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Neuromrophic Quantum Computing

Rezultaty

webpage

Webpage and communication platforms. The project website will contain the main communication node for all partners in a password protected part and provide information for the public in an open access part.

annealer implementation v2

Report on implementation of nonequilibrium quantum annealer that is built of superconducting Kerrnonlinear oscillators driven by a twophoton drive The report will cover progress in the implementation of these driven oscillators as well as their coupling into a network

Technical/scientific review meeting documents 1

Draft agenda and presentations delivered during the review meeting.

training software v2

Report on implementation of dataanalysis and training software that will cover the development of a Python code for the data analysis and generation of feedback signals that train the networks developed in the project

sweep of annealer

The report will cover experiments that sweep the developed nonequilibrium quantum annealer from a suitable initial state to a set target state It will discuss the progress in fidelity improvement and scalability aspects

Dissemination and Exploitation Plan

Plan for the dissemination and exploitation of the project results.

network simulation v1

Intermediate report on the numerical simulation of quantum neural networks that we build. These simulations can be done in a numerically exact fashion for small networks but will require the adaption of cutting edge quantum many-body simulations for larger networks.

Technical/scientific review meeting documents 2

Draft agenda and presentations delivered during the review meeting

scalability strategy v2

Report on scalability improvements for the next generation of quantum neural networks that covers our progress in developing novel concepts that require less circuit depth or less network connectivity while maintaining a useful expressive power

conference

Report on the conference on Quantum Machine Learning that will be organized The program will feature external high profile speakers as well as project representatives The report will cover the presentations main discussion results

scalability strategy v1

Intermediate report on scalability improvements for the next generation of quantum neural networks that covers our progress in developing novel concepts that require less circuit depth or less network connectivity while maintaining a useful expressive power.

network implementations v2

Report on the implementation of two types of feed forward quantum neural networks The report will cover our progress in implementing neurons based on adiabatic ram processes for fixed frequency qubits and neurons that feature nonlinear activation functions realized via a measurement and feedback control loop We will also report on progress to connect these neurons into elementary networks

training of networks

Report on the progress in training the feedforward quantum neural networks that are developed in the project in the experiments The report will cover the calibration of the networks and report on experiments that process a given input state through the network and compare it to target data for generating feedback signals

network training v1

Intermediate report on training strategies and simulation of application to a classification problem. The report will cover integrations of our simulations into a network training processes and explorations of applications to simple machine learning problems, such as recognition of hand written digits in the MNIST data set.

training software v1

Intermediate report on implementation of data-analysis and training software that will cover the development of a Python code for the data analysis and generation of feedback signals that train the networks developed in the project.

network implementation v1

Intermediate report on the implementation of two types of feed forward quantum neural networks. The report will cover our progress in implementing neurons based on adiabatic ram processes for fixed frequency qubits and neurons that feature nonlinear activation functions realized via a measurement and feedback control loop. We will also report on progress to connect these neurons into elementary networks.

netwrok simulation v2

Report on the numerical simulation of quantum neural networks that we build These simulations can be done in a numerically exact fashion for small networks but will require the adaption of cutting edge quantum manybody simulations for larger networks

annealer implementation v1

Intermediate report on implementation of non-equilibrium quantum annealer that is built of superconducting Kerr-nonlinear oscillators driven by a two-photon drive. The report will cover progress in the implementation of these driven oscillators as well as their coupling into a network.

network training v2

Report on training strategies and simulation of application to a classification problem The report will cover integrations of our simulations into a network training processes and explorations of applications to simple machine learning problems such as recognition of hand written digits in the MNIST data set

Data management plan

A data management plan that will be agreed among all partners.

