Temperature Scheduling for Energy-Based Optimization Search
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Solution Overview
Problem
Determining appropriate temperature values for methods like simulated annealing and replica exchange is challenging in solving optimization problems.
Innovation Solution
An information processing apparatus and method that acquires and adjusts temperature values by monitoring energy function updates during the search process, determining suitable temperature values based on whether the energy value is smaller than the previous smallest value, and outputting new temperature ranges for more efficient searches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If temperature values are set arbitrarily for simulated annealing or replica exchange methods, then the optimization search can proceed, but the efficiency of finding the ground state deteriorates due to inappropriate temperature selection
Solution Approach 1:
The system automatically determines appropriate temperature values by having the search unit execute preliminary searches at candidate temperature values and having the determination unit select optimal temperatures based on the energy function values obtained, eliminating the need for manual temperature value determination while optimizing search efficiency
Solution Approach 2:
The system performs preliminary searches at multiple candidate temperature values before the main optimization process to evaluate which temperature values are most suitable, allowing the determination of optimal temperature parameters in advance to guide the subsequent efficient search
2Measurement precision
If a wide range of temperature values is tested to find suitable values, then the accuracy of temperature selection improves, but the computational overhead and time consumption increase
Solution Approach 1:
The system changes the temperature parameter systematically by testing a plurality of candidate temperature values and selecting those that yield appropriate energy function values, allowing precise temperature selection through controlled parameter variation rather than exhaustive searching
Solution Approach 2:
The determination unit uses feedback from the search unit's results at different temperature values to identify which temperature values are most suitable, creating a closed-loop system where temperature selection is refined based on actual search performance rather than arbitrary selection
Data Source
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AI summary
A method includes: acquiring, from a search node configured to perform a search for a ground state represented by plural state variables included in an energy function by using plural temperature values and hold a value of the energy function for the plural state variables, a value of the energy function obtained for the plural state variables at a first temperature value among the plural temperature values; determining whether the value acquired is smaller than a smallest value of the energy function obtained for the plural state variables before reaching the first temperature value; recording update information indicating that the smallest value has been updated at the first temperature value in a case where the value is smaller than the smallest value; and outputting a second temperature value based on the first temperature value at which the update information has been recorded among the plural temperature values.