Abstract :
We study the approximation of functions from anisotropic and generalized Sobolev classes under Lq([0, 1]d) norm in the quantum model of computation. Based on the quantum algorithm for approximation of finite imbedding from LN P to LiN Q, we develop a quantum algorithm for approximating the imbedding from anisotropic Sobolev classes B(Wp r(|0, 1|d)) to Lq(|0, 1|d) space for all 1 les q,p les infin and prove their optimality. Our results show that for p < q the quantum model of computation can bring a speedup of roughly squaring the rate of classical deterministic and randomized settings.
Keywords :
approximation theory; quantum computing; anisotropic Sobolev classes; quantum algorithm; quantum approximation error; Anisotropic magnetoresistance; Approximation algorithms; Approximation error; Computational modeling; Mathematical model; Neodymium; Probability distribution; Quantum computing; Random variables;