Quantum Gate Fidelity Estimation With Random Circuit Observables
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Solution Overview
Problem
Existing methods for estimating the fidelity of quantum logic gates and circuits are limited in scalability and applicability, often assuming specific distributions and observables, and do not account for the precision needed in quantum computing hardware calibration.
Innovation Solution
A method involving defining random quantum circuits of varying depths, selecting observables dependent on the circuits, and using least mean squares minimization to estimate fidelity parameters, allowing for more accurate and scalable estimation of quantum gate and circuit fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing fidelity estimation methods are used, then the process is simpler, but the scalability and applicability are limited
Solution Approach 1:
The method segments the quantum circuit into multiple random circuits of varying depths, each contributing to the overall fidelity estimation. By dividing the estimation process across multiple circuit instances with different characteristics, the method achieves broader applicability while managing complexity through modular analysis
Solution Approach 2:
The invention changes key parameters of the estimation method by using variable circuit depths and different random seed values across multiple circuits. This parameter variation enables the method to adapt to different quantum circuit configurations and scales, improving versatility without requiring a completely new approach for each case
2Measurement precision
If multiple sets of random quantum circuits with varying depths are defined, then the fidelity estimation becomes more accurate and scalable, but the computational resources and time required increase
Solution Approach 1:
The method employs periodic action by executing multiple random quantum circuits with systematically varied depths and random seeds. This periodic repetition with controlled variation allows the system to gather sufficient statistical data for accurate fidelity estimation while maintaining a structured approach that optimizes computational resource utilization
Solution Approach 2:
The invention performs preliminary action by pre-defining multiple sets of random quantum circuits with predetermined depth variations before the actual fidelity measurement. This preparation phase enables more efficient execution during the measurement stage, as the circuit configurations are already optimized and ready for systematic evaluation
Data Source
AI summary
Methods, systems and apparatus for estimating the fidelity of quantum logic gates. In one aspect, a method includes defining multiple sets of random quantum circuits; for each set of random quantum circuits: selecting an observable for each element in the set of random quantum circuits, wherein each selected observable corresponds to a respective element of the set of random quantum circuits and is dependent on the element to which it corresponds; estimating a value of a polarization parameter for the set of random quantum circuits, comprising performing a least mean squares minimization based on multiple expectation values, wherein each expectation value comprises an expectation value of a respective selected observable with respect to an output of an experimental implementation of a random quantum circuit corresponding to the respective selected observable; and processing the estimated polarization parameter values to obtain an estimate of the fidelity of the n-qubit quantum logic gate.