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Hauptverfasser: Ekanayake, E. M. Hasantha, Venkatakrishnan, Arvind R., Bullo, Francesco, Shukla, Nikhil
Format: Preprint
Veröffentlicht: 2026
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2603.02933
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author Ekanayake, E. M. Hasantha
Venkatakrishnan, Arvind R.
Bullo, Francesco
Shukla, Nikhil
author_facet Ekanayake, E. M. Hasantha
Venkatakrishnan, Arvind R.
Bullo, Francesco
Shukla, Nikhil
contents The design of nonlinear dynamical systems whose gradient flows minimize the Ising Hamiltonian has emerged as a compelling paradigm for realizing Ising machines, forming the foundation of architectures including coherent Ising machines, simulated bifurcation machines, oscillator-based Ising machines, and dynamical Ising machines. Here, we identify a fundamental structural feature shared by these systems, a functional gap defined by the separation between the destabilization of the trivial state and the stabilization of Ising-encoded states. We demonstrate that this separation creates a finite parameter interval in which convergence to an Ising-encoded solution is no longer functionally guaranteed, and the resulting evolution is dictated by the spectral structure of the Jacobian at bifurcation. Subsequently, by introducing a hybrid dynamical framework that reshapes the bifurcation topology, we establish a principled pathway for modulating this parameter gap. The parameter gap thus emerges as a unifying structural principle for the analysis, design and optimization of analog Ising machines.
format Preprint
id arxiv_https___arxiv_org_abs_2603_02933
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Mind the Gap: Where Analog Ising Machines Cease to Minimize the Ising Hamiltonian
Ekanayake, E. M. Hasantha
Venkatakrishnan, Arvind R.
Bullo, Francesco
Shukla, Nikhil
Computational Physics
The design of nonlinear dynamical systems whose gradient flows minimize the Ising Hamiltonian has emerged as a compelling paradigm for realizing Ising machines, forming the foundation of architectures including coherent Ising machines, simulated bifurcation machines, oscillator-based Ising machines, and dynamical Ising machines. Here, we identify a fundamental structural feature shared by these systems, a functional gap defined by the separation between the destabilization of the trivial state and the stabilization of Ising-encoded states. We demonstrate that this separation creates a finite parameter interval in which convergence to an Ising-encoded solution is no longer functionally guaranteed, and the resulting evolution is dictated by the spectral structure of the Jacobian at bifurcation. Subsequently, by introducing a hybrid dynamical framework that reshapes the bifurcation topology, we establish a principled pathway for modulating this parameter gap. The parameter gap thus emerges as a unifying structural principle for the analysis, design and optimization of analog Ising machines.
title Mind the Gap: Where Analog Ising Machines Cease to Minimize the Ising Hamiltonian
topic Computational Physics
url https://arxiv.org/abs/2603.02933