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Journal articles on the topic 'Dynamical Correlation'

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Author: Grafiati
Published: 7 September 2023

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1

Handy, Nicholas C., and Aron J. Cohen. "A dynamical correlation functional." Journal of Chemical Physics 116, no. 13 (April 2002): 5411–18. http://dx.doi.org/10.1063/1.1457432.

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2

Mok, Daniel K. W., Ralf Neumann, and Nicholas C. Handy. "Dynamical and Nondynamical Correlation." Journal of Physical Chemistry 100, no. 15 (January 1996): 6225–30. http://dx.doi.org/10.1021/jp9528020.

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3

Anishchenko, V. S., T. E. Vadivasova, G. A. Okrokvertskhov, and G. I. Strelkova. "Correlation analysis of dynamical chaos." Physica A: Statistical Mechanics and its Applications 325, no. 1-2 (July 2003): 199–212. http://dx.doi.org/10.1016/s0378-4371(03)00199-7.

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4

Hotta, Takashi, and Yasutami Takada. "Dynamical localization and electron correlation." Czechoslovak Journal of Physics 46, S5 (May 1996): 2625–26. http://dx.doi.org/10.1007/bf02570299.

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5

Dubin, Joel A., and Hans-Georg Müller. "Dynamical Correlation for Multivariate Longitudinal Data." Journal of the American Statistical Association 100, no. 471 (September 2005): 872–81. http://dx.doi.org/10.1198/016214504000001989.

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6

Kalman, G., K. Kempa, and M. Minella. "Dynamical correlation effects in alkali metals." Physical Review B 43, no. 17 (June 15, 1991): 14238–40. http://dx.doi.org/10.1103/physrevb.43.14238.

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7

Evangelisti, Stefano, Thierry Leininger, and Daniel Maynau. "A local approach to dynamical correlation." Journal of Molecular Structure: THEOCHEM 580, no. 1-3 (March 2002): 39–46. http://dx.doi.org/10.1016/s0166-1280(01)00593-0.

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8

Becker, K. W., and W. Brenig. "Cumulant approach to dynamical correlation functions." Zeitschrift f�r Physik B Condensed Matter 79, no. 2 (June 1990): 195–201. http://dx.doi.org/10.1007/bf01406585.

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9

Valderrama, E., J. M. Mercero, and J. M. Ugalde. "The separation of the dynamical and non-dynamical electron correlation effects." Journal of Physics B: Atomic, Molecular and Optical Physics 34, no. 3 (January 18, 2001): 275–83. http://dx.doi.org/10.1088/0953-4075/34/3/306.

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10

Ramachandran, B. "Scaling Dynamical Correlation Energy from Density Functional Theory Correlation Functionals†." Journal of Physical Chemistry A 110, no. 2 (January 2006): 396–403. http://dx.doi.org/10.1021/jp050584x.

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11

GALKA, ANDREAS, and GERD PFISTER. "DYNAMICAL CORRELATIONS ON RECONSTRUCTED INVARIANT DENSITIES AND THEIR EFFECT ON CORRELATION DIMENSION ESTIMATION." International Journal of Bifurcation and Chaos 13, no. 03 (March 2003): 723–32. http://dx.doi.org/10.1142/s0218127403006881.

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We investigate the structure of dynamical correlations on reconstructed attractors which were obtained by time-delay embedding of periodic, quasi-periodic and chaotic time series. Within the specific sampling of the invariant density by a finite number of vectors which results from embedding, we identify two separate levels of sampling, corresponding to two different types of dynamical correlations, each of which produces characteristic artifacts in correlation dimension estimation: the well-known trajectory bias and a characteristic oscillation due to periodic sampling. For the second artifact we propose random sampling as a new correction method which is shown to provide improved sampling and to reduce dynamical correlations more efficiently than it has been possible by the standard Theiler correction. For accurate numerical analysis of correlation dimension in a bootstrap framework both corrections should be combined. For tori and the Lorenz attractor we also show how to construct time-delay embeddings which are completely free of any dynamical correlations.
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12

Hu, Juju, Qiang Ke, and Yinghua Ji. "Dynamical decoupling with initial system-environment correlations." International Journal of Modern Physics B 35, no. 05 (January 29, 2021): 2150068. http://dx.doi.org/10.1142/s0217979221500685.

