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Variational Quantum Algorithms
An overview of the field of Variational Quantum Algorithms is presented and strategies to overcome their challenges as well as the exciting prospects for using them as a means to obtain quantum advantage are discussed. Expand
Unified approach to data-driven quantum error mitigation
A novel, scalable error mitigation method that conceptually unifies ZNE and CDR, called variable-noise Clifford data regression (vnCDR), significantly outperforms these individual methods in numerical benchmarks. Expand
Effect of barren plateaus on gradient-free optimization
It is shown that gradient-free optimizers do not solve the barren plateau problem, and the main result proves that cost function differences, which are the basis for making decisions in a gradient- free optimization, are exponentially suppressed in a barren plateau. Expand
An Adaptive Optimizer for Measurement-Frugal Variational Algorithms
A novel optimizer called individual Coupled Adaptive Number of Shots (iCANS) is introduced, which frugally selects the number of measurements both for a given iteration and for aGiven partial derivative in a stochastic gradient descent. Expand
Variational Quantum State Eigensolver
Extracting eigenvalues and eigenvectors of exponentially large matrices will be an important application of near-term quantum computers. The Variational Quantum Eigensolver (VQE) treats the case whenExpand
Error mitigation with Clifford quantum-circuit data
Achieving near-term quantum advantage will require accurate estimation of quantum observables despite significant hardware noise. For this purpose, we propose a novel, scalable error-mitigationExpand
Unifying and benchmarking state-of-the-art quantum error mitigation techniques
Daniel Bultrini,1, 2, ∗ Max Hunter Gordon,3, ∗ Piotr Czarnik,1 Andrew Arrasmith,1, 4 Patrick J. Coles,1, 4 and Lukasz Cincio1, 4 Theoretical Division, Los Alamos National Laboratory, Los Alamos, NMExpand
Qubit-efficient exponential suppression of errors
Achieving a practical advantage with near-term quantum computers hinges on having effective methods to suppress errors. Recent breakthroughs have introduced methods capable of exponentiallyExpand
Variational consistent histories as a hybrid algorithm for quantum foundations
A variational hybrid quantum-classical algorithm for finding consistent histories, which should revitalize interest in this formalism by allowing classically impossible calculations to be performed. Expand
Barren Plateaus Preclude Learning Scramblers.
A no-go theorem for learning an unknown scrambling process with QML is proved, showing that it is highly probable for any variational Ansatz to have a barren plateau landscape, i.e., cost gradients that vanish exponentially in the system size. Expand