Author

Michele Grossi

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#machine learning Preprint Sep 2026

Weighted Quantum Signal Processing: Low-Depth Polynomial Approximation with Applications to Kolmogorov-Arnold Networks

Quantum Signal Processing is a powerful quantum framework for generating and approximating univariate polynomials. However, QSP is often limited by circuit-depth bottlenecks and parity constraints on the class of realizable polynomials. In this work, we introduce Weighted Quantum Signal Processing, an extension of QSP...

Rohit Sarma Sarkar, Rupayan Bhattacharjee, E. F. Combarro et al. · 0 citations

Preprint Jul 2026

Neural quantum states for non-Abelian lattice gauge theories with dynamical fermions

Determining the ground state of non-Abelian lattice gauge theories coupled to dynamical fermions is key to understanding confinement and the phase structure of gauge--matter systems. We present a variational Monte Carlo framework for the ground state of the untruncated fully-continuous SU$(2)$ lattice gauge theory coup...

Gabriel Rouxinol, Julian Bender, Michele Grossi et al. · 2 citations