Recursive Quantum Computing Algorithm Feedback Loop
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Solution Overview
Problem
Current quantum computing approaches, such as circuit model quantum computers, face challenges in maintaining qubit coherence for extended periods, which hampers the practical implementation of recursive quantum algorithms, while adiabatic quantum computation and quantum annealing struggle with achieving exact solutions due to transitions at anti-crossings, requiring impractically long evolution schedules.
Innovation Solution
The implementation of a recursive quantum computing method that accepts probabilistic transitions at anti-crossings and relaxes the pursuit of exact solutions, allowing for faster evolution schedules by iteratively refining approximate solutions until predetermined criteria are met, using adiabatic quantum computation and quantum annealing with a feedback system to improve solution accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If adiabatic quantum computation is used to achieve exact solutions, then solution accuracy is improved, but computation time increases impractically due to required evolution schedules
Solution Approach 1:
The patent applies partial action by accepting approximate solutions rather than requiring exact solutions. The system performs quantum evolution for a practical, limited time to obtain intermediate solutions that satisfy predetermined criteria, rather than continuing evolution indefinitely to achieve exact solutions. This resolves the contradiction by achieving sufficient accuracy within feasible computation time.
Solution Approach 2:
The patent implements feedback by evaluating intermediate solutions against predetermined criteria and using this evaluation to determine whether to continue or terminate the quantum evolution. The feedback mechanism allows the system to achieve satisfactory solutions efficiently by stopping evolution when criteria are met, rather than requiring fixed long evolution schedules.
2Adaptability or versatility
If circuit model quantum computers are used to implement recursive algorithms, then computational capability is improved, but qubit coherence time requirements become impractically long
Solution Approach 1:
The patent applies partial action by implementing a hybrid approach that combines classical and quantum computing. The system performs only the quantum portion of recursive algorithms using adiabatic quantum computation, while handling other computations classically. This reduces the required qubit coherence time to practical levels while maintaining the ability to implement recursive algorithms.
Solution Approach 2:
The patent uses classical computing as an intermediary to bridge between the quantum processor and the recursive algorithm requirements. The classical system prepares inputs for the quantum computer, processes intermediate results, and coordinates multiple quantum computations, thereby reducing the coherence time burden on quantum qubits while enabling recursive computation.
Data Source
AI summary
A recursive approach to quantum computing employs an initial solution, determines intermediate solutions, evaluates the intermediate solutions and repeats using the intermediate solution, if the intermediate solution does not satisfy solution criteria. A best one of the intermediate solutions may be employed in the recursion.