December 2023 arXiv papers — page 91

Xenofon Vasilakos, Shadi Moazzeni, Anderson Bravalheri, Pratchaya Jaisudthi

Leveraging the potential of Virtualised Network Functions (VNFs) requires a clear understanding of the link between resource consumption and performance. The current state of the art tries to do that by utilising Machine Learning (ML) and specifically Supervised Learning (SL) models for given network environments and VNF types assuming single-objective optim

Filipo Sharevski, Jennifer Vander Loop

Older adults habitually encounter misinformation on social media, but there is little knowledge about their experiences with it. In this study, we combined a qualitative survey (n=119) with in-depth interviews (n=21) to investigate how older adults in America conceptualize, discern, and contextualize social media misinformation. As misinformation on social m

Ana Fernández Vilas, Rebeca P. Díaz Redondo, Keeley Crockett, Majdi Owda

There is a general consensus of the good sensing and novelty characteristics of Twitter as an information media for the complex financial market. This paper investigates the permeability of Twittersphere, the total universe of Twitter users and their habits, towards relevant events in the financial market. Analysis shows that a general purpose social media i

Andrew Na, Justin Wan

In this paper, we explore the use of a deep residual U-net with self-attention to solve the the continuous time time-consistent mean variance optimal trade execution problem for multiple agents and assets. Given a finite horizon we formulate the time-consistent mean-variance optimal trade execution problem following the Almgren-Chriss model as a Hamilton-Jac

Sahil Nokhwal, Nirman Kumar

We propose a novel exemplar selection approach based on Principal Component Analysis (PCA) and median sampling, and a neural network training regime in the setting of class-incremental learning. This approach avoids the pitfalls due to outliers in the data and is both simple to implement and use across various incremental machine learning models. It also has

Rahul Gupta

The power-flow sensitivity coefficients (PFSCs) are widely used in the power system for expressing linearized dependencies between the controlled (i.e., the nodal voltages, lines currents) and control variables (e.g., active and reactive power injections, transformer tap positions, etc.). The PFSCs are often computed by knowing the compound admittance matrix

Christopher Wang

The dynamic allocation problem, also known as the `multi-armed bandit' problem, simulates a situation in which an agent is faced with a tradeoff between actions that yield an immediate reward and actions whose benefits can only be perceived in the future. In this paper, we show that the non-Markovian, discrete-time problem can be solved by following a Gittin

I. A. Ado, M. Titov, Rembert A. Duine, Arne Brataas

We diagonalize the 8-band Kane Hamiltonian with a proper inclusion of the interband matrix elements of the scalar and vector potentials. This leads, among other results, to a modification of the conventional expression for the spin-orbit coupling (SOC) strength in narrow-gap semiconductors with the zinc blende symmetry. We find that in GaAs, at low temperatu

Artem Lykov, Maria Dronova, Nikolay Naglov, Mikhail Litvinov

This paper introduces LLM-MARS, first technology that utilizes a Large Language Model based Artificial Intelligence for Multi-Agent Robot Systems. LLM-MARS enables dynamic dialogues between humans and robots, allowing the latter to generate behavior based on operator commands and provide informative answers to questions about their actions. LLM-MARS is built

Lizhe Wan

We consider the two dimensional gravity water waves with nonzero constant vorticity in infinite depth. We show that for $s\geq \frac{3}{4}$, the water waves system is locally well-posed in $\mathcal{H}^{s}$, which is the nonzero constant vorticity counterpart of the breakthrough work of Ai-Ifrim-Tataru in [4]. It is also a $\frac{1}{4}$ improvement in Sobole

N. A. Moroz, L. V. Gerasimov, A. D. Manukhova, D. V. Kupriyanov

We develop a microscopic calculation scheme for the excitation spectrum of a single-electron atom localized near a dielectric nanostructure. The atom originally has an arbitrary degenerate structure of its Zeeman sublevels on its closed optical transition and we follow how the excitation spectrum would be modified by its radiative coupling with a mesoscopica

Giorgio Almirante, Michael Urban

An analysis of the slab phase as it is expected in the innermost layer of neutron-star crusts is performed within the Hartree-Fock-Bogoliubov framework. We take the periodicity of the slabs into account using Bloch boundary conditions, in order to well describe the interplay between the band structure and superfluidity. We introduce a relative flow between t

Adrian Fischer, Robert E. Gaunt, Yvik Swan

We use Stein characterisations to derive new moment-type estimators for the parameters of several truncated multivariate distributions in the i.i.d. case; we also derive the asymptotic properties of these estimators. Our examples include the truncated multivariate normal distribution and truncated products of independent univariate distributions. The estimat

Sreya Pal, Pratap Kumar Pal, Raisa Fabiha, Supriyo Bandyopadhyay

Coupling between spin waves (SWs) and other types of waves in nanostructured magnetic media has garnered increased attention in recent years because of the rich physics and the potential to produce disruptive technologies. Among this family of intriguing phenomena, we recently reported a new one: coupling between SWs and hybridized phonon-plasmon waves, resu

Zhuoping Ruan, Ingo Witt

Hyperbolic problems can at times be solved employing symbolic arguments. This is especially true for the construction of forward (and backward) fundamental solutions. We formulate a corresponding abstract scheme and illustrate its practicality by a number of instructive examples.

