Papers

QMAI group is committed to open and transparent science. The code for absolute majority of QMAI papers can be found here. When applicable, each repository also contains Zenodo link and/or link to the extensive documentation if it's a software package. If you cannot find the data or code you're looking for in this list, they are hosted by our collaborating group - scan the paper you're interested in reproducing for github/gitlab and zenodo links.

You can also find an up-to-date overview of my publications on my Google Scholar profile.

• Arash Ahmadi, Jonas Helsen, Cagan Karaca, Eliska Greplova: Mutual information fluctuations and non-stabilizerness in random circuits
  [arxiv:2408.03831] [code]
  
  

• D. O. Oriekhov, Guliuxin Jin, Eliska Greplova: Constant search time algorithm via topological quantum walks.
  [arxiv:2406.18768] [code]
  
  

• Vinicius Hernandes, Anouk M. Heuvelmans, Valentina Gualtieri,  Dimphna H. Meijer, Geeske M. van Woerden, Eliska Greplova: autoMEA: Machine learning-based burst detection for multi-electrode array datasets.
  [biorXiv:2024.05.08.593078v1] [code]

• David van Driel, Rouven Koch, Vincent P. M. Sietses, Sebastiaan L. D. ten Haaf, Chun-Xiao Liu, Francesco Zatelli, Bart Roovers, Alberto Bordin, Nick van Loo, Guanzhong Wang, Jan Cornelis Wolff, Grzegorz P. Mazur, Tom Dvir, Ivan Kulesh, Qingzhen Wang, A. Mert Bozkurt, Sasa Gazibegovic, Ghada Badawy, Erik P. A. M. Bakkers, Michael Wimmer, Srijit Goswami, Jose L. Lado, Leo P. Kouwenhoven, Eliska Greplova: Cross-Platform Autonomous Control of Minimal Kitaev Chains
  [arXiv:2405.04596] [code]
  
  

• Lukas Johannes Splitthoff, Miguel Carrera Belo, Guliuxin Jin, Yu Li, Eliska Greplova, Christian Kraglund Andersen: Gate-tunable phase transition in a bosonic Su-Schrieffer-Heeger chain.
  [arXiv: 2404.07371]
  
  

• Valentina Gualtieri, Charles Renshaw-Whitman, Vinicius Hernandes, Eliska Greplova: QDsim: An user-friendly toolbox for simulating large scale quantum dot devices.
  [arXiv:2404.02712] [code]
  
  

• Justyna P Zwolak, Jacob M Taylor, Reed Andrews, Jared Benson, Garnett Bryant, Donovan Buterakos, Anasua Chatterjee, Sankar Das Sarma, Mark A Eriksson, Eliška Greplová, Michael J Gullans, Fabian Hader, Tyler J Kovach, Pranav S Mundada, Mick Ramsey, Torbjoern Rasmussen, Brandon Severin, Anthony Sigillito, Brennan Undseth, Brian Weber: Data Needs and Challenges of Quantum Dot Devices Automation: Workshop Report
  [arXiv: 2312.14322]
  
  

• Arash Ahmadi, Eliska Greplova: Quantifying quantum computational complexity via information scrambling, SciPost Phys. 16, 043 (2024)
  [arXiv: 2204.11236] [code]
  
  

• Rouven Koch, David van Driel, Alberto Bordin, Jose L. Lado, Eliska Greplova: Adversarial Hamiltonian learning of quantum dots in a minimal Kitaev chain, Phys. Rev. Applied 20, 044081 (2023).
  [arXiv: 2304.10852][code]
  
  

• Guliuxin Jin, Eliska Greplova: Topological Entanglement Stabilization in Superconducting Quantum Circuits, Phys. Rev. Research 5, 023088 (2023).
  [arXiv: 2205.09100][code]
  
  

• A. E. E. Dubois, D. A. Broadway, A. Stark, M. A. Tschudin, A. J. Healey, S. D. Huber, J.-P. Tetienne, E. Greplova, P. Maletinsky: Untrained physically informed neural network for image reconstruction of magnetic field sources, Phys. Rev. Applied 18, 064076 (2022), Editors' Suggestion.
  [arXiv: 2207.13720]
  
  

