Mar 17 (Mon) @ 10:30am: "Advancements in Fault-tolerant Quantum Approximate Optimization," Zichang He, Applied Research Lead, JPMorganChase

Location: Engineering Science Building (ESB), Room 1001

Abstract

Scaling quantum algorithms is essential for addressing real-world applications, which necessitates overcoming the noise inherent in today's hardware. The Quantum Approximate Optimization Algorithm (QAOA) is a promising candidate due to its modest resource requirements and its documented asymptotic speedup over state-of-the-art classical algorithms for certain problems. However, achieving better-than-classical performance with QAOA is generally believed to require fault tolerance. In this talk, we present a partially fault-tolerant implementation of QAOA using the [[k+2,k,2]] 'Iceberg' error detection code. Our results show that encoding the circuit with the Iceberg code enhances algorithmic performance compared to the unencoded circuit for problems involving tens of logical qubits on a trapped-ion quantum computer. Additionally, we provide a resource estimation for the long-term fault-tolerant implementation of QAOA.

Bio

Dr. Zichang He is the Applied Research Lead (Vice President) at the Global Technology Applied Research Center at JPMorganChase. He earned his Ph.D. in Electrical and Computer Engineering from the University of California, Santa Barbara, in 2023. Dr. He's current research primarily focuses on quantum computing and its design automation. He is the recipient of the IEE Excellence in Research Fellowship in 2021 at UCSB and has received two Best Student Paper Awards at IEEE conferences.

Hosted by: Professor Zheng Zhang <zhengzhang@ece.ucsb.edu>

Submitted by: Alexa Pazell <apazell@ece.ucsb.edu>