March 2024 arXiv papers — page 169

Alex Boyd

Real-world data often exhibits sequential dependence, across diverse domains such as human behavior, medicine, finance, and climate modeling. Probabilistic methods capture the inherent uncertainty associated with prediction in these contexts, with autoregressive models being especially prominent. This dissertation focuses on using autoregressive models to an

Anton E. Lipin, Alexander V. Osipov

Using approximation by continuous functions we prove the following statements to types of tightness in a space $Q_p(X, \mathbb{R})$ of all quasicontinuous real-valued functions with the topology $\tau_p$ of pointwise convergence: the countability of tightness (fan-tightness, strong fan-tightness) at a point $f$ of space $Q_p(X, \mathbb{R})$ implies the count

Margaret Beck, Jonathan Jaquette, Hannah Pieper

In the scalar Swift-Hohenberg equation with quadratic-cubic nonlinearity, it is known that symmetric pulse solutions exist for certain parameter regions. In this paper we develop a method to determine the spectral stability of these solutions by associating a Maslov index to them. This requires extending the method of computing the Maslov index introduced by

Yu-Ching Chen, Yuzo Ishikawa, Nadia L. Zakamska, Xin Liu

Dual quasars, two active supermassive black holes at galactic scales, represent crucial objects for studying the impact of galaxy mergers and quasar activity on the star formation rate (SFR) within their host galaxies, particularly at cosmic noon when SFR peaks. We present JWST/MIRI mid-infrared integral field spectroscopy of J074922.96+225511.7, a dual quas

Suzan Ece Ada, Hanne Say, Emre Ugur, Erhan Oztop

Human brain and behavior provide a rich venue that can inspire novel control and learning methods for robotics. In an attempt to exemplify such a development by inspiring how humans acquire knowledge and transfer skills among tasks, we introduce a novel multi-task reinforcement learning framework named Episodic Return Progress with Bidirectional Progressive

Taylor L. Tobin, Thayne Currie, Yiting Li, Jeffrey Chilcote

We present the direct-imaging discovery of a substellar companion (a massive planet or low-mass brown dwarf) to the young, $\gamma$ Doradus-type variable star, HIP 39017 (HD 65526). The companion's SCExAO/CHARIS JHK ($1.1-2.4\mu$m) spectrum and Keck/NIRC2 L$^{\prime}$ photometry indicate that it is an L/T transition object. A comparison of the JHK+L$^{\prime

Leonardo Pedroso, Andrea Agazzi, W. P. M. H. Heemels, Mauro Salazar

When users access shared resources in a selfish manner, the resulting societal cost and perceived users' cost is often higher than what would result from a centrally coordinated optimal allocation. While several contributions in mechanism design manage to steer the aggregate users choices to the desired optimum by using monetary tolls, such approaches bear t

Diwen Xue, Reethika Ramesh, Arham Jain, Michalis Kallitsis

VPN adoption has seen steady growth over the past decade due to increased public awareness of privacy and surveillance threats. In response, certain governments are attempting to restrict VPN access by identifying connections using "dual use" DPI technology. To investigate the potential for VPN blocking, we develop mechanisms for accurately fingerprinting co

Yixuan Li, Julian Parsert, Elizabeth Polgreen

Pre-trained Large Language Models (LLMs) are beginning to dominate the discourse around automatic code generation with natural language specifications. In contrast, the best-performing synthesizers in the domain of formal synthesis with precise logical specifications are still based on enumerative algorithms. In this paper, we evaluate the abilities of LLMs

Zhewei Liu, Kai Yin, Ali Mostafavi

Inspired by ideas from health risk assessment, this paper presents a new perspective for flood risk assessment. The proposed perspective focuses on three pillars for examining flood risk: (1) inherent susceptibility, (2) mitigation strategies, and (3) external stressors. These pillars collectively encompass the physical and environmental characteristics of u

He Li, Patrick M. Wensing

This work introduces an optimization-based locomotion control framework for on-the-fly synthesis of complex dynamic maneuvers. At the core of the proposed framework is a cascaded-fidelity model predictive controller (Cafe-Mpc). Cafe-Mpc strategically relaxes the planning problem along the prediction horizon (i.e., with descending model fidelity, increasingly

Sourav Ganguly, Saprativa Bhattacharjee

Modern deep learning tools are remarkably effective in addressing intricate problems. However, their operation as black-box models introduces increased uncertainty in predictions. Additionally, they contend with various challenges, including the need for substantial storage space in large networks, issues of overfitting, underfitting, vanishing gradients, an

