Reply to: Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture

Reply to: Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture

We wish to thank Stefan Boettcher for prompting us to further check and highlight the accuracy and scaling of our results. Here we provide a comprehensive response to the Comment written by him. We argue that the Comment did not account for the fairness of the comparison between different methods in...

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Veröffentlicht in:arXiv.org 2023-05
Hauptverfasser: Fan, Changjun, Shen, Mutian, Nussinov, Zohar, Liu, Zhong, Sun, Yizhou, Yang-Yu, Liu
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Ground state
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creator Fan, Changjun
Shen, Mutian
Nussinov, Zohar
Liu, Zhong
Sun, Yizhou
Yang-Yu, Liu
description We wish to thank Stefan Boettcher for prompting us to further check and highlight the accuracy and scaling of our results. Here we provide a comprehensive response to the Comment written by him. We argue that the Comment did not account for the fairness of the comparison between different methods in searching for the spin-glass ground states. We demonstrate that, with a reasonably larger number of initial spin configurations, our results agree with the asymptotic scaling form assumed by finite-size corrections.
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subjects Ground state
Spin glasses
title Reply to: Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture
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