Research Article
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Stabilization and Dissipative Information Transfer of a Superconducting Kerr-Cat Qubit

Year 2023, Volume: 11 Issue: 2, 107 - 114, 04.06.2023
https://doi.org/10.17694/bajece.1211876

Abstract

Today, the competition to build a quantum computer continues, and the number of qubits in hardware is increasing rapidly. However, the quantum noise that comes with this process reduces the performance of algorithmic applications, so alternative ways in quantum computer architecture and implementation of algorithms are discussed on the one hand. One of these alternative ways is the hybridization of the circuit-based quantum computing model with the dissipative-based computing model. Here, the goal is to apply the part of the algorithm that provides the quantum advantage with the quantum circuit model, and the remaining part with the dissipative model, which is less affected by noise. This scheme is of importance to quantum machine learning algorithms that involve highly repetitive processes and are thus susceptible to noise. In this study, we examine dissipative information transfer to a qubit model called Cat-Qubit. This model is especially important for the dissipative-based version of the binary quantum classification, which is the basic processing unit of quantum machine learning algorithms. On the other hand, Cat-Qubit architecture, which has the potential to easily implement activation-like functions in artificial neural networks due to its rich physics, also offers an alternative hardware opportunity for quantum artificial neural networks. Numerical calculations exhibit successful transfer of quantum information from reservoir qubits by a repeated-interactions-based dissipative scheme.

Supporting Institution

TÜBİTAK

Project Number

120F353

Thanks

The authors thank the funding from TÜBTAK-Grant No. 120F353. We would also like to thank the Cognitive Systems Laboratory in the Department of Electrical Engineering for providing a suitable environment for the studies.

References

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  • [24] D. Nagaj, P. Štelmachovič, V. Bužek, and M. Kim, ‘Quantum homogenization for continuous variables: Realization with linear optical elements’, Phys. Rev. A, vol. 66, no. 6, p. 062307, Dec. 2002, doi: 10.1103/PhysRevA.66.062307.
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  • [27] J. Kołodyński, J. B. Brask, M. Perarnau-Llobet, and B. Bylicka, ‘Adding dynamical generators in quantum master equations’, Phys. Rev. A, vol. 97, no. 6, p. 062124, Jun. 2018, doi: 10.1103/PhysRevA.97.062124.
  • [28] M. M. Wolf and J. I. Cirac, ‘Dividing Quantum Channels’, Communications in Mathematical Physics, vol. 279, no. 1, pp. 147–168, Apr. 2008, doi: 10.1007/s00220-008-0411-y.
  • [29] S. N. Filippov, J. Piilo, S. Maniscalco, and M. Ziman, ‘Divisibility of quantum dynamical maps and collision models’, Phys. Rev. A, vol. 96, no. 3, p. 032111, Sep. 2017, doi: 10.1103/PhysRevA.96.032111.
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  • [35] F. Verstraete, M. M. Wolf, and J. Ignacio Cirac, ‘Quantum computation and quantum-state engineering driven by dissipation’, Nature Phys, vol. 5, no. 9, pp. 633–636, Sep. 2009, doi: 10.1038/nphys1342.
  • [36] U. Korkmaz and D. Türkpençe, ‘Quantum collisional classifier driven by information reservoirs’, Phys. Rev. A, vol. 107, no. 1, p. 012432, Jan. 2023, doi: 10.1103/PhysRevA.107.012432.
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Year 2023, Volume: 11 Issue: 2, 107 - 114, 04.06.2023
https://doi.org/10.17694/bajece.1211876