Lin Luo, Hongxian Shen, Lunyong Zhang, Yongjiang Huang

Magnetocaloric microwires are very promising for energy-efficient magnetic refrigeration in micro electromechanical systems (MEMS) and nano electromechanical systems (NEMS). Creating microwires that exhibit large magnetocaloric effects around room temperature represents an important but challenging task. Here, we report a tunable giant magnetocaloric effect

Rich Kerswell, Jacob Page

Motivated by the recent numerical results of Khalid et al., Phys. Rev. Lett., 127, 134502 (2021), we consider the large-Weissenberg-number ($W$) asymptotics of the centre mode instability in inertialess viscoelastic channel flow. The instability is of the critical layer type in the distinguished ultra-dilute limit where $W(1-\beta)=O(1)$ as $W \rightarrow \i

James Schmidt

A notion of time is fundamental in the study of dynamical systems. Time arises as a standalone dynamical system and also in solutions or trajectories as a special kind of map between systems. We characterize time by a universal property and use universality to motivate an abstract definition for categories of dynamical systems. We propose this definition as

Luis Felipe Morales Bultron, Reeta Vyas, Surendra Singh

Wait-time distributions for the $n$th photo-detection at a detector illuminated by a stationary light beam are studied. Both unconditional measurements, initiated at an arbitrary instant, and conditional measurements, initiated upon a photo-detection, are considered. Simple analytic expressions are presented for several classical and quantum sources of light

Mehmet Eymen Sumer, Bengu Ozugur Uysal

Bacterial infections are a common problem in daily life that can affect human health. Researchers are looking for valuable materials that can help prevent such infections and environmental pollutants. Thin films are a well-known application for photocatalytic and biological activity. Therefore, thin-film formation is an excellent way to address these problem

Minyoung Hwang, Luca Weihs, Chanwoo Park, Kimin Lee

Customizing robotic behaviors to be aligned with diverse human preferences is an underexplored challenge in the field of embodied AI. In this paper, we present Promptable Behaviors, a novel framework that facilitates efficient personalization of robotic agents to diverse human preferences in complex environments. We use multi-objective reinforcement learning

Rutvik Choudhary, Alan Wang, Zirui Neil Zhao, Adam Morrison

Speculative execution attacks undermine the security of constant-time programming, the standard technique used to prevent microarchitectural side channels in security-sensitive software such as cryptographic code. Constant-time code must therefore also deploy a defense against speculative execution attacks to prevent leakage of secret data stored in memory o

ANNIE Collaboration, M. Ascencio-Sosa, Z. Bagdasarian, J. Beacom

The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is a 26-ton water Cherenkov neutrino detector installed on the Booster Neutrino Beam (BNB) at Fermilab. Its main physics goals are to perform a measurement of the neutron yield from neutrino-nucleus interactions, as well as a measurement of the charged-current cross section of muon neutrinos. An

Joern Ploennigs, Markus Berger, Eva Carnein

The use of generative AI in education is a controversial topic. Current technology offers the potential to create educational content from text, speech, to images based on simple input prompts. This can enhance productivity by summarizing knowledge and improving communication, quickly adjusting to different types of learners. Moreover, generative AI holds th

Vishal S. Ngairangbam, Michael Spannowsky

The Shower Deconstruction methodology is pivotal in distinguishing signal and background jets, leveraging the detailed information from perturbative parton showers. Rooted in the Neyman-Pearson lemma, this method is theoretically designed to differentiate between signal and background processes optimally in high-energy physics experiments. A key challenge, h

Yinrui Liu

Liquid argon technology is widely used by many previous and current neutrino experiments, and it is also promising for future large-scale neutrino experiments. When detecting neutrinos using liquid argon, many hadrons are involved, which can also interact with argon nuclei. In order to gain a better understanding of the detection processes, and to simulate n

