Error Mitigation-Aided Optimization of Parameterized Quantum Circuits: Convergence Analysis

Variational quantum algorithms (VQAs) offer the most promising path to
obtaining quantum advantages via noisy intermediate-scale quantum (NISQ)
processors. Such systems leverage classical optimization ...

Bayesian Optimization for QAOA

The Quantum Approximate Optimization Algorithm (QAOA) adopts a hybrid
quantum-classical approach to find approximate solutions to variational
optimization problems. Infact, it relies on a classical su ...

Continuous-variable quantum approximate optimization on a programmable photonic quantum processor

Variational quantum algorithms (VQAs) provide a promising approach to
achieving quantum advantage for practical problems on near-term noisy
intermediate-scale quantum (NISQ) devices. Thus far, intensi ...

An Empirical Review of Optimization Techniques for Quantum Variational Circuits

Quantum Variational Circuits (QVCs) are often claimed as one of the most
potent uses of both near term and long term quantum hardware. The standard
approaches to optimizing these circuits rely on a cl ...

Error propagation in NISQ devices for solving classical optimization problems

We propose a random circuit model to analyze the impact of noise on the
performance of variational quantum circuits for classical optimization
problems. Our model accounts for the propagation of arbit ...

Normalized Gradient Descent for Variational Quantum Algorithms

Variational quantum algorithms (VQAs) are promising methods that leverage
noisy quantum computers and classical computing techniques for practical
applications. In VQAs, the classical optimizers such ...

A Comparison of Various Classical Optimizers for a Variational Quantum Linear Solver

Variational Hybrid Quantum Classical Algorithms (VHQCAs) are a class of
quantum algorithms intended to run on noisy intermediate-scale quantum (NISQ)
devices. These algorithms employ a parameterized q ...

Classical Optimizers for Noisy Intermediate-Scale Quantum Devices

We present a collection of optimizers tuned for usage on Noisy
Inter-mediate-Scale Quantum (NISQ) devices. Optimizers have a range of
applications in quantum computing, including the Variational Quant ...

Quantum circuit architecture search: error mitigation and trainability enhancement for variational quantum solvers

Quantum error mitigation techniques are at the heart of quantum computation.
Conventional quantum error correction codes are promising solutions, while they
become infeasible in the noisy intermediate ...

Using models to improve optimizers for variational quantum algorithms

Variational quantum algorithms are a leading candidate for early applications
on noisy intermediate-scale quantum computers. These algorithms depend on a
classical optimization outer-loop that minimiz ...