Quantum Algorithms for Simulating Realistic Classical Mechanical Systems and Solving Optimal Control Problems
Quantum algorithms are developed to efficiently estimate quantities of interest such as kinetic energy in realistic classical mechanical systems with dissipation and forcing, as well as to solve the Riccati equation and the linear quadratic regulator problem in optimal control.
Quantum Algorithm for Estimating Rényi Entropy of Discrete Probability Distributions
This paper proposes a unified quantum algorithm framework for estimating properties of discrete probability distributions, with a focus on estimating Rényi entropies. The algorithms achieve improved dependence on the distribution size n and the desired precision ϵ compared to prior work.
Quantum Algorithms with Improved Average Query Complexity on Easier Inputs
Quantum algorithms can achieve improved average query complexity on inputs with certain structural properties, even without knowing those properties ahead of time.
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