connection b

Halil Gamsızkan

Microscopic black hole production at future hadron colliders is a promising avenue to explore low scale gravity models like ADD. This study investigates production cross-sections and final state properties of these black holes using the BlackMax event generator. We analyze scenarios with varying proton-proton collision energies (27 TeV and 100 TeV), number o

Mainak Das, Chunli Huang

We introduce a many-body state termed superpolarized electron-hole liquid to explain the multiferroic properties observed in a recent experiment on rhombohedral pentalayer graphene by Han et al. [Nature 623, 41-47, 2023] . Superpolarization refers to a state where electrons and holes are fully polarized in opposite directions within the extended spin-valley

Carlo Branchina, Vincenzo Branchina, Filippo Contino, Arcangelo Pernace

In [1] we pointed out that in the Dark Dimension scenario [2] theoretical issues arise when the prediction for the vacuum energy $\rho$, that is obtained from swampland conjectures in string theory, is confronted with the corresponding result for $\rho$ in the effective field theory (EFT) limit. One of the problems concerns the widely spread belief that in h

Xiaowei Ou, Alexander P. Ji, Anna Frebel, Rohan P. Naidu

Neutron star mergers (NSMs) produce copious amounts of heavy r-process elements after a time delayed inspiral process. Once NSMs are present in a galaxy, r-process elements, such as Eu, are expected to significantly increase with time. Yet, there has been limited observational data in support of Eu increasing within Local Group galaxies. We have obtained hig

Timon Emken, Rouven Essig, Hailin Xu

We consider the scattering of low-mass halo dark-matter particles in the hot plasma of the Sun, focusing on dark matter that interact with ordinary matter through a dark-photon mediator. The resulting ``solar-reflected'' dark matter (SRDM) component contains high-velocity particles, which significantly extend the sensitivity of terrestrial direct-detection e

Mody Sy, Raymond Knopp

This paper presents a comprehensive analysis and performance enhancement of short block length channel detection incorporating training information. The current communication systems' short block length channel detection typically consists of least squares channel estimation followed by quasi-coherent detection. By investigating the receiver structure, speci

Yujie Yang, Zhilong Zheng, Masayoshi Tomizuka, Changliu Liu

Satisfying safety constraints is a priority concern when solving optimal control problems (OCPs). Due to the existence of infeasibility phenomenon, where a constraint-satisfying solution cannot be found, it is necessary to identify a feasible region before implementing a policy. Existing feasibility theories built for model predictive control (MPC) only cons

Xiwei Chen, Yuanyuan Luan, Roger S. Zoh, Lan Xue

Wearable devices enable the continuous monitoring of physical activity (PA) but generate complex functional data with poorly characterized errors. Most work on functional data views the data as smooth, latent curves obtained at discrete time intervals with some random noise with mean zero and constant variance. Viewing this noise as homoscedastic and indepen

Siddhartha Karmakar, Amol Dighe, Rick S. Gupta

The $SU(2)_L\times U(1)_Y$ invariance of the Standard Model Effective Field Theory (SMEFT) predicts multiple restrictions in the space of Wilson coefficients of $U(1)_{em}$ invariant effective lagrangians such as the Low-energy Effective Field Theory (LEFT), used for low-energy flavor-physics observables, or the Higgs Effective Field Theory (HEFT) in unitary

A. Juráňová, E. Costantini, G. A. Kriss, M. Mehdipour

We present an analysis of the HST COS spectrum of IZw1 aiming to probe the absorbing medium associated with the active galactic nucleus (AGN). We fitted the emission spectrum and performed spectral analysis of the identified absorption features to derive the corresponding ionic column densities and covering fractions of the associated outflows. We employed p

Akhil Krishna R, Sreeja S Kartha, Blesson Mathew

In the context of the hierarchical model of galaxy evolution, polar ring galaxies (PRGs) are considered the intermediate phase between ongoing mergers and quiescent galaxies. This study explores the globular cluster system (GCS) and its properties in the nearest PRG, NGC4262, serving as a pilot investigation to study GCS in nearby PRGs. We utilize wide and d

Haochen M. Kotoi-Xie, Takumi Moriyama

In this writing, we introduce a novel biometric-authenticated key exchange protocol that allows secure and privacy-preserving key establishment between a stateless biometric sensing system and a "smart" user token that possesses biometric templates of the user. The protocol yields a shared secret incorporating random nonce from both parties when they positiv