Stephen Pasteris, Chris Hicks, Vasilios Mavroudis

In this paper we consider the adversarial contextual bandit problem in metric spaces. The paper "Nearest neighbour with bandit feedback" tackled this problem but when there are many contexts near the decision boundary of the comparator policy it suffers from a high regret. In this paper we eradicate this problem, designing an algorithm in which we can hold o

Mahmoud Abo Khamis, Ahmet Kara, Dan Olteanu, Dan Suciu

We study the dynamic query evaluation problem: Given a full conjunctive query Q and a sequence of updates to the input database, we construct a data structure that supports constant-delay enumeration of the tuples in the query output after each update. We show that a sequence of N insert-only updates to an initially empty database can be executed in total ti

Philip C. Myers, Ian W. Stephens, Simon Coudé

The Davis-Chandrasekhar-Fermi (DCF) method is widely used to evaluate magnetic fields in star-forming regions. Yet it remains unclear how well DCF equations estimate the mean plane-of-the-sky field strength in a map region. To address this question, five DCF equations are applied to an idealized cloud map. Its polarization angles have a normal distribution w

Janni Harju, Chase P. Broedersz

The interplay between bacterial chromosome organization and functions such as transcription and replication can be studied in increasing detail using novel experimental techniques. Interpreting the resulting quantitative data, however, can be theoretically challenging. In this minireview, we discuss how connecting experimental observations to biophysical the

Joseph R. Noonan, Maaz ur Rehman Shah, Luogen Xu, James. K. Freericks

The factorization method of Schrodinger shows us how to determine the energy eigenstates without needing to determine the wavefunctions in position or momentum space. A strategy to convert the energy eigenstates to wavefunctions is well known for the one-dimensional simple harmonic oscillator by employing the Rodrigues formula for the Hermite polynomials in

Zhengyao Lin, Joshua Gancher, Bryan Parno

Coarse-grained reconfigurable arrays (CGRAs) have gained attention in recent years due to their promising power efficiency compared to traditional von Neumann architectures. To program these architectures using ordinary languages such as C, a dataflow compiler must transform the original sequential, imperative program into an equivalent dataflow graph, compo

Chun Shen, Björn Schenke, Wenbin Zhao

This proceeding highlights the effects of pseudorapidity-dependent charged hadron observables $dN^\mathrm{ch}/d\eta$ and $v_2^{\rm ch}(\eta)$ in Au+Au collisions at 200 GeV on constraining the initial-state nuclear stopping for the beam remnants and the effective QGP specific shear viscosity in a recent Bayesian inference analysis using an event-by-event (3+

Ilya Peshkov, Evgeniy Romenski, Michal Pavelka

In continuum thermodynamics, models of two-phase mixtures typically obey the condition of pressure equilibrium across interfaces between the phases. We propose a new non-equilibrium model beyond that condition, allowing for microinertia of the interfaces, surface tension, and different phase pressures. The model is formulated within the framework of Symmetri

Zhaoyang Zhang, Shun Liang, Ismael Septembre, Jiawei Yu

Quasicrystals show long-range order, but lack translational symmetry. So far, theoretical and experimental studies suggest that both Hermitian and non-Hermitian quasicrystals show localized eigenstates. This localization is due to the fractal structure of the spectrum in the Hermitian case and to the transition to diffusive bands via exceptional points in th

Sutanu Kumar Ghosh, Kiavash Satvat, Rigel Gjomemo, V. N. Venkatakrishnan

Modern attacks against enterprises often have multiple targets inside the enterprise network. Due to the large size of these networks and increasingly stealthy attacks, attacker activities spanning multiple hosts are extremely difficult to correlate during a threat-hunting effort. In this paper, we present a method for an efficient cross-host attack correlat

Callum Muir, Mauro Bologna, Paolo Grigolini

This paper is devoted to the study of the interaction between two distinct forms of non-stationary processes, which we will refer to as non-stationarity of first and second kind. The non-stationarity of first kind is caused by criticality-generated events that we call crucial events. Crucial events signal ergodicity breaking emerging from the interaction bet

Jérôme Droniou, Guillaume Enchéry, Isabelle Faille, Ali Haidar

The objective of this article is to address the discretisation of fractured/faulted poromechanical models using 3D polyhedral meshes in order to cope with the geometrical complexity of faulted geological models. A polytopal scheme is proposed for contact-mechanics, based on a mixed formulation combining a fully discrete space and suitable reconstruction oper

J. D. Hernández Velázquez, Z. Nussinov, A. Gama Goicochea

The influence of a magnetic field applied perpendicularly to the plane of a quasi two dimensional, low density classical Coulomb gas, with interparticle potential U of r as 1 over r, is studied using momentum conserving dissipative particle dynamics simulations. The self diffusion and structure of the gas are studied as functions of temperature and strength

