Multiple QPU Instances for Quantum Error Mitigation
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Solution Overview
Problem
Quantum computing systems face challenges in accurately predicting and reproducing operational errors, as these errors can be difficult to understand and reproduce using classical computing resources, and existing methods like quantum error correcting codes and heuristics may not always provide accurate results due to variable error rates and processes across the system.
Innovation Solution
The approach involves evaluating results from multiple executions of a quantum algorithm across distinct quantum processor unit (QPU) instances to determine the most accurate result, leveraging variability in error rates for computational advantage by distributing computations across subdomains of the processor hardware, and using pre-defined evaluation criteria to compute the most accurate answer with a classical co-processor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If quantum error correcting codes are used to actively correct errors, then error correction capability is improved, but system complexity and computational overhead increase
Solution Approach 1:
The patent executes the same quantum algorithm multiple times on different QPU instances (creating copies of the computational process) and compares results to identify and correct errors, avoiding the need for complex quantum error correcting codes while still achieving reliable error correction through redundant execution and classical comparison
2Measurement precision
If multiple QPU instances are used to execute quantum algorithms, then computational accuracy is improved through error mitigation, but resource requirements and system complexity increase
Solution Approach 1:
The patent introduces a classical co-processor as an intermediary that receives results from multiple QPU instances, compares them using pre-defined evaluation criteria, and determines the most accurate result. This intermediary enables accurate error mitigation by leveraging classical computing resources to process and evaluate quantum computational results, achieving high accuracy without requiring all QPU resources to be simultaneously active
3Measurement precision
If quantum computations are distributed across subdomains of processor hardware, then computational accuracy is improved by leveraging error rate variability, but device complexity and coordination overhead increase
Solution Approach 1:
The patent segments the quantum processor into multiple independent QPU instances (subdomains), each executing the same quantum algorithm independently. By distributing computations across these segmented units and comparing results, the system leverages variability in error rates across different hardware segments to identify and mitigate errors, achieving improved accuracy while managing complexity through independent, modular execution units
Data Source
AI summary
In a general aspect, a plurality of distinct quantum processor unit (QPU) instances are utilized to execute a quantum computation. Hybrid classical-quantum computing methods and systems are described which utilize the plurality of QPU instances in the execution of quantum computations.