April 2023 arXiv papers — page 70

Vivian Liu, Tao Long, Nathan Raw, Lydia Chilton

Visuals can enhance our experience of music, owing to the way they can amplify the emotions and messages conveyed within it. However, creating music visualization is a complex, time-consuming, and resource-intensive process. We introduce Generative Disco, a generative AI system that helps generate music visualizations with large language models and text-to-v

Leila Khatami

In this paper, we survey the progress in the problem of finding the maximum commuting nilpotent orbit that intersects the centralizer of a given nilpotent matrix.

Shane Koscielniak

Iterative Learning Control (ILC) is a technique for adaptive feed-forward control of electro-mechanical plant that either performs programmed periodic behavior or rejects quasi-periodic disturbances. For example, ILC can suppress particle-beam RF-loading transients in RF cavities for acceleration. This paper, for the first time, explains the structural cause

Pavel Sekatski

It is well known that when two or more quantum measurements suffer from imperfections they may lose their incompatibility. For a quantum system of finite dimension d we study the incompatibility of all projective measurements subjected to white noise and loss. We derive a necessary and sufficient conditions for this set of measurements to becomes compatible

Patrik Lundström, Johan Öinert, Laura Orozco, Héctor Pinedo

We investigate properties of group gradings on matrix rings $M_n(R)$, where $R$ is an associative unital ring and $n$ is a positive integer. More precisely, we introduce very good gradings and show that any very good grading on $M_n(R)$ is necessarily epsilon-strong. We also identify a condition that is sufficient to guarantee that $M_n(R)$ is an epsilon-cro

M. R. Mumpower, M. Li, T. M. Sprouse, B. S. Meyer

We present global predictions of the ground state mass of atomic nuclei based on a novel Machine Learning (ML) algorithm. We combine precision nuclear experimental measurements together with theoretical predictions of unmeasured nuclei. This hybrid data set is used to train a probabilistic neural network. In addition to training on this data, a physics-based

Gregory Krueper, Lior Cohen, Juliet T. Gopinath

We present an innovative, platform-independent concept for multiparameter sensing where the measurable parameters are in series, or cascaded, enabling measurements as a function of position. With temporally resolved detection, we show that squeezing can give a quantum enhancement in sensitivity over that of classical states by a factor of $e^{2r}$, where $r

Rui Sakano, Tokuro Hata, Kaiji Motoyama, Yoshimichi Teratani

We theoretically and experimentally study the universal scaling property of the spin-1/2 Kondo state in the magnetic field dependence of bias-voltage linear conductance through a quantum dot at low temperatures. We discuss an efficient and reliable procedure to evaluate the Kondo temperature defined at the ground state from experimental or numerical data set

J. W. Clark, E. Krotscheck

We examine in detail two alternative descriptions of a system of $\alpha$ particles interacting via local interactions of different character, highlighting the fact that a faithful microscopic description of such systems demands a consistent treatment of both short- and long-range correlations. In preparation, we examine four different versions of modern mic

Garv Chauhan, Thomas Steingasser

Right-handed neutrinos (RHN) destabilize the electroweak vacuum by increasing its decay rate. In the SM, the latter is dominated by physics at the RG scale at which $\lambda$ reaches its minimum, $\mu_*^{\text{SM}} \sim 10^{17}$ GeV. For large neutrino Yukawa coupling $Y_\nu$, RHNs can push $\mu_*$ beyond the Planck scale, implying that gravitational effects

Subhajit Ray, Xinghua Sun, Nolan Tremelling, Maria Gordiyenko

Analog feature extraction is a power-efficient and re-emerging signal processing paradigm for implementing the front-end feature extractor in on device keyword-spotting systems. Despite its power efficiency and re-emergence, there is little consensus on what values the architectural parameters of its critical block, the analog filterbank, should be set to, e

Joshua G. Fenwick, Rainer Dick

Imposing the Born rule as a fundamental principle of quantum mechanics would require the existence of normalizable wave functions also for relativistic particles. Indeed, the Fourier transforms of normalized k-space amplitudes yield normalized x-space wave packets which reproduce the standard k-space expectation values for energy and momentum from local mome

Benjamin A. Christie, Dylan P. Losey

Robots can use auditory, visual, or haptic interfaces to convey information to human users. The way these interfaces select signals is typically pre-defined by the designer: for instance, a haptic wristband might vibrate when the robot is moving and squeeze when the robot stops. But different people interpret the same signals in different ways, so that what