Shabaz Sultan, Sapna Devi, Scott N. Mueller, Johannes Textor

The Cellular Potts Model (CPM) is a widely used simulation paradigm for systems of interacting cells that has been used to study scenarios ranging from plant development to morphogenesis, tumour growth and cell migration. Despite their wide use, CPM simulations are considered too computationally intensive for three-dimensional (3D) models at organ scale. CPM

Robert Kasumba, Dom CP Marticorena, Anja Pahor, Geetha Ramani

Cognitive modeling commonly relies on asking participants to complete a battery of varied tests in order to estimate attention, working memory, and other latent variables. In many cases, these tests result in highly variable observation models. A near-ubiquitous approach is to repeat many observations for each test independently, resulting in a distribution

Pavel Zalesskii

We describe free prosoluble subgroups of a free product of profinite groups by strengthening the theorem of Frorian Pop and answering two questions of K. Ersoy and W. Herfort. Relatively projective prosoluble groups are also described.

Ivan Matchenya, Anton Khanas, Roman Podgornyi, Daniil Shirkin

The transition to smart wearable and flexible optoelectronic devices communicating with each other and performing neuromorphic computing at the edge is a big goal in next-generation optoelectronics. These devices should perform their regular tasks supported by energy-efficient in-memory calculations. Here, we study the response of the CsPbBr$_3$ halide-perov

Umar Khalid, Hasan Iqbal, Nazmul Karim, Jing Hua

While neural fields have made significant strides in view synthesis and scene reconstruction, editing them poses a formidable challenge due to their implicit encoding of geometry and texture information from multi-view inputs. In this paper, we introduce \textsc{LatentEditor}, an innovative framework designed to empower users with the ability to perform prec

Sasha Vtyurina, Adam Roegiest

For many legal operations teams, the management of the contracts and agreements that their organization are negotiating or have been executed is an encompassing and time-consuming task. This has resulted in specialized tools for Contract Lifecycle Management (CLM) have grown steadily in demand over the last decade. Transitioning to such tools can itself be a

G. Queirolo, S. Seitz, A. Riffeser, M. Kluge

The goal of this work is to obtain a Hubble constant estimate through the study of the quadruply lensed, variable QSO SDSSJ1433+6007. To achieve this we combine multi-filter, archival $\textit{HST}$ data for lens modelling and a dedicated time delay monitoring campaign with the 2.1m Fraunhofer telescope at the $\textit{Wendelstein Observatory}$. The lens mod

Alessandro Betti, Michele Casoni, Marco Gori, Simone Marullo

Optimal control deals with optimization problems in which variables steer a dynamical system, and its outcome contributes to the objective function. Two classical approaches to solving these problems are Dynamic Programming and the Pontryagin Maximum Principle. In both approaches, Hamiltonian equations offer an interpretation of optimality through auxiliary

Abel Castorena, George H. Hitching, Erick Luna

The notion of linear stability of a variety in projective space was introduced by Mumford in the context of GIT. It has subsequently been applied by Mistretta and others to Butler's conjecture on stability of the dual span bundle (DSB) $M_{V, E}$ of a general generated coherent system $( E, V )$. We survey recent progress in this direction on rank one cohere

Denis Karateev, Zohar Komargodski, João Penedones, Biswajit Sahoo

We consider 3+1 dimensional Quantum Field Theories (QFTs) coupled to the dilaton and the graviton. We show that the graviton-dilaton scattering amplitude receives a universal contribution which is helicity flipping and is proportional to $\Delta c-\Delta a$ along any RG flow, where $\Delta c$ and $\Delta a$ are the differences of the UV and IR $c$- and $a$-t

Felix J. Meigel, Steffen Rulands

Biological systems often consist of a small number of constituents and are therefore inherently noisy. To function effectively, these systems must employ mechanisms to constrain the accumulation of noise. Such mechanisms have been extensively studied and comprise the constraint by external forces, nonlinear interactions, or the resetting of the system to a p

Roberto Bonezzi, Christoph Chiaffrino, Felipe Diaz-Jaramillo, Olaf Hohm

We formalize the computation of tree-level scattering amplitudes in terms of the homotopy transfer of homotopy algebras, illustrating it with scalar $\phi^3$ and Yang-Mills theory. The data of a (gauge) field theory with an action is encoded in a cyclic homotopy Lie or $L_{\infty}$ algebra defined on a chain complex including a space of fields. This $L_{\inf

