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Demonstration of a measurement-based adaptation protocol with quantum reinforcement learning on the IBM Q experience platform

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Abstract

Cloning an unknown state is an important task in the field of quantum computation as it is one of the basic operations required in any experiment. The no-cloning theorem states that it is impossible to create an identical copy of an arbitrary unknown quantum state. Hence, techniques are developed to clone unknown states to high fidelities, rather than to exact copies. The usual method of cloning is quantum tomography, which measures a set of observables to reconstruct the unknown state. This method proves to be very expensive when the number of copies of the unknown state is limited. Here, we try to clone an unknown state in IBM’s QASM simulator using a quantum reinforcement learning protocol (Albarran-Arriagada et al. in Phys Rev A 98:042315, 2018), where the “right” amount of punishment/reward function and boundary conditions can give much better fidelity than what tomography can offer in limited copies of the state. Using this method, we can attain above 90% fidelity in under 50 copies. This method proves to be very useful for reconstructing quantum states when only limited copies of the state are available.

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Acknowledgements

K.S.S. and D.Y.S. acknowledge the hospitality provided by IISER Kolkata during the project work. K.S.S. acknowledges Dr. Radhakrishna G. Pillai and Prof. Veeramani P.V. for their constant support. D.Y.S. acknowledges Prof. Debashis Chakraborty, Prof. Mitesh M. Khapra, Nirav D. Karelia and Jatinder Salwan for their constant support. K.S.S. and D.Y.S. also thank the NIUS Physics Program, Dr. Rajesh B. Khaparde and Dr. Praveen K. Pathak for building their interest in quantum computation. K.S.S. and D.Y.S. also like to show their gratitude to their mother and father. K.S.S. and D.Y.S. also thank Rahul Pratap Singh for showing them way around in QISKit. B.K.B. acknowledges the prestigious Prime Minister’s Research Fellowship provided by DST, Govt. of India.

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Author notes

  1. K. S. Shenoy and D. Y. Sheth are contributed equally to the work.

Authors and Affiliations

  1. Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, 600036, India

    Kishore S. Shenoy

  2. Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, 600036, India

    Dev Y. Sheth

  3. Bikash’s Quantum (OPC) Pvt. Ltd., Balindi, Mohanpur, Nadia, West Bengal, 741246, India

    Bikash K. Behera

  4. Department of Physical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, 741246, West Bengal, India

    Bikash K. Behera & Prasanta K. Panigrahi

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  1. Kishore S. Shenoy
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  4. Prasanta K. Panigrahi
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Correspondence to Bikash K. Behera.

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Shenoy, K.S., Sheth, D.Y., Behera, B.K. et al. Demonstration of a measurement-based adaptation protocol with quantum reinforcement learning on the IBM Q experience platform. Quantum Inf Process 19, 161 (2020). https://doi.org/10.1007/s11128-020-02657-x

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