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Dynamical decoupling (DD) technique is one of the most successful methods to suppress decoherence in qubit systems. In this paper, we studied a solvable pure dephasing model and investigated how DD sequences and initial correlations affect this system. We gave the analytical expressions of decoherence functions and compared the decoherence suppression effects of DD pulses in Ohmic, sub-Ohmic and super-Ohmic environments. Our results show that (1) The initial system-environment correlation will cause additional decoherence. In order to control the dynamic process of open quantum system more accurately and effectively, the initial correlation between the system and reservoir must be considered. (2) High frequency DD pulses can significantly reduce the amplitude of the decoherence function even in the presence of initial system-environment correlations.
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13

AO, PING. "DYNAMICAL CORRELATION THEORY FOR AN ESCAPE PROCESS." Modern Physics Letters B 07, no. 13n14 (June 20, 1993): 927–34. http://dx.doi.org/10.1142/s021798499300093x.

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A dynamical theory which incorporates the electron-electron correlations and the effects of external magnetic fields for an electron escaping from a helium surface are presented. The degrees of freedom in the calculation of the escape rate is reduced from 3N to 3 as compared with other approach. Explicit expressions for the escape rate in various situations are obtained. In particular, in the weak parallel magnetic field limit, the tunneling rate has an exponential dependence quadratic with magnetic field strength and an unusual exponential increase linear with temperature.
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14

Kadtke, James, and Michael Kremliovsky. "Estimating dynamical models using generalized correlation functions." Physics Letters A 260, no. 3-4 (September 1999): 203–8. http://dx.doi.org/10.1016/s0375-9601(99)00527-7.

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15

Kitanine, N., J. M. Maillet, N. A. Slavnov, and V. Terras. "Dynamical correlation functions of the spin- chain." Nuclear Physics B 729, no. 3 (November 2005): 558–80. http://dx.doi.org/10.1016/j.nuclphysb.2005.08.046.

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16

Ritchie, Burke, and Charles A. Weatherford. "Quantum-Dynamical Theory of Electron Exchange Correlation." Advances in Physical Chemistry 2013 (March 20, 2013): 1–8. http://dx.doi.org/10.1155/2013/497267.

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The relationship between the spin of an individual electron and Fermi-Dirac statistics (FDS), which is obeyed by electrons in the aggregate, is elucidated. The relationship depends on the use of spin-dependent quantum trajectories (SDQT) to evaluate Coulomb’s law between any two electrons as an instantaneous interaction in space and time rather than as a quantum-mean interaction in the form of screening and exchange potentials. Hence FDS depends in an ab initio sense on the inference of SDQT from Dirac’s equation, which provides for relativistic Lorentz invariance and a permanent magnetic moment (or spin) in the electron’s equation of motion. Schroedinger’s time-dependent equation can be used to evaluate the SDQT in the nonrelativistic regime of electron velocity. Remarkably FDS is a relativistic property of an ensemble of electron, even though it is of order c0 in the nonrelativistic limit, in agreement with experimental observation. Finally it is shown that covalent versus separated-atoms limits can be characterized by the SDQT. As an example of the use of SDQT in a canonical structure problem, the energies of the 1Σg and 3Σu states of H2 are calculated and compared with the accurate variational energies of Kolos and Wolniewitz.
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17

Goldberg, E. C., and M. C. G. Passeggi. "Correlation effects in dynamical charge-transfer processes." Journal of Physics: Condensed Matter 5, no. 33A (August 16, 1993): A259—A260. http://dx.doi.org/10.1088/0953-8984/5/33a/087.

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18

Goldberg, E. C., E. R. Gagliano, and M. C. G. Passeggi. "Correlation effects in dynamical charge-transfer processes." Physical Review B 32, no. 7 (October 1, 1985): 4375–81. http://dx.doi.org/10.1103/physrevb.32.4375.