Sergey V. Ulyanov, Viktor S. Ulyanov

The simplest technique for simulating a quantum algorithm - QA described based on the direct matrix representation of the quantum operators. Using this approach, it is relatively simple to simulate the operation of a QA and to perform fidelity analysis. A more efficient fast QA simulation technique is based on computing all or part of the operator matrices o

Ersin Daş, Skylar X. Wei, Joel W. Burdick

This paper proposes a safety controller for control-affine nonlinear systems with unmodelled dynamics and disturbances to improve closed-loop robustness. Uncertainty estimation-based control barrier functions (CBFs) are utilized to ensure robust safety in the presence of model uncertainties, which may depend on control input and states. We present a new unce

Lingling Wu, Jingjing Zhang

Recent advancements in space technology have equipped low Earth Orbit (LEO) satellites with the capability to perform complex functions and run AI applications. Federated Learning (FL) on LEO satellites enables collaborative training of a global ML model without the need for sharing large datasets. However, intermittent connectivity between satellites and gr

Anna Radovskaya, Andrew G. Semenov

In the paper by Jo\~ao F. Melo "The propagator matrix reloaded" (SciPost Phys. Core 6, 019 (2023), arXiv:2112.09119) the author provides a derivation of a formalism which includes interactions in the initial conditions for non-equilibrium quantum field theory. The main statement of this paper is that one cannot ignore interactions in the initial conditions,

Dhruvesh Patel, Hamid Eghbalzadeh, Nitin Kamra, Michael Louis Iuzzolino

In our pursuit of advancing multi-modal AI assistants capable of guiding users to achieve complex multi-step goals, we propose the task of "Visual Planning for Assistance (VPA)". Given a succinct natural language goal, e.g., "make a shelf", and a video of the user's progress so far, the aim of VPA is to devise a plan, i.e., a sequence of actions such as "san

Zhixin Chen, Iain M. Grace, Steffen L. Woltering, Lina Chen

An unresolved challenge facing electronics at a few-nm scale is that resistive channels start leaking due to quantum tunneling. This affects the performance of nanoscale transistors, with single-molecule devices displaying particularly low switching ratios and operating frequencies, combined with large subthreshold swings.1 The usual strategy to mitigate qua

Veronica Guerrini, Felipe A. Louza, Giovanna Rosone

A standard format used for storing the output of high-throughput sequencing experiments is the FASTQ format. It comprises three main components: (i) headers, (ii) bases (nucleotide sequences), and (iii) quality scores. FASTQ files are widely used for variant calling, where sequencing data are mapped into a reference genome to discover variants that may be us

C. Döring, S. Vogl

Recently, the IceCube collaboration observed a neutrino excess in the direction of NGC 1068 with high statistical significance. This constitutes the second detection of an astrophysical neutrino point source after the discovery of a variable emission originating from the blazar TXS~0506+056. Neutrinos emitted by these sources traverse huge, well-determined d

Evgeniy Klyuchikov, Elena Mikhailova, George Chernishev

In column-oriented query processing, a materialization strategy determines when lightweight positions (row IDs) are translated into tuples. It is an important part of column-store architecture, since it defines the class of supported query plans, and, therefore, impacts the overall system performance. In this paper we continue investigating materialization s

Andrew Osborne, Trevyn Larson, Sarah Jones, Ray W. Simmonds

Circuit quantization is an extraordinarily successful theory that describes the behavior of quantum circuits with high precision. The most widely used approach of circuit quantization relies on introducing a classical Lagrangian whose degrees of freedom are either magnetic fluxes or electric charges in the circuit. By combining nonlinear circuit elements (su

Allison Koenecke, Eric Giannella, Robb Willer, Sharad Goel

Algorithmically optimizing the provision of limited resources is commonplace across domains from healthcare to lending. Optimization can lead to efficient resource allocation, but, if deployed without additional scrutiny, can also exacerbate inequality. Little is known about popular preferences regarding acceptable efficiency-equity trade-offs, making it dif

Jorge Miguel-Ramiro, Zheng Shi, Luca Dellantonio, Albie Chan

Overcoming the influence of noise and imperfections in quantum devices is one of the main challenges for viable quantum applications. In this article, we present different protocols, which we denote as "superposed quantum error mitigation", that enhance the fidelity of single gates or entire computations by performing them in coherent superposition. Our resu

Jorge Miguel-Ramiro, Zheng Shi, Luca Dellantonio, Albie Chan

Overcoming the influence of noise and imperfections is a major challenge in quantum computing. Here, we present an approach based on applying a desired unitary computation in superposition between the system of interest and some auxiliary states. We demonstrate, numerically and on the IBM Quantum Platform, that parallel applications of the same operation lea