Publikacje

A neural network assisted 171Yb+ quantum magnetometer

Autorzy: Yan Chen, Yue Ban, Ran He, Jin-Ming Cui, Yun-Feng Huang, Chuan-Feng Li, Guang-Can Guo & Jorge Casanova
Opublikowane w: npj Quantum Information, 2022, ISSN 2056-6387
Wydawca: Springer Nature
DOI: 10.1038/s41534-022-00669-2

Single shot i-Toffoli gate in dispersively coupled superconducting qubits

Autorzy: Aneirin J. Baker, Gerhard B. P. Huber, Niklas J. Glaser, Federico Roy, Ivan Tsitsilin, Stefan Filipp, and Michael J. Hartmann
Opublikowane w: Applied Physics Letters, 2022, ISSN 1077-3118
Wydawca: American Institut of Physics
DOI: 10.1063/5.0077443

Realizing quantum convolutional neural networks on a superconducting quantum processor to recognize quantum phases

Autorzy: Johannes Herrmann, Sergi Masot Llima, Ants Remm, Petr Zapletal, Nathan A. McMahon, Colin Scarato, Francois Swiadek, Christian Kraglund Andersen, Christoph Hellings, Sebastian Krinner, Nathan Lacroix, Stefania Lazar, Michael Kerschbaum, Dante Colao Zanuz, Graham J. Norris, Michael J. Hartmann, Andreas Wallraff, Christopher Eichler
Opublikowane w: Nature Communications, 2022, ISSN 2041-1723
Wydawca: Nature Publishing Group
DOI: 10.1038/s41467-022-31679-5

Direct implementation of a perceptron in superconducting circuit quantum hardware

Autorzy: Marek Pechal, Federico Roy, Samuel A. Wilkinson, Gian Salis, Max Werninghaus, Michael J. Hartmann, Stefan Filipp
Opublikowane w: Physical Review Research, 2022, ISSN 2643-1564
Wydawca: American Physical Society
DOI: 10.1103/physrevresearch.4.033190

QuCAT: quantum circuit analyzer tool in Python

Autorzy: Mario F Gely, Gary A Steele
Opublikowane w: New Journal of Physics, Numer 22/1, 2020, Strona(/y) 013025, ISSN 1367-2630
Wydawca: Institute of Physics Publishing
DOI: 10.1088/1367-2630/ab60f6

Selective interactions in the quantum Rabi model

Autorzy: L. Cong, S. Felicetti, J. Casanova, L. Lamata, E. Solano, I. Arrazola
Opublikowane w: Physical Review A, Numer 101/3, 2020, ISSN 2469-9926
Wydawca: American Physical Society
DOI: 10.1103/physreva.101.032350

Flux-mediated optomechanics with a transmon qubit in the single-photon ultrastrong-coupling regime

Autorzy: Marios Kounalakis, Yaroslav M. Blanter, Gary A. Steele
Opublikowane w: Physical Review Research, Numer 2/2, 2020, ISSN 2643-1564
Wydawca: American Physical Society
DOI: 10.1103/physrevresearch.2.023335

Superconducting quantum many-body circuits for quantum simulation and computing

Autorzy: Samuel A. Wilkinson, Michael J. Hartmann
Opublikowane w: Applied Physics Letters, Numer 116/23, 2020, Strona(/y) 230501, ISSN 0003-6951
Wydawca: American Institute of Physics
DOI: 10.1063/5.0008202

Double quantum magnetometry at large static magnetic fields

Autorzy: C. Munuera-Javaloy, I. Arrazola, E. Solano, J. Casanova
Opublikowane w: Physical Review B, Numer 101/10, 2020, ISSN 2469-9950
Wydawca: American Physical Society
DOI: 10.1103/physrevb.101.104411

Quantum Memristors in Frequency-Entangled Optical Fields

Autorzy: Tasio Gonzalez-Raya, Joseph M. Lukens, Lucas C. Céleri, Mikel Sanz
Opublikowane w: Materials, Numer 13/4, 2020, Strona(/y) 864, ISSN 1996-1944
Wydawca: MDPI Open Access Publishing
DOI: 10.3390/ma13040864

Quantum Approximate Optimization of Non-Planar Graph Problems on a Planar Superconducting Processor

