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Enhanced quantum information processing targeting the near term

This is the project webpage of EQUIPTNT, a project within the Horizon 2020 program funded by the European Research Council (ERC) under grant number 101001976.


Progress in the fabrication, control and readout of systems consisting of a small number of qubits has catapulted quantum computation from a primarily theoretical pursuit into the lab. With the growing availability of small and relatively noise-free devices and the imminent arrival of larger next-generation equipment, new theoretical questions are being asked about the potential of quantum computation. In particular, one may ask if quantum computing devices may yield computational benefits even in the presence of noise or constraints on their size or geometrical layout of qubits.

Project objectives

The project EQUIPTNT will characterize the computational capabilities of near-term quantum devices by studying their potential to yield disruptive boosts in information-processing power. It will investigate and design new quantum algorithms adapted to limited hardware: the aim here is to provide computational advances while maximizing noise-tolerance without placing excessive demands on experimental capabilities. It will establish trade-off relations between noise levels, computational power, and the amount and nature of available computational resources. EQUIPTNT will also develop tools for simulating the quantum many-body dynamics of information-processing setups by classical algorithms, in order to pinpoint the origin of quantum advantage, and provide means for certifying the functionality of quantum hardware.

EQUIPTNT will establish new theoretical and algorithmic methods to address the question of ''best use'' for a given finite set of resources. Its interdisciplinary approach will yield novel principles for the design, simulation and validation quantum information processing protocols. Corresponding results will have direct application to near-term quantum devices, providing insights into the architecture and use of schemes tailored towards specific experimental platforms.


Project-related publications of EQUIPTNT are:

  1. Libor Caha, Xavier Coiteux-Roy, and Robert Koenig. Single-qubit gate teleportation provides a quantum advantage, 2023. arXiv:2209.14158.
  2. Shin Ho Choe and Robert Koenig. Long-range data transmission in a fault-tolerant quantum bus architecture, 2022. arXiv:2209.09774.
  3. Libor Caha, Alexander Kliesch, and Robert Koenig. Twisted hybrid algorithms for combinatorial optimization. Quantum Science and Technology, 7(4):045013, 2022. doi:10.1088/2058-9565/ac7f4f.
  4. Sergey Bravyi, Isaac Kim, Alexander Kliesch, and Robert Koenig. Adaptive constant-depth circuits for manipulating non-abelian anyons, 2022. arXiv:2205.01933.
  5. Beatriz Dias, Domagoj Perković, Masudul Haque, Pedro Ribeiro, and Paul A. McClarty. Quantum noise as a symmetry-breaking field. Phys. Rev. B, 108:L060302, 2023.  doi:10.1103/PhysRevB.108.L060302.
  6. Beatriz Dias and Robert Koenig. Classical simulation of non-Gaussian fermionic circuits, 2023. arXiv:2307.12912.
  7. Cambyse Rouze and Robert Koenig. Limitations of local update recovery in stabilizer-GKP codes: a quantum optimal transport approach, 2023. arXiv:2309.16241
  8. Emilio Onorati, Cambyse Rouzé, Daniel Stilck França and James D. Watson, Provably Efficient Learning of Phases of Matter via Dissipative Evolutions, 2023. arXiv:2311.07506.
  9. Libor Caha, Xavier Coiteux-Roy, and Robert Koenig. A colossal advantage: 3D-local noisy shallow quantum circuits defeat unbounded fan-in classical circuits, 2023. arXiv:2312.09209
  10. Shouzhen Gu, Eugene Tang, Libor Caha, Shin Ho Choe, Zhiyang He and Aleksander Kubica. Single-Shot Decoding of Good Quantum LDPC Codes. Commun. Math. Phys. 405, 85 (2024). doi:10.1007/s00220-024-04951-6
  11. Shin Ho Choe and Robert Koenig. How to fault-tolerantly realize any quantum circuit with local operations, 2024. arXiv:2402.13863.
  12. Beatriz Dias and Robert Koenig, Classical simulation of non-Gaussian bosonic circuits, 2024. arXiv:2403.19059.
  13. E. Onorati, J. Kitzinger, J. Helsen, M. Ioannou, A. H. Werner, I. Roth, and J. Eisert, Noise-mitigated randomized measurements and self-calibrating shadow estimation, 2024. arXiv:2403.04751

Last updated on May 15, 2023.