Liang Ma, Yi Pang, H. Lu

In an effective theory of gravity, thermodynamic quantities of black holes receive corrections from the infinite series of higher derivative terms. At the next to leading order, these can be obtained by using only the leading order solution. In this paper, we push forward this property to the next to next to leading order. We propose a formula which yields t

Nicholas Choustikov, Harley Katz, Aayush Saxena, Alex J. Cameron

Reliable indirect diagnostics of LyC photon escape from galaxies are required to understand which sources were the dominant contributors to reionization. While multiple LyC escape fraction ($f_{\rm esc}$) indicators have been proposed to trace favourable conditions for LyC leakage from the interstellar medium of low-redshift ''analog'' galaxies, it remains u

Cristian Zanoci, Yongchan Yoo, Brian Swingle

We study the thermalization properties of one-dimensional open quantum systems coupled to baths at their boundary. The baths are driven to their thermal states via Lindblad operators, while the system undergoes Hamiltonian dynamics. We specifically consider multi-site baths and investigate the extent to which the late-time steady state resembles a Gibbs stat

A. Álvarez-Hernández, M. A. P. Torres, P. Rodríguez-Gil, T. Shahbaz

We present a dynamical study of the eclipsing intermediate polar XY Ari based on time-resolved near-infrared spectroscopy obtained with the EMIR spectrograph on the 10.4-m Gran Telescopio Canarias. Using main sequence template spectra taken with the same instrument setup as the target spectra, we measure a radial velocity amplitude of the late K-type donor s

Florian Ecker, Daniel Grumiller, Carlos Valcárcel, Dmitri Vassilevich

Dilaton gravities in two dimensions can be formulated as particular Poisson sigma models. Target space diffeomorphisms map different models to each other and establish a one-to-one correspondence between their classical solutions. We obtain a general form of such diffeomorphisms in Lorentzian and Euclidean signatures and use them to extend known holographic

Máté Lencsés, Alessio Miscioscia, Giuseppe Mussardo, Gábor Takács

We study a novel class of Renormalization Group flows which connect multicritical versions of the two-dimensional Yang-Lee edge singularity described by the conformal minimal models M(2,2n+3). The absence in these models of an order parameter implies that the flows towards and between Lee-Yang edge singularities are all related to the spontaneous breaking of

Brian Lorenz, Mariska Kriek, Alice E. Shapley, Naveen A. Reddy

We investigate dust attenuation and its dependence on viewing angle for 308 star-forming galaxies at $1.3\leq z\leq2.6$ from the MOSFIRE Deep Evolution Field (MOSDEF) survey. We divide galaxies with a detected H$\alpha$ emission line and coverage of H$\beta$ into eight groups by stellar mass, star formation rate (SFR), and inclination (i.e., axis ratio), the

Vitor Cardoso, João L. Costa, José Natário, Zhen Zhong

Quantum gravity phenomenology suggests the interesting possibility that black holes are not eternal. Collapse could be halted by some unknown mechanism, or Hawking radiation might leave behind a regular spacetime. Here we investigate a simple bouncing geometry, with (outer and inner) apparent horizons but no event horizon. We show that the inner horizon blue

P. Sánchez-Sáez, J. Arredondo, A. Bayo, P. Arévalo

We present a variability, color and morphology based classifier, designed to identify transients, persistently variable, and non-variable sources, from the Zwicky Transient Facility (ZTF) Data Release 11 (DR11) light curves of extended and point sources. The main motivation to develop this model was to identify active galactic nuclei (AGN) at different redsh

Michael K. Plummer, Ji Wang

Extremely large telescopes (ELTs) present an unparalleled opportunity to study the magnetism, atmospheric dynamics, and chemistry of very low mass stars (VLMs), brown dwarfs, and exoplanets. Instruments such as the Giant Magellan Telescope - Consortium Large Earth Finder (GMT/GCLEF), the Thirty Meter Telescope's Multi-Objective Diffraction-limited High-Resol

Carlos Gómez-Guijarro, Benjamin Magnelli, David Elbaz, Stijn Wuyts

In recent years, observations have uncovered a population of massive galaxies that are invisible or very faint in deep optical/near-infrared (near-IR) surveys but brighter at longer wavelengths. However, the nature of these optically dark or faint galaxies (OFGs; one of several names given to these objects) is highly uncertain. In this work, we investigate t