Boshi Tang, Jianan Wang, Zhiyong Wu, Lei Zhang

Although Score Distillation Sampling (SDS) has exhibited remarkable performance in conditional 3D content generation, a comprehensive understanding of its formulation is still lacking, hindering the development of 3D generation. In this work, we decompose SDS as a combination of three functional components, namely mode-seeking, mode-disengaging and variance-

Lysimachos Maltoudoglou, Andreas Paisios, Ladislav Lenc, Jiří Martínek

We extend our previous work on Inductive Conformal Prediction (ICP) for multi-label text classification and present a novel approach for addressing the computational inefficiency of the Label Powerset (LP) ICP, arrising when dealing with a high number of unique labels. We present experimental results using the original and the proposed efficient LP-ICP on tw

Seyed Amir Hossein Aqajari, Sina Labbaf, Phuc Hoang Tran, Brenda Nguyen

Daily monitoring of stress is a critical component of maintaining optimal physical and mental health. Physiological signals and contextual information have recently emerged as promising indicators for detecting instances of heightened stress. Nonetheless, developing a real-time monitoring system that utilizes both physiological and contextual data to anticip

A. Galaviz, J. A. Christen, A. Capella

The paper addresses Bayesian inferences in inverse problems with uncertainty quantification involving a computationally expensive forward map associated with solving a partial differential equations. To mitigate the computational cost, the paper proposes a new surrogate model informed by the physics of the problem, specifically when the forward map involves

Julia Di

This paper presents a trade study analysis to design and evaluate the perception system architecture for ReachBot. ReachBot is a novel robotic concept that uses grippers at the end of deployable booms for navigation of rough terrain such as walls of caves and lava tubes. Previous studies on ReachBot have discussed the overall robot design, placement and numb

Ashay Burungale, Francesc Castella, Giada Grossi, Christopher Skinner

Let $E/\mathbb{Q}$ be an elliptic curve and $p$ an odd prime. In 1991 Kolyvagin conjectured that the system of cohomology classes for torsion quotients of the $p$-adic Tate module of $E$ derived from Heegner points over ring class fields of a suitable imaginary quadratic field $K$ (i.e., the Heegner point Kolyvagin system of $E/K$) is non-trivial. In this pa

Jie Ren, Yao Zhao, Tu Vu, Peter J. Liu

Safe deployment of large language models (LLMs) may benefit from a reliable method for assessing their generated content to determine when to abstain or to selectively generate. While likelihood-based metrics such as perplexity are widely employed, recent research has demonstrated the limitations of using sequence-level probability estimates given by LLMs as

Mohammad Samragh, Mehrdad Farajtabar, Sachin Mehta, Raviteja Vemulapalli

Training large transformer models from scratch for a target task requires lots of data and is computationally demanding. The usual practice of transfer learning overcomes this challenge by initializing the model with weights of a pretrained model of the same size and specification to increase the convergence and training speed. However, what if no pretrained

Jonathan J. Carter, Pascal Birckigt, Oliver Gerberding, Sina M. Koehlenbeck

Recent advances in glass fabrication technology have allowed for the development of high-precision inertial sensors in devices weighing in the order of grams. Gram-scale inertial sensors can be used in many applications with tight space or weight requirements. A key element of these devices' performance is the behaviour of a mechanical resonator. We present

Agustín Rodríguez-Medrano, Volker Springel, Federico Stasyszyn, Dante Paz

The properties of galaxies in low-density regions of the universe suggest an interplay between galaxy formation and environment. However, the specific reason why this particular large-scale environment influences the evolution of galaxies remains unclear. This paper examines the properties and evolutionary paths of galaxies within cosmic voids using the Illu

Sophia Gad-Nasr, Kimberly K. Boddy, Manoj Kaplinghat, Nadav Joseph Outmezguine

We study the evolution of isolated self-interacting dark matter (SIDM) halos that undergo gravothermal collapse and are driven deep into the short-mean-free-path regime. We assume spherical Navarro-Frenk-White (NFW) halos as initial conditions and allow for elastic dark matter self-interactions. We discuss the structure of the halo core deep in the core-coll

Cedric Westphal, Jungha Hong, Shin-Gak Kang, Leonardo Chiariglione

New applications are being supported by current and future networks. In particular, it is expected that Metaverse applications will be deployed in the near future, as 5G and 6G network provide sufficient bandwidth and sufficiently low latency to provide a satisfying end-user experience. However, networks still need to evolve to better support this type of ap

Hunter Brooks, J. Davy Kirkpatrick, Dan Caselden, Adam C. Schneider

We introduce the Wide-field Retrieval of Astrodata Program (WRAP), a tool created to aid astronomers in gathering photometric and astrometric data for point sources that may confuse simple cross-matching algorithms because of their faintness or motion. WRAP allows astronomers to correctly cross-identify objects with proper motion across multiple surveys by w