Abstract

Project Number

120F353

References

  • [1] J. Preskill, ‘Quantum Computing in the NISQ era and beyond’, Quantum, vol. 2, p. 79, Aug. 2018, doi: 10.22331/q-2018-08-06-79.
  • [2] D. Türkpençe, T. Ç. Akıncı, and S. Şeker, ‘A steady state quantum classifier’, Physics Letters A, vol. 383, no. 13, pp. 1410–1418, Apr. 2019, doi: 10.1016/j.physleta.2019.01.063.
  • [3] U. Korkmaz and D. Türkpençe, ‘Transfer of quantum information via a dissipative protocol for data classification’, Physics Letters A, vol. 426, p. 127887, Feb. 2022, doi: 10.1016/j.physleta.2021.127887.
  • [4] C. C. Gerry and E. E. Hach, ‘Generation of even and odd coherent states in a competitive two-photon process’, Physics Letters A, vol. 174, no. 3, pp. 185–189, Mar. 1993, doi: 10.1016/0375-9601(93)90756-P.
  • [5] E. E. Hach III and C. C. Gerry, ‘Generation of mixtures of Schrödinger-cat states from a competitive two-photon process’, Phys. Rev. A, vol. 49, no. 1, pp. 490–498, Jan. 1994, doi: 10.1103/PhysRevA.49.490.
  • [6] L. Gilles, B. M. Garraway, and P. L. Knight, ‘Generation of nonclassical light by dissipative two-photon processes’, Phys. Rev. A, vol. 49, no. 4, pp. 2785–2799, Apr. 1994, doi: 10.1103/PhysRevA.49.2785.
  • [7] M. Mirrahimi et al., ‘Dynamically protected cat-qubits: a new paradigm for universal quantum computation’, New J. Phys., vol. 16, no. 4, p. 045014, Apr. 2014, doi: 10.1088/1367-2630/16/4/045014.
  • [8] A. Grimm et al., ‘Stabilization and operation of a Kerr-cat qubit’, Nature, vol. 584, no. 7820, pp. 205–209, Aug. 2020, doi: 10.1038/s41586-020-2587-z.
  • [9] P. T. Cochrane, G. J. Milburn, and W. J. Munro, ‘Macroscopically distinct quantum-superposition states as a bosonic code for amplitude damping’, Phys. Rev. A, vol. 59, no. 4, pp. 2631–2634, Apr. 1999, doi:10.1103/PhysRevA.59.2631.
  • [10] R. W. Heeres et al., ‘Implementing a universal gate set on a logical qubit encoded in an oscillator’, Nat Commun, vol. 8, no. 1, p. 94, Dec. 2017, doi: 10.1038/s41467-017-00045-1.
  • [11] W. J. Munro, K. Nemoto, G. J. Milburn, and S. L. Braunstein, ‘Weak-force detection with superposed coherent states’, Phys. Rev. A, vol. 66, no. 2, p. 023819, Aug. 2002, doi: 10.1103/PhysRevA.66.023819.
  • [12] H. Jeong, M. S. Kim, and J. Lee, ‘Quantum-information processing for a coherent superposition state via a mixedentangled coherent channel’, Phys. Rev. A, vol. 64, no. 5, p. 052308, Oct. 2001, doi: 10.1103/PhysRevA.64.052308.
  • [13] P. van Loock, N. Lütkenhaus, W. J. Munro, and K. Nemoto, ‘Quantum repeaters using coherent-state communication’, Phys. Rev. A, vol. 78, no. 6, p. 062319, Dec. 2008, doi: 10.1103/PhysRevA.78.062319.
  • [14] Z. Wang et al., ‘A flying Schrödinger’s cat in multipartite entangled states’, Science Advances, vol. 8, no. 10, p. eabn1778, Mar. 2022, doi: 10.1126/sciadv.abn1778.
  • [15] S. Puri, S. Boutin, and A. Blais, ‘Engineering the quantum states of light in a Kerr-nonlinear resonator by two-photon driving’, npj Quantum Inf, vol. 3, no. 1, p. 18, Dec. 2017, doi: 10.1038/s41534-017-0019-1.
  • [16] S. Touzard et al., ‘Coherent Oscillations inside a Quantum Manifold Stabilized by Dissipation’, Phys. Rev. X, vol. 8, no. 2, p. 021005, Apr. 2018, doi: 10.1103/PhysRevX.8.021005.
