2 papers
quant-ph2025
Quantum advantage without exponential concentration: Trainable kernels for symmetry-structured data
Laura J. Henderson, Kerstin Beer, Salini Karuvade +3
Quantum kernel methods promise enhanced expressivity for learning structured data, but their usefulness has been limited by kernel concentration and barren plateaus. Both effects a…
quant-ph2025
Characterizing noisy quantum computation with imperfectly addressed errors
Riddhi S. Gupta, Salini Karuvade, Kerstin Beer +2
Quantum protocols on hardware are subject to noise that prohibits performance. Protocols for addressing errors, such as error correction or error mitigation, may fail to combat err…