Trystyn A. M. Berg, Christian R. Hayes, Stefano Cristiani, Alan McConnachie

The Gemini High-resolution Optical SpecTrograph (GHOST) is a new echelle spectrograph available on the Gemini-South telescope as of Semester 2024A. We present the first high resolution spectrum of the quasar J1449-1227 (redshift z_em=3.27) using data taken during the commissioning of GHOST. The observed quasar hosts an intervening iron-poor ([Fe/H] = -2.5) d

Alexios Christopoulos, Amos Chan, Andrea De Luca

We study the distribution of overlaps with the computational basis of a quantum state generated under generic quantum many-body chaotic dynamics, without conserved quantities, for a finite time $t$. We argue that, scaling time logarithmically with the system size $t \propto \log L$, the overlap distribution converges to a universal form in the thermodynamic

Mark N. Costantini, Maeve Madigan, Luca Mantani, James M. Moore

We present a detailed mathematical study of the Monte Carlo replica method as applied in the global fitting literature from the high-energy physics theory community. For the first time, we provide a rigorous derivation of the parameter distributions implied by the method, and show that, whilst they agree with Bayesian posteriors for linear models, they disag

Aaron R. Rowntree, Ankit Singh, Fiorenzo Vincenzo, Brad K. Gibson

Metallicity offers a unique window into the baryonic history of the cosmos, being instrumental in probing evolutionary processes in galaxies between different cosmic environments. We aim to quantify the contribution of these environments to the scatter in the mass-metallicity relation (MZR) of galaxies. By analysing the galaxy distribution within the cosmic

Niyati Rawal, Roberto Bigazzi, Lorenzo Baraldi, Rita Cucchiara

In the last few years, the research interest in Vision-and-Language Navigation (VLN) has grown significantly. VLN is a challenging task that involves an agent following human instructions and navigating in a previously unknown environment to reach a specified goal. Recent work in literature focuses on different ways to augment the available datasets of instr

Alexandra B. Tully, Rysa Greenwood, MengXing Na, Vanessa King

As an organic semiconductor and a prototypical acceptor molecule in organic photovoltaics, C$_{60}$ has broad relevance to the world of organic thin film electronics. Although highly uniform C$_{60}$ thin films are necessary to conduct spectroscopic analysis of the electronic structure of these C$_{60}$-based materials, reported C$_{60}$ films show a relativ

P. Chris Fragile, Matthew Liska

In this chapter, we review some of the interesting consequences that tilt between the spin axis of the black hole and angular momentum axis of the accretion disk can have on the dynamics, thermodynamics, and observational appearance of accreting systems, from precessing coronae and jets to standing nozzle shocks and quasi-periodic oscillations. We begin the

Joshua Job, Isaac H. Kim, Eric Johnston, Steve Adachi

We perform a detailed resource estimate for the prospect of using deep entanglement renormalization ansatz (DMERA) on a fault-tolerant quantum computer, focusing on the regime in which the target system is large. For probing a relatively large system size ($64\times 64$), we observe up to an order of magnitude reduction in the number of qubits, compared to t

Zheng-Yang Zhuang, Chaoyi Zhang, Xiao-Jiao Wang, Zhongbo Yan

We introduce ''Berry-dipole semimetals'', whose band degeneracies are characterized by quantized Berry dipoles. Through a two-band model constructed by Hopf map, we reveal that the Berry-dipole semimetals display a multitude of salient properties distinct from other topological semimetals. On the boundary, we find that the first-order Berry-dipole semimetal

Filippo Santoliquido, Ulyana Dupletsa, Jacopo Tissino, Marica Branchesi

Third-generation (3G) gravitational-wave detectors such as the Einstein Telescope (ET) will observe binary black hole (BBH) mergers at redshifts up to $z\sim 100$. However, an unequivocal determination of the origin of high-redshift sources will remain uncertain because of the low signal-to-noise ratio (S/N) and poor estimate of their luminosity distance. Th