  • [17] S. Puri et al., ‘Stabilized Cat in a Driven Nonlinear Cavity: A Fault-Tolerant Error Syndrome Detector’, Phys. Rev. X, vol. 9, no. 4, p. 041009, Oct. 2019, doi: 10.1103/PhysRevX.9.041009.
  • [18] S. Puri et al., ‘Bias-preserving gates with stabilized cat qubits’, Sci. Adv., vol. 6, no. 34, p. eaay5901, Aug. 2020, doi: 10.1126/sciadv.aay5901.
  • [19] W. Cai, Y. Ma, W. Wang, C.-L. Zou, and L. Sun, ‘Bosonic quantum error correction codes in superconducting quantum circuits’, Fundamental Research, vol. 1, no. 1, pp. 50–67, Jan. 2021, doi: 10.1016/j.fmre.2020.12.006.
  • [20] Q. Xu et al., ‘Engineering Kerr-cat qubits for hardware efficient quantum error correction’, in Quantum Computing, Communication, and Simulation II, Mar. 2022, vol. 12015, pp. 50–63. doi: 10.1117/12.2614832.
  • [21] H. Putterman et al., ‘Stabilizing a Bosonic Qubit Using Colored Dissipation’, Phys. Rev. Lett., vol. 128, no. 11, p. 110502, Mar. 2022, doi: 10.1103/PhysRevLett.128.110502.
  • [22] V. Scarani, M. Ziman, P. Štelmachovič, N. Gisin, and V. Bužek, ‘Thermalizing Quantum Machines: Dissipation and Entanglement’, Phys. Rev. Lett., vol. 88, no. 9, p. 097905, Feb. 2002, doi: 10.1103/PhysRevLett.88.097905.
  • [23] M. Ziman, P. Štelmachovič, V. Bužek, M. Hillery, V. Scarani, and N. Gisin, ‘Diluting quantum information: An analysis of information transfer in system-reservoir interactions’, Phys. Rev. A, vol. 65, no. 4, p. 042105, Mar. 2002, doi: 10.1103/PhysRevA.65.042105.
  • [24] D. Nagaj, P. Štelmachovič, V. Bužek, and M. Kim, ‘Quantum homogenization for continuous variables: Realization with linear optical elements’, Phys. Rev. A, vol. 66, no. 6, p. 062307, Dec. 2002, doi: 10.1103/PhysRevA.66.062307.
  • [25] B. Vacchini, ‘General structure of quantum collisional models’, Int. J. Quantum Inform., vol. 12, no. 02, p. 1461011, Mar. 2014, doi: 10.1142/S0219749914610115.
  • [26] S. Campbell and B. Vacchini, ‘Collision models in open system dynamics: A versatile tool for deeper insights?’, EPL, vol. 133, no. 6, p. 60001, Mar. 2021, doi: 10.1209/0295-5075/133/60001.
  • [27] J. Kołodyński, J. B. Brask, M. Perarnau-Llobet, and B. Bylicka, ‘Adding dynamical generators in quantum master equations’, Phys. Rev. A, vol. 97, no. 6, p. 062124, Jun. 2018, doi: 10.1103/PhysRevA.97.062124.
  • [28] M. M. Wolf and J. I. Cirac, ‘Dividing Quantum Channels’, Communications in Mathematical Physics, vol. 279, no. 1, pp. 147–168, Apr. 2008, doi: 10.1007/s00220-008-0411-y.
  • [29] S. N. Filippov, J. Piilo, S. Maniscalco, and M. Ziman, ‘Divisibility of quantum dynamical maps and collision models’, Phys. Rev. A, vol. 96, no. 3, p. 032111, Sep. 2017, doi: 10.1103/PhysRevA.96.032111.
  • [30] T. Yi, J. Wang, and F. Xu, ‘Binary classification of single qubits using quantum machine learning method’, J. Phys.: Conf. Ser., vol. 2006, no. 1, p. 012020, Aug. 2021, doi: 10.1088/1742-6596/2006/1/012020.
  • [31] D. Maheshwari, D. Sierra-Sosa, and B. Garcia-Zapirain, ‘Variational Quantum Classifier for Binary Classification: Real vs Synthetic Dataset’, IEEE Access, vol. 10, pp. 3705–3715, 2022, doi: 10.1109/ACCESS.2021.3139323.
