Practical Quantum Computing

Author:

Suau Adrien1,Staffelbach Gabriel2,Calandra Henri3

Affiliation:

1. CERFACS, France and LIRMM, Montpellier, France

2. CERFACS, Toulouse, France

3. TOTAL SA, Pau, France

Abstract

In the last few years, several quantum algorithms that try to address the problem of partial differential equation solving have been devised: on the one hand, “direct” quantum algorithms that aim at encoding the solution of the PDE by executing one large quantum circuit; on the other hand, variational algorithms that approximate the solution of the PDE by executing several small quantum circuits and making profit of classical optimisers. In this work, we propose an experimental study of the costs (in terms of gate number and execution time on a idealised hardware created from realistic gate data) associated with one of the “direct” quantum algorithm: the wave equation solver devised in [32]. We show that our implementation of the quantum wave equation solver agrees with the theoretical big-O complexity of the algorithm. We also explain in great detail the implementation steps and discuss some possibilities of improvements. Finally, our implementation proves experimentally that some PDE can be solved on a quantum computer, even if the direct quantum algorithm chosen will require error-corrected quantum chips, which are not believed to be available in the short-term.

Publisher

Association for Computing Machinery (ACM)

Reference66 articles.

1. 2015. Constructing Large Controlled Nots. https://algassert.com/circuits/2015/06/05/Constructing-Large-Controlled-Nots.html. Accessed: 2020-03-27. 2015. Constructing Large Controlled Nots. https://algassert.com/circuits/2015/06/05/Constructing-Large-Controlled-Nots.html. Accessed: 2020-03-27.

2. 2019. Hamiltonian simulation implementation in qiskit-aqua. https://github.com/Qiskit/qiskit-aqua/blob/master/qiskit/aqua/operators/weighted_pauli_operator.py#L837. Accessed: 2020-03-27. 2019. Hamiltonian simulation implementation in qiskit-aqua. https://github.com/Qiskit/qiskit-aqua/blob/master/qiskit/aqua/operators/weighted_pauli_operator.py#L837. Accessed: 2020-03-27.

3. 2019. IBM Quantum Computing. https://www.ibm.com/quantum-computing/. Accessed: 2020-03-27. 2019. IBM Quantum Computing. https://www.ibm.com/quantum-computing/. Accessed: 2020-03-27.

4. 2019. Melbourne gate specification. https://github.com/Qiskit/ibmq-device-information/tree/master/backends/melbourne/V1#gate-specification. Accessed: 2020-03-27. 2019. Melbourne gate specification. https://github.com/Qiskit/ibmq-device-information/tree/master/backends/melbourne/V1#gate-specification. Accessed: 2020-03-27.

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