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Superdiffusion in stochastic processes with long-range memory
Phys. Rev. E 114, 024150 – Published 24 August, 2026
DOI: https://doi.org/10.1103/j7d9-zlh9
Abstract
We investigate non-Markovian stochastic processes with long-range temporal memory described by a generalized Langevin (Mori-Zwanzig) equation with a power-law memory kernel. Special attention is paid to the critical regime where the system parameters lie on the boundary separating stable and unstable dynamics, leading to diffusionlike behavior with memory. We derive analytical expressions for the asymptotic behavior of the process and show that, under appropriate conditions on the memory kernel, the system exhibits superdiffusive scaling. In particular, we establish an explicit relation between the exponent of the power-law memory kernel and the growth rate of the variance. Analytical predictions are supported by numerical simulations, confirming the emergence of superdiffusive regimes in systems with long-range memory.
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References (20)
- M. te Vrugt and R. Wittkowski, Mori-Zwanzig projection operator formalism for far-from-equilibrium systems with time-dependent Hamiltonians, Phys. Rev. E 99, 062118 (2019).
- S. Lepri, Thermal Transport in Low Dimensions, Lecture Notes in Physics Vol. 921 (Springer, Cham, 2016).
- A. Dhar, A. Kundu, and A. Kundu, Anomalous heat transport in one dimensional systems: A description using non-local fractional-type diffusion equation, Front. Phys. 7, 159 (2019) .
- G. E. Uhlenbeck and L. S. Ornstein, On the theory of the Brownian motion, Phys. Rev. 36, 823 (1930).
- N. Van Kampen, Stochastic Processes in Physics and Chemistry, North-Holland Personal Library (North Holland, Amsterdam, 2011).
- C. Gardiner, Handbook of Stochastic Methods for Physics, Chemistry, and the Natural Sciences, Current Topics in Neuroendocrinology (Springer-Verlag, Berlin, 1983).
- W. Horsthemke and R. Lefever, Noise-Induced Transitions: Theory and Applications in Physics, Chemistry, and Biology, Springer Series in Synergetics (Springer, Berlin, 2006).
- H. Mori, Transport, collective motion, and Brownian motion, Prog. Theor. Phys. 33, 423 (1965).
- R. Zwanzig, Ensemble method in the theory of irreversibility, J. Chem. Phys. 33, 1338 (1960).
- S. S. Melnyk, V. A. Yampol'skii, and O. V. Usatenko, Continuous stochastic processes with nonlocal memory, Phys. Rev. E 100, 052141 (2019).
- S. S. Melnyk, O. V. Usatenko, and V. A. Yampol'skii, Memory-dependent noise-induced resonance and diffusion in non-Markovian systems, Phys. Rev. E 103, 032139 (2021).
- L. Rogers and D. Williams, Diffusions, Markov Processes, and Martingales, Cambridge Mathematical Library Vol. 2 (Cambridge University, Cambridge, England, 2000).
- K. Wang and M. Tokuyama, Nonequilibrium statistical description of anomalous diffusion, Phys. A 265, 341 (1999).
- S. Melnyk, O. Usatenko, and V. Yampol'skii, Source code and datasets for the paper “Super-diffusion in stochastic processes with long-range memory” [Computer software], Zenodo, 2026, https://doi.org/10.5281/zenodo.21740686.
- R. N. Mantegna and H. E. Stanley, Introduction to Econophysics: Correlations and Complexity in Finance (Cambridge University, Cambridge, England, 1999).
- G. Calafiore, L. El Ghaoui, G. Fracastoro, and A. Tsai, Financial Data Science (Cambridge University Press, Cambridge, 2025).
- P. V. Le, J. T. Randerson, R. Willett, S. Wright, P. Smyth, C. Guilloteau, A. Mamalakis, and E. Foufoula-Georgiou, Climate-driven changes in the predictability of seasonal precipitation, Nat. Commun. 14, 3822 (2023).
- I. Price, A. Sanchez-Gonzalez, F. Alet, T. R. Andersson, A. El-Kadi, D. Masters, T. Ewalds, J. Stott, S. Mohamed, P. Battaglia, et al., Probabilistic weather forecasting with machine learning, Nature (London) 637, 84 (2025).
- L. E. Reichl, Translational Brownian motion in a fluid with internal degrees of freedom, Phys. Rev. A 24, 1609 (1981).
- A. Aharony, Anomalous diffusion on percolating clusters, in Scaling Phenomena in Disordered Systems, edited by R. Pynn and A. Skjeltorp (Springer, Boston, 1991), pp. 289–300.