Quantum Circuit Exponentiation via Ordered Binary Multitree Synthesis
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Solution Overview
Problem
Existing quantum computing technologies face challenges in efficiently implementing an exponentiation module in a quantum circuit, particularly in reducing the number of resources required for the implementation.
Innovation Solution
The implementation involves representing the exponentiation module using a multitree data structure that converts into an ordered binary multitree, allowing for the synthesis of a quantum circuit that optimizes resource usage by implementing basis change and parity summation stages efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a conventional quantum circuit implementation of an exponentiation module is used, then the functionality is achieved, but the number of quantum gates and resources required is excessive
Solution Approach 1:
The patent segments the exponentiation module into distinct computational stages represented by the multitree data structure, where each node represents a specific operation. This segmentation allows for systematic optimization of each stage independently, reducing the overall gate count while maintaining functionality.
Solution Approach 2:
The patent merges redundant operations across different Pauli-term implementations by identifying common subexpressions in the multitree structure. Shared computational steps are combined into single operations, eliminating duplicate gates and reducing resource requirements.
2Manufacturing precision
If the exponentiation module is implemented with high precision, then accuracy is improved, but the resource consumption increases
Solution Approach 1:
The patent performs preliminary analysis of the exponentiation requirements to determine the minimum precision needed. By pre-calculating the necessary accuracy level, the system avoids unnecessary high-precision operations that would consume excessive gates, while still achieving the required precision for the application.
Solution Approach 2:
The patent dynamically adjusts precision parameters based on the specific computational requirements of different Pauli-terms. By varying the precision level according to the actual needs of each term rather than using uniform high precision, the system maintains accuracy where needed while reducing gate count where lower precision suffices.
Data Source
AI summary
A method, apparatus, and computer product comprising: obtaining a multitree data structure that represents a plurality of ordered Pauli-terms, the plurality of ordered Pauli-terms representing an exponentiation module, wherein implementing a Pauli-term in a quantum circuit requires to implement a basis change stage and a parity summation stage, the multitree data structure comprises root nodes representing the plurality of Pauli-terms, leaf nodes representing qubits, and a non-leaf node; converting the multitree data structure to an ordered binary multitree that comprises an additional node; and synthesizing the quantum circuit based on the ordered binary multitree, whereby the quantum circuit comprises an implementation of the parity summation stage and an implementation of the basis change stage, whereby the quantum circuit implements at least one cancellation of a given CX gate of the parity summation stage.