July 2023 arXiv papers — page 2

Nikhil Mishra, Pieter Abbeel, Xi Chen, Maximilian Sieb

Dense packing in pick-and-place systems is an important feature in many warehouse and logistics applications. Prior work in this space has largely focused on planning algorithms in simulation, but real-world packing performance is often bottlenecked by the difficulty of perceiving 3D object geometry in highly occluded, partially observed scenes. In this work

Jiuhong Xiao, Gao Zhu, Giuseppe Loianno

Visual Geo-localization (VG) is a critical research area for identifying geo-locations from visual inputs, particularly in autonomous navigation for robotics and vehicles. Current VG methods often learn feature extractors from geo-labeled images to create dense, geographically relevant representations. Recent advances in Self-Supervised Learning (SSL) have d

Yuqian Cheng, Daniel M. Kane, Zhicheng Zheng

We develop a new technique for proving distribution testing lower bounds for properties defined by inequalities involving the bin probabilities of the distribution in question. Using this technique we obtain new lower bounds for monotonicity testing over discrete cubes and tight lower bounds for log-concavity testing. Our basic technique involves constructin

Peter L. McMahon

There has been a resurgence of interest in optical computing over the past decade, both in academia and in industry, with much of the excitement centered around special-purpose optical computers for neural-network processing. Optical computing has been a topic of periodic study for over 50 years, including for neural networks three decades ago, and a wide va

Chuye Ji, Yixiang Wang

Pickering emulsions have been widely studied due to their good stability and potential applications. Nanocellulose including cellulose nanocrystals (CNCs), cellulose nanofibrils (CNFs), and bacterial cellulose nanofibrils (BCNFs) has emerged as sustainable stabilizers/emulsifiers in food-related Pickering emulsions due to their favorable properties such as r

Tarmo Nurmi, Mikko Kivelä

To understand the structure of a network, it can be useful to break it down into its constituent pieces. This is the approach taken in a multitude of successful network analysis methods, such as motif analysis. These methods require one to enumerate or sample small connected subgraphs of a network, which can be computationally intractable if naive methods ar

Francesco Bajardi, Salvatore Capozziello, Tiziana Di Salvo, Francesca Spinnato

We sketch the main features of the Noether Symmetry Approach, a method to reduce and solve dynamics of physical systems by selecting Noether symmetries, which correspond to conserved quantities. Specifically, we take into account the vanishing Lie derivative condition for general canonical Lagrangians to select symmetries. Furthermore, we extend the prescrip

Mehwish Alam, Frank van Harmelen, Maribel Acosta

Embedding based Knowledge Graph (KG) Completion has gained much attention over the past few years. Most of the current algorithms consider a KG as a multidirectional labeled graph and lack the ability to capture the semantics underlying the schematic information. In a separate development, a vast amount of information has been captured within the Large Langu

S. L. Cacciatori, P. Ursino

We investigate the notion of concentration locus introduced in \cite{CacUrs22}, in the case of Riemann manifolds sequences and its relationship with the volume of tubes. After providing a general formula for the volume of a tube around a Riemannian submanifold of a Riemannian manifold, we specialize it to the case of totally geodesic submanifolds of compact

Robin Kenis, Emanuel Laude, Panagiotis Patrinos

In this paper we derive a moment relaxation for large-scale nonsmooth optimization problems with graphical structure and spherical constraints. In contrast to classical moment relaxations for global polynomial optimization that suffer from the curse of dimensionality we exploit the partially separable structure of the optimization problem to reduce the dimen

Jamie Lee, Zhaoyuan Su, Yunan Chen

Mobile health apps hold great potential for promoting children's health and wellbeing. However, there is limited understanding of how these technologies are currently designed to support children with their health concerns or wellness goals. To gain insight into the current landscape of mobile apps designed for children's health, we retrieved and reviewed 43

Md Rubel Ahmed, Bardia Nadimi, Hao Zheng

Modeling system-level behaviors of intricate System-on-Chip (SoC) designs is crucial for design analysis, testing, and validation. However, the complexity and volume of SoC traces pose significant challenges in this task. This paper proposes an approach to automatically infer concise and abstract models from SoC communication traces, capturing the system-lev

Khushnaseeb Roshan, Aasim Zafar, Shiekh Burhan Ul Haque

Network Intrusion Detection System (NIDS) is an essential tool in securing cyberspace from a variety of security risks and unknown cyberattacks. A number of solutions have been implemented for Machine Learning (ML), and Deep Learning (DL) based NIDS. However, all these solutions are vulnerable to adversarial attacks, in which the malicious actor tries to eva