Autorzy: Frank Arute, Kunal Arya, Ryan Babbush, Dave Bacon, Joseph C. Bardin, Rami Barends, Sergio Boixo, Michael Broughton, Bob B. Buckley, David A. Buell, Brian Burkett, Nicholas Bushnell, Yu Chen, Zijun Chen, Ben Chiaro, Roberto Collins, William Courtney, Sean Demura, Andrew Dunsworth, Edward Farhi, Austin Fowler, Brooks Foxen, Craig Gidney, Marissa Giustina, Rob Graff, Steve Habegger, Matthew P. Harrig
Opublikowane w: Nature ~Physics, 2020, ISSN 1745-2481
Wydawca: Springer Nature
DOI: 10.1038/s41567-020-01105-y

Quantized Three-Ion-Channel Neuron Model for Neural Action Potentials

Autorzy: Tasio Gonzalez-Raya, Enrique Solano, Mikel Sanz
Opublikowane w: Quantum, Numer 4, 2020, Strona(/y) 224, ISSN 2521-327X
Wydawca: Quantum
DOI: 10.22331/q-2020-01-20-224

Hybrid Microwave-Radiation Patterns for High-Fidelity Quantum Gates with Trapped Ions

Autorzy: I. Arrazola, M.B. Plenio, E. Solano, J. Casanova
Opublikowane w: Physical Review Applied, Numer 13/2, 2020, ISSN 2331-7019
Wydawca: American Physical Society
DOI: 10.1103/physrevapplied.13.024068

Shortcuts to adiabaticity for an interacting Bose-Einstein condensate via exact solutions of the generalized Ermakov equation

Autorzy: Tang-You Huang, Boris A. Malomed, Xi Chen
Opublikowane w: Chaos, Numer 30, 2020, Strona(/y) 053131, ISSN 1054-1500
Wydawca: American Institute of Physics
DOI: 10.1063/5.0004309

Retrieving Quantum Information with Active Learning

Autorzy: Yongcheng Ding, José D. Martín-Guerrero, Mikel Sanz, Rafael Magdalena-Benedicto, Xi Chen, Enrique Solano
Opublikowane w: Physical Review Letters, Numer 124/14, 2020, ISSN 0031-9007
Wydawca: American Physical Society
DOI: 10.1103/physrevlett.124.140504

Enhancing the Robustness of Dynamical Decoupling Sequences with Correlated Random Phases

Autorzy: Zhenyu Wang, Jorge Casanova, Martin B. Plenio
Opublikowane w: Symmetry, Numer 12/5, 2020, Strona(/y) 730, ISSN 2073-8994
Wydawca: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/sym12050730

Digital-analog quantum algorithm for the quantum Fourier transform

Autorzy: Ana Martin, Lucas Lamata, Enrique Solano, Mikel Sanz
Opublikowane w: Physical Review Research, Numer 2/1, 2020, ISSN 2643-1564
Wydawca: American Physical Society
DOI: 10.1103/physrevresearch.2.013012

Smooth bang-bang shortcuts to adiabaticity for atomic transport in a moving harmonic trap

Autorzy: Yongcheng Ding, Tang-You Huang, Koushik Paul, Minjia Hao, Xi Chen
Opublikowane w: Physical Review A, Numer 101/6, 2020, ISSN 2469-9926
Wydawca: American Physical Society
DOI: 10.1103/physreva.101.063410

Realizing Repeated Quantum Error Correction in a Distance-Three Surface Code

Autorzy: Sebastian Krinner, Nathan Lacroix, Ants Remm, Agustin Di Paolo, Elie Genois, Catherine Leroux, Christoph Hellings, Stefania Lazar, Francois Swiadek, Johannes Herrmann, Graham J. Norris, Christian Kraglund Andersen, Markus Müller, Alexandre Blais, Christopher Eichler, Andreas Wallraff
Opublikowane w: Nature, 2022, ISSN 1476-4687
Wydawca: Springer Nature
DOI: 10.1038/s41586-022-04566-8