Mirko Curti, Roberto Maiolino, Emma Curtis-Lake, Jacopo Chevallard

We analyse the gas-phase metallicity properties of a sample of low stellar mass (log M*/M_sun <= 9) galaxies at 3 < z < 10, observed with JWST/NIRSpec as part of the JADES programme in its deep GOODS-S tier. By combining this sample with more massive galaxies at similar redshifts from other programmes, we study the scaling relations between stellar mass, oxy

He-Ran Wang, Dong Yuan, Shun-Yao Zhang, Zhong Wang

Quantum many-body scars are non-thermal excited eigenstates of non-integrable Hamiltonians, which could support coherent revival dynamics from special initial states when scars form an equally spaced tower in the energy spectrum. For open quantum systems, engineering many-body scarred dynamics by a controlled coupling to the environment remains largely unexp

M. Del Santo, C. Pinto, A. Marino, A. D'Aì

The transient X-ray source MAXI J1810-222 was discovered in 2018 and has been active ever since. A long combined radio and X-ray monitoring campaign was performed with ATCA and Swift respectively. It has been proposed that MAXI J1810-222 is a relatively distant black hole X-ray binary, albeit showing a very peculiar outburst behaviour. Here, we report on the

Julia M. Sisk-Reynes, Christopher S. Reynolds, James H. Matthews

We discuss our recent constraints on the coupling of Very-Light Axion-Like Particles (of masses $<$$ 10^{-12} \ \mathrm{eV}$) to electromagnetism from $Chandra$ observations of the cluster-hosted Active Galactic Nuclei (AGN) H1821+643 and NGC1275. In both cases, the inferred high-quality AGN spectra excluded all photon-ALP couplings $g_\mathrm{a\gamma} > (6.

Matthew Reece

These notes are an expanded version of lectures given at the 2022 TASI summer school in Boulder, Colorado. One goal of these lecture notes is to (partially) bridge the gap between what one learns in typical introductory quantum field theory classes and what one needs to understand to follow modern developments in particle theory beyond the Standard Model. To

Michael V. Maseda, Zach Lewis, Jorryt Matthee, Joseph F. Hennawi

Deep VLT/MUSE optical integral field spectroscopy has recently revealed an abundant population of ultra-faint galaxies ($M_{UV} \approx -15$; 0.01 $L_{\star}$) at $z=$2.9$-$6.7 due to their strong Lyman-$\alpha$ emission with no detectable continuum. The implied Lyman-$\alpha$ equivalent widths can be in excess of 100-200 Angstrom, challenging existing model

Javier Moreno, Ángel J. Murcia

Generalized Quasitopological Gravities (GQTGs) are higher-order extensions of Einstein gravity in $D$ dimensions satisfying a number of interesting properties, such as possessing second-order linearized equations of motion on top of maximally symmetric backgrounds, admitting non-hairy generalizations of the Schwarzschild-Tangherlini black hole which are char

Elias Bernreuther, Bogdan A. Dobrescu

We study a renormalizable theory that includes a heavy weak-singlet vectorlike lepton, $\tau^\prime$, that decays into a pseudoscalar boson and a tau lepton. We show that this can be the dominant decay mode of $\tau^\prime$ provided the pseudoscalar couplings deviate from the case of a Nambu-Goldstone boson. For a range of parameters, the pseudoscalar is lon

Leiyao Cui, Xiaoxue Chen, Hao Zhao, Guyue Zhou

With significant annotation savings, point supervision has been proven effective for numerous 2D and 3D scene understanding problems. This success is primarily attributed to the structured output space; i.e., samples with high spatial affinity tend to share the same labels. Sharing this spirit, we study affordance segmentation with point supervision, wherein

Xinyu Liu, Beiwen Tian, Zhen Wang, Rui Wang

Thanks to the impressive progress of large-scale vision-language pretraining, recent recognition models can classify arbitrary objects in a zero-shot and open-set manner, with a surprisingly high accuracy. However, translating this success to semantic segmentation is not trivial, because this dense prediction task requires not only accurate semantic understa

Yuexi Du, Ziyang Chen, Justin Salamon, Bryan Russell

The sound effects that designers add to videos are designed to convey a particular artistic effect and, thus, may be quite different from a scene's true sound. Inspired by the challenges of creating a soundtrack for a video that differs from its true sound, but that nonetheless matches the actions occurring on screen, we propose the problem of conditional Fo

Nathan C. Hara, Jean-Baptiste Delisle

The detection of terrestrial planets by radial velocity and photometry is hindered by the presence of stellar signals. Those are often modeled as stationary Gaussian processes, whose kernels are based on qualitative considerations, which do not fully leverage the existing physical understanding of stars. Our aim is to build a formalism which allows to transf

