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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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Validating quantum-classical programming models with tensor network simulations.

Alexander McCaskey^1,2, Eugene Dumitrescu^1,3, Mengsu Chen⁴

¹Quantum Computing Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States of America.

|December 12, 2018

Summary

Researchers developed a new quantum circuit simulator using tensor network theory. This tool aids in validating hybrid quantum-classical algorithms on near-term quantum hardware, enabling larger simulations.

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Area of Science:

Quantum Computing
Computational Science

Background:

Hybrid quantum-classical algorithms are emerging for near-term quantum hardware.
Validating these algorithms is crucial as they scale towards classical intractability.

Purpose of the Study:

To introduce a novel quantum circuit simulator based on tensor network theory.
To enable verification and validation of hybrid quantum-classical computing frameworks.

Main Methods:

Developed the tensor-network quantum virtual machine (TNQVM) simulator.
Utilized matrix product states for compressed wavefunction storage, allowing larger qubit registers on single nodes.
Designed TNQVM for extensibility across tensor network forms and classical hardware (multicore, GPU, distributed) via pluggable numerical backends like ITensor and ExaTENSOR.

Main Results:

Demonstrated TNQVM's capability for intermediate-scale verification and validation.
Successfully verified randomized quantum circuits and the variational quantum eigensolver algorithm within the XACC programming model.
Showcased efficient simulation of larger qubit systems compared to brute-force state-vector methods.

Conclusions:

The TNQVM simulator provides a scalable approach for validating hybrid quantum-classical algorithms.
Tensor network methods are effective for simulating quantum circuits on classical hardware.
The TNQVM facilitates the development and benchmarking of next-generation quantum computing frameworks.