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Modelling non-markovian quantum processes with recurrent neural networks

Leonardo Banchi, Edward Grant, Andrea Rocchetto, Simone Severini
2018 New Journal of Physics  
Quantum systems interacting with an unknown environment are notoriously difficult to model, especially in presence of non-Markovian and non-perturbative effects.  ...  Here we introduce a neural network based approach, which has the mathematical simplicity of the Gorini-Kossakowski-Sudarshan-Lindblad master equation, but is able to model non-Markovian effects in different  ...  Part of this work was conducted while AR and SS were at the Institut Henri Poincaré in Paris. EG would further like to acknowledge support from Rahko Limited.  ... 
doi:10.1088/1367-2630/aaf749 fatcat:yp3rfwhvhvglvnpccnpflkhunu

A discrete memory-kernel for multi-time correlations in non-Markovian quantum processes [article]

Mathias R. Jørgensen, Felix A. Pollock
2020 arXiv   pre-print
As an illustration of the utility of the method, we study the build-up of system-environment correlations in the paradigmatic spin-boson model, and compute steady-state emission spectra, taking fully into  ...  account system-environment correlations present in the steady state.  ...  Furthermore we could study the build up of system-environment correlations during the dynamical evolution, by looking at the relative entropy measure of non-Markovianity.  ... 
arXiv:2007.03234v1 fatcat:dllr6ru2kvdktogg76wczuc2g4

Interactive Learning of Temporal Features for Control: Shaping Policies and State Representations From Human Feedback

Rodrigo Perez-Dattari, Carlos Celemin, Giovanni Franzese, Javier Ruiz-del-Solar, Jens Kober
2020 IEEE robotics & automation magazine  
Background and Related Work Our method combines elements from SRL, IL, and memory in NN models to build a framework that enables non-expert teachers to interactively shape policies in tasks with non-Markovian  ...  The combination of SRL and the teacher' s feedback is a powerful strategy for efficient learning of temporal features from raw observations in non-Markovian environments.  ...  Background and Related Work Our method combines elements from SRL, IL, and memory in NN models to build a framework that enables non-expert teachers to interactively shape policies in tasks with non-Markovian  ... 
doi:10.1109/mra.2020.2983649 fatcat:vl43q4xjb5bupcrp4kqk2r25ue

Memory Strength and Recoverability of Non-Markovian Quantum Stochastic Processes [article]

Philip Taranto, Felix A. Pollock, Kavan Modi
2019 arXiv   pre-print
We then apply our framework to an exactly solvable non-Markovian model, highlighting the decay of memory for certain instruments that justify its truncation.  ...  Simulating complex processes can be intractable when memory effects are present, often necessitating approximations in the length or strength of the memory.  ...  Memory effects thus pervade quantum evolutions, resulting in non-Markovian dynamics [2] .  ... 
arXiv:1907.12583v1 fatcat:cjijruqrgzaqldlihn6yrc6woi

Exploiting Non-Markovianity for Quantum Control

Daniel M. Reich, Nadav Katz, Christiane P. Koch
2015 Scientific Reports  
The ladder is immersed in an environment of two-level systems. Strongly coupled two-level systems lead to non-Markovian effects, whereas the weakly coupled ones result in single-exponential decay.  ...  When the environment of an open quantum system is non-Markovian, amplitude and phase flow not only from the system into the environment but also back.  ...  How the build-up of memory influences controllability is currently unknown, and control strategies for non-Markovian dynamics of open quantum systems remain largely uncharted territory.  ... 
doi:10.1038/srep12430 pmid:26199059 pmcid:PMC4510487 fatcat:tr53z4ejtnf5jpaukuy6mxedra

Optimal non-Markovian search strategies with n-step memory [article]

Hugues Meyer, Heiko Rieger
2021 arXiv   pre-print
probabilities for non-Markovian random walks on a lattice.  ...  Stochastic search processes are ubiquitous in nature and are expected to become more efficient when equipped with a memory, where the searcher has been before.  ...  of non-Markovian search processes in general and of the autochemotactic in particular, and present results for the optimal search strategies.  ... 
arXiv:2105.10207v2 fatcat:pfza5aa5pzez7mzb5x6rk37jvm

Controlling open quantum systems: tools, achievements, and limitations

Christiane P Koch
2016 Journal of Physics: Condensed Matter  
A major obstacle is decoherence which is caused by interaction with the environment. Optimal control theory is a tool that can be used to identify control strategies in the presence of decoherence.  ...  Optimal control theory is also a useful tool to exploit the environment for control. We discuss examples and point out possible future extensions.  ...  non-Markovianity.  ... 
doi:10.1088/0953-8984/28/21/213001 pmid:27143501 fatcat:26qx4krmozambbnmyp43g4c7eq

