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The potential of multidimensional photonic computing

Nature Reviews Physics volume 7, pages 439–450 (2025)Cite this article

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Abstract

The rapidly increasing demands on computational throughput, bandwidth and memory capacity fuelled by breakthroughs in machine learning pose substantial challenges for conventional electronic computing platforms. Historically, advancing compute performance relied on miniaturization to increase the transistor count on a given chip area and, more recently, on the development of parallel and multicore architectures. Computing platforms that process data using multiple, orthogonal dimensions can achieve exponential scaling on trajectories much steeper than what is possible with conventional strategies. One promising analog platform is photonics, which makes use of the physics of light, such as sensitivity to material properties and ability to encode information across multiple degrees of freedom. With recent breakthroughs in integrated photonic hardware and control, large-scale photonic systems have become a practical and timely solution for data-intensive, real-time computational tasks. Here, we explain developments in the realization of multidimensional computing platforms based on photonic systems. Moving to such architectures holds promise for low-latency, high-bandwidth information processing at reduced energy consumption.

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Fig. 1: Degrees of freedom in optical computing.
Fig. 2: Overview of basic building blocks for neuromorphic photonic computing approaches and platforms.
Fig. 3: Configuration of a quantum neural network.
Fig. 4: Perspective for neuromorphic quantum photonics.

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Acknowledgements

The authors thank J. Stuhrmann, from Illustrato, for his assistance with the illustrations. The research is funded by the 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’ — European Union’s Horizon 2020 research and innovation programme (grant no. 101017237, PHOENICS project, grant no. 101119489, 2DNEURALVISION project) and the European Union’s Innovation Council Pathfinder programme (grant no. 101046878, HYBRAIN project).

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Author notes

  1. These authors contributed equally: Ivonne Bente, Shabnam Taheriniya.

Authors and Affiliations

  1. Physics Institute, University of Münster, Münster, Germany

    Ivonne Bente, Frank Brückerhoff-Plückelmann & Wolfram Pernice

  2. Kirchhoff-Institute for Physics, Heidelberg University, Heidelberg, Germany

    Shabnam Taheriniya, Frank Brückerhoff-Plückelmann & Wolfram Pernice

  3. Consiglio Nazionale delle Ricerche, Istituto di Fotonica e Nanotecnologie (CNR-IFN), Milan, Italy

    Francesco Lenzini

  4. Institute for Photonics, Leibniz University Hannover, Hannover, Germany

    Michael Kues

  5. Department of Materials, University of Oxford, Oxford, UK

    Harish Bhaskaran

  6. Department of Engineering, University of Exeter, Exeter, UK

    C. David Wright

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  1. Ivonne Bente
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  2. Shabnam Taheriniya
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Contributions

I.B., S.T. and F.L. wrote the initial version of the article. All authors contributed substantially to discussion of the content. All authors reviewed and/or edited the manuscript before submission.

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Correspondence to Wolfram Pernice.

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Bente, I., Taheriniya, S., Lenzini, F. et al. The potential of multidimensional photonic computing. Nat Rev Phys 7, 439–450 (2025). https://doi.org/10.1038/s42254-025-00843-3

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