Coupling Light with Matter for Identifying Dominant Subnetworks

• URL: http://arxiv.org/abs/2405.17296v1
• Date: Mon, 27 May 2024 16:00:21 GMT
• Title: Coupling Light with Matter for Identifying Dominant Subnetworks
• Authors: Airat Kamaletdinov, Natalia G. Berloff,
• Abstract summary: We present a novel light-matter platform that uses complex neural networks to identify dominantworks and uncover indirect correlations within larger networks. This approach offers significant advantages, including low energy consumption, high processing speed, and the immediate identification of co-valued and counter-regulated nodes without post-processing.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present a novel light-matter platform that uses complex-valued oscillator networks, a form of physical neural networks, to identify dominant subnetworks and uncover indirect correlations within larger networks. This approach offers significant advantages, including low energy consumption, high processing speed, and the immediate identification of co- and counter-regulated nodes without post-processing. The effectiveness of this approach is demonstrated through its application to biological networks, and we also propose its applicability to a wide range of other network types.

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