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19

Murao, K., F. Matsubara, and S. Inawashiro. "Dynamical spin correlation function in CsCopMg1-pCl3." Journal of Physics: Condensed Matter 4, no. 10 (March 9, 1992): 2641–50. http://dx.doi.org/10.1088/0953-8984/4/10/026.

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20

You, Cheol-Hwan, Ki-Ho Chang, Jun-Ho Lee, and Kyungsik Kim. "Dynamical behavior of the correlation between meteorological factors." Journal of the Korean Physical Society 71, no. 12 (July 31, 2017): 875–79. http://dx.doi.org/10.3938/jkps.71.875.

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21

Strahov, Eugene. "Dynamical correlation functions for products of random matrices." Random Matrices: Theory and Applications 04, no. 04 (October 2015): 1550020. http://dx.doi.org/10.1142/s2010326315500203.

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We introduce and study a family of random processes with a discrete time related to products of random matrices. Such processes are formed by singular values of random matrix products, and the number of factors in a random matrix product plays a role of a discrete time. We consider in detail the case when the (squared) singular values of the initial random matrix form a polynomial ensemble, and the initial random matrix is multiplied by standard complex Gaussian matrices. In this case, we show that the random process is a discrete-time determinantal point process. For three special cases (the case when the initial random matrix is a standard complex Gaussian matrix, the case when it is a truncated unitary matrix, or the case when it is a standard complex Gaussian matrix with a source) we compute the dynamical correlation functions explicitly, and find the hard edge scaling limits of the correlation kernels. The proofs rely on the Eynard–Mehta theorem, and on contour integral representations for the correlation kernels suitable for an asymptotic analysis.
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22

Sakai, Kazumitsu. "Dynamical correlation functions of theXXZmodel at finite temperature." Journal of Physics A: Mathematical and Theoretical 40, no. 27 (June 19, 2007): 7523–42. http://dx.doi.org/10.1088/1751-8113/40/27/007.

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23

Refolio, M. C., J. M. López Sancho, J. Rubio, and M. P. López Sancho. "Dynamical correlation-hole approach to the Hubbard model." Physical Review B 59, no. 8 (February 15, 1999): 5384–97. http://dx.doi.org/10.1103/physrevb.59.5384.

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24

Nishino, Tomotoshi, and Kazuo Ueda. "Dynamical correlation functions of one-dimensional Kondo insulators." Physica B: Condensed Matter 206-207 (February 1995): 813–15. http://dx.doi.org/10.1016/0921-4526(94)00593-k.

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25

Lesage, F., V. Pasquier, and D. Serban. "Dynamical correlation functions in the Calogero-Sutherland model." Nuclear Physics B 435, no. 3 (February 1995): 585–603. http://dx.doi.org/10.1016/0550-3213(94)00453-l.

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26

Giner, E., C. Angeli, A. Scemama, and J. P. Malrieu. "Orthogonal Valence Bond Hamiltonians incorporating dynamical correlation effects." Computational and Theoretical Chemistry 1116 (September 2017): 134–40. http://dx.doi.org/10.1016/j.comptc.2017.03.001.

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27

Li, Y., T. Sato, and K. L. Ishikawa. "High-harmonic generation enhanced by dynamical electron correlation." Journal of Physics: Conference Series 1412 (January 2020): 072012. http://dx.doi.org/10.1088/1742-6596/1412/7/072012.

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28

Paech, Kerstin. "Dynamical correlation length near the chiral critical point." European Physical Journal C 33, S1 (September 24, 2003): s627—s629. http://dx.doi.org/10.1140/epjcd/s2003-03-617-y.

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29

Becke, Axel D. "Density functionals for static, dynamical, and strong correlation." Journal of Chemical Physics 138, no. 7 (February 21, 2013): 074109. http://dx.doi.org/10.1063/1.4790598.

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30

Cao, Jianshu, and Gregory A. Voth. "Semiclassical approximations to quantum dynamical time correlation functions." Journal of Chemical Physics 104, no. 1 (January 1996): 273–85. http://dx.doi.org/10.1063/1.470898.

