SESSION 7: NISQ algorithm and applications

Chair: (Barbara Jones (IBM) )
10:15am - 11:00amBirgitta Whaley, University of California, Berkeley (invited)
Quantum control for quantum algorithm design
Abstract. Optimization is central to the explicit construction of many quantum algorithms. It plays a particularly important role in quantum algorithms characterized by heuristics, such as the Quantum Approximate Optimization Algorithm (QAOA) and hybrid quantum-classical algorithms, such as the variational quantum eigensolver approach to electronic structure calculations. It is also important in development of efficient quantum algorithms for quantum simulations. I shall describe the use of techniques from quantum control and optimization to enable co-design of quantum algorithms, presenting examples of robust design of QAOA protocols and explicit construction of quantum signal processing (QSP) protocols for Hamiltonian simulation and linear algebra.
11:00am-11:30amNicholas Rubin, Google
Demonstration of a large-scale quantum chemistry calculations using the Sycamore quantum processor
Abstract. Variational simulation of quantum chemistry is a likely first application for noisy intermediate scale quantum (NISQ) computers in the post supremacy age. We simulate a chemistry model that is significantly larger than previous implementations on any quantum computing platform. The model is optimized through a variational outer loop and a new iterative method based on the generalized Brillouin stopping condition that allows for the use of an approximate Hessian. Upon application of an error mitigation scheme based on pure-state n-representability conditions our experiments run on Google’s Sycamore quantum processor achieve chemical accuracy. The model provides an efficiently verifiable circuit that has a large degree of entanglement and is a circuit primitive for fermionic simulation. More broadly, we demonstrate how this fermionic simulation circuit primitive can be used to benchmark large-scale devices.
11:30am - 12:00pmMichael Foss-Feig, Honeywell
Matrix product state simulations on a quantum computer
Abstract. Matrix product states (MPS) afford a compressed representation of many states that are relevant to physical systems. While numerous classical algorithms have been developed to compute the properties of physical systems using MPS as an ansatz, in many cases of practical interest these algorithms still require exponential resources (for example in the size of the system, or in the evolution time when out of equilibrium). We discuss near-term prospects for using small and non-error-corrected quantum computers to aid in MPS simulations.

SQuInT Chief Organizer
Akimasa Miyake, Associate Professor

SQuInT Co-Organizer
Brian Smith, Associate Professor UO

SQuInT Program Committee
Postdoctoral Fellows:
Markus Allgaier (UO OMQ)
Sayonee Ray (UNM CQuIC)
Pablo Poggi (UNM CQuIC)
Valerian Thiel (UO OMQ)

SQuInT Event Co-Organizers (Oregon)
Jorjie Arden
Holly Lynn

SQuInT Event Administrator (Oregon)
Brandy Todd

SQuInT Administrator (CQuIC)
Gloria Cordova
505 277-1850

SQuInT Founder
Ivan Deutsch, Regents' Professor, CQuIC Director

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