Shikhar Bahl, Russell Mendonca, Lili Chen, Unnat Jain

Building a robot that can understand and learn to interact by watching humans has inspired several vision problems. However, despite some successful results on static datasets, it remains unclear how current models can be used on a robot directly. In this paper, we aim to bridge this gap by leveraging videos of human interactions in an environment centric ma

Mengdi Xu, Yuchen Lu, Yikang Shen, Shun Zhang

Decision Transformers (DT) have demonstrated strong performances in offline reinforcement learning settings, but quickly adapting to unseen novel tasks remains challenging. To address this challenge, we propose a new framework, called Hyper-Decision Transformer (HDT), that can generalize to novel tasks from a handful of demonstrations in a data- and paramete

Kathryn Wantlin, Chenwei Wu, Shih-Cheng Huang, Oishi Banerjee

Medical data poses a daunting challenge for AI algorithms: it exists in many different modalities, experiences frequent distribution shifts, and suffers from a scarcity of examples and labels. Recent advances, including transformers and self-supervised learning, promise a more universal approach that can be applied flexibly across these diverse conditions. T

Haotian Liu, Chunyuan Li, Qingyang Wu, Yong Jae Lee

Instruction tuning large language models (LLMs) using machine-generated instruction-following data has improved zero-shot capabilities on new tasks, but the idea is less explored in the multimodal field. In this paper, we present the first attempt to use language-only GPT-4 to generate multimodal language-image instruction-following data. By instruction tuni

Luisa Eck, Paul Fendley

Arrays of Rydberg atoms in the blockade regime realize a wealth of strongly correlated quantum physics, but theoretical analysis beyond the chain is rather difficult. Here we study a tractable model of Rydberg-blockade atoms on the square ladder with a $\mathbb{Z}_2 \times \mathbb{Z}_2$ symmetry and at most one excited atom per square. We find $D_4$, $\mathb

Yuming Jiang, Shuai Yang, Tong Liang Koh, Wayne Wu

Text-driven content creation has evolved to be a transformative technique that revolutionizes creativity. Here we study the task of text-driven human video generation, where a video sequence is synthesized from texts describing the appearance and motions of a target performer. Compared to general text-driven video generation, human-centric video generation r

Aramayis Dallakyan

The fields of time series and graphical models emerged and advanced separately. Previous work on the structure learning of continuous and real-valued time series utilizes the time domain, with a focus on either structural autoregressive models or linear (non-)Gaussian Bayesian Networks. In contrast, we propose a novel frequency domain approach to identify a

Xuan Xiong, Yicheng Liu, Tianyuan Yuan, Yue Wang

High-definition (HD) semantic maps are crucial in enabling autonomous vehicles to navigate urban environments. The traditional method of creating offline HD maps involves labor-intensive manual annotation processes, which are not only costly but also insufficient for timely updates. Recent studies have proposed an alternative approach that generates local ma

Yihao Chen, Xianbiao Qi, Jianan Wang, Lei Zhang

We propose DisCo-CLIP, a distributed memory-efficient CLIP training approach, to reduce the memory consumption of contrastive loss when training contrastive learning models. Our approach decomposes the contrastive loss and its gradient computation into two parts, one to calculate the intra-GPU gradients and the other to compute the inter-GPU gradients. Accor

Jindong Gu, Ahmad Beirami, Xuezhi Wang, Alex Beutel

With the advent of vision-language models (VLMs) that can perform in-context and prompt-based learning, how can we design prompting approaches that robustly generalize to distribution shift and can be used on novel classes outside the support set of the prompts? In this work, we first define two types of robustness to distribution shift on VLMs, namely, robu

Seiji Terashima

In this paper, we construct a general bulk wave packet in the AdS/CFT correspondence. This wave packet can be described both in bulk and CFT descriptions. Then, we compute the time evolution of the energy density of this wave packet state on the vacuum in the CFT picture of $AdS_3/CFT_2$. We find that the energy density of the wave packet is localized in two

Jie An, Songyang Zhang, Harry Yang, Sonal Gupta

We propose Latent-Shift -- an efficient text-to-video generation method based on a pretrained text-to-image generation model that consists of an autoencoder and a U-Net diffusion model. Learning a video diffusion model in the latent space is much more efficient than in the pixel space. The latter is often limited to first generating a low-resolution video fo

Steven Amelotte, Benjamin Briggs

A fundamental result in toric topology identifies the cohomology ring of the moment-angle complex $\mathcal{Z}_K$ associated to a simplicial complex $K$ with the Koszul homology of the Stanley--Reisner ring of $K$. By studying cohomology operations induced by the standard torus action on the moment-angle complex, we extend this to a topological interpretatio