Damian S. Steiger, Thomas Häner, Scott N. Genin, Helmut G. Katzgraber

The Variational Quantum Eigensolver (VQE) is a promising algorithm for future Noisy Intermediate-Scale Quantum (NISQ) devices to simulate chemical systems. In this paper, we consider the classical simulation of the iterative Qubit Coupled Cluster (iQCC) ansatz. To this end, we implement a multi-threaded sparse wave function simulator and simulate iQCC circui

Lingyuan Kong, Michał Papaj, Hyunjin Kim, Yiran Zhang

Superconducting states that break space-group symmetries of the underlying crystal can exhibit nontrivial spatial modulation of the order parameter. Previously, such remarkable states were intimately associated with the breaking of translational symmetry, giving rise to the density-wave orders, with wavelengths spanning several unit cells. However, a related

P. Nazari, B. Tabone, G. P. Rosotti, E. F. van Dishoeck

Column density ratios of complex organic molecules are generally constant across protostellar systems with some low-level scatter. However, the scatter in formamide (NH$_2$CHO) to methanol (CH$_3$OH) column density ratio is one of the highest. This larger scatter is sometimes interpreted as evidence of gas-phase formation of NH$_2$CHO. In this work we propos

Ricard Puig, Marc Drudis, Supanut Thanasilp, Zoë Holmes

The barren plateau phenomenon, characterized by loss gradients that vanish exponentially with system size, poses a challenge to scaling variational quantum algorithms. Here we explore the potential of warm starts, whereby one initializes closer to a solution in the hope of enjoying larger loss variances. Focusing on an iterative variational method for learni

Nico Gubernari

I review the state of the art of the theoretical calculations for decays mediated by $b\to s \ell^+ \ell^-$ transitions, for $\ell=e,\mu$. I focus on the predictions of observables in $B\to K \mu^+\mu^-$, $B\to K^* \mu^+\mu^-$, and $B_s\to \phi \mu^+\mu^-$ decays, as many of these predictions are in tension with the corresponding experimental measurements. I

Mikako Matsuura, M. Boyer, Richard G. Arendt, J. Larsson

JWST/NIRCam obtained high angular-resolution (0.05-0.1''), deep near-infrared 1--5 micron imaging of Supernova (SN) 1987A taken 35 years after the explosion. In the NIRCam images, we identify: 1) faint H2 crescents, which are emissions located between the ejecta and the equatorial ring, 2) a bar, which is a substructure of the ejecta, and 3) the bright 3-5 m

Daniele Bielli, Silvia Penati, Anayeli Ramirez

We study the geometries obtained by performing super non-Abelian T-duality of the Principal Chiral Model on OSp$(1|2)$. While the initial model represents an appropriate 3D supergravity background, interpretable as the superspace version of AdS$_{3}$, the T-dual model fails solving the 3D supergravity torsion constraints. We argue that this has to do with a

Alberto Torralba-Torregrosa, Jorryt Matthee, Rohan P. Naidu, Ruari Mackenzie

The increasingly neutral intergalactic gas at $z>6$ impacts the Lyman-$\alpha$ flux observed from galaxies. One luminous galaxy, COLA1, stands out because of its unique double-peaked Ly$\alpha$ line at $z=6.6$, unseen in any simulation of reionization. Here we present JWST/NIRCam wide-field slitless spectroscopy in a 21 arcmin$^2$ field centered on COLA1. We

Javier F. Acevedo, Joseph Bramante, Qinrui Liu, Narayani Tyagi

We present a new inelastic dark matter search: neutron stars in dark matter-rich environments capture inelastic dark matter which, for interstate mass splittings between about $45 - 285 \ \rm MeV$, will annihilate away before becoming fully trapped inside the object. This means a sizable fraction of the dark matter particles can annihilate while being outsid

Pavlo O. Sukhachov, Erik Wegner Hodt, Jacob Linder

We propose altermagnet-superconductor junctions as a way to achieve a thermoelectric response in metals free of external or stray magnetic fields. We combine qualitative analysis in a simplified model with a more rigorous approach based on the inverse proximity effect in the functional-integral formulation. We show that coupling an altermagnet to a supercond

Takahiro Morishita, Massimo Stiavelli, Stefan Schuldt, Claudio Grillo

We report JWST/NIRSpec observations of a star-forming galaxy at $z=2.76$, MACSJ1149-WR1. We securely detect two temperature-sensitive auroral lines, [SIII]6312 (7.4$\sigma$) and [OII]7320+7331 doublets (10$\sigma$), and tentatively [NII]5755 ($2.3\sigma$) for the first time in an individual galaxy at $z>1$. We perform a detailed analysis of its interstellar

