Koopman analysis of quantum systems*
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Publication:5057844
DOI10.1088/1751-8121/ac7d22OpenAlexW4293149789MaRDI QIDQ5057844
Stefan Klus, Sebastian Peitz, Feliks Nüske
Publication date: 1 December 2022
Published in: Journal of Physics A: Mathematical and Theoretical (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2201.12062
stochastic controlstochastic differential equationsSchrödinger equationquantum mechanicsmachine learningKoopman operator
Related Items (2)
Overcoming the timescale barrier in molecular dynamics: Transfer operators, variational principles and machine learning ⋮ Finite-data error bounds for Koopman-based prediction and control
Cites Work
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- A kernel-based method for data-driven Koopman spectral analysis
- On the numerical approximation of the Perron-Frobenius and Koopman operator
- Data-driven model reduction and transfer operator approximation
- A data-driven approximation of the koopman operator: extending dynamic mode decomposition
- The Fokker-Planck equation. Methods of solution and applications.
- Chaos, fractals, and noise: Stochastic aspects of dynamics.
- An analytic framework for identifying finite-time coherent sets in time-dependent dynamical systems
- Tensor-based computation of metastable and coherent sets
- Data-driven approximation of the Koopman generator: model reduction, system identification, and control
- Variational approach for learning Markov processes from time series data
- Eigendecompositions of transfer operators in reproducing kernel Hilbert spaces
- Controlled Markov processes and viscosity solutions
- On dynamic mode decomposition: theory and applications
- Applied Koopmanism
- Dynamic mode decomposition of numerical and experimental data
- Tensor-based dynamic mode decomposition
- Pathwise Stochastic Optimal Control
- Hamiltonian Systems and Transformation in Hilbert Space
- Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator
- Quantum Theory for Mathematicians
- Data-Driven Model Predictive Control using Interpolated Koopman Generators
- Stochastic Processes and Applications
- Kernel methods for detecting coherent structures in dynamical data
- Transport in time-dependent dynamical systems: Finite-time coherent sets
- Space-Time Approach to Non-Relativistic Quantum Mechanics
- Linearly Recurrent Autoencoder Networks for Learning Dynamics
- A Variational Approach to Modeling Slow Processes in Stochastic Dynamical Systems
- RELATIONS BETWEEN TWO SETS OF VARIATES
- On Distributions of Certain Wiener Functionals
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