Evaluating the performance of sigmoid quantum perceptrons in quantum neural networks

Autorzy: Samuel A Wilkinson, Michael J Hartmann
Opublikowane w: 2022
Wydawca: arrive.org
DOI: 10.48550/arxiv.2208.06198

Quantum Supremacy in Cryptography with a Low-Connectivity Quantum Annealer

Autorzy: Feng Hu, Lucas Lamata, Chao Wang, Xi Chen, Enrique Solano, Mikel Sanz
Opublikowane w: arXiv, 2020
Wydawca: arXiv

Logistic Network Design with a D-Wave Quantum Annealer

Autorzy: Yongcheng Ding, Xi Chen, Lucas Lamata, Enrique Solano, Mikel Sanz
Opublikowane w: arXiv, 2020
Wydawca: arXiv

Benchmarking the noise sensitivity of different parametric two-qubit gates in a single superconducting quantum computing platform

Autorzy: M. Ganzhorn, G. Salis, D. J. Egger, A. Fuhrer, M. Mergenthaler, C. Müller, P. Müller, S. Paredes, M. Pechal, M. Werninghaus, S. Filipp
Opublikowane w: arXiv, 2020
Wydawca: arXiv

Time-resolved tomography of a driven adiabatic quantum simulation

Autorzy: Gian Salis, Nikolaj Moll, Marco Roth, Marc Ganzhorn, Stefan Filipp
Opublikowane w: arXiv, 2020
Wydawca: arXiv

Enhanced connectivity of quantum hardware with digital-analog control

Autorzy: Asier Galicia, Borja Ramon, Enrique Solano, Mikel Sanz
Opublikowane w: arXiv, 2020
Wydawca: arXiv

Superconducting resonator single-photon spectroscopy through electromagnetically induced transparency

Autorzy: Byoung-moo Ann, Gary A. Steele
Opublikowane w: arXiv, 2020
Wydawca: arXiv

Speed-up Quantum Perceptron via Shortcuts to Adiabaticity

Autorzy: Yue Ban, Xi Chen, E. Torrontegui, E. Solano, J. Casanova
Opublikowane w: 2020
Wydawca: arXiv

TensorFlow Quantum: A Software Framework for Quantum Machine Learning Michael Broughton

Autorzy: Michael Broughton, Guillaume Verdon, Trevor McCourt, Antonio J. Martinez, Jae Hyeon Yoo, Sergei V. Isakov, Philip Massey, Murphy Yuezhen Niu, Ramin Halavati, Evan Peters, Martin Leib, Andrea Skolik, Michael Streif, David Von Dollen, Jarrod R. McClean, Sergio Boixo, Dave Bacon, Alan K. Ho, Hartmut Neven, Masoud Mohseni
Opublikowane w: arXiv, 2020
Wydawca: arXiv

Approximating the Quantum Approximate Optimisation Algorithm

Autorzy: David Headley, Thorge Müller, Ana Martin, Enrique Solano, Mikel Sanz, Frank K. Wilhelm
Opublikowane w: arXiv, 2020
Wydawca: arXiv

Wehrl entropy production rate across a dynamical quantum phase transition

Autorzy: B. O. Goes, G. T. Landi, E. Solano, M. Sanz, L. C. Céleri
Opublikowane w: arXiv, 2020
Wydawca: arXiv

Versatile Atomic Magnetometry Assisted by Bayesian Inference

Autorzy: R. Puebla, Y. Ban, J. F. Haase, M. B. Plenio, M. Paternostro, J. Casanova
Opublikowane w: arXiv, 2020
Wydawca: arXiv

Training the Quantum Approximate Optimization Algorithm without access to a Quantum Processing Unit

Autorzy: Streif, Michael; Leib, Martin
Opublikowane w: Quantum Science and Technology, 2020, ISSN 2058-9565
Wydawca: Institute of Physics
DOI: 10.1088/2058-9565/ab8c2b

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