Panchamy Krishnakumari, Sascha Hoogendoorn-Lanser, Jeroen Steenbakkers, Serge Hoogendoorn

This paper presents novel technology and methodology aimed at enhancing crowd management in both the planning and operational phases. The approach encompasses innovative data collection techniques, data integration, and visualization using a 3D Digital Twin, along with the incorporation of artificial intelligence (AI) tools for risk identification. The paper

Khushnaseeb Roshan, Aasim Zafar

Anomaly detection and its explanation is important in many research areas such as intrusion detection, fraud detection, unknown attack detection in network traffic and logs. It is challenging to identify the cause or explanation of why one instance is an anomaly? and the other is not due to its unbounded and lack of supervisory nature. The answer to this que

Haipeng An, Boye Su, Hanwen Tai, Lian-Tao Wang

The gravitational wave (GW) signal offers a promising window into the dynamics of the early universe. The recent results from the pulsar timing arrays (PTAs) could be the first glimpse of such new physics. In particular, they could point to new details during inflation, which can not be probed by other means. We explore the possibility that the new results c

Arpit Das, Chethan N. Gowdigere, Sunil Mukhi, Jagannath Santara

Studies of modular linear differential equations (MLDE) for the classification of rational CFT characters have been limited to the case where the coefficient functions (in monic form) have no poles, or poles at special points of moduli space. Here we initiate an exploration of the vast territory of MLDEs with two characters and any number of poles at arbitra

John Etnyre, Nur Saglam

In this note we will determine which contact structures on manifolds obtained by certain surgeries on the right handed trefoil are Stein fillable and which are not. This continues a long line of research and shows that there seems to be few underlying patterns to when a contact structure is Stein fillable or not.

Jonathan M. Lilly, Joel Feske, Baylor Fox-Kemper, Jeffrey Early

The familiar divergence and Kelvin-Stokes theorem are generalized by a tensor-valued identity that relates the volume integral of the gradient of a vector field to the integral over the bounding surface of the outer product of the vector field with the exterior normal. The importance of this long-established yet little-known result is discussed. In flat two-

Seunguk Song, Kwan-Ho Kim, Srikrishna Chakravarthi, Zirun Han

Al$_{0.68}$Sc$_{0.32}$N (AlScN) has gained attention for its outstanding ferroelectric properties, including a high coercive field and high remnant polarization. Although AlScN-based ferroelectric field-effect transistors (FETs) for memory applications have been demonstrated, a device for logic applications with minimal hysteresis has not been reported. This

Andy Nilipour, James R. A. Davenport, Steve Croft, Andrew P. V. Siemion

Spatiotemporal techniques for signal coordination with actively transmitting extraterrestrial civilizations, without the need for prior communication, can constrain technosignature searches to a significantly smaller coordinate space. With the variable star catalog from Gaia Data Release 3, we explore two related signaling strategies: the SETI Ellipsoid, and

Sören Schenke, Fabian Sewerin, Berend van Wachem, Fabian Denner

We investigate the amplitude modulation of acoustic waves in accelerating flows, a problem that is still not fully understood, but essential to many technical applications, ranging from medical imaging to acoustic remote sensing. The proposed modeling framework is based on a convective form of the Kuznetsov equation, which incorporates the background flow fi

Alexandre Baraviera, Pedro Duarte, Longmei Shu, Maria Joana Torres

Isospectral reduction is an important tool for network/matrix analysis as it reduces the dimension of a matrix/network while preserving its eigenvalues and eigenvectors. The main contribution of this manuscript is a proposed algorithmic scheme to approximate the stationary measure of a stochastic matrix based on isospectral reductions. We run numerical exper

John Higgins, Tarun Sabarwal

We study proliferation of an action in binary action network coordination games that are generalized to include global effects. This captures important aspects of proliferation of a particular action or narrative in online social networks, providing a basis to understand their impact on societal outcomes. Our model naturally captures complementarities among

Henrik Beccard, Elke Beyreuther, Benjamin Kirbus, Samuel D. Seddon

For the last decade, conductive domain walls (CDWs) in single crystals of the uniaxial model ferroelectric lithium niobate (LiNbO$_3$, LNO) have shown to reach resistances more than 10 orders of magnitude lower as compared to the surrounding bulk, with charge carriers being firmly confined to sheets of a few nanometers in width. LNO thus currently witnesses

Markus Redeker

Number-conserving cellular automata are discrete dynamical systems that simulate interacting particles like e.g. grains of sand. In an earlier paper, I had already derived a uniform construction for all transition rules of one-dimensional number-conserving automata. Here I describe in greater detail how one can simulate the automata on a computer and how to

