7 papers
Scientific discovery as meta-optimization: a combinatorial optimization case study
Yuan-Hang Zhang, Chesson Sipling, Massimiliano Di Ventra
Scientific discovery is fundamentally an optimization problem, defined by a vast "state space" of theories and experiments, and an evaluation criterion based on quality, novelty, a…
Memory-induced long-range order drag
Yuan-Hang Zhang, Chesson Sipling, Massimiliano Di Ventra
Recent research has shown that memory, in the form of slow degrees of freedom, can induce a phase of long-range order (LRO) in locally-coupled fast degrees of freedom, producing po…
CrSe_2 and CrTe_2 Monolayers as Efficient Air Pollutants Nanosensors
Hakkim Vovusha, Puspamitra Panigrahi, Yash Pal +4
Nanosensors are critical in environmental monitoring, industrial safety, and public health by detecting specific hazardous gases like CO, NO, SO_2, and CH_4 at trace levels. This s…
Phase-Space Engineering and Collective Dynamics in Memcomputing
Chesson Sipling, Yuan-Hang Zhang, Massimiliano Di Ventra
Digital Memcomputing machines (DMMs) are dynamical systems with memory (time non-locality) that have been designed to solve combinatorial optimization problems. Their corresponding…
On the solvable-unsolvable transition due to noise-induced chaos in digital memcomputing
Dyk Chung Nguyen, Thomas Chetaille, Yuan-Hang Zhang +2
Digital memcomputing machines (DMMs) have been designed to solve complex combinatorial optimization problems. Since DMMs are fundamentally classical dynamical systems, their ordina…
A Generative Neural Annealer for Black-Box Combinatorial Optimization
Yuan-Hang Zhang, Massimiliano Di Ventra
We propose a generative, end-to-end solver for black-box combinatorial optimization that emphasizes both sample efficiency and solution quality on NP problems. Drawing inspiration…