Ala Shaabana, Zahra Gharaee, Paul Fieguth

Machine comprehension of visual information from images and videos by neural networks faces two primary challenges. Firstly, there exists a computational and inference gap in connecting vision and language, making it difficult to accurately determine which object a given agent acts on and represent it through language. Secondly, classifiers trained by a sing

Antonios Valkanas, Yuening Wang, Yingxue Zhang, Mark Coates

Recommender systems have become an integral part of online platforms. Every day the volume of training data is expanding and the number of user interactions is constantly increasing. The exploration of larger and more expressive models has become a necessary pursuit to improve user experience. However, this progression carries with it an increased computatio

Aaron Miller, Adam Glos, Zoltán Zimborás

Quantum computers hold great promise for efficiently simulating Fermionic systems, benefiting fields like quantum chemistry and materials science. To achieve this, algorithms typically begin by choosing a Fermion-to-qubit mapping to encode the Fermioinc problem in the qubits of a quantum computer. In this work, we introduce "treespilation," a technique for e

Tomohiro Itogawa, Yugo Takada, Yutaka Hirano, Keisuke Fujii

Magic state distillation (MSD) is an essential element for universal fault-tolerant quantum computing, which distills a high-fidelity magic state from noisy magic states using ideal (error-corrected) Clifford operations. For ideal Clifford operations, it needs to be performed on the logical qubits and hence incurs a large spatiotemporal overhead, which is on

Brent Harrison, Jason Necaise, Andrew Projansky, James D. Whitfield

The binary indexed tree, or Fenwick tree, is a data structure that can efficiently update values and calculate prefix sums in an array. It allows both of these operations to be performed in $O(\log_2 N)$ time. Here we present a novel data structure resembling the Sierpinski triangle, which accomplishes these operations with the same memory usage in $O(\log_3

Mathieu Boisvert, Pietro Ferrero

We consider the $(p+2)$-dimensional gauged supergravities arising as a consistent truncation of type II on $S^{8-p}$, which are associated with the near-horizon limit of D$p$-branes, for $p=2,4,5,6$ (and NS5-branes for $p=5$). In a truncation of these theories with only abelian gauge fields and scalars, we find several classes of new solutions, with and with

Pietro Ferrero

We present new solutions of 8d gauged supergravity which, upon uplift to type IIA, represent D6 branes wrapped on spindles. A further circle uplift gives 11d supergravity on a Calabi-Yau three-fold which is the cone over five-dimensional $Y^{p,q}$ manifolds. This highlights a connection between co-homogeneity one Sasaki-Einstein metrics in general dimension

S. Molendi, S. Ghizzardi, S. De Grandi, M. Balboni

Aims. The goal of this work is to devise a description of the enrichment process in large-scale structure that explains the available observations and makes predictions for future measurements. Methods. We took a spartan approach to this study, employing observational results and algebra to connect stellar assembly in star-forming halos with metal enrichment

Luke Causer, Mari Carmen Bañuls, Juan P. Garrahan

We study the dynamics and thermalization of the Fredkin spin chain, a system with local three-body interactions, particle conservation and explicit kinetic constraints. We consider deformations away from its stochastic point in order to tune between regimes where kinetic energy dominates and those where potential energy does. By means of exact diagonalisatio

Stefan Waterval, Andrea V. Macciò, Tobias Buck, Aura Obreja

We present the High-$z$ Evolution of Large and Luminous Objects (HELLO) project, a set of $\sim\!30$ high-resolution cosmological simulations aimed to study Milky Way analogues ($M_\star\sim10^{10-11}$\,\Msun) at high redshift ($z\sim [2-4]$). Based on the Numerical Investigation of a Hundred Astrophysical Objects (NIHAO), HELLO features an updated scheme fo

F. R. N. Schneider, Ph. Podsiadlowski, E. Laplace

The majority of massive stars are expected to exchange mass or merge with a companion during their lives. This immediately implies that most supernovae (SNe) are from such post-mass-exchange objects. Here, we explore how mass accretion and merging affect the pre-SN structures of stars and their final fates. We use the stellar evolution code MESA, infer the o

Jennifer I. Li, Sean D. Johnson, Erin Boettcher, Sebastiano Cantalupo

We investigate the group-scale environment of 15 luminous quasars (luminosity $L_{\rm 3000}>10^{46}$ erg s$^{-1}$) from the Cosmic Ultraviolet Baryon Survey (CUBS) at redshift $z\approx1$. Using the Multi Unit Spectroscopic Explorer (MUSE) integral field spectrograph on the Very Large Telescope (VLT), we conduct a deep galaxy redshift survey in the CUBS quas

