[HTML][HTML] The variational quantum eigensolver: a review of methods and best practices
The variational quantum eigensolver (or VQE), first developed by Peruzzo et al.(2014), has
received significant attention from the research community in recent years. It uses the …
received significant attention from the research community in recent years. It uses the …
Provably efficient machine learning for quantum many-body problems
Classical machine learning (ML) provides a potentially powerful approach to solving
challenging quantum many-body problems in physics and chemistry. However, the …
challenging quantum many-body problems in physics and chemistry. However, the …
Unbiasing fermionic quantum Monte Carlo with a quantum computer
Interacting many-electron problems pose some of the greatest computational challenges in
science, with essential applications across many fields. The solutions to these problems will …
science, with essential applications across many fields. The solutions to these problems will …
Shallow shadows: Expectation estimation using low-depth random Clifford circuits
We provide practical and powerful schemes for learning properties of a quantum state using
a small number of measurements. Specifically, we present a randomized measurement …
a small number of measurements. Specifically, we present a randomized measurement …
Learning to predict arbitrary quantum processes
We present an efficient machine-learning (ML) algorithm for predicting any unknown
quantum process E over n qubits. For a wide range of distributions D on arbitrary n-qubit …
quantum process E over n qubits. For a wide range of distributions D on arbitrary n-qubit …
Optimizing shadow tomography with generalized measurements
HC Nguyen, JL Bönsel, J Steinberg, O Gühne - Physical Review Letters, 2022 - APS
Advances in quantum technology require scalable techniques to efficiently extract
information from a quantum system. Traditional tomography is limited to a handful of qubits …
information from a quantum system. Traditional tomography is limited to a handful of qubits …
[HTML][HTML] Classical shadows with noise
The classical shadows protocol, recently introduced by Huang, Kueng, and Preskill [Nat.
Phys. 16, 1050 (2020)], is a quantum-classical protocol to estimate properties of an unknown …
Phys. 16, 1050 (2020)], is a quantum-classical protocol to estimate properties of an unknown …
Classical shadow tomography with locally scrambled quantum dynamics
We generalize the classical shadow tomography scheme to a broad class of finite-depth or
finite-time local unitary ensembles, known as locally scrambled quantum dynamics, where …
finite-time local unitary ensembles, known as locally scrambled quantum dynamics, where …
Scalable and flexible classical shadow tomography with tensor networks
Classical shadow tomography is a powerful randomized measurement protocol for
predicting many properties of a quantum state with few measurements. Two classical …
predicting many properties of a quantum state with few measurements. Two classical …
Classical shadows for quantum process tomography on near-term quantum computers
Quantum process tomography is a powerful tool for understanding quantum channels and
characterizing the properties of quantum devices. Inspired by recent advances using …
characterizing the properties of quantum devices. Inspired by recent advances using …