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The observable spacetime can be viewed as worldline coincidences (events) between a particle system and the observers of an extended (material) reference frame (ERF). Particle positions are then operationally well defined with respect to…

General Relativity and Quantum Cosmology · Physics 2026-04-07 Eduardo O. Dias

In this paper, we present a new space-time Petrov-Galerkin-like method. This method utilizes a mixed formulation of Tensor Train (TT) and Quantized Tensor Train (QTT), designed for the spectral element discretization (Q1-SEM) of the…

When analyzing temporal networks, a fundamental task is the identification of dense structures (i.e., groups of vertices that exhibit a large number of links), together with their temporal span (i.e., the period of time for which the high…

Data Structures and Algorithms · Computer Science 2020-12-09 Edoardo Galimberti , Martino Ciaperoni , Alain Barrat , Francesco Bonchi , Ciro Cattuto , Francesco Gullo

Kulldorff's (1997) seminal paper on spatial scan statistics (SSS) has led to many methods considering different regions of interest, different statistical models, and different approximations while also having numerous applications in…

Machine Learning · Statistics 2019-08-13 Mingxuan Han , Michael Matheny , Jeff M. Phillips

The quantum-mechanical framework in which observables are associated with Hermitian operators is too narrow to discuss measurements of such important physical quantities as elapsed time or harmonic-oscillator phase. We introduce a broader…

Quantum Physics · Physics 2009-10-28 Samuel L. Braunstein , Carlton M. Caves , G. J. Milburn

Completing multidimensional tensor-structured data with missing entries is a fundamental task for many real-world applications involving incomplete or corrupted datasets. For data with spatial or temporal side information, low-rank…

Machine Learning · Statistics 2025-02-12 Mengying Lei , Lijun Sun

We propose efficient random features for approximating a new and rich class of kernel functions that we refer to as Generalized Zonal Kernels (GZK). Our proposed GZK family, generalizes the zonal kernels (i.e., dot-product kernels on the…

Machine Learning · Computer Science 2022-02-09 Insu Han , Amir Zandieh , Haim Avron

The exponential growth of available data has increased the need for interactive exploratory analysis. Dataset can no longer be understood through manual crawling and simple statistics. In Geographical Information Systems (GIS), the dataset…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-05-29 Erik Saule , Dinesh Panchananam , Alexander Hohl , Wenwu Tang , Eric Delmelle

Ordinary differential equation (ODE) is widely used in modeling biological and physical processes in science. In this article, we propose a new reproducing kernel-based approach for estimation and inference of ODE given noisy observations.…

Methodology · Statistics 2021-10-26 Xiaowu Dai , Lexin Li

The use of a relational time in quantum mechanics is a framework in which one promotes to quantum operators all variables in a system, and later chooses one of the variables to operate like a ``clock''. Conditional probabilities are…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Rodolfo Gambini , Rafael Porto , Jorge Pullin

We give the upper and the lower estimates of heat kernels for Schr\"odinger operators $H=-\Delta+V$, with nonnegative and locally bounded potentials $V$ in $\mathbb{R}^d$, $d \geq 1$. We observe a factorization: the contribution of the…

Functional Analysis · Mathematics 2023-03-13 Miłosz Baraniewicz , Kamil Kaleta

Spiking neural networks (SNNs) are biologically inspired energy-efficient models that use sparse binary spike-based communication between neurons, making them attractive for resource-constrained edge devices. Federated learning enables such…

Machine Learning · Computer Science 2026-05-18 Sanja Karilanova , Subhrakanti Dey , Ayça Özçelikkale

We investigate the emergence of thermodynamic arrow of time in the context of AdS/CFT correspondence. We show that, on the CFT side, if the two copies of the field theory are not initially correlated the entropy can only increase such that…

General Physics · Physics 2019-04-09 Ovidiu Racorean

We derive the leading asymptotic behavior and build a new series representation for the Fredholm determinant of integrable integral operators appearing in the representation of the time and distance dependent correlation functions of…

Mathematical Physics · Physics 2015-04-30 K. K. Kozlowski

We present a real-space formulation and higher-order finite-difference implementation of periodic Orbital-free Density Functional Theory (OF-DFT). Specifically, utilizing a local reformulation of the electrostatic and kernel terms, we…

Computational Physics · Physics 2015-12-23 Swarnava Ghosh , Phanish Suryanarayana

Due to the surge of data storage techniques, the need for the development of appropriate techniques to identify patterns and to extract knowledge from the resulting enormous data sets, which can be viewed as collections of dependent…

Methodology · Statistics 2018-12-04 Anne van Delft , Holger Dette

Continuing our investigation of the regularization of the noise kernel in curved spacetimes [N. G. Phillips and B. L. Hu, Phys. Rev. D {\bf 63}, 104001 (2001)] we adopt the modified point separation scheme for the class of optical…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Nicholas G Phillips , B. L. Hu

We experimentally disentangle the contributions of different quantum paths in high-order harmonic generation (HHG) from the spectrally and spatially resolved harmonic spectra. By adjusting the laser intensity and focusing position, we…

Atomic Physics · Physics 2015-10-08 Lixin He , Pengfei Lan , Qingbin Zhang , Chunyang Zhai , Feng Wang , Wenjing Shi , Peixiang Lu

The calculation of entanglement entropy S of quantum fields in spacetimes with horizon shows that, quite generically, S (a) is proportional to the area A of the horizon and (b) is divergent. I argue that this divergence, which arises even…

General Relativity and Quantum Cosmology · Physics 2010-12-24 T. Padmanabhan

Tensor time series (TTS) data, a generalization of one-dimensional time series on a high-dimensional space, is ubiquitous in real-world scenarios, especially in monitoring systems involving multi-source spatio-temporal data (e.g.,…

Machine Learning · Computer Science 2023-06-08 Jiewen Deng , Jinliang Deng , Renhe Jiang , Xuan Song