Quantum Circuit Simulation Shot Reduction via Gate Operation Grouping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Quantum circuit simulations require a large number of shots due to noise models, leading to high computing time and resource consumption, as each shot produces varied statevectors and intermediate measurements cause different results.
Innovation Solution
Applying a noise model like Pauli or Kraus to each shot, identifying subsets with the same gate operation, and performing a single simulation for these subsets, reducing the number of shots needed by grouping shots with identical gate operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a noise model is applied to each shot of a quantum circuit simulation, then the simulation accuracy is improved, but the number of shots required increases significantly
Solution Approach 1:
The patent merges multiple shots that have identical gate operations into a single simulation execution. By identifying shots with the same sequence of gate operations and combining them into one simulation, the system reduces redundant computations while preserving the statistical distribution required for accurate noisy circuit simulation. This directly addresses the contradiction by maintaining simulation accuracy through proper noise modeling while significantly reducing computing time.
Solution Approach 2:
The patent creates a universal simulation approach where a single simulation execution can serve multiple shots simultaneously. By identifying common gate operation patterns across multiple shots and performing one universal simulation that represents all identical shots, the system achieves multi-functionality. This universal simulation maintains the accuracy benefits of noise modeling while eliminating the time penalty of running separate simulations for each shot.
2Measurement precision
If a noise model is applied to each shot of a quantum circuit simulation, then the simulation accuracy is improved, but the resource consumption increases
Solution Approach 1:
The patent combines multiple identical shots into a single simulation execution, thereby merging redundant computational resources. By identifying shots with identical gate operations and executing them as one, the system reduces CPU usage, memory allocation, and overall resource consumption while preserving simulation accuracy through maintained noise model application.
Solution Approach 2:
Instead of creating separate simulation instances for each shot, the patent uses a copying approach where the results of a single universal simulation are replicated and assigned to multiple shots that share identical gate operations. This eliminates redundant resource consumption while maintaining the statistical integrity required for accurate noisy circuit simulation.
3Reliability
If multiple shots are performed with random gate operations selected by a noise model, then the statistical distribution is maintained, but the computing efficiency decreases
Solution Approach 1:
The patent merges shots with identical gate operation sequences into single simulation executions while preserving the statistical distribution through proper weighting and counting. By grouping identical shots and maintaining their frequency distribution, the system ensures reliability of statistical results while dramatically improving computing efficiency by eliminating redundant simulations.
Solution Approach 2:
The patent performs preliminary analysis to identify and group shots with identical gate operations before executing simulations. This preliminary action of categorizing shots by their gate operation patterns enables the system to perform universal simulations for groups of identical shots, thereby maintaining statistical distribution requirements while improving computing efficiency through reduced redundancy.
Data Source
AI summary
A method, system and computer program product for reducing the number of shots required to perform a noisy circuit simulation. A noise model, such as the Pauli noise model or the Kraus noise model, is applied to each shot of the quantum circuit, where the noise model randomly selects a gate operation to be performed in simulating the quantum circuit. A subset of shots are identified (e.g., shot numbers 1 and 3), where each of the selected subset of shots has the same gate operation(s) selected by the noise model to be performed in simulating the quantum circuit. A single simulation of the quantum circuit will then be performed for such a subset of shots using the selected gate operation (e.g., Pauli Z gate) for such a group of shots. In this manner, the number of shots required to perform a noisy circuit simulation is reduced.