3 papers
quant-ph2025
Quantum Krylov Subspace Diagonalization via Time Reversal Symmetries
Nicola Mariella, Enrique Rico, Adam Byrne +1
Krylov quantum diagonalization methods have emerged as a promising use case for quantum computers. However, many existing implementations rely on controlled operations, which pose…
quant-ph2024
Mitigating exponential concentration in covariant quantum kernels for subspace and real-world data
Gabriele Agliardi, Giorgio Cortiana, Anton Dekusar +6
Fidelity quantum kernels have shown promise in classification tasks, particularly when a group structure in the data can be identified and exploited through a covariant feature map…
quant-ph2024
The quantum super-Krylov method
Adam Byrne, William Kirby, Kirk M. Soodhalter +1
The problem of estimating the ground-state energy of a quantum system is ubiquitous in chemistry and condensed matter physics. Krylov quantum diagonalization (KQD) has emerged as a…