Quantum Computing: NISQ and Beyond.

Richard A. Muller

Andrew S. Glassner

Kevin J. Sung

Noisy intermediate-scale quantum (NISQ) computers are coming online. The lack of error-correction in these devices prevents them from realizing the full potential of fault-tolerant quantum computation, a technology that is known to have significant practical applications, but which is years, if not decades, away. A major open question is whether NISQ devices will have practical applications. In this thesis, we explore and implement proposals for using NISQ devices to achieve practical applications. In particular, we develop and execute variational quantum algorithms for solving problems in combinatorial optimization and quantum chemistry. We also execute a prototype of a protocol for generating certified random numbers. We perform our experiments on a superconducting qubit processor developed at Google. While we do not perform any quantum computations that are beyond the capabilities of classical computers, we address many implementation challenges that must be overcome to succeed in such an endeavor, including optimization, efficient compilation, and error mitigation. In addressing these challenges, we push the limits of what can currently be done with NISQ technology, going beyond previous quantum computing demonstrations in terms of the scale of our experiments and the types of problems we tackle. While our experiments demonstrate progress in the utilization of quantum computers, the limits that we reached underscore the fundamental challenges in scaling up towards the classically intractable regime. Nevertheless, our results are a promising indication that NISQ devices may indeed deliver practical applications.

Mehdi Bozzo-Rey, John Longbottom, Hausi A. Müller

Tirthak Patel, Devesh Tiwari

Current Noisy Intermediate-Scale Quantum (NISQ) computers are useful in developing the quantum computing stack, test quantum algorithms, and establish the feasibility of quantum computing. However, different statistically significant errors permeate NISQ computers. To reduce the effect of these errors, recent research has focused on effective mapping of a quantum algorithm to a quantum computer in an error-and-constraints-aware manner. We propose the first work, QRAFT, to leverage the reversibility property of quantum algorithms to considerably reduce the error beyond the reduction achieved by effective circuit mapping.

Mikio Nakahara