Aniruddha Chakraborty, Suvodip Mukherjee

Gravitational lensing is the phenomenon where the presence of matter (called a lens) bends the path of light-like trajectories travelling nearby. Similar to the geometric optics limit of electromagnetic waves, gravitational lensing of gravitational waves (GWs) can occur in geometric optics condition when GW wavelength is much smaller than the Schwarzschild r

Federico Esposito, Almudena Alonso-Herrero, Santiago García-Burillo, Viviana Casasola

We present new optical GTC/MEGARA seeing-limited (0.9") integral-field observations of NGC 5506, together with ALMA observations of the CO(3-2) transition at a 0.2" (25 pc) resolution. NGC 5506 is a luminous (bolometric luminosity of $\sim 10^{44}$ erg/s) nearby (26 Mpc) Seyfert galaxy, part of the Galaxy Activity, Torus, and Outflow Survey (GATOS). We model

Yantao Li, Maxim Dzero

We consider a problem of nonlinear response to an external electromagnetic radiation of conventional disordered superconductors which contain a small amount of weak magnetic impurities. We focus on the diffusive limit and use Usadel equation to analyze the collective excitations and obtain the dispersion relations for the collective modes. We determine the r

David H. Oaknin, Amir Kalev, Itay Hen

We re-examine the CHSH experiment, which we abstract here as a multi-round game played between two parties with each party reporting a single binary outcome at each round. We explore in particular the role that symmetries, and the spontaneous breaking thereof, play in determining the maximally achievable correlations between the two parties. We show, with th

Soumangsu Chakraborty, Amit Giveon, Akikazu Hashimoto

We derive a compact formula for the one-loop, bosonic string partition function of Euclideanized $J_3 \bar J_3$ deformed $AdS_3$ with periodic Euclidean time as an integral transform of the partition function of the undeformed Euclideanized $AdS_3$. Such a deformation is interpretable as an irrelevant "single-trace $T \bar T$ deformation" of the boundary. We

M. C. Powell, M. Krumpe, A. Coil, T. Miyaji

The connection between active galactic nuclei (AGN) and their host dark matter halos provides powerful insights into how supermassive black holes (SMBHs) grow and coevolve with their host galaxies. Here we investigate the impact of observational AGN selection on the AGN halo occupation distribution (HOD) by forward-modeling AGN activity into cosmological N-b

G. Venturi, S. Carniani, E. Parlanti, M. Kohandel

The study of gas-phase metallicity and its spatial distribution at high redshift is crucial to understand the processes that shaped the growth and evolution of galaxies in the early Universe. Here we study the spatially resolved metallicity in three systems at $z\sim6-8$, namely A2744-YD4, BDF-3299, and COSMOS24108, with JWST NIRSpec IFU low-resolution ($R\s

Matteo Fael, Florian Herren

We calculate the next-to-next-to-leading order QCD corrections to the leptonic invariant mass ($q^2$) spectrum of semileptonic $b \to c$ inclusive decays, taking into account the mass of the charm quark and the charged lepton in the final state. We obtain analytic results in terms of generalized polylogarithms and present numerical studies of the $\mathcal{O

Marcus Mayrhofer, Una Radojičić, Peter Filzmoser

This work introduces the Matrix Minimum Covariance Determinant (MMCD) method, a novel robust location and covariance estimation procedure designed for data that are naturally represented in the form of a matrix. Unlike standard robust multivariate estimators, which would only be applicable after a vectorization of the matrix-variate samples leading to high-d

Tom Rose, B. R. McNamara, F. Combes, A. C. Edge

We present new ALMA observations of CO, CN, CS, HCN and HCO$^{+}$ absorption seen against the bright and compact radio continuum sources of eight massive galaxies. Combined with archival observations, they reveal two distinct populations of molecular clouds, which we identify by combining CO emission and absorption profiles to unambiguously reveal each cloud

Federico Bonetti, Sakura Schafer-Nameki, Jingxiang Wu

We propose a correspondence between topological order in 2+1d and Seifert three-manifolds together with a choice of ADE gauge group $G$. Topological order in 2+1d is known to be characterized in terms of modular tensor categories (MTCs), and we thus propose a relation between MTCs and Seifert three-manifolds. The correspondence defines for every Seifert mani

Marianne Moore, Tracy R. Slatyer

We investigate the hypothesis that sexaquarks, hypothetical stable six-quark states, could be a significant component of the dark matter. We expand on previous studies of sexaquark cosmology, accounting for the possibility that some relevant interaction cross sections might be strongly suppressed below expectations based on dimensional analysis. We update di

