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Accurate spectral analysis of high-energy astrophysical sources often relies on comparing observed data to incident spectral models convolved with the instrument response. However, for Gamma-Ray Bursts and other high-energy transient events…

Cross-correlated contrast source inversion (CC-CSI) is a non-linear iterative inversion method that is proposed recently for solving the inverse scattering problems. In CC-CSI, a cross-correlated error is constructed and introduced to the…

Signal Processing · Electrical Eng. & Systems 2019-06-27 Shilong Sun , Bert Jan Kooij , Alexander G. Yarovoy

Structural seismic interpretation and quantitative characterization are historically intertwined processes. The latter provides estimates of properties of the subsurface which can be used to aid structural interpretation alongside the…

Geophysics · Physics 2021-10-13 Matteo Ravasi , Claire Emma Birnie

Spectral clustering is a popular unsupervised learning technique which is able to partition unlabelled data into disjoint clusters of distinct shapes. However, the data under consideration are often experimental data, implying that the data…

Machine Learning · Statistics 2025-05-26 Jürgen Dölz , Jolanda Weygandt

Phase aberrations, despite degrading ultrasound images, also encode valuable information about the spatial distribution of the speed of sound in tissue. In pulse-echo ultrasound, we can quantify them by exploiting speckle correlations.…

Medical Physics · Physics 2025-11-20 Naiara Korta Martiartu , Michael Jaeger

When x-rays penetrate soft matter, their phase changes more rapidly than their amplitude. In- terference effects visible with high brightness sources creates higher contrast, edge enhanced images. When the object is piecewise smooth (made…

New high statistics data from the second generation of ultrarelativistic heavy-ion experiments open up new possibilities in terms of data analysis. To fully utilize the potential we propose to analyze the $m_\perp$-spectra of hadrons using…

Nuclear Theory · Physics 2009-10-28 Ekkard Schnedermann

To assess whether a given time series can be modeled by a stochastic process possessing long range correlation one usually applies one of two types of analysis methods: the spectral method and the random walk analysis. The first objective…

Statistical Mechanics · Physics 2009-11-07 Govindan Rangarajan , Mingzhou Ding

Here, we present a new method to evaluate the expectation value of the power spectrum of a time series. A statistical approach is adopted to define the method. After its demonstration, it is validated showing that it leads to the known…

High Energy Astrophysical Phenomena · Physics 2015-06-16 G. A. Caliandro , D. F. Torres , N. Rea

The Phase Retrieval problem is dealt with for the challenging case where just a single set of (phaseless) radiated field data is available. In particular, even still emulating the solution of crosswords puzzles, we provide decisive…

Signal Processing · Electrical Eng. & Systems 2023-08-16 Giada Maria Battaglia , Andrea Francesco Morabito , Roberta Palmeri , Tommaso Isernia

We exploit a slightly noncollinear second-harmonic cross-correlation scheme to map the 3D space-time intensity distribution of an unknown complex-shaped ultrashort optical pulse. We show the capability of the technique to reconstruct both…

The study and application of signal detection techniques based on cross-correlation method for acoustic transient signals in noisy and reverberant environments are presented. These techniques are shown to provide high signal to noise ratio,…

Instrumentation and Detectors · Physics 2015-02-19 S. Adrián-Martínez , M. Ardid , M. Bou-Cabo , I. Felis , C. Llorens , J. A. Martínez-Mora , M. Saldaña

The spectral density matrix is a fundamental object of interest in time series analysis, and it encodes both contemporary and dynamic linear relationships between component processes of the multivariate system. In this paper we develop…

Statistics Theory · Mathematics 2025-02-04 Jinyuan Chang , Qing Jiang , Tucker S. McElroy , Xiaofeng Shao

The periodogram is a popular tool that tests whether a signal consists only of noise or if it also includes other components. The main issue of this method is to define a critical detection threshold that allows identification of a…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-19 R. Vio , P. Andreani , A. Biggs

The interferometric analysis of meson correlations provides a measure of the average phase space density of the mesons in the final state. This quantity is a useful indicator of the statistical properties of the system, and it can be…

Nuclear Theory · Physics 2009-10-22 George F. Bertsch

It is now well understood that convex programming can be used to estimate the frequency components of a spectrally sparse signal from $2m+1$ uniform temporal measurements. It is conjectured that a phase transition on the success of the…

Information Theory · Computer Science 2021-10-18 Maxime Ferreira Da Costa , Wei Dai

Quantum correlation, such as entanglement and squeezing have shown to improve phase estimation in interferometric setups on one side, and non-interferometric imaging scheme of amplitude object on the other. In the last case, quantum…

Quantitative thermodynamical, dynamical and magnetic properties of the solar and stellar plasmas are obtained by interpreting their emergent non-polarized and polarized spectrum. This inference requires the selection of a set of spectral…

Solar and Stellar Astrophysics · Physics 2016-05-25 A. Asensio Ramos , J. de la Cruz Rodriguez , M. J. Martinez Gonzalez , A. Pastor Yabar

An algorithm is presented which generates pairs of oscillatory random time series which have identical periodograms but differ in the number of oscillations. This result indicate the intrinsic limitations of spectral methods when it comes…

Data Analysis, Statistics and Probability · Physics 2007-05-23 A. G. Rossberg

An emerging way to deal with high-dimensional non-euclidean data is to assume that the underlying structure can be captured by a graph. Recently, ideas have begun to emerge related to the analysis of time-varying graph signals. This work…

Machine Learning · Computer Science 2017-05-08 Francesco Grassi , Andreas Loukas , Nathanaël Perraudin , Benjamin Ricaud