• Anna Dawid, Julian Arnold, Borja Requena, Alexander Gresch, Marcin Płodzień, Kaelan Donatella, Kim Nicoli, Paolo Stornati, Rouven Koch, Miriam Büttner, Robert Okuła, Gorka Muñoz-Gil, Rodrigo A. Vargas-Hernández, Alba Cervera-Lierta, Juan Carrasquilla, Vedran Dunjko, Marylou Gabrié, Patrick Huembeli, Evert van Nieuwenburg, Filippo Vicentini, Lei Wang, Sebastian J. Wetzel, Giuseppe Carleo, Eliška Greplová, Roman Krems, Florian Marquardt, Michał Tomza, Maciej Lewenstein, Alexandre Dauphin: Modern Applications of Machine Learning in Quantum Sciences [arXiv: 2204.04198]
  
  

•  Jozef Bucko, Frank Schäfer, František Herman, Rebekka Garreis, Chuyao Tong, Annika Kurzmann, Thomas Ihn, Eliska Greplova: Automated reconstruction of bound states in bilayer graphene quantum dots, Phys. Rev. Applied 19, 024015 (2023).
  [arXiv: 2203.00697][code]
  
  

• Agnes Valenti, Eliska Greplova, Netanel Lindner, Sebastian Huber: Correlation-Enhanced Neural Networks as Interpretable Variational Quantum States, Phys. Rev. A 105, 023302 (2022)
  [arXiv:2103.05017][code]
  
  

• Agnes Valenti, Guliuxin Jin, Julian Leonard, Sebastian Huber, Eliska Greplova: Scalable Hamiltonian learning for large-scale out-of-equilibrium quantum dynamics, Phys. Rev. Research 4, L012010 (2022)
  [arXiv:2103.01240][code]
  
  

• Titus Neupert, Mark H Fischer, Eliska Greplova, Kenny Choo, Michael Denner: Introduction to Machine Learning for the Sciences,
  [arXiv: 2102.04883][Jupyterbook]
  
  

• Eliska Greplova, Reinforcement learning: Solving optimization tasks in condensed matter, Nature Machine Intelligence, 1-2 (2020)
  
  

• Anton Akhmerov, Xavier Bonet-Monroig, Valla Fatemi, Eliska Greplova, Evert van Nieuwenburg, Babak Seradjeh, Daniel Varjas: Let's take this discussion online, Europhysics News 51, 20-212 (2020)
  
  

• Eliska Greplova, Carolin Gold, Benedikt Kratochwil, Tim Davatz, Riccardo Pisoni, Annika Kurzmann, Peter Rick- haus, Mark H. Fischer, Thomas Ihn, Sebastian Huber: Fully automated identification of 2D material samples, Phys. Rev. Applied 13, 064017 (2020)
  [arXiv: 1911.00066][code]
  
  

• Renato Durrer, Benedikt Kratochwil, Jonne V. Koski, Andreas J. Landig, Christian Reichl, Werner Wegscheider, Thomas Ihn, Eliska Greplova: Automated tuning of double quantum dots into specific charge states using neural networks, Phys. Rev. Applied 13, 054019 (2020), editors’ suggestion
  [arXiv: 1912.02777][code]
  
  

• Eliska Greplova, Agnes Valenti, Gregor Boschung, Frank Schäfer, Niels Lörch, Sebastian Huber: Unsupervised identification of topological order using predictive models, New J. Phys. 22 045003 (2020)
  [arXiv: 1910.10124][code]
  
  

• Agnes Valenti, Evert van Nieuwenburg, Sebastian Huber, Eliska Greplova: Hamiltonian learning for quantum error correction; Phys. Rev. Research 1, 033092 (2019)
  [arXiv: 1907.02540][code]
  
  

• Eliska Greplova, Geza Giedke: Degradability of Fermionic Gaussian Channels, Physical Review Letters 121, 200501 (2018),
  [arXiv: 1604.01954]
  
  

• Eliska Greplova, Christian Kraglund Andersen, Klaus Mølmer: Quantum parameter estimation with a neural network
  [arXiv: 1711.05238]
  
  

• Eliska Greplova, Edward E. Laird, G. Andrew D. Briggs, Klaus Mølmer: Conditioned spin and charge dynamics of a single electron quantum dot, Physical Review A 96, 052104 (2017), editors’ suggestion
  [arXiv: 1708.06680]
  
  

• Eliska Greplova, Klaus Mølmer, Christian Kraglund Andersen: Quantum teleportation with continuous measurements, Physical Review A 94, 042334 (2016)
  [arXiv: 1608.01814]
  
  

• Qing Xu, Eliska Greplova, Brian Julsgaard, Klaus Mølmer: Correlation functions and conditioned quantum dynamics in photodetection theory, Physica Scripta 90, 128004 (2015) (Invited Comment)
  [arXiv: 1506.08654]