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31

Hou, Mo, Ying-Qing Xia, and Xi-Wen Hou. "Dynamical correlations of mutual information and tripartite entanglement for vibrational states in a trimer molecule." International Journal of Modern Physics B 29, no. 09 (April 7, 2015): 1550063. http://dx.doi.org/10.1142/s0217979215500630.

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Quantum mutual information and concurrence are two important measures of quantum correlations, and their similar behavior for a bipartite pure state calls for inspecting whether such a behavior remains for a multipartite pure state. The dynamical correlation of quantum mutual information and tripartite entanglement is analytically and numerically studied for initial states, total boson numbers and coupling parameters in a symmetric trimer molecule, where the entanglement is measured in terms of concurrence. A correlation parameter is introduced to describe the correlation between mutual information and concurrence. It is shown that both quantities are positively or anti-correlated in irregular manner. However, they exhibit completely positive correlation for suitable states, with their explicit expressions being presented for arbitrary model parameters. The dynamical correlation between bipartite and tripartite entanglement is discussed as well. Those shed new light on the understanding of quantum correlations of vibrational states in polyatomic molecules.
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32

Ulbikas, J., A. Čenys, D. Žemaitytė, and G. Varoneckas. "Correlation in the heart rate data." Nonlinear Analysis: Modelling and Control 2 (December 21, 1998): 141–48. http://dx.doi.org/10.15388/na.1998.2.0.15301.

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Variety of methods of nonlinear dynamics have been used for possibility of an analysis of time series in experimental physiology. Dynamical nature of experimental data was checked using specific methods. Statistical properties of the heart rate have been investigated. Correlation between of cardiovascular function and statistical properties of both, heart rate and stroke volume, have been analyzed. Possibility to use a data from correlations in heart rate for monitoring of cardiovascular function was discussed.
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33

Donner, R. V., and G. Balasis. "Correlation-based characterisation of time-varying dynamical complexity in the Earth's magnetosphere." Nonlinear Processes in Geophysics 20, no. 6 (November 12, 2013): 965–75. http://dx.doi.org/10.5194/npg-20-965-2013.

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Abstract. The dynamical behaviour of the magnetosphere is known to be a sensitive indicator for the response of the system to solar wind coupling. Since the solar activity commonly displays very interesting non-stationary and multi-scale dynamics, the magnetospheric response also exhibits a high degree of dynamical complexity associated with fundamentally different characteristics during periods of quiescence and magnetic storms. The resulting temporal complexity profile has been explored using several approaches from applied statistics, dynamical systems theory and statistical mechanics. Here, we propose an alternative way of looking at time-varying dynamical complexity of nonlinear geophysical time series utilising subtle but significant changes in the linear autocorrelation structure of the recorded data. Our approach is demonstrated to sensitively trace the dynamic signatures associated with intense magnetic storms, and to display reasonable skills in distinguishing between quiescence and storm periods. The potentials and methodological limitations of this new viewpoint are discussed in some detail.
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34

Krakovská, Anna. "Correlation Dimension Detects Causal Links in Coupled Dynamical Systems." Entropy 21, no. 9 (August 21, 2019): 818. http://dx.doi.org/10.3390/e21090818.

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It is becoming increasingly clear that causal analysis of dynamical systems requires different approaches than, for example, causal analysis of interconnected autoregressive processes. In this study, a correlation dimension estimated in reconstructed state spaces is used to detect causality. If deterministic dynamics plays a dominant role in data then the method based on the correlation dimension can serve as a fast and reliable way to reveal causal relationships between and within the systems. This study demonstrates that the method, unlike most other causal approaches, detects causality well, even for very weak links. It can also identify cases of uncoupled systems that are causally affected by a hidden common driver.
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35

Yamamoto, Takashi, and Mitsuhiro Arikawa. "Dynamical correlation functions of the spin Calogero-Sutherland model." Journal of Physics A: Mathematical and General 32, no. 18 (January 1, 1999): 3341–56. http://dx.doi.org/10.1088/0305-4470/32/18/309.

