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Engineered dissipation for quantum information science
PM Harrington, EJ Mueller, KW Murch - Nature Reviews Physics, 2022 - nature.com
Quantum information processing relies on the precise control of non-classical states in the
presence of many uncontrolled environmental degrees of freedom. The interactions …
presence of many uncontrolled environmental degrees of freedom. The interactions …
Quantum algorithms for quantum dynamics
A Miessen, PJ Ollitrault, F Tacchino… - Nature Computational …, 2023 - nature.com
Among the many computational challenges faced across different disciplines, quantum-
mechanical systems pose some of the hardest ones and offer a natural playground for the …
mechanical systems pose some of the hardest ones and offer a natural playground for the …
Artificial intelligence and machine learning for quantum technologies
M Krenn, J Landgraf, T Foesel, F Marquardt - Physical Review A, 2023 - APS
In recent years the dramatic progress in machine learning has begun to impact many areas
of science and technology significantly. In the present perspective article, we explore how …
of science and technology significantly. In the present perspective article, we explore how …
Nonequilibrium boundary-driven quantum systems: Models, methods, and properties
GT Landi, D Poletti, G Schaller - Reviews of Modern Physics, 2022 - APS
Recent years have seen tremendous progress in the theoretical understanding of quantum
systems driven dissipatively by coupling to different baths at their edges. This was possible …
systems driven dissipatively by coupling to different baths at their edges. This was possible …
NetKet 3: Machine learning toolbox for many-body quantum systems
F Vicentini, D Hofmann, A Szabó, D Wu… - SciPost Physics …, 2022 - scipost.org
We introduce version 3 of NetKet, the machine learning toolbox for many-body quantum
physics. NetKet is built around neural-network quantum states and provides efficient …
physics. NetKet is built around neural-network quantum states and provides efficient …
Machine learning for quantum matter
J Carrasquilla - Advances in Physics: X, 2020 - Taylor & Francis
Quantum matter, the research field studying phases of matter whose properties are
intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter …
intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter …
Fermionic neural-network states for ab-initio electronic structure
K Choo, A Mezzacapo, G Carleo - Nature communications, 2020 - nature.com
Neural-network quantum states have been successfully used to study a variety of lattice and
continuous-space problems. Despite a great deal of general methodological developments …
continuous-space problems. Despite a great deal of general methodological developments …
Photonic materials in circuit quantum electrodynamics
I Carusotto, AA Houck, AJ Kollár, P Roushan… - Nature Physics, 2020 - nature.com
Photonic synthetic materials provide an opportunity to explore the role of microscopic
quantum phenomena in determining macroscopic material properties. There are, however …
quantum phenomena in determining macroscopic material properties. There are, however …
Variational quantum Monte Carlo method with a neural-network ansatz for open quantum systems
A Nagy, V Savona - Physical review letters, 2019 - APS
The possibility to simulate the properties of many-body open quantum systems with a large
number of degrees of freedom (dof) is the premise to the solution of several outstanding …
number of degrees of freedom (dof) is the premise to the solution of several outstanding …
Simulation methods for open quantum many-body systems
H Weimer, A Kshetrimayum, R Orús - Reviews of Modern Physics, 2021 - APS
Coupling a quantum many-body system to an external environment dramatically changes its
dynamics and offers novel possibilities not found in closed systems. Of special interest are …
dynamics and offers novel possibilities not found in closed systems. Of special interest are …