T. Eftekhari, A. Tchekhovskoy, K. D. Alexander, E. Berger

The tidal disruption event (TDE) AT2022cmc represents the fourth known example of a relativistic jet produced by the tidal disruption of a stray star providing a unique probe of the formation and evolution of relativistic jets in otherwise dormant supermassive black holes (SMBHs). Here we present deep, late-time Chandra observations of AT2022cmc extending to

Sergio Hernández-Cuenca

We study the general framework of effective theories obtained via exact path integration of a complete theory over some sector of its degrees of freedom. Theories constructed this way contain multi-integrals which couple fields arbitrarily far apart, and in certain settings even on path-disconnected components of the space. These are not just entanglement, b

Chieh Hubert Lin, Changil Kim, Jia-Bin Huang, Qinbo Li

Neural Radiance Field (NeRF) is a representation for 3D reconstruction from multi-view images. Despite some recent work showing preliminary success in editing a reconstructed NeRF with diffusion prior, they remain struggling to synthesize reasonable geometry in completely uncovered regions. One major reason is the high diversity of synthetic contents from th

Jorge G. Russo, Paul K. Townsend

For the general theory of nonlinear electrodynamics (NLED), we prove that causality implies both the Dominant Energy Condition (DEC) and, surprisingly, the Strong Energy Condition (SEC). This has implications for gravitational applications, such as regular black holes supported by NLED matter. For self-dual NLED theories, weak-field causality alone implies b

Yu-Ju Tsai, Jin-Cheng Jhang, Jingjing Zheng, Wei Wang

Inherent ambiguity in layout annotations poses significant challenges to developing accurate 360{\deg} room layout estimation models. To address this issue, we propose a novel Bi-Layout model capable of predicting two distinct layout types. One stops at ambiguous regions, while the other extends to encompass all visible areas. Our model employs two global co

Shulin Tian, Ziniu Zhang, Liangyu Chen, Ziwei Liu

Autonomous embodied agents live on an Internet of multimedia websites. Can they hop around multimodal websites to complete complex user tasks? Existing benchmarks fail to assess them in a realistic, evolving environment for their embodiment across websites. To answer this question, we present MMInA, a multihop and multimodal benchmark to evaluate the embodie

Amir Bar, Arya Bakhtiar, Danny Tran, Antonio Loquercio

Animals perceive the world to plan their actions and interact with other agents to accomplish complex tasks, demonstrating capabilities that are still unmatched by AI systems. To advance our understanding and reduce the gap between the capabilities of animals and AI systems, we introduce a dataset of pet egomotion imagery with diverse examples of simultaneou

Mude Hui, Siwei Yang, Bingchen Zhao, Yichun Shi

This study introduces HQ-Edit, a high-quality instruction-based image editing dataset with around 200,000 edits. Unlike prior approaches relying on attribute guidance or human feedback on building datasets, we devise a scalable data collection pipeline leveraging advanced foundation models, namely GPT-4V and DALL-E 3. To ensure its high quality, diverse exam

Fanjie Sun, Xiao Yan Xu

Determinant Quantum Monte Carlo (DQMC) provides numerically exact solutions for strongly correlated fermionic systems but faces significant computational challenges with increasing system size. While submatrix updates were originally developed for Hirsch-Fye QMC with onsite interactions at finite temperatures [Phys. Rev. B 80, 195111 (2009)], their comprehen

Pablo Ruiz Ponce, German Barquero, Cristina Palmero, Sergio Escalera

Generating human-human motion interactions conditioned on textual descriptions is a very useful application in many areas such as robotics, gaming, animation, and the metaverse. Alongside this utility also comes a great difficulty in modeling the highly dimensional inter-personal dynamics. In addition, properly capturing the intra-personal diversity of inter

Jinyue Chen, Lingyu Kong, Haoran Wei, Chenglong Liu

Chart parsing poses a significant challenge due to the diversity of styles, values, texts, and so forth. Even advanced large vision-language models (LVLMs) with billions of parameters struggle to handle such tasks satisfactorily. To address this, we propose OneChart: a reliable agent specifically devised for the structural extraction of chart information. Si