Quantum Noise Process Analysis With Transfer Tensor Maps
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Solution Overview
Problem
Existing quantum noise process analysis methods, such as quantum process tomography (QPT), provide insufficient information for accurate and comprehensive analysis of quantum noise processes, failing to determine whether the process is Markovian or non-Markovian, obtain frequency spectra, and analyze correlated noise between quantum devices.
Innovation Solution
Perform quantum process tomography (QPT) on quantum noise processes to obtain dynamical maps, and extract transfer tensor maps (TTMs) to represent the evolution of these processes, enabling more comprehensive analysis, including Markov process determination, state evolution prediction, correlation function and frequency spectrum extraction, and correlated noise analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If quantum process tomography (QPT) is performed to obtain dynamical maps of quantum noise processes, then the quantum noise process can be reconstructed, but the information obtained is insufficient for accurate and comprehensive analysis
Solution Approach 1:
The patent segments the quantum noise process analysis into multiple components: dynamical maps from QPT, transfer tensor maps (TTMs) for temporal evolution, correlation functions for noise characteristics, and frequency spectra for spectral analysis. This segmentation allows comprehensive extraction of different aspects of quantum noise information that cannot be obtained by a single method.
Solution Approach 2:
The patent extends the analysis from static dynamical maps to temporal evolution by introducing transfer tensor maps that capture the time-dependent behavior of quantum noise. This adds a temporal dimension to the analysis, enabling determination of Markovian vs non-Markovian characteristics and providing more comprehensive information for accurate noise process analysis.
2Device complexity
If only quantum process tomography is used to analyze quantum noise processes, then the measurement process is relatively simple, but comprehensive analysis including Markov process determination, frequency spectrum extraction, and correlated noise analysis cannot be performed
Solution Approach 1:
The patent creates a multi-functional analysis framework where the same experimental setup and QPT procedure serve multiple purposes: reconstructing dynamical maps, extracting transfer tensor maps for Markov process determination, obtaining correlation functions for noise characterization, and deriving frequency spectra. This universal approach enables comprehensive analysis capabilities from a single measurement protocol.
Solution Approach 2:
The patent introduces transfer tensor maps as an intermediary that connects the dynamical maps from QPT to various analysis objectives. The TTMs serve as a mediator that enables determination of Markovian characteristics, prediction of state evolution, and extraction of noise properties without requiring separate experimental procedures for each analysis type.
3Loss of time
If quantum process tomography is performed to reconstruct quantum noise processes, then the basic dynamical maps are obtained, but the temporal evolution characteristics and Markovian properties cannot be determined
Solution Approach 1:
The patent performs preliminary extraction of transfer tensor maps from the dynamical maps obtained through QPT. This preliminary action captures the temporal evolution characteristics and Markovian properties in advance, enabling subsequent analysis of time-dependent behavior without requiring additional time-consuming measurements.
Solution Approach 2:
The patent uses the transfer tensor maps to provide feedback about the temporal evolution characteristics of the quantum noise process. The TTMs contain information about Markovian vs non-Markovian behavior and are used to predict future state evolution, creating a feedback mechanism that enhances understanding of the noise process temporal dynamics.
Data Source
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AI summary
A quantum noise process analysis method and apparatus, a device, and a storage medium, relating to the technical field of quanta. The method comprises: performing quantum process tomography on a quantum noise process of a target quantum system to obtain dynamical mapping of the quantum noise process (201); extracting tensor transfer mapping of the quantum noise process from the dynamical mapping (202); and analyzing the quantum noise process according to the tensor transfer mapping (203). The tensor transfer mapping is used for representing the dynamical evolution of the quantum noise process, i.e., embodying the evolution law of the dynamical mapping of the quantum noise process over time. Therefore, a quantum noise process is analyzed on the basis of tensor transfer mapping of the quantum noise process. Compared with pure quantum process tomography, richer and more comprehensive information about the quantum noise process can be obtained, so that the quantum noise process is analyzed more accurately and comprehensively.