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Related papers: Asymmetric Huber Periodogram

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In this paper, we suggest a new heterogeneous multiscale method (HMM) for the time-harmonic Maxwell equations in locally periodic media. The method is constructed by using a divergence-regularization in one of the cell problems. This allows…

Numerical Analysis · Mathematics 2015-09-15 Patrick Henning , Mario Ohlberger , Barbara Verfürth

Recent and future generation observatories will enable the study of variable astronomical phenomena through their time-domain capabilities. High temporal fidelity will allow for unprecedented investigations into the nature of variable…

Instrumentation and Methods for Astrophysics · Physics 2021-11-16 Michael Gowanlock , Nathaniel R. Butler , David E. Trilling , Andrew McNeill

High harmonic spectroscopy has the potential to combine attosecond temporal with sub-Angstrom spatial resolution of the early nuclear and multielectron dynamics in molecules. It involves strong field ionization of the molecule by the IR…

Atomic Physics · Physics 2013-08-08 Valeria Serbinenko , Olga Smirnova

Observing critical phases in lattice models is challenging due to the need to analyze the finite time or size scaling of observables. We study how the computational topology technique of persistent homology can be used to characterize…

Disordered Systems and Neural Networks · Physics 2022-09-05 Yu He , Shiqi Xia , Dimitris G. Angelakis , Daohong Song , Zhigang Chen , Daniel Leykam

This paper proposes a new method for determining similarity and anomalies between time series, most practically effective in large collections of (likely related) time series, by measuring distances between structural breaks within such a…

Machine Learning · Computer Science 2020-12-01 Nick James , Max Menzies , Lamiae Azizi , Jennifer Chan

Inference for statistics of a stationary time series often involve nuisance parameters and sampling distributions that are difficult to estimate. In this paper, we propose the method of orthogonal samples, which can be used to address some…

Methodology · Statistics 2016-11-03 Suhasini Subba Rao

The visibility algorithm has been recently introduced as a mapping between time series and complex networks. This procedure allows to apply methods of complex network theory for characterizing time series. In this work we present the…

Data Analysis, Statistics and Probability · Physics 2010-02-25 Bartolo Luque , Lucas Lacasa , Fernando Ballesteros , Jordi Luque

A general one-dimensional quantum optical mode is described by a shape in the time or frequency domain. A fundamental problem is to measure a quadrature operator of such a mode. If the shape is narrow in frequency this can be done by pulsed…

Quantum Physics · Physics 2025-03-04 Ezad Shojaee , James R. van Meter , Karl Mayer , Scott Glancy , Emanuel Knill

Quantitative phase microscopy (QPM) is often based on recording an object-reference interference pattern and its further phase demodulation. We propose Pseudo Hilbert Phase Microscopy (PHPM) where we combine pseudo thermal light source…

This paper proposes a novel asymmetric continuous probabilistic score (ACPS) for evaluating and comparing density forecasts. It extends the proposed score and defines a weighted version, which emphasizes regions of interest, such as the…

Methodology · Statistics 2020-09-02 Matteo Iacopini , Francesco Ravazzolo , Luca Rossini

The mechanism underlying high harmonic generation (HHG) in gases has been well clarified, characterizing attosecond pulse trains (APT) in the time domain, significantly advances the synthesis of isolated attosecond pulse (IAP). However, the…

Optics · Physics 2025-07-25 Qing-Guo Fan , Kang Lai , Wen-hao Liu , Zhi Wang , Lin-Wang Wang , Jun-Wei Luo

Asteroseismic time-series data have imprints of stellar oscillation modes, whose detection and characterization through time-series analysis allows us to probe stellar interior physics. Such analyses usually occur in the Fourier domain by…

Instrumentation and Methods for Astrophysics · Physics 2024-05-30 Aarya A. Patil , Gwendolyn M. Eadie , Joshua S. Speagle , David J. Thomson

In this paper we propose a novel machine-learning method for anomaly detection applicable to data with periodic characteristics where randomly varying period lengths are explicitly allowed. A multi-dimensional time series analysis is…

Signal Processing · Electrical Eng. & Systems 2019-05-22 Lia Ahrens , Julian Ahrens , Hans D. Schotten

We provide a method for estimating spectral gaps in low-dimensional systems. Unlike traditional phase estimation, our approach does not require ancillary qubits nor does it require well characterised gates. Instead, it only requires the…

Quantum Physics · Physics 2016-06-22 Ilia Zintchenko , Nathan Wiebe

The antisymmetrized geminal power (AGP) wavefunction has a long history and is known by different names in various chemical and physical problems. There has been recent interest in using AGP as a starting point for strongly correlated…

Chemical Physics · Physics 2020-09-15 Rishab Dutta , Thomas M. Henderson , Gustavo E. Scuseria

The forecasting of irregular multivariate time series (IMTS) is crucial in key areas such as healthcare, biomechanics, climate science, and astronomy. However, achieving accurate and practical predictions is challenging due to two main…

Machine Learning · Computer Science 2025-11-18 Xvyuan Liu , Xiangfei Qiu , Xingjian Wu , Zhengyu Li , Chenjuan Guo , Jilin Hu , Bin Yang

A novel hierarchical search technique is presented for all-sky surveys for continuous gravitational-wave sources, such as rapidly spinning nonaxisymmetric neutron stars. Analyzing yearlong detector data sets over realistic ranges of…

General Relativity and Quantum Cosmology · Physics 2015-03-18 Holger J. Pletsch

Periodicity is often studied in timeseries modelling with autoregressive methods but is less popular in the kernel literature, particularly for higher dimensional problems such as in textures, crystallography, and quantum mechanics. Large…

Machine Learning · Statistics 2018-05-15 Anthony Tompkins , Fabio Ramos

Dynamical phase transitions (DPTs), characterized by non-analytic behaviors in time domain, extend the equilibrium phase transitions to far-from-equilibrium situations. It has been predicted that DPTs can be precisely identified by the…

Quantum Physics · Physics 2019-07-30 Tian Tian , Yongguan Ke , Liang Zhang , Shaochun Lin , Zhifu Shi , Pu Huang , Chaohong Lee , Jiangfeng Du

This work presents a set of new statistics, the cumulant correlators, aimed at high precision analysis of the galaxy distribution. They form a symmetric matrix, $Q_{NM}$, related to moment correlators the same way as cumulants are related…

Astrophysics · Physics 2009-10-30 István Szapudi , Alexander S. Szalay