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| Open quantum systems | |
|---|---|
| Name | Open quantum systems |
| Field | Quantum physics |
| Related | Quantum decoherence, Quantum information |
Open quantum systems Open quantum systems study the dynamics of quantum systems interacting with external environments such as baths, reservoirs, detectors, or measurement apparatus. They bridge foundational questions about the quantum-to-classical transition addressed in debates involving Niels Bohr, Albert Einstein, Erwin Schrödinger, Werner Heisenberg, and institutions like Cavendish Laboratory and Institute for Advanced Study. Modern research links experimental platforms developed at places such as Bell Labs, IBM Research, Harvard University, MIT Lincoln Laboratory, and Max Planck Institute for Quantum Optics with theoretical programs influenced by figures including Hendrik Casimir, Lev Landau, Richard Feynman, John von Neumann, and Rudolf Peierls.
Open quantum systems quantify how a principal quantum system exchanges energy, particles, and information with an environment. Foundational experiments at CERN, Rutherford Appleton Laboratory, Los Alamos National Laboratory, Caltech, and Stanford University demonstrated environmental effects relevant to superconducting qubits developed by groups at Yale University and Google Quantum AI. The field informs technologies pursued by companies such as Microsoft, Intel Corporation, D-Wave Systems, and agencies like DARPA and National Institute of Standards and Technology.
The formal structure builds on quantum statistical mechanics from schools including Kadanoff–Baym methods and formalisms by Rolf Landauer, Lev Keldysh, Gordon Baym, and Leo Kadanoff. One models system-plus-environment Hamiltonians influenced by work at Bell Labs and theoretical contributions from Hermann Weyl, Paul Dirac, Max Born, Eugene Wigner, and John Bell. Tools include influence functionals introduced by Richard Feynman and Frank Vernon, projection-operator techniques by Hendrik Nakajima and Shun-ichi Zwanzig, and path-integral approaches used in contexts like the Kondo effect studied at Bell Laboratories. Connections extend to symmetry and topology research linked to Michael Berry, Tony Leggett, and Frank Wilczek.
Master equations describe reduced dynamics through generators such as the Gorini–Kossakowski–Sudarshan–Lindblad form derived by Vladimir Gorini, Gilles Kossakowski, E. C. G. Sudarshan, and Göran Lindblad. Completely positive trace-preserving maps (CPTP) follow from results related to Paul Dirac and mathematical frameworks studied at Princeton University and University of Cambridge. Non-Markovian techniques cite influence from work by H.-P. Breuer, Francesco Petruccione, Alberto Recati, and numerical schemes developed at Los Alamos National Laboratory. Semigroup theory and dilation theorems connect to mathematicians at Institut des Hautes Études Scientifiques and École Normale Supérieure influenced by I. M. Gelfand.
Decoherence mechanisms explain suppression of quantum interference studied in experiments like those at Harvard, Bell Labs, and École Polytechnique and discussed by theorists Wojciech Zurek, Dietrich Walls, Howard Carmichael, and Eugene Zubarev. Dissipative phenomena relate to relaxation in ionic traps pioneered at NIST and superconducting circuit losses characterized by teams at Yale, UCSB, and IBM Research – Almaden. Decoherence underpins conceptual analyses by Erwin Schrödinger (through thought experiments), critiques by John Bell, and developments in quantum measurement theory at Los Alamos National Laboratory and Perimeter Institute.
Stochastic unravelings and quantum jump methods trace to experimental and theoretical advances by Howard Carmichael, Graham Milburn, Klaus Mølmer, and H. J. Carmichael with laboratory realizations at Max Planck Institute for Quantum Optics, CERN, and NIST. Quantum Monte Carlo trajectory techniques influenced numerical work at Lawrence Livermore National Laboratory and RAL (Rutherford Appleton Laboratory), and experimental feedback control connects to projects at Caltech and ETH Zurich led by groups influenced by Serge Haroche and David Wineland.
Open-system theory enables error modeling in quantum error correction schemes applied at Google Quantum AI, IBM, and Microsoft Research and underlies implementations of quantum sensors from teams at NIST, EPFL, Imperial College London, and University of Tokyo. Platforms include trapped ions (advances by David Wineland at NIST), superconducting circuits (work at Yale University and University of California, Berkeley), quantum dots studied at IBM Thomas J. Watson Research Center and University of Cambridge, and cold atoms experiments at Max Planck Institute for Quantum Optics and Joint Quantum Institute. Applications span quantum thermodynamics investigated at Los Alamos National Laboratory and École Normale Supérieure, quantum metrology in projects by National Physical Laboratory (UK), and quantum biology collaborations involving Harvard Medical School and Princeton University.
Analytical methods use spectral theory advanced at Institute for Advanced Study and computational methods draw on tensor-network algorithms developed at École Polytechnique Fédérale de Lausanne (EPFL), Perimeter Institute, and University of Waterloo. Numerical approaches include matrix product states used by groups at Max Planck Institute for the Physics of Complex Systems and stochastic wavefunction techniques implemented at Lawrence Berkeley National Laboratory. Optimization and control theory contributions come from researchers at California Institute of Technology and Stanford University integrating methods like dynamical mean-field theory shaped by Max Planck Institute for Solid State Research.