Abhijit B. Bendre, Jennifer Schober, Prasun Dhang, Kandaswamy Subramanian

We describe a novel method to compute the components of dynamo tensors from direct magnetohydrodynamic (MHD) simulations. Our method relies upon an extension and generalisation of the standard H\"ogbom CLEAN algorithm widely used in radio astronomy to systematically remove the impact of the strongest beams onto the corresponding image. This generalisation, c

Guilhem Madiot, Marcus Albrechtsen, Clivia M. Sotomayor-Torres, Søren Stobbe

Chip-scale multimode optomechanical systems have unique benefits for sensing, metrology and quantum technologies relative to their single-mode counterparts. Slot-mode optomechanical crystals enable sideband resolution and large optomechanical couplings of a single optical cavity to two microwave-frequency mechanical modes. Still, previous implementations hav

Nicholas Susemiehl, Avi M. Mandell, Geronimo L. Villanueva, Giuliano Liuzzi

Techniques to retrieve the atmospheric properties of exoplanets via direct observation of their reflected light have often been limited in scope due to computational constraints imposed by the forward-model calculations. We have developed a new set of techniques which significantly decreases the time required to perform a retrieval while maintaining accurate

Efstratios Koukoutsis, Kyriakos Hizanidis, Abhay K. Ram, George Vahala

In dispersive media, dissipation appears in the Schr\"odinger representation of classical Maxwell equations as a sparse diagonal operator occupying an $r$-dimensional subspace. A first order Suzuki-Trotter approximation for the evolution operator enables us to isolate the non-unitary operators (associated with dissipation) from the unitary operators (associa

Zhehua Zhou, Jiayang Song, Xuan Xie, Zhan Shu

As a representative cyber-physical system (CPS), robotic manipulator has been widely adopted in various academic research and industrial processes, indicating its potential to act as a universal interface between the cyber and the physical worlds. Recent studies in robotics manipulation have started employing artificial intelligence (AI) approaches as contro

Alexander Clow, Christopher M van Bommel

We consider the eternal distance-2 domination problem, recently proposed by Cox, Meger, and Messinger, on trees. We show that finding a minimum eternal distance-2 dominating set of a tree is linear time in the order of the graph by providing a fast algorithm. Additionally, we characterise when trees have an eternal distance-2 domination number equal to their

Susmita Ghosh, Abhiroop Chatterjee

In recent years, deep neural networks are yielding better performance in image classification tasks. However, the increasing complexity of datasets and the demand for improved performance necessitate the exploration of innovative techniques. The present work proposes a new deep neural network (called as, T-Fusion Net) that augments multiple localizations bas

Alessandro Pinto

Several sources of uncertainty have to be taken into account in the analysis and design of CPS. The set of parameters used in the model of the physical plant of a CPS may be uncertain due, for example, to manufacturing processes that are precise up to some bounded tolerance. Physical quantities are sensed by electronic components that add noise to the sensed

Jay N. Paranjape, Shameema Sikder, Vishal M. Patel, S. Swaroop Vedula

Surgical tool presence detection is an important part of the intra-operative and post-operative analysis of a surgery. State-of-the-art models, which perform this task well on a particular dataset, however, perform poorly when tested on another dataset. This occurs due to a significant domain shift between the datasets resulting from the use of different too

Javier de la Bodega, Eduardo de Lorenzo Poza

In arXiv:1911.08213 it was conjectured that the compactly supported cohomology of the $m$-th restricted contact locus of an isolated hypersurface singularity coincides, up to a shift, with the Floer cohomology of the $m$-th iterate of the monodromy of the Milnor fiber. In this paper we give an affirmative answer to this conjecture in the case of plane curves

Antonio Lerario, Michele Stecconi

We explain how to use the probabilistic method to prove the existence of real polynomial singularities with rich topology, i.e. with total Betti number of the maximal possible order. We show how similar ideas can be used to produce real algebraic projective hypersurfaces with a rich structure of umbilical points.

