Christopher Heins is a researcher at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Germany, and a member of the Magnonics group. His research focuses on nonlinear spin-wave dynamics and their application to unconventional and neuromorphic computing. In particular, he investigates magnetic vortices as platforms for magnon-based information processing and explores electrical spin-wave detection as a route toward integrated, energy-efficient magnonic computing architectures.

The rapidly growing computational demands of artificial intelligence call for alternative computing concepts that overcome the energy and architectural limitations of conventional electronics. Physical reservoir computing offers such an approach by exploiting the intrinsic nonlinear dynamics of a physical system for information processing. Magnons, the wave-like excitations of magnetically ordered materials, are particularly promising in this context due to their rich nonlinear interactions and characteristic microwave frequencies.

Here, we use magnetic vortices as a versatile platform for nonlinear magnon dynamics and neuromorphic information processing. By encoding information into sequences of microwave excitations, nonlinear scattering between confined magnon modes maps input signals onto a multidimensional spectral response. This enables temporal pattern recognition directly in reciprocal space, without requiring information transport between spatially separated computational nodes [1].

Beyond information processing, the characteristic separation of timescales between high-frequency magnon modes and the low-frequency gyration of the vortex core provides access to strongly driven dynamical regimes, thereby enhancing the complexity of the system. Coherent vortex-core motion periodically modulates the magnetic texture, resulting in the formation of self-induced Floquet magnon bands and frequency combs [2].

A key step toward practical magnonic neuromorphic hardware is the integration of such dynamics with electrical interfaces. We demonstrate electrical spin-wave detection using foundry-fabricated nanoscale magnetic tunnel junctions [3]. Combining nonlinear magnon dynamics with electrical readout provides a pathway toward compact and energy-efficient magnonic neuromorphic devices.

1. L. Körber, C. Heins et al., Nat. Commun. 14, 3954 (2023), DOI: 10.1038/s41467-023-39452-y
2. C. Heins et al., Science 391, 190–194 (2026), DOI: 10.1126/science.adq9891
3. C. Heins et al., arXiv:2509.19483 (2025).