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36

Evangelista, Francesco A. "Perspective: Multireference coupled cluster theories of dynamical electron correlation." Journal of Chemical Physics 149, no. 3 (July 21, 2018): 030901. http://dx.doi.org/10.1063/1.5039496.

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37

Torres-Herrera, E. J., and Lea F. Santos. "Dynamical manifestations of quantum chaos: correlation hole and bulge." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 375, no. 2108 (October 30, 2017): 20160434. http://dx.doi.org/10.1098/rsta.2016.0434.

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A main feature of a chaotic quantum system is a rigid spectrum where the levels do not cross. We discuss how the presence of level repulsion in lattice many-body quantum systems can be detected from the analysis of their time evolution instead of their energy spectra. This approach is advantageous to experiments that deal with dynamics, but have limited or no direct access to spectroscopy. Dynamical manifestations of avoided crossings occur at long times. They correspond to a drop, referred to as correlation hole, below the asymptotic value of the survival probability and to a bulge above the saturation point of the von Neumann entanglement entropy and the Shannon information entropy. By contrast, the evolution of these quantities at shorter times reflects the level of delocalization of the initial state, but not necessarily a rigid spectrum. The correlation hole is a general indicator of the integrable–chaos transition in disordered and clean models and as such can be used to detect the transition to the many-body localized phase in disordered interacting systems. This article is part of the themed issue ‘Breakdown of ergodicity in quantum systems: from solids to synthetic matter’.
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38

Kühner, Till D., and Steven R. White. "Dynamical correlation functions using the density matrix renormalization group." Physical Review B 60, no. 1 (July 1, 1999): 335–43. http://dx.doi.org/10.1103/physrevb.60.335.

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39

Yang, Chou-Hsun, and Chao-Ping Hsu. "The dynamical correlation in spacer-mediated electron transfer couplings." Journal of Chemical Physics 124, no. 24 (June 28, 2006): 244507. http://dx.doi.org/10.1063/1.2207613.

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40

Pittalis, Stefano, Alain Delgado, and Carlo Andrea Rozzi. "Same-spin dynamical correlation effects on the electron localization." Journal of Self-Assembly and Molecular Electronics (SAME) 2015, no. 1 (2015): 1–14. http://dx.doi.org/10.13052/jsame2245-4551.2015008.

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41

Kutzelnigg, Werner. "Separation of strong (bond-breaking) from weak (dynamical) correlation." Chemical Physics 401 (June 2012): 119–24. http://dx.doi.org/10.1016/j.chemphys.2011.10.020.

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42

Baglin, F. G., and E. J. Rose. "Dynamical properties of supracritical methane via correlation function analysis." Chemical Physics Letters 210, no. 1-3 (July 1993): 84–88. http://dx.doi.org/10.1016/0009-2614(93)89104-p.

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43

Tran, Minh-Tien. "Cumulant approach to dynamical correlation functions at finite temperatures." Zeitschrift f�r Physik B Condensed Matter 95, no. 4 (December 1994): 515–18. http://dx.doi.org/10.1007/bf01313362.

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44

Leonel, S. A., and A. S. T. Pires. "Calculation of the out-of-plane dynamical correlation forCsNiF3." Physical Review B 54, no. 17 (November 1, 1996): 11944–46. http://dx.doi.org/10.1103/physrevb.54.11944.

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45

El Khatib, Muammar, Gian Luigi Bendazzoli, Stefano Evangelisti, Wissam Helal, Thierry Leininger, Lorenzo Tenti, and Celestino Angeli. "Beryllium Dimer: A Bond Based on Non-Dynamical Correlation." Journal of Physical Chemistry A 118, no. 33 (June 12, 2014): 6664–73. http://dx.doi.org/10.1021/jp503145u.

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46

Hohl, M., J. Roth, and H. R. Trebin. "Correlation functions and the dynamical structure factor of quasicrystals." European Physical Journal B 17, no. 4 (October 2000): 595–601. http://dx.doi.org/10.1007/s100510070096.