Anirudh Deb, Gabi Zafrir

It was previously noted that for 3d SCFTs with $\mathcal{N}\geq 6$ the moduli space has the form of $\mathbb{C}^{4r}/\Gamma$, where $\Gamma$ is a complex reflection group, at least following suitable gauging of finite symmetries. Here we argue that this observation can be extended also to 3d SCFTs with $\mathcal{N}\geq 5$ SUSY, where $\Gamma$ is now a quater

Alexander C. Tyner, Cormac Grindall, J. H. Pixley

In two-dimensional topological insulators, a disorder induced topological phase transition is typically identified with an Anderson localization transition at the Fermi energy. However, in higher-order, spin-resolved topological insulators it is the spectral gap of the spin-spectrum, in addition to the bulk mobility gap, which protects the non-trivial topolo

Rose E. Wang, Pawan Wirawarn, Omar Khattab, Noah Goodman

Many online content portals allow users to ask questions to supplement their understanding (e.g., of lectures). While information retrieval (IR) systems may provide answers for such user queries, they do not directly assist content creators -- such as lecturers who want to improve their content -- identify segments that _caused_ a user to ask those questions

Anasuya Lyons

We consider the problem of a generic stabilizer Hamiltonian under local, incoherent Pauli errors. Using two different approaches -- (i) Haah's polynomial formalism arXiv:1204.1063 and (ii) the homological perspective on CSS codes -- we construct a mapping from the $n$th moment of the decohered ground state density matrix to a classical statistical mechanics

Yanjie Ze, Gu Zhang, Kangning Zhang, Chenyuan Hu

Imitation learning provides an efficient way to teach robots dexterous skills; however, learning complex skills robustly and generalizablely usually consumes large amounts of human demonstrations. To tackle this challenging problem, we present 3D Diffusion Policy (DP3), a novel visual imitation learning approach that incorporates the power of 3D visual repre

Philip Boyle Smith, Yunqin Zheng

For a fermionic quantum field theory in $d=1+1$ dimensions, there is a subtle difference between summing over spin structures and gauging $(-1)^F$. If the gravitational anomaly vanishes mod 16, then both operations are equivalent and yield a bosonic theory. But if the gravitational anomaly only vanishes mod 8, then only gauging $(-1)^F$ is allowed, and the r

Yupeng Hou, Jiacheng Li, Xiangjun Fu, Zhankui He

Feature engineering has long been central to recommender systems, yet effectively leveraging textual item features remains challenging. Recent advances in large language models (LLMs) have enabled their use as semantic encoders for recommendation, but their roles and behaviors in this setting are still not well understood. Prior studies often rely on general

Lachlan P. Lindoy, Arkajit Mandal, David R. Reichman

In this paper we develop quantum dynamical methods capable of treating the dynamics of chemically reacting systems in an optical cavity in the vibrationally strong-coupling (VSC) limit at finite temperatures and in the presence of a dissipative solvent in both the few and many molecule limits. In the context of two simple models we demonstrate how reactivity

Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taïga

Value functions are a central component of deep reinforcement learning (RL). These functions, parameterized by neural networks, are trained using a mean squared error regression objective to match bootstrapped target values. However, scaling value-based RL methods that use regression to large networks, such as high-capacity Transformers, has proven challengi

Marcel Torne, Anthony Simeonov, Zechu Li, April Chan

Imitation learning methods need significant human supervision to learn policies robust to changes in object poses, physical disturbances, and visual distractors. Reinforcement learning, on the other hand, can explore the environment autonomously to learn robust behaviors but may require impractical amounts of unsafe real-world data collection. To learn perfo

Jonas Christoffer Lindstrøm, Terese Bekkevold, Cathinka Halle Julin, Anna Hayman Robertson

The Secondary Attack Rate (SAR) is a measure of how infectious a communicable disease is, and is often estimated based on studies of disease transmission in households. The Chain Binomial model is a simple model for disease outbreaks, and the final size distribution derived from it can be used to estimate the SAR using simple summary statistics. The final si

Pedro Ramoneda, Minhee Lee, Dasaem Jeong, J. J. Valero-Mas

Automatically estimating the performance difficulty of a music piece represents a key process in music education to create tailored curricula according to the individual needs of the students. Given its relevance, the Music Information Retrieval (MIR) field depicts some proof-of-concept works addressing this task that mainly focuses on high-level music abstr

T. I. Weinberger, Z. Wu, A. J. Hickey, D. E. Graf

The phase landscape of UTe$_2$ features a remarkable diversity of superconducting phases under applied pressure and magnetic field. Recent quantum oscillation studies at ambient pressure have revealed the quasi-2D Fermi surface of this material. However, the pressure-dependence of the Fermi surface remains an open question. Here we track the evolution of the

Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin Vechev

Federated learning is a framework for collaborative machine learning where clients only share gradient updates and not their private data with a server. However, it was recently shown that gradient inversion attacks can reconstruct this data from the shared gradients. In the important honest-but-curious setting, existing attacks enable exact reconstruction o

Bitan Sarkar, Yang Ni

Motivation: Mendelian randomization (MR) infers causal relationships between exposures and outcomes using genetic variants as instrumental variables. Typically, MR considers only a pair of exposure and outcome at a time, limiting its capability of capturing the entire causal network. We overcome this limitation by developing 'MR.RGM' (Mendelian randomization

A Guinness, AA Beaton, JM Franck

When deploying a spectrometer in an adverse environment, such as during a typical ODNP experiment or experiments that require low-volume low-field measurements, a clear and modern protocol for characterizing and quantifying the absolute signal and noise levels proves essential. This paper provides such a protocol. It also highlights the clarity and insight t

Adithya Bhaskar, Dan Friedman, Danqi Chen

Prior work has found that pretrained language models (LMs) fine-tuned with different random seeds can achieve similar in-domain performance but generalize differently on tests of syntactic generalization. In this work, we show that, even within a single model, we can find multiple subnetworks that perform similarly in-domain, but generalize vastly differentl

Helge Frerichs

We develop a general deformation principle for families of Riemannian metrics on smooth manifolds with possibly non-compact boundary, preserving lower scalar curvature bounds. The principle is used in order to strengthen boundary conditions, from mean convex to totally geodesic or doubling. The deformation principle preserves further geometric properties suc

Joscha Prochno

The work of Gantert, Kim, and Ramanan [Large deviations for random projections of $\ell^p$ balls, Ann. Probab. 45 (6B), 2017] has initiated and inspired a new direction of research in the asymptotic theory of geometric functional analysis. The moderate deviations perspective, describing the asymptotic behavior between the scale of a central limit theorem and

Annette Karrer, Babak Miraftab, Stefanie Zbinden

We study connected components of the Morse boundary and their stabilisers. We introduce the notion of point-convergence and show that if the set of non-singleton connected components of the Morse boundary of a finitely generated group $G$ is point-convergent, then every non-singleton connected component is the (relative) Morse boundary of its stabiliser. The

Bartosz Cywiński, Kamil Deja, Tomasz Trzciński, Bartłomiej Twardowski

We introduce GUIDE, a novel continual learning approach that directs diffusion models to rehearse samples at risk of being forgotten. Existing generative strategies combat catastrophic forgetting by randomly sampling rehearsal examples from a generative model. Such an approach contradicts buffer-based approaches where sampling strategy plays an important rol

Mahsa Derakhshan, Emily Ryu, S. Matthew Weinberg, Eric Xue

The competition complexity of an auction setting is the number of additional bidders needed such that the simple mechanism of selling items separately (with additional bidders) achieves greater revenue than the optimal but complex (randomized, prior-dependent, Bayesian-truthful) optimal mechanism without the additional bidders. Our main result settles the co

Roberto Feola, Jessica Elisa Massetti

We consider the infinite dimensional vector of frequencies $\omega(m)=( \sqrt{j^2+m})_{j\in \mathbb{Z}}$, $m\in [1,2]$ arising form a linear Klein-Gordon equation on the one dimensional torus and prove that there exists a positive measure set of masses $m'$s for which $\omega(m)$ satisfies a diophantine condition similar to the one introduced by Bourgain in

Mohamed El Louadi

This paper explores the complex relationship between demographics and artificial intelligence (AI) advances in Europe and Africa, projecting into the year 2050. The advancement of AI technologies has occurred at diverse rates, with Africa lagging behind Europe. Moreover, the imminent economic consequences of demographic shifts require a more careful examinat

Dario Stein, Richard Samuelson

An open stochastic system \`a la Jan Willems is a system affected by two qualitatively different kinds of uncertainty: one is probabilistic fluctuation, and the other one is nondeterminism caused by a fundamental lack of information. We present a formalization of open stochastic systems in the language of category theory. Central to this is the notion of cop

Sasank Mouli

For every $n >0$, we show the existence of a CNF tautology over $O(n^2)$ variables of width $O(\log n)$ such that it has a Polynomial Calculus Resolution refutation over $\{0,1\}$ variables of size $O(n^3polylog(n))$ but any Polynomial Calculus refutation over $\{+1,-1\}$ variables requires size $2^{\Omega(n)}$. This shows that Polynomial Calculus sizes over

Ismail Abouamal

We study different types of von Neumann algebras arising from the Connes-Marcolli $GSp_4$-system and show that a phase transition occurs at the level of these algebras. More precisely, we show that the type of these algebras transitions from type $I_\infty$ to type $III_1$, with this transition occurring precisely at the inverse temperature $\beta = 4$.

