arXiv subjects

Andrea Caprotti

Publications and source records attributed to Andrea Caprotti.

2 recordsLinked to original sources

arXiv2026

Post-processing optimization and optimal bounds for non-adaptive shadow tomography

Informationally overcomplete POVMs are known to outperform minimally complete measurements in many tomography and estimation tasks, and they also leave a purely classical freedom in shadow tomography: the same observable admits infinitely many unbiased linear reconstructions from identical measurement data. We formulate the choice of reconstruction coefficients as a convex minimax problem and give an algorithm with guaranteed convergence that returns the tightest state-independent variance bound achievable by post-processing for a fixed POVM and observable. Numerical examples show that the resulting estimators can dramatically reduce sampling complexity relative to standard (canonical) reconstructions, and can even improve the qualitative scaling with system size for structured noncommuting targets.

quant-ph↗

arXiv2024

Optimising quantum tomography via shadow inversion

In quantum information theory, the accurate estimation of observables is pivotal for quantum information processing, playing a crucial role in compute and communication protocols. This work introduces a novel technique for estimating such objects, leveraging an underutilised resource in the inversion map of classical shadows that greatly refines the estimation cost of target observables without incurring any additional overhead. A generalised framework for computing and optimising additional degrees of freedom in the homogeneous space of the shadow inversion is given that may be adapted to a variety of near-term problems. In the special case of local measurement strategies we show feasible optimisation leading to an exponential separation in sample complexity versus the standard approach and in an exceptional case we give non-trivial examples of optimised post-processing for local measurements, achieving the same efficiency as the global Cliffords shadows.

quant-ph↗