Probabilistic Quantum Circuits With Fallback For Cost Reduction
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Solution Overview
Problem
Existing quantum computing systems face challenges in implementing high-level quantum algorithms as a sequence of reliable and cost-effective gates due to the limitations of different architectures and the increased costs associated with longer gate sequences.
Innovation Solution
The method employs probabilistic quantum circuits with fallback (PQF) that include multiple probabilistic stages and a final deterministic fallback stage to implement target rotations, allowing for probabilistic selection of projective rotation circuits based on their proximity to the target state, thereby reducing the overall cost while maintaining accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If deterministic gate sequences are used to implement quantum operations, then reliability is improved, but cost increases in proportion to the length of gate sequences
Solution Approach 1:
The patent applies dynamics by transitioning from deterministic to probabilistic gate sequences. The system dynamically selects between multiple possible circuit paths based on measurement outcomes, allowing the gate sequence length to vary rather than being fixed. This enables shorter average gate sequences while maintaining reliability through fallback mechanisms when probabilistic attempts fail.
Solution Approach 2:
The patent introduces measurement as an intermediary between the quantum state and the control logic. By measuring intermediate quantum states and using classical feedback to determine subsequent gate operations, the system can terminate early when successful outcomes are achieved, reducing the average gate sequence length while maintaining reliability through conditional fallback paths.
2Manufacturing precision
If longer gate sequences are used to achieve better approximation of target unitary, then manufacturing precision is improved, but loss of time increases
Solution Approach 1:
The system dynamically adjusts the gate sequence length based on measurement outcomes. When probabilistic circuits successfully approximate the target unitary, execution terminates early with shorter gate sequences. When approximations fail, the system dynamically extends the sequence by selecting alternative circuits or activating fallback mechanisms, thus adapting the time investment to the actual approximation quality achieved.
Solution Approach 2:
The patent applies preliminary action by pre-identifying multiple candidate projective rotation circuits with different approximation qualities and costs. By having these circuits prepared in advance and selecting among them based on probabilistic outcomes, the system can achieve good approximations more quickly without needing to systematically explore all possible gate sequences, thereby reducing execution time while maintaining precision.
3Productivity
If multiple projective rotation circuits are probabilistically selected, then cost is reduced, but reliability may worsen due to probabilistic nature
Solution Approach 1:
The patent applies beforehand cushioning by incorporating fallback mechanisms that are prepared in advance. When probabilistic projective rotation circuits fail to achieve the desired approximation, pre-planned fallback circuits are activated to correct the error. This cushioning mechanism ensures reliability is maintained despite the probabilistic nature of the primary circuits, as the fallback paths are ready to compensate for potential failures.
Solution Approach 2:
The system uses feedback by measuring the outcome of probabilistic projective rotation circuits and using this information to determine whether fallback correction is needed. The measurement results feed back into the control logic, which then selects appropriate corrective actions. This feedback loop ensures that reliability is maintained by detecting and correcting failures of probabilistic circuits while still benefiting from their cost advantages when they succeed.
Data Source
AI summary
A low-cost solution for performing a quantum operation provides for defining a target unitary that rotates a single qubit by a target rotation to place the qubit in a target state. The method further provides for identifying multiple projective rotation circuits that each implement an approximation of the target rotation upon successful measurement and assigning a selection probability to each of the multiple identified projective rotation circuits, the selection probability being defined by a metric that increases in value in proportion to a proximity between a qubit state resulting from the approximation and the target qubit state. The method further provides for probabilistically selecting one of the multiple projective rotation circuits according to the assigned selection probabilities and outputting a circuit definition that includes the selected projective rotation circuit.