Manjunath Malligawad, S. K. Narasimhamurthy, Z. Nekouee, Rajesh Kumar

The current study explores the novel potential of traversable wormhole solutions within the framework of Finsler geometry, incorporating conformal symmetry alongside traceless fluid dynamics. Using the Conformal Killing vector approach, we have discussed the wormholes based on traceless fluid within the intriguing framework of Finsler geometry. The field equ

Stefania Caggioli, Francesco Gentile, Domenico Seminara, Erik Tonni

The holographic bit threads are an insightful tool to investigate the holographic entanglement entropy and other quantities related to the bipartite entanglement in AdS/CFT. We mainly explore the geodesic bit threads in various static backgrounds, for the bipartitions characterized by either a sphere or an infinite strip. In pure AdS and for the sphere, the

Cristian Meo, Ankush Roy, Mircea Lică, Junzhe Yin

This paper presents an innovative approach to extreme precipitation nowcasting by employing Transformer-based generative models, namely NowcastingGPT with Extreme Value Loss (EVL) regularization. Leveraging a comprehensive dataset from the Royal Netherlands Meteorological Institute (KNMI), our study focuses on predicting short-term precipitation with high ac

Tullia Dymarz, Beibei Liu, Nataša Macura, Rose Morris-Wright

In this paper we explore the interplay between aspects of the geometry and algebra of three families of groups of the form B semidirect the integers Z, namely Lamplighter groups, solvable Baumslag-Solitar groups and lattices in SOL. In particular we examine what kind of maps are induced on B by quasi-isometries that coarsely permute cosets of the Z subgroup.

Gabriele Barbieri, Jordan Watts, Francois Ziegler

A recent paper [R22] established "Frobenius reciprocity" as a bijection $t$ between certain symplectically reduced spaces (which need not be manifolds), and conjectured: 1{\deg}) $t$ is a diffeomorphism when these spaces are endowed with their natural subquotient diffeologies, 2{\deg}) $t$ respects the reduced diffeological $2$-forms they may (or might not)

Varda F. Hagh, Sidney R. Nagel

A disordered solid, such as an athermal jammed packing of soft spheres, exists in a rugged potential-energy landscape in which there are a myriad of stable configurations that defy easy enumeration and characterization. Nevertheless, in three-dimensional monodisperse particle packings, we demonstrate an astonishing regularity in the distribution of basin vol

Johannes Kleiner

Computational functionalism posits that consciousness is a computation. Here we show, perhaps surprisingly, that it cannot be a Turing computation. Rather, computational functionalism implies that consciousness is a novel type of computation that has recently been proposed by Geoffrey Hinton, called mortal computation.

Georgiy Baroncha, Alexander Perepukhov, Boris V. Fine

We investigate both experimentally and theoretically the relaxation of pseudo-pure maximally entangled states (Bell states) of two nuclear spins 1H-13C belonging to a molecule in a liquid. The Bell states are obtained by a method based on a detuned Hartmann-Hahn cross-polarization condition. Their entangled character is verified by quantum-state tomography.

Ben Peters, André F. T. Martins

Neural machine translation (MT) models achieve strong results across a variety of settings, but it is widely believed that they are highly sensitive to "noisy" inputs, such as spelling errors, abbreviations, and other formatting issues. In this paper, we revisit this insight in light of recent multilingual MT models and large language models (LLMs) applied t

Nico Baumgart, Markus Lange-Hegermann, Mike Mücke

In industrial manufacturing, deploying deep learning models for visual inspection is mostly hindered by the high and often intractable cost of collecting and annotating large-scale training datasets. While image synthesis from 3D CAD models is a common solution, the individual techniques of domain and rendering randomization to create rich synthetic training

A. Aligayev, M. Landeiro Dos Reis, A. Chartier, Q. Huang

Concentrated solid--solution alloys (CSAs) in single--phase form have recently garnered considerable attention owing to their potential for exceptional irradiation resistance. This computational study delves into the intricate interplay of alloying elements on the generation, recombination, and evolution of irradiation-induced defects. Molecular dynamics sim

Bryan A. Curtis, Leslie Hogben, Adriana Roux

Irredundance has been studied in the context of dominating sets, via the concept of private neighbor. Here irredundance of zero forcing sets is introduced via the concept of a private fort and the upper and lower zero forcing irrdedundance numbers $\mbox{ZIR}(G)$ and $\mbox{zir}(G)$ are defined. Bounds on $\mbox{ZIR}(G)$ and $\mbox{zir}(G)$ are established a