Ben Kain

Charged Dirac fields minimally coupled to gravity have spherically symmetric wormhole solutions known as Einstein-Dirac-Maxwell (EDM) wormholes. EDM wormholes do not make use of exotic matter and exist in asymptotically flat general relativity. We construct static spherically symmetric EDM wormhole configurations in quantum field theory using semiclassical a

Christian Gorges, Azur Hodžić, Fabien Evrard, Berend van Wachem

A significant computational expense and source of numerical errors in front tracking is the remeshing of the triangulated front, required due to distortion and compaction of the front following the Lagrangian advection of its vertices. Additionally, in classic front tracking, the remeshing of the front mesh is required not only due to the deformation of the

Meredith Stone, Jianwei Lyu, George H. Rieke, Stacey Alberts

We characterize the stellar mass of J2239+0207, a z~6.25 sub-Eddington quasar (M_1450=-24.6), using dedicated JWST/NIRCam medium-band observations of a nearby PSF star to remove the central point source and reveal the underlying galaxy emission. We detect the host galaxy in two bands longward of the Balmer break, obtaining a stellar mass of ~10^10 M_sun, mor

Carl Lian

We consider the problem of enumerating maps $f$ of degree $d$ from a fixed general curve $C$ of genus $g$ to $\mathbb{P}^r$ satisfying incidence conditions of the form $f(p_i)\in X_i$, where $p_i\in C$ are general points and $X_i\subset\mathbb{P}^r$ are general linear spaces. We give a complete answer in the case where the $X_i$ are points, where the counts,

Abhirup Roy Karmakar, A. Taraphder, G. P. Das

The recent discovery of the Weyl semimetal CeAlSi with simultaneous breaking of inversion and time-reversal symmetries has opened up new avenues for research into the interaction between light and topologically protected bands. In this work, we present a comprehensive examination of the shift current and injection current responsible for the circular photoga

Giuseppe Scriva, Nikita Astrakhantsev, Sebastiano Pilati, Guglielmo Mazzola

Quantum enhanced optimization of classical cost functions is a central theme of quantum computing due to its high potential value in science and technology. The variational quantum eigensolver (VQE) and the quantum approximate optimization algorithm (QAOA) are popular variational approaches that are considered the most viable solutions in the noisy-intermedi

Roger Casals, Honghao Gao

We show that each cluster seed in the augmentation variety is inhabited by an embedded exact Lagrangian filling. This resolves the matter of surjectivity of the map from Lagrangian fillings to cluster seeds. The main new technique to produce these Lagrangian fillings is the construction and study of a quiver with potential associated to curve configurations.

Lukas J. Furtak, Ashish K. Meena, Erik Zackrisson, Adi Zitrin

We present JWST/NIRSpec observations of a highly magnified star candidate at a photometric redshift of $z_{\mathrm{phot}}\simeq4.8$, previously detected in JWST/NIRCam imaging of the strong lensing (SL) cluster MACS J0647+7015 ($z=0.591$). The spectroscopic observation allows us to precisely measure the redshift of the host arc at $z_{\mathrm{spec}}=4.758\pm

Alec Martin, Yicheng Guo, Xin Wang, Anton M. Koekemoer

Giant star-forming clumps are a prominent feature of star-forming galaxies (SFGs) and contain important clues on galaxy formation and evolution. However, basic demographics of clumps and their host galaxies remain uncertain. Using the HST/WFC3 F275W images from the Ultraviolet Imaging of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (UVC

Matthew J. Blacker, Sirui Ning

We solve the Wheeler DeWitt equation for the planar Reissner-Nordstr\"om-AdS black hole in a minisuperspace approximation. We construct semiclassical Wheeler DeWitt states from Gaussian wavepackets that are peaked on classical black hole interior solutions. By using the metric component $g_{xx}$ as a clock, these states are evolved through both the exterior

Riccardo Middei, Matteo Perri, Simonetta Puccetti, Ioannis Liodakis

The lower energy peak of the spectral energy distribution of blazars has commonly been ascribed to synchrotron radiation from relativistic particles in the jets. Despite the consensus regarding jet emission processes, the particle acceleration mechanism is still debated. Here, we present the first X-ray polarization observations of PG 1553+113, a high-synchr

A. H. Anupam, Chandramouli Chowdhury, Ashoke Sen

We compute logarithmic correction to five dimensional BPS black hole entropy using finite temperature black hole geometry and find perfect agreement with the microscopic results and macroscopic computations based on zero temperature near horizon geometry. We also reproduce the Bekenstein-Hawking term for zero temperature black hole entropy from the correspon

Michele Maltoni

In this note we describe how to complement the neutrino evolution matrix calculated at a given energy and trajectory with additional information which allows to reliably extrapolate it to nearby energies or trajectories without repeating the full computation. Our method works for arbitrary matter density profiles, can be applied to any propagation model desc

James Munday, P. -E. Tremblay, J. J. Hermes, Brad Barlow

We present the discovery of the eclipsing double white dwarf (WD) binary WDJ 022558.21-692025.38 that has an orbital period of 47.19 min. Following identification with the Transiting Exoplanet Survey Satellite, we obtained time-series ground based spectroscopy and high-speed multi-band ULTRACAM photometry which indicate a primary DA WD of mass 0.40 +- 0.04 M

