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Formal Constraint-based Compilation for Noisy Intermediate-Scale Quantum Systems

Authors :
Murali, Prakash
Javadi-Abhari, Ali
Chong, Frederic T.
Martonosi, Margaret
Murali, Prakash
Javadi-Abhari, Ali
Chong, Frederic T.
Martonosi, Margaret
Publication Year :
2019

Abstract

Noisy, intermediate-scale quantum (NISQ) systems are expected to have a few hundred qubits, minimal or no error correction, limited connectivity and limits on the number of gates that can be performed within the short coherence window of the machine. The past decade's research on quantum programming languages and compilers is directed towards large systems with thousands of qubits. For near term quantum systems, it is crucial to design tool flows which make efficient use of the hardware resources without sacrificing the ease and portability of a high-level programming environment. In this paper, we present a compiler for the Scaffold quantum programming language in which aggressive optimization specifically targets NISQ machines with hundreds of qubits. Our compiler extracts gates from a Scaffold program, and formulates a constrained optimization problem which considers both program characteristics and machine constraints. Using the Z3 SMT solver, the compiler maps program qubits to hardware qubits, schedules gates, and inserts CNOT routing operations while optimizing the overall execution time. The output of the optimization is used to produce target code in the OpenQASM language, which can be executed on existing quantum hardware such as the 16-qubit IBM machine. Using real and synthetic benchmarks, we show that it is feasible to synthesize near-optimal compiled code for current and small NISQ systems. For large programs and machine sizes, the SMT optimization approach can be used to synthesize compiled code that is guaranteed to finish within the coherence window of the machine.<br />Comment: Invited paper in Special Issue on Quantum Computer Architecture: a full-stack overview, Microprocessors and Microsystems

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1106334271
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1016.j.micpro.2019.02.005