Gabriele Bressanini, Marco G. Genoni, M. S. Kim, Matteo G. A. Paris

We discuss the ultimate precision bounds on the multiparameter estimation of single- and two-mode pure Gaussian states. By leveraging on previous approaches that focused on the estimation of a complex displacement only, we derive the Holevo Cram\'er-Rao bound (HCRB) for both displacement and squeezing parameter characterizing single and two-mode squeezed sta

Christopher R. Glein

Quantifying disequilibria is important to understand whether an environment could be habitable. It has been proposed that the exoplanet K2-18b has a hydrogen-rich atmosphere and a water ocean, making it a "hycean world". The James Webb Space Telescope recently made measurements of methane, CO$_2$, and possibly dimethyl sulfide (DMS) in the atmosphere of this

Celeste Damiani, Shin Satoh

We introduce the notion of wen knots, and prove that the set of wen knots is a proper subset of the set of extended welded knots. Furthermore we prove that the complementary subset consists of welded knots up to horizontal mirror reflections. This allow us to characterise completely extended welded knots by the parity of their number of wens, that we can alw

David Alvarez-Castillo, Piotr Homola, Oleksandr Sushchov, Jarosław Stasielak

This contribution presents the recent research developments within the Cosmic Ray Extremely Distributed Observatory (CREDO) in the search for resolution of various scientific puzzles, ranging from fundamental physical questions to applications like the determination of earthquake precursors. The state-of-the art theoretical, numerical and computational aspec

Xin Yue Ren, Dena Firoozi

In this paper, we address linear-quadratic-Gaussian (LQG) risk-sensitive mean field games (MFGs) with common noise. In this framework agents are exposed to a common noise and aim to minimize an exponential cost functional that reflects their risk sensitivity. We leverage the convex analysis method to derive the optimal strategies of agents in the limit as th

Beth A Cimini

As microscopy diversifies and becomes ever-more complex, the problem of quantification of microscopy images has emerged as a major roadblock for many researchers. All researchers must face certain challenges in turning microscopy images into answers, independent of their scientific question and the images they've generated. Challenges may arise at many stage

Arman Duha, Mario Borunda

We investigate the transport properties of massive Dirac fermions subjected to uncorrelated scalar potential disorder, and mass disorder. Using a finite difference method, the conductance is calculated for a wide variety of combinations of these two disorder strengths. By calculating the scaling of conductivity with system size we find that, depending on the

Luka Baković, David Ohlin, Giacomo Como, Emma Tegling

Motivated by empirical research on bias and opinion formation, we formulate a multidimensional nonlinear opinion-dynamical model where agents have individual biases, which are fixed, as well as opinions, which evolve. The dimensions represent competing options, of which each agent has a relative opinion, and are coupled through normalization of the opinion v

Jean-François Burnol

The harmonic sum of the integers which are missing $p$ given digits in a base $b$ is expressed as $b\log(b)/p$ plus corrections indexed by the excluded digits and expressed as integrals involving the digamma function and a suitable measure. A number of consequences are derived, such as explicit bounds, monotony, series representations and asymptotic expansio

Sukirt Thakur, Ehsan Esmaili, Sarah Libring, Luis Solorio

Resolving the diffusion coefficient is a key element in many biological and engineering systems, including pharmacological drug transport and fluid mechanics analyses. Additionally, these systems often have spatial variation in the diffusion coefficient which must be determined, such as for injectable drug-eluting implants into heterogeneous tissues. Unfortu

Fang Xie, Yuan Fang, Ying Li, Yuefei Huang

Kagome metals offer a unique platform for investigating robust electron-correlation effects because of their lattice geometry, flat bands and multi-orbital nature. In the cases with active flat bands, recent theoretical studies have pointed to a rich phase diagram that contains not only electronic orders but also quantum criticality. Very recently, $\rm CsCr

Quan Ouyang, Nourallah Ghaeminezhad, Yang Li, Torsten Wik

Lithium-ion battery packs demand effective active equalization systems to enhance their usable capacity and lifetime. Despite numerous topologies and control schemes proposed in the literature, conducting quantitative analyses, comprehensive comparisons, and systematic optimization of their performance remains challenging due to the absence of a unified math

Tanja Samardzic, Ximena Gutierrez, Christian Bentz, Steven Moran

Typologically diverse benchmarks are increasingly created to track the progress achieved in multilingual NLP. Linguistic diversity of these data sets is typically measured as the number of languages or language families included in the sample, but such measures do not consider structural properties of the included languages. In this paper, we propose assessi