Rong Zhao, Lindsey Bignell, David E. Jaffe, Richard Rosero

This study reports the performance and light yield of 1% concentration water-based liquid scintillator (WbLS) deployed in a 1000-liter detector. A light yield of 99$\pm$15 photons per MeV is determined by comparing data with simulation. This result aligns with our previous light yield determination using smaller detectors, thus establishing a solid foundatio

Jack Y. Araz, Michael Spannowsky, Matthew Wingate

This study investigates the thermal properties of the repulsive Fermi-Hubbard model with chemical potential using variational quantum algorithms, crucial in comprehending particle behaviour within lattices at high temperatures in condensed matter systems. Conventional computational methods encounter challenges, especially in managing chemical potential, prom

Matilda Delgado

The bubble of nothing is a solution to Einstein's equations where a circle shrinks and pinches off smoothly. As such, it is one of the simplest examples of a dynamical cobordism to nothing. We take a first step in studying how this solution transforms under T-duality in bosonic string theory. Applying Buscher's rules reveals that the dual solution features a

Florian Ernst, Luigi Favaro, Claudius Krause, Tilman Plehn

Whenever invertible generative networks are needed for LHC physics, normalizing flows show excellent performance. In this work, we investigate their performance for fast calorimeter shower simulations with increasing phase space dimension. We use fast and expressive coupling spline transformations applied to the CaloChallenge datasets. In addition to the bas

Erik Zackrisson, Adam Hultquist, Aron Kordt, José M. Diego

Gravitational lensing may render individual high-mass stars detectable out to cosmological distances, and several extremely magnified stars have in recent years been detected out to redshifts $z\approx 6$. Here, we present Muspelheim, a model for the evolving spectral energy distributions of both metal-enriched and metal-free stars at high redshifts. Using t

Olof Ohlsson Sax, Dmitrii Riabchenko, Bogdan Stefański

String theory on AdS${}_3\times$ S${}^3\times$ T${}^4$ geometries supported by a combination of NS-NS and R-R charges is believed to be integrable. We elucidate the kinematics and analytic structure of worldsheet excitations in mixed charge and pure NS-NS backgrounds, when expressed in momentum, Zhukovsky variables and the rapidity $u$ which appears in the q

Peter L. Taylor, Matthew Craigie, Yuan-Sen Ting

Recent measurements of the $4$-point correlation functions (4PCF) from spectroscopic surveys provide evidence for parity-violations in the large-scale structure of the Universe. If physical in origin, this could point to exotic physics during the epoch of inflation. However, searching for parity-violations in the 4PCF signal relies on a large suite of simula

Yueqing Chang, Jinjing Yi, Ang-Kun Wu, Fabian B. Kugler

In single sheets of graphene, vacancy-induced states have been shown to host an effective spin-1/2 hole that can be Kondo-screened at low temperatures. Here, we show how these vacancy-induced impurity states survive in twisted bilayer graphene (TBG), which thus provides a tunable system to probe the critical destruction of the Kondo effect in pseudogap hosts

Dorian W. P. Amaral, Enrico D. Schiappacasse

Primordial black holes (PBHs) as an all-dark matter (DM) hypothesis has recently been demotivated by the prediction that these objects would source an excessive rate of fast radio bursts (FRBs). However, these predictions were based on several simplifying assumptions to which this rate is highly sensitive. In this article, we improve previous estimates of th

H Perry Hatchfield, Cara Battersby, Ashley T. Barnes, Natalie Butterfield

In this work, we constrain the star-forming properties of all possible sites of incipient high-mass star formation in the Milky Way's Galactic Center. We identify dense structures using the CMZoom 1.3mm dust continuum catalog of objects with typical radii of $\sim$0.1pc, and measure their association with tracers of high-mass star formation. We incorporate c

Johan Henriksson, Petr Kravchuk, Brett Oertel

The number of local operators in a CFT below a given twist grows with spin. Consistency with analyticity in spin then requires that at low spin, infinitely many Regge trajectories must decouple from local correlation functions, implying infinitely many vanishing conditions for OPE coefficients. In this paper we explain the mechanism behind this infinity of z

Maximilian Dichtl, Jacopo Nava, Silvia Pascoli, Filippo Sala

We propose a framework of baryogenesis and leptogenesis that relies on a supercooled confining phase transition (PT) in the early universe. The baryon or lepton asymmetry is sourced by decays of hadrons of the strong dynamics after the PT, and it is enhanced compared to the non-confining case, which was the only one explored so far. This widens the energy ra

