CAFQA: A Classical Simulation Bootstrap for Variational Quantum Algorithms
Gokul Subramanian Ravi, Pranav Gokhale, Yi Ding, William Kirby, Kaitlin N. Smith, Jonathan M. Baker, Peter J. Love, Henry Hoffmann, Kenneth R. Brown, Frederic T. Chong
Abstract
Classical computing plays a critical role in the advancement of quantum frontiers in the NISQ era. In this spirit, this work uses classical simulation to bootstrap Variational Quantum Algorithms (VQAs). VQAs rely upon the iterative optimization of a parameterized unitary circuit (ansatz) with respect to an objective function. Since quantum machines are noisy and expensive resources, it is imperative to classically choose the VQA ansatz initial parameters to be as close to optimal as possible to improve VQA accuracy and accelerate their convergence on today’s devices.
Topics & Concepts
AnsatzParameterized complexityUnitary stateComputer scienceQuantumConvergence (economics)AlgorithmQuantum algorithmQuantum computerQuantum circuitFunction (biology)QubitMathematical optimizationTheoretical computer scienceMathematicsQuantum error correctionQuantum mechanicsPhysicsEconomicsEconomic growthLawPolitical scienceEvolutionary biologyMathematical physicsBiologyQuantum Computing Algorithms and ArchitectureQuantum-Dot Cellular AutomataQuantum Information and Cryptography