Saved in:
Bibliographic Details
Main Authors: Zhang, Haiyang, Wang, Hao, Zhou, Rui, Chang, Sheng
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2603.02771
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866918367426772992
author Zhang, Haiyang
Wang, Hao
Zhou, Rui
Chang, Sheng
author_facet Zhang, Haiyang
Wang, Hao
Zhou, Rui
Chang, Sheng
contents The Ising model, originally proposed a century ago, has become a cornerstone of combinatorial optimization in recent decades. However, Ising machines remain constrained by a fundamental hardware-speed trade-off. We introduce the Bounce-Bind Ising Machine (BBIM), a mechanism with a single tunable parameter that modulates spin dynamics without altering the energy landscape, building upon the classic golf-ball analogy but replacing it with a dynamic tennis ball/shot put system. The Bounce mode (accelerating escapes from local minima) and Bind mode (enabling rapid convergence) dynamically balance speed and quality. Benchmarked on dense MAX-CUT (edge density=0.5), BBIM achieves a peak speedup of 6.15 times at n=200. For sparse 3-Regular 3-XORSAT (second-order), the peak speedup reaches 27.3 times at n=160. Both results incur negligible additional hardware resource consumption. This work demonstrates a critical pathway to circumventing the hardware-speed bottleneck and its practical applicability to large-scale optimization hardware, validated on structurally distinct benchmarks.
format Preprint
id arxiv_https___arxiv_org_abs_2603_02771
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Changing the Game: The Bounce-Bind Ising Machine
Zhang, Haiyang
Wang, Hao
Zhou, Rui
Chang, Sheng
Hardware Architecture
The Ising model, originally proposed a century ago, has become a cornerstone of combinatorial optimization in recent decades. However, Ising machines remain constrained by a fundamental hardware-speed trade-off. We introduce the Bounce-Bind Ising Machine (BBIM), a mechanism with a single tunable parameter that modulates spin dynamics without altering the energy landscape, building upon the classic golf-ball analogy but replacing it with a dynamic tennis ball/shot put system. The Bounce mode (accelerating escapes from local minima) and Bind mode (enabling rapid convergence) dynamically balance speed and quality. Benchmarked on dense MAX-CUT (edge density=0.5), BBIM achieves a peak speedup of 6.15 times at n=200. For sparse 3-Regular 3-XORSAT (second-order), the peak speedup reaches 27.3 times at n=160. Both results incur negligible additional hardware resource consumption. This work demonstrates a critical pathway to circumventing the hardware-speed bottleneck and its practical applicability to large-scale optimization hardware, validated on structurally distinct benchmarks.
title Changing the Game: The Bounce-Bind Ising Machine
topic Hardware Architecture
url https://arxiv.org/abs/2603.02771