A team of researchers from various universities and institutions has developed a quantum circuit compiler that prepares an algorithm-specific graph state from quantum circuits described in high-level languages. This approach allows for a better understanding of resource costs and eliminates wasteful measurements on the quantum device. The compiler is applicable in measurement-based quantum computing, NISQ devices, and logical-level compilation for fault-tolerant implementations. The team’s method also allows for efficient classical performance of the computation, leaving only the non-Clifford part to the quantum device.
Quantum Circuit Compiler Development
A team of researchers, including from the Centre for Quantum Software and Information at the University of Technology Sydney, Aalto University, Centre for Quantum Computation and Communication Technology, School of Computing and Information Systems at The University of Melbourne, and Silicon Quantum Computing Pty Ltd, have developed a quantum circuit compiler. This compiler prepares an algorithm-specific graph state from quantum circuits described in high-level languages such as Cirq and Q sharp.
Understanding Resource Costs and Eliminating Wasteful Measurements
The team’s approach to compiling the graph state directly, instead of starting with a standard lattice cluster state and preparing it throughout the computation, allows for a better understanding of the resource costs involved. It also eliminates wasteful Pauli measurements on the actual quantum device. This algorithm-specific graph state also allows for optimization over locally equivalent graph states to implement the same quantum circuit.
Application in Measurement-Based Quantum Computing
The compiler finds ready applications in measurement-based quantum computing (MBQC), NISQ devices, and logical-level compilation for fault-tolerant implementations. In MBQC, a standard square lattice cluster state, a certain type of quantum graph state, is used and single qubit measurements are performed to teleport the logical quantum state through the lattice.
Alternate Workflow and Efficiency
The team presents an alternate workflow where instead of starting with the lattice cluster state, an algorithm-specific graph state is prepared. This method allows for the efficient classical performance of the Clifford part of the computation, leaving only the non-Clifford part to the quantum device. This approach completely determines the quantum computation, allowing the circuit model to be discarded and the computation to be treated as an instruction set to prepare a graph state and perform a sequence of measurements.
Addressing Optimal Implementations and Resource Requirements
In this framework, questions of optimal implementations can be addressed in terms of graph optimization in local Clifford orbits. The algorithm-specific graph state also naturally represents the connectivity requirements for implementing a particular algorithm, allowing for the determination of the minimum device resources needed.
Application in Fault-Tolerant Error Correction Code
Another application of algorithm-specific graphs is for logical-level compilation for a fault-tolerant error correction code. By encoding the computation in a graph state, the requirement of performing complex state evolution in an error-corrected code is dispensed with, and only the generation of the graph state followed by logical qubit measurements is required.
The article titled “Compilation of algorithm-specific graph states for quantum circuits” was published in the Quantum Science and Technology journal on January 16, 2024. The authors of this research paper are Madhav Krishnan Vijayan, Alexandru Paler, Jason Gavriel, Casey R. Myers, Peter P. Rohde, and Simon J. Devitt. The paper discusses the development of specific graph states for quantum circuits. The DOI reference for this article is https://doi.org/10.1088/2058-9565/ad1f39.