Quantum Algorithms on a Programmable Atomic Tweezer Array

Computing Systems
Written By Alexis Avedisian

Video

Team Information

Team Members

  • Aaron Holman, PhD Student, Department of Physics, Graduate School of Arts and Sciences, Columbia University

  • Faculty Advisor: Sebastian Will, Assistant Professor of Physics, Faculty of Arts and Sciences

Abstract

We present progress towards the realization of a programmable atomic tweezer array that will serve as a platform for quantum computation. Quantum computing is a rapidly growing field in which physical platforms currently lag behind the theoretical possibilities. As such, it is important to develop multiple, unique architectures to best serve the Noisy Intermediate-Scale Quantum (NISQ) era and beyond. Neutral atoms serve as a newer platform that have significant benefits over existing architectures in terms of scalability, fidelity, and connectivity. In particular, the Maximum Independent Set problem maps natively on to the Hamiltonian of our system. We discuss two possible algorithms to solve this NP-hard problem: the Quantum Adiabatic Algorithm and the Quantum Approximate Optimization Algorithm. Looking forward, we are excited to push the boundaries of how quantum technology can have a significant impact on our daily lives.

Team Lead Contact

Aaron Holman: a.holman@columbia.edu

Alexis Avedisian
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