  • [32] M. Schuld, A. Bocharov, K. M. Svore, and N. Wiebe, ‘Circuit-centric quantum classifiers’, Phys. Rev. A, vol. 101, no. 3, p. 032308, Mar. 2020, doi: 10.1103/PhysRevA.101.032308.
  • [33] R. Dilip, Y.-J. Liu, A. Smith, and F. Pollmann, ‘Data compression for quantum machine learning’, Phys. Rev. Res., vol. 4, no. 4, p. 043007, Oct. 2022, doi: 10.1103/PhysRevResearch.4.043007.
  • [34] N. Schetakis, D. Aghamalyan, P. Griffin, and M. Boguslavsky, ‘Review of some existing QML frameworks and novel hybrid classical–quantum neural networks realising binary classification for the noisy datasets’, Sci Rep, vol. 12, no. 1, p. 11927, Jul. 2022, doi: 10.1038/s41598-022-14876-6.
  • [35] F. Verstraete, M. M. Wolf, and J. Ignacio Cirac, ‘Quantum computation and quantum-state engineering driven by dissipation’, Nature Phys, vol. 5, no. 9, pp. 633–636, Sep. 2009, doi: 10.1038/nphys1342.
  • [36] U. Korkmaz and D. Türkpençe, ‘Quantum collisional classifier driven by information reservoirs’, Phys. Rev. A, vol. 107, no. 1, p. 012432, Jan. 2023, doi: 10.1103/PhysRevA.107.012432.
  • [37] F. Rosenblatt, ‘The perceptron: A probabilistic model for information storage and organization in the brain.’, Psychological Review, vol. 65, no. 6, pp. 386–408, 1958, doi: 10.1037/h0042519.
  • [38] M. M. Wolf and J. I. Cirac, ‘Dividing Quantum Channels’, Commun. Math. Phys., vol. 279, no. 1, pp. 147–168, Apr. 2008, doi: 10.1007/s00220-008-0411-y.
  • [39] J. R. Johansson, P. D. Nation, and F. Nori, ‘QuTiP 2: A Python framework for the dynamics of open quantum systems’, Computer Physics Communications, vol. 184, no. 4, pp. 1234–1240, Apr. 2013, doi: 10.1016/j.cpc.2012.11.019.
  • [40] A. Blais, A. L. Grimsmo, S. M. Girvin, and A. Wallraff, ‘Circuit quantum electrodynamics’, Rev. Mod. Phys., vol. 93, no. 2, p. 025005, May 2021, doi: 10.1103/RevModPhys.93.025005.
  • [41] P. Krantz, M. Kjaergaard, F. Yan, T. P. Orlando, S. Gustavsson, and W. D. Oliver, ‘A quantum engineer’s guide to superconducting qubits’, Applied Physics Reviews, vol. 6, no. 2, p. 021318, Jun. 2019, doi: 10.1063/1.5089550. [42] X.-H. Deng, E. Barnes, and S. E. Economou, ‘Robustness of error-suppressing entangling gates in cavity-coupled transmon qubits’, Phys. Rev. B, vol. 96, no. 3, p. 035441, Jul. 2017, doi: 10.1103/PhysRevB.96.035441. [43] J. Majer et al., ‘Coupling superconducting qubits via a cavity bus’, Nature, vol. 449, no. 7161, pp. 443–447, Sep. 2007, doi: 10.1038/nature06184.
There are 41 citations in total.

Details

Primary Language English
Subjects Artificial Intelligence
Journal Section Araştırma Articlessi
Authors

Ufuk Korkmaz 0000-0001-5836-5262

Deniz Türkpençe 0000-0002-5182-374X

Project Number 120F353
Early Pub Date May 13, 2023
Publication Date June 4, 2023
Published in Issue Year 2023 Volume: 11 Issue: 2

Cite

APA Korkmaz, U., & Türkpençe, D. (2023). Stabilization and Dissipative Information Transfer of a Superconducting Kerr-Cat Qubit. Balkan Journal of Electrical and Computer Engineering, 11(2), 107-114. https://doi.org/10.17694/bajece.1211876

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