Stefano De Angelis, Gauthier Durieux

We present a new on-shell method for the matching of ultraviolet models featuring massive states onto their massless effective field theory. We employ a dispersion relation in the space of complex momentum dilations to capture, in a single variable, the relevant analytic structure of scattering amplitudes at any multiplicity. Multi-variate complex analysis a

Diego Guadagnoli, Camille Normand, Silvano Simula, Ludovico Vittorio

$B_s \to \mu^+ \mu^- \gamma$, measured at high $q^2$ as a partially reconstructed decay, can probe the origin of the existing discrepancies in semi-leptonic $b \to s$ and $b \to c$ decays. We perform a complete study of this possibility. We start by reassessing the alleged discrepancies, with a focus on a unified EFT description. Using the SMEFT, we find tha

Vladimir Rosenhaus, Gregory Falkovich

We consider turbulence of waves that interact weakly via four-wave scattering (sea waves, plasma waves, spin waves, and many others). In the first non-vanishing order in the interaction, the occupation number of waves satisfy a closed kinetic equation which has stationary solutions describing turbulent cascades. We show that a straightforward perturbation th

Georgios K. Karananas, Marco Michel, Javier Rubio

The Eisenhart lift allows to formulate the dynamics of a scalar field in a potential as pure geodesic motion in a curved field-space manifold involving an additional fictitious vector field. Making use of the formalism in the context of inflation, we show that the main inflationary observables can be expressed in terms of the geometrical properties of a two-

Giorgio Franceschelli, Mirco Musolesi

Generative Artificial Intelligence (AI) is one of the most exciting developments in Computer Science of the last decade. At the same time, Reinforcement Learning (RL) has emerged as a very successful paradigm for a variety of machine learning tasks. In this survey, we discuss the state of the art, opportunities and open research questions in applying RL to g

Antonio Pich, Arthur Platschorre, Mario Reig

We consider electroweak (EW) gauge boson corrections to the masses of pseudoscalar mesons to next to leading order (NLO) in $\alpha_s$ and $1/N_C$. The pion mass shift induced by the $Z$-boson is shown to be $m_{\pi^\pm}-m_{\pi^0} = -0.00201(12)$ MeV. While being small compared to the electromagnetic mass shift, the prediction lies about a factor of $\sim 4$

Nils Quetschlich, Vincent Koch, Lukas Burgholzer, Robert Wille

Hundreds of satellites equipped with cameras orbit the Earth to capture images from locations for various purposes. Since the field of view of the cameras is usually very narrow, the optics have to be adjusted and rotated between single shots of different locations. This is even further complicated by the fixed speed -- determined by the satellite's altitude

Kyle Lee, Ian Moult, Felix Ringer, Wouter J. Waalewijn

The continued success of the jet substructure program will require widespread use of tracking information to enable increasingly precise measurements of a broader class of observables. The recent reformulation of jet substructure in terms of energy correlators has simplified the incorporation of universal non-perturbative matrix elements, so called "track fu

Jona Ackerschott, Rahool Kumar Barman, Dorival Gonçalves, Theo Heimel

Optimal kinematic observables are often defined in specific frames and then approximated at the reconstruction level. We show how multi-dimensional unfolding methods allow us to reconstruct these observables in their proper rest frame and in a probabilistically faithful way. We illustrate our approach with a measurement of a CP-phase in the top Yukawa coupli

Daniel Junghans

It has been proposed that flux compactifications of supercritical string theories (i.e., with spacetime dimension $D>10$) have dS vacua, with large $D$ acting as a control parameter for corrections to the classical spacetime effective action. In this paper, we provide a detailed analysis of the self-consistency of such models, focussing on $\alpha^\prime$ an

Alessandro Candido, Stefano Forte, Tommaso Giani, Felix Hekhorn

We revisit our argument that shows that parton distribution Functions (PDFs) in the MSbar{ scheme are non-negative in the perturbative region, with the main goals of elucidating its domain of validity and clarifying its theoretical underpinnings. We specifically discuss recent results proving that PDFs can turn negative at sufficiently low scale, we clarify

Theo Glauch, Ali Kheirandish, Tomas Kontrimas, Qinrui Liu

The recent detection of TeV neutrino emission from the nearby active galaxy NGC 1068 by IceCube suggests that AGN could make a sizable contribution to the total high-energy cosmic neutrino flux. The absence of TeV gamma rays from NGC 1068, indicates neutrino production originates in the innermost region of the AGN. Disk-corona models predict a correlation be