Yu Zhao, Hongyu Wang, Yuting Hu, Yidun Wan

We investigate the composite systems consisting of topological orders separated by gapped domain walls. We derive a pair of domain-wall Verlinde formulae, that elucidate the connection between the braiding of interdomain excitations labeled by pairs of anyons in different domains and quasiparticles in the gapped domain wall with their respective fusion rules

Abhijit Biswas, Rui Xu, Joyce Christiansen-Salameh, Eugene Jeong

Boron nitride (BN) is an exceptional material and among its polymorphs, two-dimensional (2D) hexagonal and three-dimensional (3D) cubic BN (h-BN and c-BN) phases are most common. The phase stability regimes of these BN phases are still under debate and phase transformations of h-BN/c-BN remain a topic of interest. Here, we investigate the phase stability of

Hermann Tchatchiem Kamche, Hervé Talé Kalachi

Several problems in algebraic geometry and coding theory over finite rings are modeled by systems of algebraic equations. Among these problems, we have the rank decoding problem, which is used in the construction of public-key cryptography. In 2004, Nechaev and Mikhailov proposed two methods for solving systems of polynomial equations over finite chain rings

Hongjie Dong, Zhuolun Yang, Hanye Zhu

We study the insulated conductivity problem with closely spaced insulators embedded in a homogeneous matrix where the current-electric field relation is the power law $J = |E|^{p-2}E$. The gradient of solutions may blow up as $\varepsilon$, the distance between insulators, approaches to 0. In 2D, we prove an upper bound of the gradient to be of order $\varep

Azadeh Moradinezhad Dizgah, Emilio Bellini, Garrett K. Keating

Line intensity mapping (LIM) can provide a powerful means to constrain the theory of gravity and the nature of dark energy at low and high redshifts by mapping the large-scale structure (LSS) over many redshift epochs. In this paper, we investigate the potential of the next generation ground-based millimeter-wavelength LIM surveys in constraining several mod

Nair Bini Balakrishnan, P. S. Sreeja, Jisha Jose Panackal

Alzheimers Disease AD is an acute neuro disease that degenerates the brain cells and thus leads to memory loss progressively. It is a fatal brain disease that mostly affects the elderly. It steers the decline of cognitive and biological functions of the brain and shrinks the brain successively, which in turn is known as Atrophy. For an accurate diagnosis of

Jiaqi Cai, Eric Anderson, Chong Wang, Xiaowei Zhang

The interplay between spontaneous symmetry breaking and topology can result in exotic quantum states of matter. A celebrated example is the quantum anomalous Hall (QAH) state, which exhibits an integer quantum Hall effect at zero magnetic field thanks to its intrinsic ferromagnetism. In the presence of strong electron-electron interactions, exotic fractional

Yinqi Chen, Konstantin N. Nesterov, Hugh Churchill, Javad Shabani

We describe the generation of entangling gates on superconductor-semiconductor hybrid qubits by ac voltage modulation of the Josephson energy. Our numerical simulations demonstrate that the unitary error can be below $10^{-5}$ in a variety of 75-ns-long two-qubit gates (CZ, $i$SWAP, and $\sqrt{i\mathrm{SWAP}}$) implemented using parametric resonance. We anal

Nishant Chandgotia, Scott Sheffield, Catherine Wolfram

In 2000, Cohn, Kenyon and Propp studied uniformly random perfect matchings of large induced subgraphs of $\mathbb Z^2$ (a.k.a. dimer configurations or domino tilings) and developed a large deviation theory for the associated height functions. We establish similar results for large induced subgraphs of $\mathbb Z^3$. To formulate these results, recall that a

Jesse Mu, Xiang Lisa Li, Noah Goodman

Prompting is the primary way to utilize the multitask capabilities of language models (LMs), but prompts occupy valuable space in the input context window, and repeatedly encoding the same prompt is computationally inefficient. Finetuning and distillation methods allow for specialization of LMs without prompting, but require retraining the model for each tas

Shekoofeh Azizi, Simon Kornblith, Chitwan Saharia, Mohammad Norouzi

Deep generative models are becoming increasingly powerful, now generating diverse high fidelity photo-realistic samples given text prompts. Have they reached the point where models of natural images can be used for generative data augmentation, helping to improve challenging discriminative tasks? We show that large-scale text-to image diffusion models can be

Mingdeng Cao, Xintao Wang, Zhongang Qi, Ying Shan

Despite the success in large-scale text-to-image generation and text-conditioned image editing, existing methods still struggle to produce consistent generation and editing results. For example, generation approaches usually fail to synthesize multiple images of the same objects/characters but with different views or poses. Meanwhile, existing editing method