Géraldine Servant, Peera Simakachorn

We investigate gravitational-wave backgrounds (GWBs) of primordial origin that would manifest only at ultra-high frequencies, from kilohertz to 100 gigahertz, and leave no signal at either LIGO, Einstein Telescope, Cosmic Explorer, LISA, or pulsar-timing arrays. We focus on GWBs produced by cosmic strings and make predictions for the GW spectra scanning over

Martin Esmann, Stephen C. Wein, Carlos Antón-Solanas

In this review, we describe the current landscape of emergent quantum materials for quantum photonic applications. We focus on three specific solid-state platforms: single emitters in monolayers of transition metal dichalcogenides, defects in hexagonal boron nitride, and colloidal quantum dots in perovskites. These platforms share a unique technological acce

Märta A. Tschudin, David A. Broadway, Patrick Reiser, Carolin Schrader

Since their first observation in 2017, atomically thin van der Waals (vdW) magnets have attracted significant fundamental, and application-driven attention. However, their low ordering temperatures, $T_c$, sensitivity to atmospheric conditions and difficulties in preparing clean large-area samples still present major limitations to further progress. The rema

Albert Aloy, Thomas D. Galley, Caroline L. Jones, Stefan L. Ludescher

How can detector click probabilities respond to spatial rotations around a fixed axis, in any possible physical theory? Here, we give a thorough mathematical analysis of this question in terms of "rotation boxes", which are analogous to the well-known notion of non-local boxes. We prove that quantum theory admits the most general rotational correlations for

Christian Copetti, Lorenzo Di Pietro, Ziming Ji, Shota Komatsu

Anti-de-Sitter space acts as an infra-red cut off for asymptotically free theories, allowing interpolation between a weakly-coupled small-sized regime and a strongly-coupled flat-space regime. We scrutinize the interpolation for theories in two dimensions from the perspective of boundary conformal theories. We show that the appearance of a singlet marginal o

Paul Bennet, Ekta Patel, Sangmo Tony Sohn, Andres del Pino

We have determined the proper motions (PMs) of 12 dwarf galaxies in the Local Group (LG), ranging from the outer Milky Way (MW) halo to the edge of the LG. We used HST as the first and Gaia as the second epoch using the GaiaHub software. For Leo A and Sag DIG we also used multi-epoch HST measurements relative to background galaxies. Orbital histories derived

Manuel R. Izquierdo, J. Fernando Abalos, Carlos Palenzuela

We present the new Guided Moments ($\texttt{GM}$) formalism for neutrino modeling in astrophysical scenarios like core-collapse supernovae and neutron star mergers. The truncated moments approximation ($\texttt{M1}$) and Monte-Carlo ($\texttt{MC}$) schemes have been proven to be robust and accurate in solving the Boltzmann's equation for neutrino transport.

Harun Acaroğlu, Monika Blanke, Jan Heisig, Michael Krämer

We study a simplified Dark Matter model in the Dark Minimal Flavour Violation framework. Our model complements the Standard Model with a flavoured Dark Matter Majorana triplet and a coloured scalar mediator that share a Yukawa coupling with the right-handed up-type quarks with the coupling matrix $\lambda$. We extend previous work on this topic by exploring

Linda M. Carpenter, Katherine Schwind, Taylor Murphy

The diverse and distinct collider phenomenology of color-sextet scalars motivates thorough investigation of their effective couplings to the Standard Model at the LHC. Some of the more unique sextet signals involve not only jets but also leptons. In previous work, we proposed an LHC search for color-sextet scalars in a channel with jets and a hard opposite-s

Enis Simsar, Alessio Tonioni, Yongqin Xian, Thomas Hofmann

Diffusion models (DMs) have gained prominence due to their ability to generate high-quality varied images with recent advancements in text-to-image generation. The research focus is now shifting towards the controllability of DMs. A significant challenge within this domain is localized editing, where specific areas of an image are modified without affecting

Mu-Chun Chen, Stephen F. King, Omar Medina, José W. F. Valle

The so-called Golden Mass Relation provides a testable correlation between charged-lepton and down-type quark masses, that arises in certain flavor models that do not rely on Grand Unification. Such models typically involve broken family symmetries. In this work, we demonstrate that realistic fermion mass relations can emerge naturally in modular invariant m

Luca Bartolomei, Matteo Poggi, Andrea Conti, Fabio Tosi

This paper proposes a new framework for depth completion robust against domain-shifting issues. It exploits the generalization capability of modern stereo networks to face depth completion, by processing fictitious stereo pairs obtained through a virtual pattern projection paradigm. Any stereo network or traditional stereo matcher can be seamlessly plugged i

