Quantum annealing (QA) is a heuristic quantum optimization algorithm that can be used to
solve combinatorial optimization problems. In recent years, advances in quantum …

Abstract The Quantum Approximate Optimization Algorithm (QAOA) is a highly promising
variational quantum algorithm that aims to solve combinatorial optimization problems that …

Quantum annealing is a computing paradigm that has the ambitious goal of efficiently
solving large-scale combinatorial optimization problems of practical importance. However …

This tutorial aims at giving an introductory treatment of the circuit analysis of
superconducting qubits, ie, two-level systems in superconducting circuits. It also touches …

Quantum advantage in solving physical problems is still hard to assess due to hardware
limitations. However, algorithms designed for quantum computers may engender …

Quantum annealing aims at solving combinatorial optimization problems mapped to Ising
interactions between quantum spins. Here, with the objective of developing a noise-resilient …

Quantum computers with Kerr-nonlinear parametric oscillators (KPOs) have recently been
proposed by the author and others. Quantum computation using KPOs is based on quantum …

Fast, high-fidelity, and quantum nondemolition (QND) qubit readout is an essential element
of quantum information processing. For superconducting qubits, state-of-the-art readout is …

Quantum phenomena have the potential to speed up the solution of hard optimization
problems. For example, quantum annealing, based on the quantum tunneling effect, has …

A key problem in financial mathematics is the forecasting of financial crashes: If we perturb
asset prices, will financial institutions fail on a massive scale? This was recently shown to be …