Light Waveform Spectrum Control Using Simulated Annealing
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Solution Overview
Problem
Existing methods for controlling light waveforms using spatial light modulators (SLMs) face challenges in accurately calculating optimal spectrum intensities, leading to localized solutions and reduced waveform control accuracy.
Innovation Solution
A data generating device and method that employs a simulated annealing algorithm to iteratively refine the intensity spectrum function, using an initial candidate solution, neighborhood solution generation, evaluation value calculation, and temperature updating to converge on an optimal intensity spectrum for desired time-intensity waveforms, reducing the likelihood of localized solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the iterative Fourier transform algorithm (IFTA) is used to calculate the intensity spectrum, then the calculation process is simple and fast, but localized solutions occur at a relatively high ratio, reducing waveform control accuracy
Solution Approach 1:
The patent changes the calculation parameters by introducing a simulated annealing mechanism with temperature parameter T that evolves over iterations. The acceptance probability P = exp(-ΔE/T) allows the system to transition from greedy optimization to probabilistic exploration, changing the search behavior from deterministic to stochastic as temperature decreases, thereby avoiding localized solutions while maintaining convergence.
Solution Approach 2:
The patent introduces dynamic behavior to the optimization process through the temperature parameter T that decreases over time according to a cooling schedule. This dynamic parameter allows the system to adapt its search strategy: at high temperatures, it explores broadly; at low temperatures, it exploits locally, creating a time-varying optimization process that balances exploration and exploitation.
2Device complexity
If conventional optimization methods are used to find the intensity spectrum, then the computational complexity is low, but the solution accuracy deteriorates due to frequent localized solutions
Solution Approach 1:
The patent introduces an intermediary probabilistic acceptance mechanism that mediates between the simple IFTA approach and the need for global optimization. The probability function P = exp(-ΔE/T) acts as an intermediary that allows occasional acceptance of worse solutions during early iterations, enabling escape from localized optima without requiring complex global optimization algorithms.
3Manufacturing precision
If the iterative process repeats many times to avoid localized solutions, then the solution accuracy improves, but the calculation time increases
Solution Approach 1:
The patent implements periodic action through the cooling schedule where the temperature parameter T is reduced at regular intervals according to T_{n+1} = αT_n. This periodic reduction creates phases of broad exploration followed by focused exploitation, allowing the system to achieve high accuracy without requiring an excessively large number of iterations.
Data Source
AI summary
A data generating device sets an initial candidate solution of an intensity spectrum function, a phase spectrum function, and an initial temperature and a cooling rate, generates a neighborhood solution, transforms a first waveform function of a frequency domain including the neighborhood solution and the phase spectrum function into a second waveform function of a time domain including a time-intensity waveform function and a time-phase waveform function and calculates an evaluation value representing a degree of difference between the time-intensity waveform function and the desired time-intensity waveform, sets the neighborhood solution as an n-th candidate solution for a certain probability, and lowers the temperature on the basis of the cooling rate. A decrease in the temperature acts in a direction in which the probability P is lowered when the evaluation value of the neighborhood solution is worse than the evaluation value of the candidate solution.