Martyna Chruślińska, Ruediger Pakmor, Jorryt Matthee, Tadafumi Matsuno

Our current knowledge of star-forming metallicity relies primarily on gas-phase oxygen abundance measurements. This may not allow one to accurately describe differences in stellar evolution and feedback driven by variations in iron abundance. $\alpha$-elements (such as oxygen) and iron are produced by sources that operate on different timescales and the link

Paul Caucal, Farid Salazar, Björn Schenke, Tomasz Stebel

We compute the back-to-back dijet cross-section in deep inelastic scattering (DIS) at small $x$ to next-to-leading order (NLO) in the Color Glass Condensate effective field theory. Our result can be factorized into a convolution of the Weizs\"{a}cker-Williams gluon transverse momentum dependent distribution function (WW gluon TMD) with a universal soft facto

Vojtěch Witzany, Gabriel Andres Piovano

Rapidly rotating bodies moving in curved space-time experience the so-called spin-curvature force, which becomes important for the motion of compact objects in gravitational-wave inspirals. As a first approximation, this effect is captured in the motion of a spinning test particle. We solve the equations motion of a spinning particle to leading order in spin

James E. Owen, Hilke E. Schlichting

Understanding atmospheric escape in close-in exoplanets is critical to interpreting their evolution. We map out the parameter space over which photoevaporation and core-powered mass loss dominate atmospheric escape. Generally, the transition between the two regimes is determined by the location of the Bondi radius (i.e. the sonic point of core-powered outflo

Miguel P. Bento, Joao P. Silva, Andreas Trautner

The flavor puzzle of the Standard Model quark sector is formulated in a non-perturbative way, using basis invariants that are independent of the choice of quark field basis. To achieve this, we first derive the algebraic ring of 10 CP even (primary) and 1 CP odd (secondary) basis invariants, using the Hilbert series and plethystic logarithm. An orthogonal ba

Cheng-You Lu, Peisen Zhou, Angela Xing, Chandradeep Pokhariya

Advances in neural fields are enabling high-fidelity capture of the shape and appearance of dynamic 3D scenes. However, their capabilities lag behind those offered by conventional representations such as 2D videos because of algorithmic challenges and the lack of large-scale multi-view real-world datasets. We address the dataset limitation with DiVa-360, a r

Jeya Maria Jose Valanarasu, Yucheng Tang, Dong Yang, Ziyue Xu

Harnessing the power of pre-training on large-scale datasets like ImageNet forms a fundamental building block for the progress of representation learning-driven solutions in computer vision. Medical images are inherently different from natural images as they are acquired in the form of many modalities (CT, MR, PET, Ultrasound etc.) and contain granulated inf

Anastasios N. Angelopoulos, Emmanuel J. Candes, Ryan J. Tibshirani

We study the problem of uncertainty quantification for time series prediction, with the goal of providing easy-to-use algorithms with formal guarantees. The algorithms we present build upon ideas from conformal prediction and control theory, are able to prospectively model conformal scores in an online setting, and adapt to the presence of systematic errors

Theron Guo, Ondřej Rokoš, Karen Veroy

In recent years, there has been a growing interest in understanding complex microstructures and their effect on macroscopic properties. In general, it is difficult to derive an effective constitutive law for such microstructures with reasonable accuracy and meaningful parameters. One numerical approach to bridge the scales is computational homogenization, in

Amir Bar, Florian Bordes, Assaf Shocher, Mahmoud Assran

Masked Image Modeling (MIM) is a promising self-supervised learning approach that enables learning from unlabeled images. Despite its recent success, learning good representations through MIM remains challenging because it requires predicting the right semantic content in accurate locations. For example, given an incomplete picture of a dog, we can guess tha

Tharindu Fernando, Ting Cao

We introduce a novel gauge-invariant, quantized interband index in two-dimensional (2D) multiband systems. It provides a bulk topological classification of a submanifold of parameter space (e.g., an electron valley in a Brillouin zone), and therefore overcomes difficulties in characterizing topology of submanifolds. We confirm its topological nature by numer

Sinéad M. Griffin

A recent report of room temperature superconductivity at ambient pressure in Cu-substituted apatite (`LK99') has invigorated interest in the understanding of what materials and mechanisms can allow for high-temperature superconductivity. Here I perform density functional theory calculations on Cu-substituted lead phosphate apatite, identifying correlated iso

Sriram Anbalagan, Deepesh Agarwal, Balasubramaniam Natarajan, Babji Srinivasan

A majority of recent advancements related to the fault diagnosis of electrical motors are based on the assumption that training and testing data are drawn from the same distribution. However, the data distribution can vary across different operating conditions during real-world operating scenarios of electrical motors. Consequently, this assumption limits th

