Abstract
Probabilistic computing excels in approximating combinatorial problems and modeling uncertainty. However, using conventional deterministic hardware for probabilistic models is challenging: (pseudo) random number generation introduces computational overhead and additional data shuffling. Therefore, there is a pressing need for different probabilistic computing architectures that achieve low latencies with reasonable energy consumption. Physical computing offers a promising solution, as these systems do not rely on an abstract deterministic representation of data but directly encode the information in physical quantities, enabling inherent probabilistic architectures utilizing entropy sources. Photonic computing is a prominent variant of physical computing due to the large available bandwidth, several orthogonal degrees of freedom for data encoding and optimal properties for in-memory computing and parallel data transfer. Here, we highlight key developments in physical photonic computing and photonic random number generation. We further provide insights into the realization of probabilistic photonic processors and their impact on artificial intelligence systems and future challenges.
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Acknowledgements
We thank J. Stuhrmann, from Illustrato, for his assistance with the illustrations. This research was supported by the European Union’s Horizon 2020 research and innovation program (grant no. 101017237, PHOENICS project) and the European Union’s Innovation Council Pathfinder program (grant no. 101046878, HYBRAIN project). We acknowledge funding support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy EXC 2181/1—390900948 (the Heidelberg STRUCTURES Excellence Cluster), the Excellence Cluster 3D Matter Made to Order (EXC-2082/1—390761711) and CRC 1459 ‘Intelligent Matter’.
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Conceptualization: F.B.-P., W.P. Methodology: F.B.-P., A.P.O., A.V., H. Borras, B.K., G.S.S. Investigation: F.B.-P., A.P.O., A.V., H. Borras, B.K., G.S.S. Visualization: F.B.-P., A.P.O., A.V. Funding acquisition: W.P., H.F., C.D.W., H. Bhaskaran, A.S., H.F. Project administration: W.P., H.F. Supervision: W.P., H.F., C.D.W., H. Bhaskaran, G.S.S., A.S. - Writing—original draft: F.B.-P., A.P.O., A.V. - Writing—review & editing: all authors.
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Brückerhoff-Plückelmann, F., Ovvyan, A.P., Varri, A. et al. Probabilistic photonic computing for AI. Nat Comput Sci 5, 377–387 (2025). https://doi.org/10.1038/s43588-025-00800-1
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DOI: https://doi.org/10.1038/s43588-025-00800-1