Yifan Yin, Yutai Wang, Yunpu Zhang, Russell H. Taylor

We present a robust markerless image based visual servoing method that enables precision robot control without hand-eye and camera calibrations in 1, 3, and 5 degrees-of-freedom. The system uses two cameras for observing the workspace and a combination of classical image processing algorithms and deep learning based methods to detect features on camera image

Yilun Du, Cameron Smith, Ayush Tewari, Vincent Sitzmann

We introduce a method for novel view synthesis given only a single wide-baseline stereo image pair. In this challenging regime, 3D scene points are regularly observed only once, requiring prior-based reconstruction of scene geometry and appearance. We find that existing approaches to novel view synthesis from sparse observations fail due to recovering incorr

Eugene Zhang

In this paper, we present a general formula for derived sets in general topology. Consequently, more results can be proved in general topology involving derived sets and isolated point sets. More specifically, we can prove that isolated point sets are nowhere dense in general topological space.

Alexander O. Sushkov, Oleg P. Sushkov, Alexander Yaresko

Laboratory-scale precision experiments are a promising approach to searching for physics beyond the standard model. Non-centrosymmetric solids offer favorable statistical sensitivity for efforts that search for new fields, whose interactions violate the discrete parity and time-reversal symmetries. One example is the electric Cosmic Axion Spin Precession Exp

Abdullatif Köksal, Timo Schick, Anna Korhonen, Hinrich Schütze

Instruction tuning enables language models to more effectively generalize and better follow user intent. However, obtaining instruction data is costly and challenging. Prior work employs methods such as expensive human annotation, crowd-sourced datasets with alignment issues, and generating noisy examples via LLMs. We introduce the LongForm-C dataset, which

Tianji Shen, Vamoua Yachongka, Yuto Hama, Hideki Ochiai

In this work, we investigate the performance of indoor visible light communication (VLC) networks based on power domain non-orthogonal multiple access (NOMA) for mobile devices, where multiple legitimate users are equipped with photodiodes (PDs). We propose a body blockage model for both the legitimate users and eavesdropper to address scenarios where the co

Haroldo V. Ribeiro, Diego D. Lopes, Arthur A. B. Pessa, Alvaro F. Martins

Recent advances in deep learning methods have enabled researchers to develop and apply algorithms for the analysis and modeling of complex networks. These advances have sparked a surge of interest at the interface between network science and machine learning. Despite this, the use of machine learning methods to investigate criminal networks remains surprisin

Brian L Burrows

Two types of non-Hermitian systems are considered. One of them is both non-Hermitian and non-Linear and an iterative process is used to obtain excited state solutions; the ground state may be solved exactly. The model has been used in many physical systems and the method of calculation uses a simple Hilbert space with a generalised inner product. The second

Mustapha Azreg-Aïnou, Hoang Ky Nguyen

The closed-form expression for pure $\mathcal{R}^{2}$ vacuum solution obtained in Phys. Rev. D \textbf{107}, 104008 (2023) lends itself to a generalization to axisymmetric setup via the modified Newman--Janis algorithm. We adopt the procedure put forth in Phys. Rev. D \textbf{90}, 064041 (2014) bypassing the complexification of the radial coordinate. The pro

Christoph Kehle, Ryan Unger

In this paper, we initiate the study of characteristic event horizon gluing in vacuum. More precisely, we prove that Minkowski space can be glued along a null hypersurface to any round symmetry sphere in a Schwarzschild black hole spacetime as a $C^2$ solution of the Einstein vacuum equations. The method of proof is fundamentally nonperturbative and is close

Jinzheng Li, Pran Nath

A variety of supergravity and string models involve hidden sectors where the hidden sectors may couple feebly with the visible sectors via a variety of portals. While the coupling of the hidden sector to the visible sector is feeble its coupling to the inflaton is largely unknown. It could couple feebly or with the same strength as the visible sector which w

Victor Agostinelli, Lizhong Chen

Various natural language processing (NLP) tasks necessitate models that are efficient and small based on their ultimate application at the edge or in other resource-constrained environments. While prior research has reduced the size of these models, increasing computational efficiency without considerable performance impacts remains difficult, especially for

Sebastian Horvat, Iulian D. Toader

Timothy Williamson has recently argued that the applicability of classical mathematics in the natural and social sciences raises a problem for the endorsement, in non-mathematical domains, of a wide range of non-classical logics. We first reconstruct his argument and present its restriction to the case of quantum logic (QL). Then we show that there is no pro

Lei Chen, Zhan Tong, Yibing Song, Gangshan Wu

Streaming video clips with large-scale video tokens impede vision transformers (ViTs) for efficient recognition, especially in video action detection where sufficient spatiotemporal representations are required for precise actor identification. In this work, we propose an end-to-end framework for efficient video action detection (EVAD) based on vanilla ViTs.

