TensorCircuit: a Quantum Software Framework for the NISQ Era

Abstract

TensorCircuit is an open source quantum circuit simulator based on tensor network contraction, designed for speed, flexibility and code efficiency. Written purely in Python, and built on top of industry-standard machine learning frameworks, TensorCircuit supports automatic differentiation, just-in-time compilation, vectorized parallelism and hardware acceleration. These features allow TensorCircuit to simulate larger and more complex quantum circuits than existing simulators, and are especially suited to variational algorithms based on parameterized quantum circuits. TensorCircuit enables orders of magnitude speedup for various quantum simulation tasks compared to other common quantum software, and can simulate up to 600 qubits with moderate circuit depth and low-dimensional connectivity. With its time and space efficiency, flexible and extensible architecture and compact, user-friendly API, TensorCircuit has been built to facilitate the design, simulation and analysis of quantum algorithms in the Noisy Intermediate-Scale Quantum (NISQ) era.

arXiv commentWhitepaper for TensorCircuit, 43 pages, 11 figures, 9 tables

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Cited by in corpus (52)

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• Understanding quantum machine learning also requires rethinking generalization
• A Hybrid Quantum Computing Pipeline for Real World Drug Discovery
• Generative quantum machine learning via denoising diffusion probabilistic models
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• Absence of barren plateaus in finite local-depth circuits with long-range entanglement
• Trainability Enhancement of Parameterized Quantum Circuits via Reduced-Domain Parameter Initialization
• Non-IID Quantum Federated Learning with One-shot Communication Complexity
• Probing many-body localization by excited-state VQE
• Learning quantum states and unitaries of bounded gate complexity
• Symmetry restoration and quantum Mpemba effect in many-body localization systems
• Benchmarking Quantum Computer Simulation Software Packages: State Vector Simulators
• Training variational quantum algorithms with random gate activation
• Neural network encoded variational quantum algorithms
• Distributed quantum architecture search
• TenCirChem: An Efficient Quantum Computational Chemistry Package for the NISQ Era
• Quantum algorithms for scientific computing
• GSQAS: Graph Self-supervised Quantum Architecture Search
• Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics
• Symmetry Breaking Dynamics in Quantum Many-Body Systems
• Quantum Vision Transformers for Quark-Gluon Classification
• Efficient Quantum Simulation of Electron-Phonon Systems by Variational Basis State Encoder
• Efficient and Robust Parameter Optimization of the Unitary Coupled-Cluster Ansatz
• Zero and Finite Temperature Quantum Simulations Powered by Quantum Magic
• Subsystem Information Capacity in Random Circuits and Hamiltonian Dynamics
• Skin Effect Induced Anomalous Dynamics from Charge-Fluctuating Initial States
• Simulating the quantum Fourier transform, Grover's algorithm, and the quantum counting algorithm with limited entanglement using tensor-networks
• Stabilizer ground states for simulating quantum many-body physics: theory, algorithms, and applications
• Universal imaginary-time critical dynamics on a quantum computer
• Holographic deep thermalization for secure and efficient quantum random state generation
• Quantum neural compressive sensing for ghost imaging
• Learning the expressibility of quantum circuit ansatz using transformer
• Determination of Molecular Energies via Quantum Imaginary Time Evolution in a Superconducting Qubit System
• Correlated states in super-moiré materials with a kernel polynomial quantics tensor cross interpolation algorithm
• Exploring the topological sector optimization on quantum computers
• Enhancing Variational Quantum Circuit Training: An Improved Neural Network Approach for Barren Plateau Mitigation
• Variational post-selection for ground states and thermal states simulation
• Quantum Machine Learning of Molecular Energies with Hybrid Quantum-Neural Wavefunction
• Quantum Pontus-Mpemba Effects in Real and Imaginary-time Dynamics
• Entanglement growth and information capacity in a quasiperiodic system with a single-particle mobility edge
• Variational LOCC-assisted quantum circuits for long-range entangled states
• Supersymmetry dynamics on Rydberg atom arrays
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• Learning complexity gradually in quantum machine learning models
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• Non-Markovianity Benefits Quantum Dynamics Simulation
• Scaling Laws of Quantum Information Lifetime in Monitored Quantum Dynamics
• Quantum generative classification with mixed states