Gate set tomography (GST) is a protocol for detailed, predictive characterization of logic
operations (gates) on quantum computing processors. Early versions of GST emerged …

The problem of finding the ground state energy of a Hamiltonian using a quantum computer
is currently solved using either the quantum phase estimation (QPE) or variational quantum …

The efficient characterization of quantum systems,,, the verification of the operations of
quantum devices,, and the validation of underpinning physical models,,, are central …

We introduce a new method called rejection filtering that we use to perform adaptive
Bayesian phase estimation. Our approach has several advantages: it is classically efficient …

We study the problem of learning the Hamiltonian of a many-body quantum system from
experimental data. We show that the rate of learning depends on the amount of control …

In recent years quantum simulation has made great strides, culminating in experiments that
existing supercomputers cannot easily simulate. Although this raises the possibility that …

We design and analyze two new low depth algorithms for amplitude estimation (AE)
achieving an optimal tradeoff between the quantum speedup and circuit depth. For $\beta\in …

Unwanted interaction between a quantum system and its fluctuating environment leads to
decoherence and is the primary obstacle to establishing a scalable quantum information …

In this work we combine two distinct machine learning methodologies, sequential Monte
Carlo and Bayesian experimental design, and apply them to the problem of inferring the …

The number of measurements demanded by hybrid quantum-classical algorithms such as
the variational quantum eigensolver (VQE) is prohibitively high for many problems of …