Jessy Lin, Yuqing Du, Olivia Watkins, Danijar Hafner

To interact with humans and act in the world, agents need to understand the range of language that people use and relate it to the visual world. While current agents can learn to execute simple language instructions, we aim to build agents that leverage diverse language -- language like "this button turns on the TV" or "I put the bowls away" -- that conveys

Stephen Kelly, Daniel S. Park, Xingyou Song, Mitchell McIntire

Autonomous robots deployed in the real world will need control policies that rapidly adapt to environmental changes. To this end, we propose AutoRobotics-Zero (ARZ), a method based on AutoML-Zero that discovers zero-shot adaptable policies from scratch. In contrast to neural network adaptation policies, where only model parameters are optimized, ARZ can buil

Jun Yan, Vikas Yadav, Shiyang Li, Lichang Chen

Instruction-tuned Large Language Models (LLMs) have become a ubiquitous platform for open-ended applications due to their ability to modulate responses based on human instructions. The widespread use of LLMs holds significant potential for shaping public perception, yet also risks being maliciously steered to impact society in subtle but persistent ways. In

Sanjay Pant, Debanjan Karan

We perform a holographic study of the high and low temperature behaviours of logarithmic negativity (LN) and entanglement wedge cross section (EWCS) in a large $N$ strongly coupled thermal field theory with critical point having a well defined gravity dual known as 1RC black hole. The critical point is defined via $\xi \to 2$ limit where, $\xi$ is dimensionl

Mohammad Alminawi, Ilaria Brivio, Joe Davighi

For scalar field theories, such as those EFTs describing the Higgs, it is well-known that the 2-derivative Lagrangian is captured by geometry. That is, the set of operators with exactly 2 derivatives can be obtained by pulling back a metric from a field space manifold $M$ to spacetime $\Sigma$. We here generalise this geometric understanding of scalar field

Wonoo Choo, Erkan Kayacan

This paper develops a data-based moving horizon estimation (MHE) method for agile quadrotors. Accurate state estimation of the system is paramount for precise trajectory control for agile quadrotors; however, the high level of aerodynamic forces experienced by the quadrotors during high-speed flights make this task extremely challenging. These complex turbul

Youssef Hakiki, Frederi Viens

Let $X$ be a $d$-dimensional Gaussian process in $[0,1]$, where the component are independent copies of a scalar Gaussian process $X_0$ on $[0,1]$ with a given general variance function $\gamma^2(r)=\operatorname{Var}\left(X_0(r)\right)$ and a canonical metric $\delta(t,s):=(\mathbb{E}\left(X_0(t)-X_0(s)\right)^2)^{1/2}$ which is commensurate with $\gamma(t-

Hsien-Chih Chang, Jonathan Conroy, Hung Le, Lazar Milenkovic

The notion of shortcut partition, introduced recently by Chang, Conroy, Le, Milenkovi\'c, Solomon, and Than [CCLMST23], is a new type of graph partition into low-diameter clusters. Roughly speaking, the shortcut partition guarantees that for every two vertices $u$ and $v$ in the graph, there exists a path between $u$ and $v$ that intersects only a few cluste

Matteo Turisini, Giorgio Amati, Mirko Cestari

A new pre-exascale computer cluster has been designed to foster scientific progress and competitive innovation across European research systems, it is called LEONARDO. This paper describes the general architecture of the system and focuses on the technologies adopted for its GPU-accelerated partition. High density processing elements, fast data movement capa

Javier Mas, David Travieso Mayo

We revisit the case of a real scalar field in global AdS$_4$ subject to a periodic driving. We address the issue of adiabatic preparation and deformation of a time-periodic solution dual to a Floquet condensate. Then we carefully study the case of driving close to the normal mode resonant frequencies. We examine different slow protocols that adiabatically ch

Ehsan Kamalloo, Aref Jafari, Xinyu Zhang, Nandan Thakur

The rise of large language models (LLMs) had a transformative impact on search, ushering in a new era of search engines that are capable of generating search results in natural language text, imbued with citations for supporting sources. Building generative information-seeking models demands openly accessible datasets, which currently remain lacking. In this

Vittorio Vitale, Aniket Rath, Petar Jurcevic, Andreas Elben

We present the experimental measurement, on a quantum processor, of a series of polynomial lower bounds that converge to the quantum Fisher information (QFI), a fundamental quantity for certifying multipartite entanglement that is useful for metrological applications. We combine advanced methods of the randomized measurement toolbox to obtain estimators that

Arijit Ghosh, Chandrima Kayal, Soumi Nandi, S. Venkitesh

Alon and F\"uredi (European J. Combin. 1993) gave a tight bound for the following hyperplane covering problem: find the minimum number of hyperplanes required to cover all points of the n-dimensional hypercube {0,1}^n except the origin. Their proof is among the early instances of the polynomial method, which considers a natural polynomial (a product of linea

John M. Ball

We make some remarks on the linear wave equation concerning the existence and uniqueness of weak solutions, satisfaction of the energy equation, growth properties of solutions, the passage from bounded to unbounded domains, and reconciliation of different representations of solutions.