Tizian Blatz, Joyce Kwan, Julian Léonard, Annabelle Bohrdt

New generations of ultracold-atom experiments are continually raising the demand for efficient solutions to optimal control problems. Here, we apply Bayesian optimization to improve a state-preparation protocol recently implemented in an ultracold-atom system to realize a two-particle fractional quantum Hall state. Compared to manual ramp design, we demonstr

Hongsuk Choi, Isaac Kasahara, Selim Engin, Moritz Graule

Recently introduced ControlNet has the ability to steer the text-driven image generation process with geometric input such as human 2D pose, or edge features. While ControlNet provides control over the geometric form of the instances in the generated image, it lacks the capability to dictate the visual appearance of each instance. We present FineControlNet t

Jinguo Zhu, Xiaohan Ding, Yixiao Ge, Yuying Ge

In this work, we introduce Vision-Language Generative Pre-trained Transformer (VL-GPT), a transformer model proficient at concurrently perceiving and generating visual and linguistic data. VL-GPT achieves a unified pre-training approach for both image and text modalities by employing a straightforward auto-regressive objective, thereby enabling the model to

Thomas W. Mitchel, Carlos Esteves, Ameesh Makadia

We introduce a framework for intrinsic latent diffusion models operating directly on the surfaces of 3D shapes, with the goal of synthesizing high-quality textures. Our approach is underpinned by two contributions: field latents, a latent representation encoding textures as discrete vector fields on the mesh vertices, and field latent diffusion models, which

Ruoxi Shi, Xinyue Wei, Cheng Wang, Hao Su

We present ZeroRF, a novel per-scene optimization method addressing the challenge of sparse view 360{\deg} reconstruction in neural field representations. Current breakthroughs like Neural Radiance Fields (NeRF) have demonstrated high-fidelity image synthesis but struggle with sparse input views. Existing methods, such as Generalizable NeRFs and per-scene op

Martin Gazo, Andrey Karailiev, Tanish Satoor, Christoph Eigen

Coarsening of an isolated far-from-equilibrium quantum system is a paradigmatic many-body phenomenon, relevant from subnuclear to cosmological lengthscales, and predicted to feature universal dynamic scaling. Here, we observe universal scaling in the coarsening of a homogeneous two-dimensional Bose gas, with exponents that match analytical predictions. For d

Ankita Chakrabarti, Nicolas Laflorencie, Bertrand Georgeot, Cyril Martins

Interacting fermions in the presence of disorder pose one of the most challenging problems in condensed matter physics, primarily due to the absence of accurate numerical tools. Our investigation delves into the intricate interplay between interaction-induced Mott insulation and disorder-driven Anderson localization in the Hubbard model subjected to a random

Minghao Chen, Junyu Xie, Iro Laina, Andrea Vedaldi

We propose a novel feed-forward 3D editing framework called Shap-Editor. Prior research on editing 3D objects primarily concentrated on editing individual objects by leveraging off-the-shelf 2D image editing networks. This is achieved via a process called distillation, which transfers knowledge from the 2D network to 3D assets. Distillation necessitates at l

Erfei Cui, Wenhai Wang, Zhiqi Li, Jiangwei Xie

Large language models (LLMs) have opened up new possibilities for intelligent agents, endowing them with human-like thinking and cognitive abilities. In this work, we delve into the potential of large language models (LLMs) in autonomous driving (AD). We introduce DriveMLM, an LLM-based AD framework that can perform close-loop autonomous driving in realistic

Jacob Eisenstein, Chirag Nagpal, Alekh Agarwal, Ahmad Beirami

Reward models play a key role in aligning language model applications towards human preferences. However, this setup creates an incentive for the language model to exploit errors in the reward model to achieve high estimated reward, a phenomenon often termed \emph{reward hacking}. A natural mitigation is to train an ensemble of reward models, aggregating ove

Chubin Zhang, Juncheng Yan, Yi Wei, Jiaxin Li

Occupancy prediction reconstructs 3D structures of surrounding environments. It provides detailed information for autonomous driving planning and navigation. However, most existing methods heavily rely on the LiDAR point clouds to generate occupancy ground truth, which is not available in the vision-based system. In this paper, we propose an OccNeRF method f

Hao Ouyang, Kathryn Heal, Stephen Lombardi, Tiancheng Sun

We introduce Text2Immersion, an elegant method for producing high-quality 3D immersive scenes from text prompts. Our proposed pipeline initiates by progressively generating a Gaussian cloud using pre-trained 2D diffusion and depth estimation models. This is followed by a refining stage on the Gaussian cloud, interpolating and refining it to enhance the detai