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47

Takaishi, Tetsuya. "Dynamical cross-correlation of multiple time series Ising model." Evolutionary and Institutional Economics Review 13, no. 2 (August 12, 2016): 455–68. http://dx.doi.org/10.1007/s40844-016-0051-4.

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48

Del Vecchio Del Vecchio, Giuseppe, and Benjamin Doyon. "The hydrodynamic theory of dynamical correlation functions in the XX chain." Journal of Statistical Mechanics: Theory and Experiment 2022, no. 5 (May 1, 2022): 053102. http://dx.doi.org/10.1088/1742-5468/ac6667.

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Abstract By the hydrodynamic linear response theory, dynamical correlation functions decay as power laws along certain velocities, determined by the flux Jacobian. Such correlations are obtained by hydrodynamic projections, and physically, they are due to propagating ‘sound waves’ or generalisation thereof, transporting conserved quantities between the observables. However, some observables do not emit sound waves, such as order parameters associated to symmetry breaking. In these cases correlation functions decay exponentially everywhere, a behaviour not captured by the hydrodynamic linear response theory. Focussing on spin–spin correlation functions in the XX quantum chain, we first review how hydrodynamic linear response works, emphasising that the necessary fluid cell averaging washes out oscillatory effects. We then show how, beyond linear response, Euler hydrodynamics can still predict the exponential decay of correlation functions of order parameters. This is done by accounting for the large-scale fluctuations of domain walls, via the recently developed ballistic fluctuation theory. We use the framework of generalised hydrodynamics, which is particularly simple in this model due to its free fermion description. In particular, this reproduces, by elementary calculations, the exponential decay in the celebrated formulae by Its et al (1993) and by Jie (1998), which were originally obtained by intricate Fredholm determinant analysis; and gives a new formula in a parameter domain where no result was obtained before. We confirm the results by numerical simulations.
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49

Martin, E. A., and J. Davidsen. "Estimating time delays for constructing dynamical networks." Nonlinear Processes in Geophysics 21, no. 5 (September 11, 2014): 929–37. http://dx.doi.org/10.5194/npg-21-929-2014.

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Abstract. Dynamical networks – networks inferred from multivariate time series – have been widely applied to climate data and beyond, resulting in new insights into the underlying dynamics. However, these inferred networks can suffer from biases that need to be accounted for to properly interpret the results. Here, we report on a previously unrecognized bias in the estimate of time delays between nodes in dynamical networks inferred from cross-correlations, a method often used. This bias results in the maximum correlation occurring disproportionately often at large time lags. This is of particular concern in dynamical networks where the large number of possible links necessitates finding the correct time lag in an automated way. We show that this bias can arise due to the similarity of the estimator to a random walk, and are able to map them to each other explicitly for some cases. For the random walk there is an analytical solution for the bias that is closely related to the famous Lévy arcsine distribution, which provides an upper bound in many other cases. Finally, we show that estimating the cross-correlation in frequency space effectively eliminates this bias. Reanalysing large lag links (from a climate network) with this method results in a distribution peaked near zero instead, as well as additional peaks at the originally assigned lag. Links that are reassigned smaller time lags tend to have a smaller distance between them, which indicates that the new time delays are physically reasonable.
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50

Dorfman, Konstantin E., and Shaul Mukamel. "Multidimensional photon correlation spectroscopy of cavity polaritons." Proceedings of the National Academy of Sciences 115, no. 7 (January 31, 2018): 1451–56. http://dx.doi.org/10.1073/pnas.1719443115.

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The strong coupling of atoms and molecules to radiation field modes in optical cavities creates dressed matter/field states known as polaritons with controllable dynamical and energy transfer properties. We propose a multidimensional optical spectroscopy technique for monitoring polariton dynamics. The response of a two-level atom to the time-dependent coupling to a single-cavity mode is monitored through time-and-frequency–resolved single-photon coincidence measurements of spontaneous emission. Polariton population and coherence dynamics and its variation with cavity photon number and controlled by gating parameters are predicted by solving the Jaynes–Cummings model.
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