Optical Trap Reconfiguration Algorithm Minimizes Atom Loss
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Solution Overview
Problem
Existing algorithms for reconfiguring particles in optical traps face challenges such as high particle loss probability and inefficiency due to arbitrary displacement trajectory ordering, which increases the number of transfer operations and uncertainty about lost atoms, and do not optimize for minimizing the number of displaced atoms.
Innovation Solution
The implementation of an ordering subroutine to ensure each atom is displaced at most once and a rerouting subroutine to reduce the number of displaced atoms without increasing total displacement distance, combined with all-pairs shortest path and assignment problem solutions, to create a cycle-free path system that minimizes both displacement and transfer operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If assignment algorithms are used to solve reconfiguration problems, then a sequence of displacement trajectories can be generated, but the trajectories are sorted and executed in an arbitrary order which causes early trajectories to obstruct later trajectories and increases the number of transfer operations
Solution Approach 1:
The patent applies preliminary action by computing and storing all-pairs shortest paths before generating displacement trajectories. This pre-computation allows the algorithm to efficiently determine optimal paths and ordering during trajectory generation, preventing obstructions and minimizing transfer operations without requiring re-computation during execution
Solution Approach 2:
The patent uses feedback mechanisms by iteratively refining the trajectory sequence based on obstruction detection. The algorithm evaluates the impact of each trajectory on subsequent trajectories and adjusts the ordering to eliminate obstructions, using information from each evaluation step to improve the overall sequence
2Reliability
If the same atom is displaced multiple times due to arbitrary ordering, then the probability of losing the atom increases
Solution Approach 1:
The patent applies preliminary action by pre-computing all-pairs shortest paths and using this information to determine an optimal execution order of displacement trajectories. This ensures that each atom is displaced at most once by identifying and eliminating trajectories that would cause re-displacement, thereby reducing particle loss probability
Solution Approach 2:
The patent uses feedback by evaluating trajectory intersections and detecting when executing a trajectory would cause an atom to be displaced multiple times. The algorithm adjusts the trajectory sequence based on this feedback to minimize re-displacement events and associated particle loss
3Productivity
If algorithms do not optimize for the number of displaced atoms, then the total number of displacement operations may be minimized, but the uncertainty about which atoms will be lost increases
Solution Approach 1:
The patent uses feedback mechanisms to track and count the number of displaced atoms throughout the trajectory execution. By monitoring which atoms are displaced and how many times, the algorithm reduces uncertainty about particle loss while maintaining efficient processing through optimized trajectory ordering
4Ease of operation
If the number of displaced atoms is increased to achieve target configuration, then the number of transfer operations increases, but this increases the probability of losing atoms
Solution Approach 1:
The patent applies parameter changes by optimizing the displacement trajectory parameters to minimize the number of displaced atoms. By adjusting the path selection and execution order based on pre-computed shortest paths, the algorithm achieves the target configuration with fewer transfer operations, thereby reducing particle loss probability while maintaining reconfiguration flexibility
Data Source
AI summary
A computer-implemented method of solving a reconfiguration problem, the method comprising: solving an all-pairs shortest path (APSP) problem, including computing a distance between each token source location and each token target location; solving an assignment problem on the computed distances, said solving the assignment problem yielding a path system having a set of shortest paths; performing a cycle breaking function on the path system, the cycle-breaking function breaking all cycles in the path system; and ordering order the cycle free path system.