612 citations · 3.6k across the 33 of their papers we have counts for
5 papers · 1 filter
Efficiently learning non-Markovian noise in many-body quantum simulators
Jordi A. Montañà-López, Andreas Elben, Joonhee Choi +1
As quantum simulators are scaled up to larger system sizes and lower noise rates, non-Markovian noise channels are expected to become dominant. While provably efficient protocols f…
Analytically Continuing the Randomized Measurement Toolbox
Akash Vijay, Ayush Raj, Jonah Kudler-Flam +3
We develop a framework for extracting non-polynomial analytic functions of density matrices in randomized measurement experiments by a method of analytical continuation. A central…
Classical shadows for sample-efficient measurements of gauge-invariant observables
Jacob Bringewatt, Henry Froland, Andreas Elben +1
Classical shadows provide a versatile framework for estimating many properties of quantum states from repeated, randomly chosen measurements without requiring full quantum state to…
RandomMeas.jl: A Julia Package for Randomized Measurements in Quantum Devices
Andreas Elben, Benoît Vermersch
We introduce $\texttt{RandomMeas$.$jl}$, a modular and high-performance open-source software package written in Julia for implementing and analyzing randomized measurement protocol…
Optimal randomized measurements for a family of non-linear quantum properties
Zhenyu Du, Yifan Tang, Andreas Elben +3
Quantum learning encounters fundamental challenges when estimating non-linear properties, owing to the inherent linearity of quantum mechanics. Although recent advances in single-c…