Quantum Devices and Circuits

Dipankar Bhattacharyya, Jyotirmoy Guha

Marvin Bechtold, Johanna Barzen, Frank Leymann +4 more

Abstract Noisy intermediate-scale quantum (NISQ) devices are restricted by their limited number of qubits and their short decoherence times. An approach addressing these problems is quantum circuit cutting. It decomposes the execution of a large quantum circuit into the execution of multiple smaller quantum circuits with additional classical postprocessing. Since these smaller quantum circuits require fewer qubits and gates, they are more suitable for NISQ devices. To investigate the effect of quantum circuit cutting in a quantum algorithm targeting NISQ devices, we design two experiments using the quantum approximate optimization algorithm (QAOA) for the Maximum Cut (MaxCut) problem and conduct them on state-of-the-art superconducting devices. Our first experiment studies the influence of circuit cutting on the objective function of QAOA, and the second evaluates the quality of results obtained by the whole algorithm with circuit cutting. The results show that circuit cutting can reduce the effects of noise in QAOA, and therefore, the algorithm yields better solutions on NISQ devices.

Wiphoo Methachawalit, Prabhas Chongstitvatana

This paper reports the experiments on IBM quantum devices. We design an adder circuit based on Thomas G. Draper proposal. This circuit is a part of a general circuit to build Shor prime number factorization algorithm. We perform the experiments on three IBM quantum devices. The result of the experiment shows that on IBM Essex device, the best possible adder for one qubits has 100% accuracy. However, the results for two qubits adder circuit are much worse. The details analysis of the accuracy of three IBM devices are reported.

Samudra Dasgupta, Travis S. Humble

The ability of a quantum computer to reproduce or replicate the results of a quantum circuit is a key concern for verifying and validating applications of quantum computing. Statistical variations in circuit outcomes that arise from ill-characterized fluctuations in device noise may lead to computational errors and irreproducible results. While device characterization offers a direct assessment of noise, an outstanding concern is how such metrics bound the reproducibility of a given quantum circuit. Here, we first directly assess the reproducibility of a noisy quantum circuit, in terms of the Hellinger distance between the computational results, and then we show that device characterization offers an analytic bound on the observed variability. We validate the method using an ensemble of single qubit test circuits, executed on a superconducting transmon processor with well-characterized readout and gate error rates. The resulting description for circuit reproducibility, in terms of a composite device parameter, is confirmed to define an upper bound on the observed Hellinger distance, across the variable test circuits. This predictive correlation between circuit outcomes and device characterization offers an efficient method for assessing the reproducibility of noisy quantum circuits.

Madhusudan Singh Irish Singh, Bharat S. Rawal