Randomized Quantum Gate Benchmarking for Decoherence Separation
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Solution Overview
Problem
Existing benchmarking techniques for quantum computers are limited in their universality and cannot effectively identify infidelity contributed by qubit decoherence separate from state preparation and measurement errors, particularly for non-Clifford quantum gates.
Innovation Solution
The implementation of fully-randomized benchmarking methods that generate and apply sequences of random unitary quantum gates with recovery gates to assess the fidelity of quantum gates, allowing for the separation of decoherence-induced infidelity from other error sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing benchmarking techniques are used, then the benchmarking process is simple, but the techniques cannot be universally applied to arbitrary quantum circuits and cannot separate decoherence-induced infidelity from other errors
Solution Approach 1:
The benchmarking method segments the total infidelity into distinct components: decoherence-induced infidelity and state preparation/measurement errors. This is achieved by separating the measurement of random gate sequences (which capture decoherence) from the measurement of identity sequences (which capture SPAM errors), allowing each error source to be independently quantified and addressed.
Solution Approach 2:
The patent creates a universal benchmarking framework that can evaluate any quantum gate (Clifford or non-Clifford) through a standardized procedure involving random unitary sequences. The method uses a single coherent approach that adapts to different gate types and circuit configurations, eliminating the need for gate-specific benchmarking techniques.
2Measurement precision
If fully-randomized benchmarking with multiple sequences is implemented, then the fidelity measurement accuracy improves, but the number of measurements and computational overhead increases
Solution Approach 1:
The method performs preliminary measurements of random gate sequences to establish a baseline decoherence rate before conducting the full benchmarking procedure. This preliminary data is used to weight and normalize subsequent measurements, reducing the total number of measurements needed while maintaining statistical accuracy.
Solution Approach 2:
The benchmarking process uses feedback from intermediate measurement results to adjust the weighting of different sequence types. By analyzing the decay rates from random sequences and comparing them with identity sequences, the method dynamically weights contributions to achieve accurate fidelity estimation with fewer total measurements.
Data Source
AI summary
Methods, apparatuses, and systems include: based on a parameter of a quantum gate, generating representations of m1 random unitary quantum gates; determining a representation of a first quantum-gate sequence equivalent to an identity operator; determining a representation of a second quantum-gate sequence equivalent to the identity operator; sending, to a quantum computing device, hardware instructions corresponding to the representation of the first quantum-gate sequence the second quantum-gate sequence; receiving a first number of measurements of a qubit after applying the first quantum-gate sequence to the qubit for the first number of times by the quantum computing device and a second number of measurements of the qubit after applying the second quantum-gate sequence to the qubit for the second number of times by the quantum computing device; and determining a fidelity value of the quantum gate based on a first probability and a second probability.