Jet: Fast quantum circuit simulations with parallel task-based tensor-network contraction

Abstract

We introduce a new open-source software library Jet, which uses task-based parallelism to obtain speed-ups in classical tensor-network simulations of quantum circuits. These speed-ups result from i) the increased parallelism introduced by mapping the tensor-network simulation to a task-based framework, ii) a novel method of reusing shared work between tensor-network contraction tasks, and iii) the concurrent contraction of tensor networks on all available hardware. We demonstrate the advantages of our method by benchmarking our code on several Sycamore-53 and Gaussian boson sampling (GBS) supremacy circuits against other simulators. We also provide and compare theoretical performance estimates for tensor-network simulations of Sycamore-53 and GBS supremacy circuits for the first time.

Code: https://github.com/XanaduAI/jet

References in corpus (10)

• Supplementary information for "Quantum supremacy using a programmable superconducting processor"
• Hyper-optimized tensor network contraction
• Leveraging Secondary Storage to Simulate Deep 54-qubit Sycamore Circuits
• Quantum Computational Advantage via High-Dimensional Gaussian Boson Sampling
• Classical Simulation of Quantum Supremacy Circuits
• Simulation of low-depth quantum circuits as complex undirected graphical models
• Octo-Tiger: A New, 3D Hydrodynamic Code for Stellar Mergers that uses HPX Parallelisation
• Tensor Network Quantum Simulator With Step-Dependent Parallelization
• Algorithms for Tensor Network Contraction Ordering
• Tensor Network Quantum Virtual Machine for Simulating Quantum Circuits at Exascale

Cited by in corpus (19)

• The MQT Handbook: A Summary of Design Automation Tools and Software for Quantum Computing
• Simulation of quantum many-body dynamics with Tensor Processing Units: Floquet prethermalization
• The computational power of random quantum circuits in arbitrary geometries
• Benchmarking Quantum Computer Simulation Software Packages: State Vector Simulators
• Tensor networks for interpretable and efficient quantum-inspired machine learning
• Quantum AI simulator using a hybrid CPU-FPGA approach
• Towards an Automated Framework for Realizing Quantum Computing Solutions
• Tensor Networks for Lattice Gauge Theories beyond one dimension: a Roadmap
• Simulation Paths for Quantum Circuit Simulation with Decision Diagrams
• QFactor: A Domain-Specific Optimizer for Quantum Circuit Instantiation
• Towards an Automatic Framework for Solving Optimization Problems with Quantum Computers
• Simulation of Quantum Computers: Review and Acceleration Opportunities
• Loop Series Expansions for Tensor Networks
• Application-Oriented Benchmarking of Quantum Generative Learning Using QUARK
• A Predictive Approach for Selecting the Best Quantum Solver for an Optimization Problem
• RosneT: A Block Tensor Algebra Library for Out-of-Core Quantum Computing Simulation
• QuForge: A Library for Qudits Simulation
• Enabling Multi-threading in Heterogeneous Quantum-Classical Programming Models
• Single-Qudit Quantum Neural Networks for Multiclass Classification