Optimal Prediction by Cellular Signaling Networks

Nils B. Becker, Andrew Mugler, Pieter Rein ten Wolde
2015 Physical Review Letters  
We study how accurately linear signaling networks in cells can predict future signals.  ...  Multilayer networks allow oscillatory kernels that can optimally predict non-Markovian signals.  ...  Moreover, a slow response may enhance prediction by building a memory of the signal history which is informative about the future signal.  ... 
doi:10.1103/physrevlett.115.258103 pmid:26722947 fatcat:5kpmnfklq5fnjbki2knqeapqoq

Learning Without State-Estimation in Partially Observable Markovian Decision Processes [chapter]

Satinder P. Singh, Tommi Jaakkola, Michael I. Jordan
1994 Machine Learning Proceedings 1994  
Many realworld decision tasks, however, are inherently non-Markovian, i.e., the state of the environment is only incompletely known to the learning agent.  ...  In this paper we consider only partially observable MDPs (POMDPs), a useful class of non-Markovian decision processes.  ...  The project was also supported by NSF grant ASC-9217041 in support of the Center for Biological and Computational Learning at MIT, including funds provided by D ARPA under the HPCC program.  ... 
doi:10.1016/b978-1-55860-335-6.50042-8 dblp:conf/icml/SinghJJ94 fatcat:22vp5lktdzbbxbe7vslfeb35qi

Precursors of non-Markovianity

Steve Campbell, Maria Popovic, Dario Tamascelli, Bassano Vacchini
2019 New Journal of Physics  
In particular, we consider a quantitative framework to assess the role that established system-environment correlations together with changes in environmental states play in an emerging non-Markovian dynamics  ...  Using the paradigm of information backflow to characterize a non-Markovian evolution, we introduce so-called precursors of non-Markovianity, i.e. necessary properties that the system and environment state  ...  We have shown that the evaluation of these precursors of non-Markovianity can be simplified when the environment can be decomposed into smaller constituent parts, thus leading to a strategy of general  ... 
doi:10.1088/1367-2630/ab1ed6 fatcat:ql7ubeoxwvar7lyothg7ds5pny

Precursors of non-Markovianity [article]

Steve Campbell, Maria Popovic, Dario Tamascelli, Bassano Vacchini
2019 arXiv   pre-print
In particular, we consider a quantitative framework to assess the role that established system-environment correlations together with changes in environmental states play in an emerging non-Markovian dynamics  ...  Using the paradigm of information backflow to characterize a non-Markovian evolution, we introduce so-called precursors of non-Markovianity, i.e. necessary properties that the system and environment state  ...  We have shown that the evaluation of these precursors of non-Markovianity can be simplified when the environment can be decomposed into smaller constituent parts, thus leading to a strategy of general  ... 
arXiv:1902.03156v1 fatcat:xboe7o5b3rgd7mfhreaqb5pxj4

Optimal quantum thermometry by dephasing

Dong Xie, Chunling Xu, An Min Wang
2017 Quantum Information Processing  
Base on it, we define a new way to measure non-Markovian effect.  ...  Decoherence often happens in the quantum world. We try to utilize quantum dephasing to build an optimal thermometry.  ...  MEASURING NON-MARKOVIAN EFFECT If the external environments have memory, there is non-Markovian effect, which is quantified by a lot of ways [12, [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27]  ... 
doi:10.1007/s11128-017-1605-z fatcat:irl66pjtwbguxmmbgwxvfgqe5u

Protecting quantum resources via frequency modulation of qubits in leaky cavities

Ali Mortezapour, Rosario Lo Franco
2018 Scientific Reports  
The dynamics of open quantum systems can be classified in Markovian (memoryless) and non-Markovian (memory-keeping) regimes 52,53 .  ...  Differently, non-Markovian regime implies that the past history of the system affects the present one: such a memory effect results in an information feedback from the environment to the system 48,52-62  ...  Non-Markovianity.  ... 
doi:10.1038/s41598-018-32661-2 pmid:30250130 pmcid:PMC6155175 fatcat:owsa3l2pijexzg3bnaziwgaarm

Protecting quantum resources via frequency modulation of qubits in leaky cavities [article]

Ali Mortezapour, Rosario Lo Franco
2018 arXiv   pre-print
We relate this behavior to the inhibition of the qubit effective decay rate rather than to stronger memory effects (non-Markovianity) of the system.  ...  Finding strategies to preserve quantum resources in open systems is nowadays a main requirement for reliable quantum-enhanced technologies.  ...  Differently, non-Markovian regime implies that the past history of the system affects the present one: such a memory effect results in an information feedback from the environment to the system [48, [  ... 
arXiv:1801.02165v2 fatcat:mhj5y3vn6nbo3gvz4rri5b6tle

Learning Non-Markovian Reward Models in MDPs [article]

Gavin Rens, Jean-François Raskin
2020 arXiv   pre-print
non-Markovian reward function.  ...  There are situations in which an agent should receive rewards only after having accomplished a series of previous tasks. In other words, the reward that the agent receives is non-Markovian.  ...  optimally in M under MR in a finite memory strategy (the memory required for MR; but memoryless if viewed as P = M ⊗ λ MR).  ... 
arXiv:2001.09293v1 fatcat:ziawcsiu4jgyrjvf4c3ywf4pcm
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