Author

Alexander Makarovskiy

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Preprint Jul 2026

The trainability of photonic quantum circuits

Variational quantum algorithms are a leading approach to near-term quantum computing, but their scalability can be limited by barren plateaus and the sampling cost of resolving small changes in the loss landscape. Here, we study the trainability of passive linear-optical quantum circuits and introduce a framework based...

Alexander Makarovskiy, Adam J. Taylor, Zheng-Hao Li et al. · 1 citation

Open access Jul 2026

Hybrid quantum-classical de novo design of MHC-binding peptides

Deep generative models have become a leading approach for designing therapeutic molecules, yet efficiently exploring vast biomolecular sequence spaces remains difficult, particularly for targets with limited training data. The prior distribution that seeds a generative model shapes which regions of sequence space it ex...

E. S. Engdal, Jonathan Funk, O. Bacarreza et al. · bioRxiv · 0 citations