Eliška Greplová
Research
Papers
Talks & Teaching
About
I am a physicist interested in quantum devices, artificial intelligence and topology in condensed matter physics.
I am leading Quantum Matter and AI (QMAI) group at Kavli Institute of Nanoscience (TU Delft). Get to know the rest of our team here and learn more about the boundary crossing research that my group is doing here.
Get in touch via email: e.greplova@tudelft.nl.
News
10/2024 Congratulations to Ana! We made a user-friendly tutorial with code that teaches you randomized benchmarking. See our preprint on arXiv!
09/2024 Congratulations to Tom, Arash and Bokai! Our new preprint on how to calculate quantum resources of quantum and classical variational wavefunction now on arXiv!
09/2024 Congratulations to Vini! Our preprint on how to use quantum GANs to generate biological neuronal activity now on arXiv!
09/2024 QMAI enters its dual affiliation era: We've joined QuTech in addition to our existing Quantum Nanoscience affiliation.
08/2024 Congrations to Yicong Wang and Mohammed Boky on the brilliant master theses defenses!
08/2024 Congratulations to Arash and Cagan and big thank you to Jonas for a wonderful collaboration: our new preprint connects fluctuations of mutual information to quantumness of a system.
06/2024 Congratulations to Dima and Jin on the newest fusion of topology and quantum algorithms: we made a topological quantum walk that can be viewed as a search algorithm.
06/2024 Congratulations to Sibren van der Meer, Stan Bergkamp, Cagan Karaca and Badr Zouggari for successful defense of their masters (Sibren, Stan and Cagan) and bachelors (Badr) theses!
05/2024 We are delighted to be part of the Quantum Limits consortium that received NWO Summit grant!
05/2024 our biggest tuning collaboration to-date is released: we show how to experimentally tune Kitaev chain with the model that was trained on a diffent experimental platform. Congratulations David, Rouven, Vincent and Bas!
05/2024 autoMEA package is released. Conratulations Vini, Anouk, and Valentina! This one is very interdisciplinary: it's ML for processing of signals from bio neurons. Learn more and contribute here.
04/2024 Tunable SSH chain experiment is out - a topogical phase transition you can watch by turning a button! Big thank you to Andersen Lab for an awesome collaboration and big congratulations to Lukas, Miguel and Jin!
04/2024 code and extra learning material for ICTP ML school available here.
04/2024 QDsim package is released! Congratulations Valentina, Charles and Vini! If you are interested in quantum dots, please give QDsim a try and feel free to contribute!
02/2024 new PhD student Aram Shojaei. Welcome!
02/2024 Arash's paper on quantifying non-stabilizerness of quantum circuits published in SciPost Physics. Congratulations!
01/2024 Eliska's high level intro talk on intersection of quantum physics and machine learning @ CERN can be streamed here
12/2023 New preprint about needs and challenges in automating semiconductor quantum devices.
11/2023 We have three new postdocs: Ana Silva, Dmytro Oriekhov and Thomas Spriggs. Ana is supported by NWO Quantum Inspire, Dima by Kavli Innovation Award and Thomas by Quantum Delta. Welcome!
11/2023 Arash and Vini presented their results at QTML2023.
10/2023 Our conditional generative adversarial technique for Hamiltonian learning published in Physical Review Applied. Congratulations, Rouven!
10/2023 Our EdX course "Machine Learning for Semiconductor Quantum Devices" is up!
09/2023 Together with Delft colleagues we received a 5 million EUR Kavli Institute Innovation Award.
06/2023 Eliska's Perimeter talk on Automated Control of Engineered Quantum Materials can be streamed here.
06/2023 Together with QuTech and amazing team of international collaborators we received an ARO grant. We'll be doubling our efforts on automated control of spin qubits!
05/2023 Jin's second PhD paper published in Physical Review Research! We figured out how to use topology to stabilize entanglement on a superconducting chip.
04/2023 Together with QuTech and Uni Aalto we made a generative model that can learn key parameters in experimental Kitaev chains really really well. Paper now on arXiv! Congratulations Rouven!
02/2023 Automated Bound State Reconstruction in Bilayer Graphene Quantum Dots now published
in Physical Review Applied! Congratultions Jozef!01/2023 New PhD student Valentina Gualtieri!
12/2022 Untrained Physically Informed Neural Network for Image Reconstruction of Magnetic Field Sources
now published in Physical Review Applied as Editors' Suggestion.12/2022 We received NWO Quantum Delta funding!
11/2022 Together with other EU institutions we kicked off Quantum Flagship project IGNITE!
10/2022 Machine Learning for Quantum Experiments course is live!
09/2022 new PhD student Tanko Tanev!
08/2022 Eliska's lectures and notebooks for Topological Matter School now online
07/2022 very cool collaboration with Basel University on NN-assisted reconstruction of magnetization maps on arXiv!
05/2022 Jin's second PhD paper out on arXiv! We show how to engineer superconducting circuits using symmetries that protect entanglement in a topological way.
05/2022 Arash's first PhD paper out on arXiv! We show exciting connection between specific correlators in quantum circuits and quantum resources of the resulting state.
04/2022 Book of lecture notes from Warsaw Machine Learning School is now on arXiv!
03/2022 Our new optimizer for recontructing Hamiltonians of bilayer graphene quantum dots is now on arXiv!
02/2022 Our Hamiltonian learning for large scale quantum systems (and Jin's first PhD paper) now published in Physical Review A!
02/2022 Our interpretable neural network quantum states now published in Physical Review Research .
12/2021 Eliska receives NWO grant VENI.
12/2021 QMAI is joining Dutch Quantum Cloud computer Quantum Inspire.