Journal Club for Quantum Physics and Machine Learning
Schedule
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Next Journal Club Meeting: 13th December 2022, 6:00 pm CET. Â
Speaker: Michael Goerz
Affiliation: Stanford University
Title:Â Quantum Optimal Control via Semi-Automatic Differentiation
Reference: arXiv:2205.15044
URL: https://arxiv.org/abs/2205.15044
Abstract:Â We develop a framework of "semi-automatic differentiation" that combines existing gradient-based methods of quantum optimal control with automatic differentiation. The approach allows to optimize practically any computable functional and is implemented in two open source Julia packages, GRAPE.jl and Krotov.jl, part of the QuantumControl.jl framework. Our method is based on formally rewriting the optimization functional in terms of propagated states, overlaps with target states, or quantum gates. An analytical application of the chain rule then allows to separate the time propagation and the evaluation of the functional when calculating the gradient. The former can be evaluated with great efficiency via a modified GRAPE scheme. The latter is evaluated with automatic differentiation, but with a profoundly reduced complexity compared to the time propagation. Thus, our approach eliminates the prohibitive memory and runtime overhead normally associated with automatic differentiation and facilitates further advancement in quantum control by enabling the direct optimization of non-analytic functionals for quantum information and quantum metrology, especially in open quantum systems. We illustrate and benchmark the use of semi-automatic differentiation for the optimization of perfectly entangling quantum gates on superconducting qubits coupled via a shared transmission line. This includes the first direct optimization of the non-analytic gate concurrence.
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Upcoming Journal Club meetings:
Date | Time | Speaker | Affiliation | Reference |
13th December 2022 | Â 6:00pm CET | Â Michael Goerz | Â Stanford University | Quantum Optimal Control via Semi-Automatic Differentiation |
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Past Journal Club Meetings:
Date | Time | Speaker | Affiliation | Reference |
29th November 2022 | 5:30pm CET | Abigail McClain Gomez | Harvard University | Reconstructing quantum states using basis-enhanced Born machines |
15th November 2022 | 5:30pm CET | Nicolas Sadoune | University of Munich / MCQST | Unsupervised Interpretable Learning of Phases From Many-Qubit Systems |
 1st November 2022 |  5:30pm CET | Flavia Alejandra Gómez AlbarracÃn | University of La Plata |  Machine learning techniques to construct detailed phase diagrams for skyrmion system |
18th October 2022 | 5:30pm CET | Riccardo Fabbricatore | Skolkovo Institute of Science and Technology | Gradient dynamics in reinforcement learning |
4th October 2022Â | Â 5:30pm CET | Â Bogdan Zviazhynski | Â University of Cambridge | Â Unveil the unseen: Exploit information hidden in noise |
21st June 2022Â | 5:30pm CET | Javier Robledo Moreno | Flatiron Institute / NYU |
Fermionic wave functions from neural-network constrained hidden states |
 7th June 2022 | 5:30pm CET |  Francesco Carnazza |  Universität Tübingen | |
24th May 2022 | 5:30pm CET | Niklas Käming |  Universität Hamburg |
 Unsupervised machine learning of topological phase transitions from experimental data |
10th May 2022 | 5:30pm CET | Â Julian Arnold | University of Basel |
Replacing neural networks by optimal analytical predictors for the detection of phase transitions |
26th April 2022 | 5:30pm CET | Katerina Gratsea | ICFO | |
12th April 2022 | 5:30pm CET | Â Anna Dawid | Â University of Warsaw / ICFO |
Hessian-based toolbox for reliable and interpretable machine learning in physics |
12th December 2021 | 5:30pm CET | Jonathon Brown | Queen's University Belfast | Reinforcement learning-enhanced protocols for coherent population-transfer in three-level quantum systems |
7th December 2021 | 5:30pm CET | M. Michael Denner | University of Zürich | Efficient learning of a one-dimensional density functional theory |
23rd November 2021 |  5:30pm CET | Robert Huang | California Institute of Technology | Provably efficient machine learning for quantum many-body problems |
9th November 2021 |  5:30pm CET | Paolo Andrea Erdman | Freie Universität Berlin | Identifying optimal cycles in quantum thermal machines with reinforcement-learning |
26th October 2021 |  5:30pm CET | Maciej Koch-Janusz | University of Zurich /  University of Chicago | Relevant operators and symmetries through the lens of real-space mutual information |
12th October 2021 | 5:30pm CET | Moritz Reh | Heidelberg University | Time-dependent variational principle for open quantum systems with artificial neural networks |
15th June 2021 | 4:30pm CET | Nishad Maskara | Harvard University | A learning algorithm with emergent scaling behavior for classifying phase transitions |
1st June 2021 | 4:30pm CET | Rouven Koch | Aalto University | Neural network enhanced hybrid quantum many-body dynamical distributions |
18th May 2021 | 4:30pm CET | Wei Chen | PUC Rio de Janeiro | A supervised learning algorithm for interacting topological insulators based on local curvature |
4th May 2021 | 4:30pm CET | Agnes Valenti | ETH Zürich |  Scalable Hamiltonian learning for large-scale out-of-equilibrium quantum dynamics |
20th April 2021 | 4:30pm CET | Rui Lin | ETH Zürich |
Minimal model of permutation symmetry in unsupervised learning |
6th April 2021 | 4:30pm CET | Miriam Büttner | University of Freiburg |
Learning Potentials of Quantum Systems using Deep Neural Networks |
 23rd March 2021 | 4:30pm CET | Luuk Coopmans | Trinity College Dublin/Dublin Institute for Advanced Studies | Protocol Discovery for the Quantum Control of Majoranas by Differential Programming and Natural Evolution Strategies |
 9th March 2021 | 4:30pm CET | Axel Lode | University of Freiburg |
Interpretable Phase Detection and Classification with Persistent Homology |
 23rd February 2021 |  4:30pm CET | Evert van Nieuwenburg | University of Copenhagen | A NEAT Quantum Error Decoder |
 9th February 2021 |  3pm CET | Shahnawaz Ahmed |  Chalmers University of  Technology | Classification and reconstruction of optical quantum states with deep neural networks |
 26th January 2021 |  3pm CET | Julian Arnold |  University of Basel | Interpretable and unsupervised phase classification |
 12th January 2021 |  3pm CET | Paolo Molignini |  University of Cambridge |
Scientific intuition inspired by machine learning generated hypotheses |