Mengping Yang, Zhe Wang

Deep generative models, which target reproducing the given data distribution to produce novel samples, have made unprecedented advancements in recent years. Their technical breakthroughs have enabled unparalleled quality in the synthesis of visual content. However, one critical prerequisite for their tremendous success is the availability of a sufficient num

G. M. Shahariar, Tahmid Hasan, Anindya Iqbal, Gias Uddin

We present a novel approach - CLAA - for API aspect detection in API reviews that utilizes transformer models trained with a supervised contrastive loss objective function. We evaluate CLAA using performance and impact analysis. For performance analysis, we utilized a benchmark dataset on developer discussions collected from Stack Overflow and compare the re

Vaibhav Adlakha, Parishad BehnamGhader, Xing Han Lu, Nicholas Meade

Retriever-augmented instruction-following models are attractive alternatives to fine-tuned approaches for information-seeking tasks such as question answering (QA). By simply prepending retrieved documents in its input along with an instruction, these models can be adapted to various information domains and tasks without additional fine-tuning. While the mod

Haijin Ding, Nina H. Amini, Guofeng Zhang, John E. Gough

In this paper, we show that quantum feedback control may be applied to generate desired states for atomic and photonic systems based on a semi-infinite waveguide coupled with multiple two-level atoms. In this set-up, an initially excited atom can emit one photon into the waveguide, which can be reflected by the terminal mirror or other atoms to establish dif

Arnav Hiray, Pratvi Shah, Vishwa Shah, Agam Shah

Over the last decade, the cryptocurrency market has experienced unprecedented growth, emerging as a prominent financial market. As this market rapidly evolves, it necessitates re-evaluating which cryptocurrencies command the market and steer the direction of blockchain technology. We implement a network-based cryptocurrency market analysis to investigate thi

Xing-Zhou Qu, Dai-Wei Qu, Jialin Chen, Congjun Wu

The recently discovered nickelate superconductor La$_3$Ni$_2$O$_7$ has a high transition temperature near 80 K under pressure, which offers additional avenues of unconventional superconductivity. Here with state-of-the-art tensor-network methods, we study a bilayer $t$-$J$-$J_\perp$ model for La$_3$Ni$_2$O$_7$ and find a robust $s$-wave superconductive (SC)

Patrick Lierle, Carl Schmidt, Jeffrey Baumgardner, Luke Moore

The Rapid Imaging Planetary Spectrograph (RIPS) was designed as a long-slit high-resolution spectrograph for the specific application of studying atmospheres of spatially extended solar system bodies. With heritage in terrestrial airglow instruments, RIPS uses an echelle grating and order-sorting filters to obtain optical spectra at resolving powers up to R~

Alessandro Bondi, Enrico Priola

Given a Brownian motion $W$ and a stationary Poisson point process $p$ with values in ${\mathbb R}^d$, we prove a Dynamic Programming Principle (DPP) in a strong formulation for a stochastic control problem involving controlled SDEs of the form \begin{align} \label{ci1} \nonumber dX_{t}=&\,b(t, X_{t}, a_t) dt + \alpha \left(t, X_{t}, a_t \right) dW_t+ \! \!

Maxime Oliva

The advent of quantum computers promises exponential speed ups in the execution of various computational tasks. While their capabilities are hindered by quantum decoherence, they can be exactly simulated on classical hardware at the cost of an exponential scaling in terms of number of qubits. To circumvent this, quantum states can be represented as matrix pr

K. Mouloudakis, J. Kong, A. Sierant, E. Arkin

We perform spin-noise spectroscopy on an unpolarized $^{87}\mathrm{Rb}$ vapor in the spin-exchange-relaxation-free (SERF) regime. We observe noise spectral distributions that deviate strongly from Lorentzian models that accurately describe lower-density regimes. For example, at magnetic fields of $\sim 1 \mathrm{\mu T}$ and $^{87}\mathrm{Rb}$ densities $\gtr