Thomas Harvey, Christopher J. Conselice, Nathan J. Adams, Duncan Austin

We utilize deep JWST NIRCam observations for the first direct constraints on the Galaxy Stellar Mass Function (GSMF) at $z>10$. Our EPOCHS v1 sample includes 1120 galaxy candidates at $6.5<z<13.5$ taken from a consistent reduction and analysis of publicly available deep JWST NIRCam data covering the PEARLS, CEERS, GLASS, JADES GOOD-S, NGDEEP, and SMACS0723 s

Nila Cibu, Kexin Ding, Steven DiSilvio, Sasha Kononova

Chess graphs encode the moves that a particular chess piece can make on an $m\times n$ chessboard. We study through these graphs through the lens of chip-firing games and graph gonality. We provide upper and lower bounds for the gonality of king's, bishop's, and knight's graphs, as well as for the toroidal versions of these graphs. We also prove that among a

Emily Clark, Chloe Georgiou, Katelyn Poon, Marek Chrobak

In his 2018 paper, Herlihy introduced an atomic protocol for multi-party asset swaps across different blockchains. His model represents an asset swap by a directed graph whose nodes are the participating parties and edges represent asset transfers, and rational behavior of the participants is captured by a preference relation between a protocol's outcomes. A

Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey

The $k$-principal component analysis ($k$-PCA) problem is a fundamental algorithmic primitive that is widely-used in data analysis and dimensionality reduction applications. In statistical settings, the goal of $k$-PCA is to identify a top eigenspace of the covariance matrix of a distribution, which we only have black-box access to via samples. Motivated by

Dominikus Noll

We discuss topological versions of the closed graph theorem, where continuity is inferred from near continuity in tandem with suitable conditions on source or target spaces. We seek internal characterizations of spaces satisfying a closed graph theorem, and we compare closed graph and open mapping spaces.

Nils Baumgartner, Elke Pulvermüller

In this study, we explore advanced strategies for enhancing software quality by detecting and refactoring data clumps, special types of code smells. Our approach transcends the capabilities of integrated development environments, utilizing a novel method that separates the detection of data clumps from the source access. This method facilitates data clump pr

Rafael Chiclana, Mark A. Iwen, Mark Philip Roach

The celebrated Johnson-Lindenstrauss lemma states that for all $\varepsilon \in (0,1)$ and finite sets $X \subseteq \mathbb{R}^N$ with $n>1$ elements, there exists a matrix $\Phi \in \mathbb{R}^{m \times N}$ with $m=\mathcal{O}(\varepsilon^{-2}\log n)$ such that \[ (1 - \varepsilon) \|x-y\|_2 \leq \|\Phi x-\Phi y\|_2 \leq (1+\varepsilon)\| x- y\|_2 \quad \fo

Ellen Powell, Avelio Sepúlveda

We present an elementary proof establishing the equality of the right and left-sided $\sqrt{\kappa}$-quantum lengths for an SLE$_\kappa$ curve, where $\kappa\in (0,4]$. We achieve this by demonstrating that the$\sqrt{\kappa}$-quantum length is equal to the $(\sqrt{\kappa}/2)$-Gaussian multiplicative chaos with reference measure given by half the conformal Mi

Marco Cicalese, Tim Heilmann, Andrea Kubin, Fumihiko Onoue

In this paper we propose a notion of $s$-fractional mass for $1$-currents in $\R^d$. Such a notion generalizes the notion of $s$-fractional perimeters for sets in the plane to higher codimension one-dimensional singularities. Remarkably, the limit as $s\to 1$ of the $s$-fractional mass gives back the classical notion of length for regular enough curves in $\

Chengkai Liu, Jianghao Lin, Jianling Wang, Hanzhou Liu

Sequential recommendation aims to estimate the dynamic user preferences and sequential dependencies among historical user behaviors. Although Transformer-based models have proven to be effective for sequential recommendation, they suffer from the inference inefficiency problem stemming from the quadratic computational complexity of attention operators, espec

Ali Akhtari, Oleg Zikanov, Dmitry Krasnov

Magnetoconvection in a tall vertical box with vertical hot and cold walls, and an imposed steady uniform magnetic field perpendicular to the temperature gradient, is analyzed numerically. The geometry and the values of the non-dimensional parameters - the Prandtl number of 0.025, the Rayleigh number of $7.5 \times 10^5$, and the Hartmann number between 0 and

Nan Lu, Quan Ouyang, Yang Li, Changfu Zou

Accurate electrical load forecasting is of great importance for the efficient operation and control of modern power systems. In this work, a hybrid long short-term memory (LSTM)-based model with online correction is developed for day-ahead electrical load forecasting. Firstly, four types of features are extracted from the original electrical load dataset, in