Sebastian Horvat, Iulian D. Toader

This paper gives a formulation of quantum logic in the abstract algebraic setting laid out by Dunn and Hardegree (2001). On this basis, it provides a comparative analysis of viable quantum logical bivalent semantics and their classical counterparts, thereby showing that the truth-functional status of classical and quantum connectives is not as different as u

Tao Jiang, Peter P. Orth, Liang Luo, Lin-Lin Wang

Laser-driven coherent phonons can act as modulated strain fields and modify the adiabatic ground state topology of quantum materials. Here we use time-dependent first-principles and effective model calculations to simulate the effect of the coherent phonon induced by strong terahertz electric field on electronic carriers in the topological insulator ZrTe$_5$

Chong Ma, Zihao Wu, Jiaqi Wang, Shaochen Xu

The 'Impression' section of a radiology report is a critical basis for communication between radiologists and other physicians, and it is typically written by radiologists based on the 'Findings' section. However, writing numerous impressions can be laborious and error-prone for radiologists. Although recent studies have achieved promising results in automat

Yahia Dalbah, Jean Lahoud, Hisham Cholakkal

The performance of perception systems developed for autonomous driving vehicles has seen significant improvements over the last few years. This improvement was associated with the increasing use of LiDAR sensors and point cloud data to facilitate the task of object detection and recognition in autonomous driving. However, LiDAR and camera systems show deteri

Daniel Wines, Tian Xie, Kamal Choudhary

Finding new superconductors with a high critical temperature ($T_c$) has been a challenging task due to computational and experimental costs. We present a diffusion model inspired by the computer vision community to generate new superconductors with unique structures and chemical compositions. Specifically, we used a crystal diffusion variational autoencoder

Robert Penner

Wigner's unitary representation of the Lorentz group is extended to a representation of the complex orthosymplectic Lie super group OSp_C(1|2) acting on Minkowski (3,1|4)-dimensional super space essentially by Hermitean conjugation. The invariant quadratic form is [x_1 x_2-x xbar+phi psi+phibar psibar] in Wigner's real coordinates x_1,x_2 and complex coordin

Yu Guo, Yuan Gao, Ryan Wen Liu, Yuxu Lu

The presence of non-homogeneous haze can cause scene blurring, color distortion, low contrast, and other degradations that obscure texture details. Existing homogeneous dehazing methods struggle to handle the non-uniform distribution of haze in a robust manner. The crucial challenge of non-homogeneous dehazing is to effectively extract the non-uniform distri

Armando J. Cabrera Pacheco, Melanie Graf, Raquel Perales

The rigidity of the Riemannian positive mass theorem for asymptotically hyperbolic manifolds states that the total mass of such a manifold is zero if and only if the manifold is isometric to the hyperbolic space. This leads to study the stability of this statement, that is, if the total mass of an asymptotically hyperbolic manifold is almost zero, is this ma

Jean Kaddour

The ever-growing diversity of pre-training text corpora has equipped language models with generalization capabilities across various downstream tasks. However, such diverse datasets are often too large for academic budgets; hence, most research on Transformer architectures, training procedures, optimizers, etc. gets conducted on smaller, homogeneous datasets

Nils Kürbis

This article is the text of a commentary on a talk delivered by Mark Textor entitled 'Brentano's Positing Theory of Existence' in December 2015. It contains ideas on implementing Textor's Neo-Brentanian theory of existence in a natural deduction proof system for negative free logic.

Foued Saâdaoui

Multifractal analysis is a forecasting technique used to study the scaling regularity properties of financial returns, to analyze the long-term memory and predictability of financial markets. In this paper, we propose a novel structural detrended multifractal fluctuation analysis (S-MF-DFA) to investigate the efficiency of the main cryptocurrencies. The new

Arunava Chakravarty, Taha Emre, Oliver Leingang, Sophie Riedl

The lack of reliable biomarkers makes predicting the conversion from intermediate to neovascular age-related macular degeneration (iAMD, nAMD) a challenging task. We develop a Deep Learning (DL) model to predict the future risk of conversion of an eye from iAMD to nAMD from its current OCT scan. Although eye clinics generate vast amounts of longitudinal OCT