Virtual Quantum Machine Benchmarking for Error Syndrome Modeling
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Solution Overview
Problem
Current quantum computing benchmarking techniques struggle to provide architecture-independent and scalable methods for diagnosing operational issues and improving the quality of near-term quantum devices, as they often produce noisy results that fail to accurately inform how to enhance device performance.
Innovation Solution
A hybrid quantum-classical computer system that simulates a near-term quantum device using a virtual quantum machine (VQM) to reproduce the probability distribution of error syndromes, allowing for indirect benchmarking and error correction, thereby enabling the identification of non-unitary processes and improving device fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current quantum computing benchmarking techniques are used, then architecture independence and scalability are satisfied, but the ability to provide useful experimental feedback is compromised due to noisy results
Solution Approach 1:
The patent introduces a virtual quantum machine (VQM) as an intermediary between the physical quantum device and the benchmarking process. The VQM simulates the quantum device's behavior including its error characteristics, allowing benchmarking to be performed on the simulated system rather than directly on the noisy physical device. This intermediary approach filters out the harmful noise while preserving the essential error patterns, thereby improving measurement precision and the reliability of experimental feedback simultaneously
2Measurement precision
If random circuits with short range entanglement are used to benchmark quantum devices, then device performance can be quantified, but it becomes difficult to distinguish between long range entanglement effects and decoherence effects
Solution Approach 1:
The patent creates a copy of the quantum device's error characteristics through the virtual quantum machine. The VQM is trained to reproduce the probability distribution of error syndromes from the physical device, including all its noise and decoherence patterns. By performing benchmarking on this accurate copy, one can distinguish between genuine entanglement effects and decoherence effects more easily, since the VQM allows for controlled manipulation and analysis of different error sources without the confounding factors present in direct physical device measurement
3Reliability
If quantum error correcting codes are applied to initialize states and perform logical operations, then error correction can be implemented, but the benchmarking process becomes more complex
Solution Approach 1:
The patent implements a self-service approach where the virtual quantum machine automatically learns and internalizes the error correction characteristics of the physical device. By training the VQM on data from the physical device including error correction operations, the system creates a self-contained model that encapsulates the error correction behavior. This allows benchmarking to be performed on the simpler VQM while still capturing the complex error correction dynamics, effectively reducing the apparent complexity of the benchmarking process while maintaining full error correction capability
Data Source
AI summary
A hybrid quantum classical (HQC) computer system, which includes both a classical computer component and a quantum computer component, implements indirect benchmarking of a near term quantum device by directly benchmarking a virtual quantum machine that models the quantum computer device and that has a level of errors that corresponds to the level of errors associated with the quantum computer device. The direct benchmarking, conducted using quantum error correction tools, produces a probability distribution of error syndromes that may be used as a probability distribution of error syndromes for the quantum computer device.