17 citations · 36 across the 6 of their papers we have counts for
6 papers
Exploiting overcompleteness of Platonic-solid POVMs for shadow estimation
Dario Melegari, Stefano Mangini, Keijo Korhonen +2
Accurately estimating expectation values of observables from a finite number of measurement shots is a central challenge in quantum information science. Informationally overcomplet…
Improving shadow estimation with locally-optimal dual frames
Keijo Korhonen, Stefano Mangini, Joonas Malmi +2
Accurate estimation of observables in quantum systems is a central challenge in quantum information science, yet practical implementations are fundamentally constrained by the limi…
Practical techniques for high-precision measurements on near-term quantum hardware and applications in molecular energy estimation
Keijo Korhonen, Hetta Vappula, Adam Glos +6
Achieving high-precision measurements on near-term quantum devices is critical for advancing quantum computing applications. Quantum computers suffer from high readout errors, maki…
Low variance estimations of many observables with tensor networks and informationally-complete measurements
Stefano Mangini, Daniel Cavalcanti
Accurately estimating the properties of quantum systems is a central challenge in quantum computing and quantum information. We propose a method to obtain unbiased estimators of mu…
Tensor network noise characterization for near-term quantum computers
Stefano Mangini, Marco Cattaneo, Daniel Cavalcanti +3
Characterization of noise in current near-term quantum devices is of paramount importance to fully use their computational power. However, direct quantum process tomography becomes…
Enhanced observable estimation through classical optimization of informationally over-complete measurement data -- beyond classical shadows
Joonas Malmi, Keijo Korhonen, Daniel Cavalcanti +1
In recent years, informationally complete measurements have attracted considerable attention, especially in the context of classical shadows. In the particular case of informationa…