Superconducting Circuit Design Variation Simulation
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Solution Overview
Problem
It is challenging to determine how to adjust superconducting electronic circuit designs to improve performance and yield due to their fragility and frequent failure during traditional simulation techniques.
Innovation Solution
A system and method that simulate superconducting electronic circuit designs using different process and design variations, selecting the worst-performing variations that still pass logic verification, and iteratively updating the design to optimize performance metrics while ignoring failing variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional simulation techniques are used to evaluate superconducting electronic circuit designs, then performance metrics can be obtained, but the designs frequently fail and require repeated adjustments increasing complexity and time
Solution Approach 1:
The system performs preliminary simulations using multiple process variations before finalizing the design. By evaluating worst-case scenarios and adjusting designs proactively before manufacturing, the system reduces the need for repeated adjustments and improves first-pass yield.
Solution Approach 2:
The system varies multiple design parameters simultaneously across different process corners during simulation. By changing parameters like Josephson junction critical current, inductor quality factor, and capacitor values in conjunction with process variations, the system identifies robust designs that tolerate manufacturing variability.
2Reliability
If multiple process variations are simulated to improve design robustness, then yield increases, but computing resources and simulation time increase
Solution Approach 1:
The system extracts and focuses only on the critical process variations that have the most significant impact on design performance. By identifying and simulating only the dominant variation sources rather than all possible variations, the system achieves robust design evaluation with reduced computational overhead.
Solution Approach 2:
The system uses simplified surrogate models and approximate simulations for initial evaluation of multiple process corners. These lighter-weight simulations allow rapid screening of many variations, with full-accuracy simulations reserved only for promising design candidates.
3Reliability
If design parameters are adjusted to optimize performance, then performance metrics improve, but susceptibility to process variations may increase
Solution Approach 1:
The system applies preliminary anti-action by pre-compensating for expected process variations in the design parameters. During simulation, the system adjusts nominal values to counteract anticipated manufacturing deviations, ensuring that the final design meets specifications despite process variability.
Solution Approach 2:
The system incorporates design margins and tolerance buffers before encountering actual process variations. By cushioning the design against expected variations through conservative parameter selection and robust topology choices, the system maintains performance reliability without requiring excessive optimization.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reliably improves the performance and yield of superconducting electronic circuit designs by optimizing performance metrics and reducing susceptibility to variations, while minimizing computing resources and processor usage.
Implementation Method 1
Superconducting electronic components or circuits may conduct electricity with zero resistance when cooled below a critical temperature (Tc)
Implementation Method 2
Superconducting electronic components or circuits may conduct electricity with zero resistance and expel magnetic flux (Meisner effect) when cooled below a critical temperature (Tc)
Data Source
AI summary
The present disclosure describes systems and methods for generating a superconducting electronic circuit design. The system includes a memory and a processor. The processor simulates a superconducting electronic circuit design using a first process variation to produce a first score and simulates the superconducting electronic circuit design using a second process variation to produce a second score. The processor, in response to determining that the first score is lower than the second score, simulates the superconducting electronic circuit design using the first process variation and a first design variation to produce a third score and simulates the superconducting electronic circuit design using the first process variation and a second design variation to produce a fourth score. The processor updates the superconducting electronic circuit design using the first process variation and the first design variation in response to determining that the third score is higher than the fourth score.