Tirthak Patel’s Dissertation Defense

“Robust System Software for Quantum Computing”

Committee Members:

Prof. Devesh Tiwari (Advisor)

Prof. David Kaeli

Prof. Ningfang Mi

Prof. Gene Cooperman

Prof. Kenneth Brown

Abstract:

Despite rapid progress in quantum computing in the last decade, the limited usability of quantum computers remains a major roadblock toward its wider adoption. Current noisy intermediate-scale quantum (NISQ) computers produce highly erroneous program outputs for quantum-advantage-proven algorithms — that is, algorithms that are infeasible or orders of magnitude slower on classical supercomputing and high-performance computing (HPC) clusters. Unfortunately, currently, quantum computing programmers lack robust system software tools and methods to make meaningful use of erroneous program executions on quantum computers.

This lack of capability is the core motivation behind the fundamental question this dissertation poses: “can we build system software tools for programmers to make the quantum program execution and output meaningful on NISQ machines?” This dissertation answers this question in the affirmative— experimentally demonstrating on real-system quantum computers that it is possible to extract near-accurate program output from noisy executions on today’s erroneous quantum computers, ironically using classical HPC resources and knowledge. This dissertation demonstrates how to achieve this goal without requiring user intervention, domain knowledge about quantum algorithms, or additional quantum hardware support.

Unfortunately, as this dissertation uncovers, progressing toward making quantum computers usable is a double-edged sword. In the near future, only a few entities in the world may have access to powerful quantum computers, and these quantum computers will be used to solve previously-unsolved large-scale optimization problems, possibly without an explicit trust model between the service provider and the customer. Therefore, this dissertation envisions that the solutions to such large-scale optimization problems will be considered sensitive and will need to be protected. This dissertation takes the first few steps toward preparing us for that future by developing a novel method that intelligently obfuscates near-accurate program output and quantum circuit structure to preserve a customer’s privacy under a specified computation model and resource availability.

The approaches introduced in this dissertation open up new research avenues for hybrid quantum-classical computing and lower the barrier to entry for quantum computing research for the experimental computer systems and HPC community by open-sourcing multiple novel datasets and software frameworks implemented for real-system quantum computers.

Candidate Bio:

Tirthak Patel is an incoming Assistant Professor in the Department of Computer Science at Rice University; currently, a PhD candidate at Northeastern University, advised by Professor Devesh Tiwari. Tirthak conducts systems-level research at the intersection of quantum computing and high-performance computing (HPC). His research contributions have appeared at rigorously peer-reviewed publication venues including ASPLOS, Supercomputing (SC), HPDC, HPCA, and USENIX FAST, and have been recognized with multiple award distinctions. He has received the ACM-IEEE CS George Michael Memorial HPC Fellowship, the NSERC Alexander Graham Bell Canada Graduate Scholarship, and the Northeastern University Outstanding Graduate Student in Research award, for his research contributions toward making noisy quantum computing systems useful and helping HPC programmers solve computationally challenging problems.