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Univariate superpositions of Ornstein--Uhlenbeck-type processes (OU), called supOU processes, provide a class of continuous time processes capable of exhibiting long memory behavior. This paper introduces multivariate supOU processes and…

Probability · Mathematics 2011-01-04 Ole Eiler Barndorff-Nielsen , Robert Stelzer

This paper investigates the continuous-time limit of score-driven models with long memory. By extending score-driven models to incorporate infinite-lag structures with coefficients exhibiting heavy-tailed decay, we establish their weak…

Probability · Mathematics 2025-12-09 Yinhao Wu , Ping He

Stochastic processes are as ubiquitous throughout the quantitative sciences as they are notorious for being difficult to simulate and predict. In this letter we propose a unitary quantum simulator for discrete-time stochastic processes…

Quantum Physics · Physics 2018-07-06 Felix C. Binder , Jayne Thompson , Mile Gu

For classical Markovian stochastic systems, past and future events become statistically independent when conditioned to a given state at the present time. Memory non-Markovian effects break this condition, inducing a non-vanishing…

Quantum Physics · Physics 2018-12-14 Adrián A. Budini

Based on some recent work of the author on stochastic approximation in non-markovian environments, the situation when the driving random process is non-ergodic in addition to being non-markovian is considered. Using this, we propose an…

Machine Learning · Statistics 2026-03-24 Vivek Shripad Borkar

It is common, when dealing with quantum processes involving a subsystem of a much larger composite closed system, to treat them as effectively memory-less (Markovian). While open systems theory tells us that non-Markovian processes should…

Quantum Physics · Physics 2019-05-02 Pedro Figueroa-Romero , Kavan Modi , Felix A. Pollock

We study a class of multipartite open quantum dynamics for systems of arbitrary number of qubits. The non-Markovian quantum master equation can involve arbitrary single or multipartite and time-dependent dissipative coupling mechanisms,…

Quantum Physics · Physics 2021-09-09 Adrián A. Budini , Juan P. Garrahan

In this paper, we are interested in linear prediction of a particular kind of stochastic process, namely a marked temporal point process. The observations are event times recorded on the real line, with marks attached to each event. We show…

Methodology · Statistics 2022-07-18 Maximilian Aigner , Valérie Chavez-Demoulin

The study of quantum dynamics featuring memory effects has always been a topic of interest within the theory of open quantum system, which is concerned about providing useful conceptual and theoretical tools for the description of the…

Quantum Physics · Physics 2020-08-25 Bassano Vacchini

Using a real-time path integral approach we develop an algorithm to calculate multi-time correlation functions of open few-level quantum systems that is applicable to highly nonequilibrium dynamics. The calculational scheme fully keeps the…

Mesoscale and Nanoscale Physics · Physics 2018-09-12 Michael Cosacchi , Moritz Cygorek , Florian Ungar , Andreas M. Barth , Alexei Vagov , Vollrath Martin Axt

The paper considers the problem of estimating the parameters in a continuous time regression model with a non-Gaussian noise of pulse type. The noise is specified by the Ornstein-Uhlenbeck process driven by the mixture of a Brownian motion…

Statistics Theory · Mathematics 2019-09-17 Evgeny Pchelintsev

The expansion of a stochastic Liouville equation for the coupled evolution of a quantum system and an Ornstein-Uhlenbeck process into a hierarchy of coupled differential equations is a useful technique that simplifies the simulation of…

Quantum Physics · Physics 2012-10-02 Mohan Sarovar , Matthew D. Grace

In the last years, the application of machine learning methods has become increasingly relevant in different fields of physics. One of the most significant subjects in the theory of open quantum systems is the study of the characterization…

Quantum Physics · Physics 2021-03-03 Felipe F. Fanchini , Göktuğ Karpat , Daniel Z. Rossatto , Ariel Norambuena , Raúl Coto

We extend the Longstaff-Schwartz algorithm for approximately solving optimal stopping problems on high-dimensional state spaces. We reformulate the optimal stopping problem for Markov processes in discrete time as a generalized statistical…

Probability · Mathematics 2007-05-23 Daniel Egloff

We demonstrate the equivalence of a Non--Markovian evolution equation with a linear memory--coupling and a Fokker--Planck equation (FPE). In case the feedback term offers a direct and permanent coupling of the current probability density to…

Statistical Mechanics · Physics 2009-11-11 Knud Zabrocki , Steffen Trimper , Svetlana Tatur , Reinhard Mahnke

We extend the Nakajima-Zwanzig projection operator technique to the determination of multitime correlation functions of open quantum systems. The correlation functions are expressed in terms of certain multitime homogeneous and…

Quantum Physics · Physics 2017-02-16 Anton Ivanov , Heinz-Peter Breuer

Generative modeling via stochastic processes has led to remarkable empirical results as well as to recent advances in their theoretical understanding. In principle, both space and time of the processes can be discrete or continuous. In this…

Machine Learning · Statistics 2024-05-07 Ludwig Winkler , Lorenz Richter , Manfred Opper

We derive a non-Markovian theory for waiting time distributions of consecutive single electron transfer events. The presented microscopic Pauli rate equation formalism couples the open electrodes to the many-body system, allowing to take…

Mesoscale and Nanoscale Physics · Physics 2015-05-14 Sven Welack , YiJing Yan

We explore two notions of stationary processes. The first is called a random-step Markov process in which the stationary process of states, $(X_i)_{i \in \mathbb{Z}}$ has a stationary coupling with an independent process on the positive…

Probability · Mathematics 2014-10-07 Neal Bushaw , Karen Gunderson , Steven Kalikow

Natural spatiotemporal processes can be highly non-stationary in many ways, e.g. the low-level non-stationarity such as spatial correlations or temporal dependencies of local pixel values; and the high-level variations such as the…

Machine Learning · Computer Science 2019-04-23 Yunbo Wang , Jianjin Zhang , Hongyu Zhu , Mingsheng Long , Jianmin Wang , Philip S Yu