QFactor: A Domain-Specific Optimizer for Quantum Circuit Instantiation

Abstract

We introduce a domain-specific algorithm for numerical optimization operations used by quantum circuit instantiation, synthesis, and compilation methods. QFactor uses a tensor network formulation together with analytic methods and an iterative local optimization algorithm to reduce the number of problem parameters. Besides tailoring the optimization process, the formulation is amenable to portable parallelization across CPU and GPU architectures, which is usually challenging in general purpose optimizers (GPO). Compared with several GPOs, our algorithm achieves exponential memory and performance savings with similar optimization success rates. While GPOs can handle directly circuits of up to six qubits, QFactor can process circuits with more than 12 qubits. Within the BQSKit optimization framework, we enable optimizations of 100+ qubit circuits using gate deletion algorithms to scale out linearly with the hardware resources allocated for compilation in GPU environments.

arXiv comment11 pages, 8 figures

References in corpus (23)

• Hardware-efficient Variational Quantum Eigensolver for Small Molecules and Quantum Magnets
• The theory of variational hybrid quantum-classical algorithms
• A Practical Introduction to Tensor Networks: Matrix Product States and Projected Entangled Pair States
• A Quantum Approximate Optimization Algorithm
• Fermionic quantum computation
• Multi-particle entanglement of hot trapped ions
• Benchmarking an 11-qubit quantum computer
• Generalization in quantum machine learning from few training data
• t$|$ket$⟩$ : A Retargetable Compiler for NISQ Devices
• Phonon-derived ultrafast relaxation of spin-valley polarized states in MoS_{2}
• Machine learning of noise-resilient quantum circuits
• Classical Optimizers for Noisy Intermediate-Scale Quantum Devices
• Classically optimized Hamiltonian simulation
• Escaping local minima with derivative-free methods: a numerical investigation
• Quantum Fourier Transform Has Small Entanglement
• Jet: Fast quantum circuit simulations with parallel task-based tensor-network contraction
• Approaching the theoretical limit in quantum gate decomposition
• An Introduction to Cartan's KAK Decomposition for QC Programmers
• LEAP: Scaling Numerical Optimization Based Synthesis Using an Incremental Approach
• Verifying Random Quantum Circuits with Arbitrary Geometry Using Tensor Network States Algorithm
• Efficient variational synthesis of quantum circuits with coherent multi-start optimization
• Efficient quantum gate decomposition via adaptive circuit compression
• Large-scale simulations of Floquet physics on near-term quantum computers

Cited by in corpus (5)

• Tensor networks for quantum computing
• Deep Circuit Compression for Quantum Dynamics via Tensor Networks
• OrQstrator: An AI-Powered Framework for Advanced Quantum Circuit Optimization
• Batched Line Search Strategy for Navigating through Barren Plateaus in Quantum Circuit Training
• Quantum circuit synthesis with SQiSW