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Related Articles from SNS
Optimizing Energy-based Neural Network Training with Coherent Ising Machine
Announce Type: new Abstract: While Ising machines serve as advanced physical solvers for the Ising model,enabling applications in combinatorial optimization and neural network training,their scalability for large-scale neural networks remains constrained by hardware connectivity limitations and suboptimal training methodologies. In this work,we leverage a Coherent Ising Machine (CIM) to train an energy-based neural network using Equilibrium Propagation, achieving performance comparable to...
Beyond Gradient Descent: Adam for Analog Ising Machines
Announce Type: new Abstract: As Moore's law reaches its limits, Ising machines offer a promising alternative computing approach for difficult optimization problems. However, many analog, time-continuous Ising machines rely on gradient-descent-like dynamics to find solutions, which can limit speed and robustness.
Beyond Gradient Descent: Adam for Analog Ising Machines
Announce Type: cross Abstract: As Moore's law reaches its limits, Ising machines offer a promising alternative computing approach for difficult optimization problems. However, many analog, time-continuous Ising machines rely on gradient-descent-like dynamics to find solutions, which can limit speed and robustness.
A Cluster Expansion and the Decay of Correlations of the 1D Long-Range Ising Model at Low Temperatures
Mathematical Physics [Submitted on 12 Feb 2026 (v1), last revised 29 May 2026 (this version, v2)] Title:A Cluster Expansion and the Decay of Correlations of the 1D Long-Range Ising Model at Low Temperatures View PDF HTML (experimental)Abstract:In this work, a convergent low-temperature cluster expansion of the one-dimensional long-range ferromagnetic Ising model with polynomial decay $\alpha\in (1,2]$ is developed; that is, $J(r)=r^{-\alpha}$. As an application, the $n$-point correlations...
Exact solution of the two-dimensional (2D) Ising model at an external magnetic field
arXiv:2512.16935v4 Announce Type: replace Abstract: The exact solution of the two-dimensional (2D) Ising model at an external magnetic field is derived by a modified Clifford algebraic approach. At first, the transfer matrices are analyzed in three representations, i.e., Clifford algebraic representation, transfer tensor representation and schematic representation, to inspect nonlocal effects in this many-body interacting system. It is ensured that nontrivial topological structures exist in...
Cosm: Collective Switched Motion for Fast and Accurate Sparse Ising Optimization
arXiv:2605.30355v1 Announce Type: new Abstract: We introduce Collective Switched Motion (Cosm), a heuristic algorithm for solving sparse Ising-type optimization problems. Cosm combines locally interacting continuous circular variables with global coordination rules that facilitate collective dynamics. Pairwise interactions occur sequentially over a set of conflict-free edge partitions, resulting in an interaction network that switches periodically.
Cosm: Collective Switched Motion for Fast and Accurate Sparse Ising Optimization
arXiv:2605.30355v1 Announce Type: cross Abstract: We introduce Collective Switched Motion (Cosm), a heuristic algorithm for solving sparse Ising-type optimization problems. Cosm combines locally interacting continuous circular variables with global coordination rules that facilitate collective dynamics. Pairwise interactions occur sequentially over a set of conflict-free edge partitions, resulting in an interaction network that switches periodically.
Hybridizing Equilibrium Propagation with Ising Machines for Efficient Energy-Based Learning
arXiv:2606.09112v1 Announce Type: new Abstract: The rapid evolution of artificial intelligence has led to substantial advances in deep neural networks. Nonetheless, conventional GPU-based training remains highly energy-demanding, motivating the exploration of physical dynamics and compatible energy-based learning schemes, such as equilibrium propagation (EP). EP-based training, however, frequently suffers from convergence to local minima due to phase-space contraction.
Cosm: Collective Switched Motion for Fast and Accurate Sparse Ising Optimization
Announce Type: replace Abstract: We introduce Collective Switched Motion (Cosm), a dynamical system-based heuristic algorithm. Cosm combines locally interacting continuous circular variables with novel global coordination rules that facilitate collective dynamics. Pairwise interactions occur sequentially over a set of conflict-free edge partitions, resulting in an interaction network that switches periodically.
Cosm: Collective Switched Motion for Fast and Accurate Sparse Ising Optimization
Announce Type: replace-cross Abstract: We introduce Collective Switched Motion (Cosm), a dynamical system-based heuristic algorithm. Cosm combines locally interacting continuous circular variables with novel global coordination rules that facilitate collective dynamics. Pairwise interactions occur sequentially over a set of conflict-free edge partitions, resulting in an interaction network that switches periodically.