We report all-optical implementation of the optimization algorithm for the famous "ant colony" problem. Ant colonies progressively optimize pathway to food discovered by one of the ants through identifying the discovered route with volatile chemicals (pheromones) secreted on the way back from the food deposit. Mathematically this is an important example of graph optimization problem with dynamically changing parameters. Using an optical network with nonlinear waveguides to represent the graph and a feedback loop, we experimentally show that photons traveling through the network behave like ants that dynamically modify the environment to find the shortest pathway to any chosen point in the graph. This proof-of-principle demonstration illustrates how transient nonlinearity in the optical system can be exploited to tackle complex optimization problems directly, on the hardware level, which may be used for self-routing of optical signals in transparent communication networks and energy flow in photonic systems.
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http://dx.doi.org/10.1038/srep26283 | DOI Listing |
Nanophotonics
August 2024
Photonics Initiative, Advanced Science Research Center, City University of New York, New York, NY 10031, USA.
Reciprocal scatterers necessarily extinguish the same amount of incoming power when excited from opposite directions. This property implies that it is not possible to realize scatterers that are transparent when excited from one direction but that scatter and absorb light for the opposite excitation, limiting opportunities in the context of asymmetric imaging and nanophotonic circuits. This reciprocity constraint may be overcome with an external bias that breaks time-reversal symmetry, posing however challenges in terms of practical implementations and integration.
View Article and Find Full Text PDFNanophotonics
May 2024
Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH, UK.
Nanophotonics
May 2024
Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA.
Chalcogenide-based nonvolatile phase change materials (PCMs) have a long history of usage, from bulk disk memory to all-optic neuromorphic computing circuits. Being able to perform uniform phase transitions over a subwavelength scale makes PCMs particularly suitable for photonic applications. For switching between nonvolatile states, the conventional chalcogenide phase change materials are brought to a melting temperature to break the covalent bonds.
View Article and Find Full Text PDFOptical neural networks (ONNs) are custom optical circuits promising a breakthrough in low-power, parallelized, and high-speed hardware, for the growing demands of artificial intelligence applications. All-optical implementation of ONNs has proven burdensome chiefly due to the lack of optical devices that can emulate the neurons' non-linear activation function, thus forcing hybrid optical-electronic implementations. Moreover, ONNs suffer from a large footprint in comparison to their electronic (CMOS-based) counterparts.
View Article and Find Full Text PDFThe generation and structural characteristics of random speckle patterns impact the implementation and imaging quality of computational ghost imaging. Their modulation is limited by traditional electronic hardware. We aim to address this limitation using the features of an all-optical neural network.
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