Quantum Compiler Calibration Adaptation for Lower Gate Error
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Solution Overview
Problem
Quantum processors exhibit varying physical characteristics over time, leading to error rates in qubits and quantum gates that are not adequately addressed by current calibration methods, which are typically performed only once or twice daily.
Innovation Solution
A method for noise and calibration adaptive compilation of quantum programs that involves executing calibration operations on qubits to produce parameters, selecting qubits based on acceptability criteria, and forming quantum gates using specific qubits to minimize error rates and coherence times, with iterative processes to optimize qubit and gate performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If quantum processors are calibrated only once or twice daily, then operational simplicity is maintained, but error rates increase and reliability deteriorates
Solution Approach 1:
The system dynamically adjusts calibration frequency and parameters based on real-time performance monitoring. The compilation process adapts to changing quantum processor states by selecting optimal qubits and gates from current calibration data, allowing the system to maintain reliability without requiring frequent full recalibrations.
Solution Approach 2:
The system changes operational parameters (qubit selection, gate composition, circuit depth) based on calibration data to optimize performance. By adjusting which qubits and gates are used rather than recalibrating hardware, the system maintains reliability while avoiding frequent recalibration operations.
2Reliability
If calibration operations are performed frequently, then error rates decrease and reliability improves, but operational complexity and time consumption increase
Solution Approach 1:
The system performs calibration operations in advance and stores the results for later use during compilation. By pre-calibrating qubits and gates and caching their performance characteristics, the system avoids repeated calibration operations while maintaining the ability to select optimal components based on current calibration data.
Solution Approach 2:
The system creates virtual representations of quantum circuits with annotated error rates and performance metrics from calibration data. These copied circuit representations allow the compiler to simulate and optimize without physically re-calibrating the quantum processor, saving time while maintaining accuracy.
3Reliability
If qubits with lower error rates are selected, then gate reliability improves, but the number of available qubits decreases and device complexity increases
Solution Approach 1:
The system uses feedback from calibration operations to inform qubit and gate selection during compilation. By incorporating real-time performance data into the compilation decisions, the system automatically identifies and selects the most reliable qubits and gates without manual intervention, managing complexity through automated feedback-driven optimization.
Solution Approach 2:
The compilation system performs self-optimization by automatically selecting optimal qubits and gates based on calibration data without external intervention. The system serves itself by making intelligent decisions about resource allocation, reducing the need for complex external control mechanisms while maintaining high reliability.
Data Source
AI summary
A method includes executing a calibration operation on a set of qubits, in a first iteration, to produce a set of parameters, a first subset of the set of parameters corresponding to a first qubit of the set of qubits, and a second subset of the set of parameters corresponding to a second qubit of the set of qubits. In an embodiment, the method includes selecting the first qubit, responsive to a parameter of the first subset meeting an acceptability criterion. In an embodiment, the method includes forming a quantum gate, responsive to a second parameter of the second subset failing to meet a second acceptability criterion, using the first qubit and a third qubit.