This paper is devoted to the derivation of a digital quantum algorithm for the Cauchy problem for symmetric first order linear hyperbolic systems, thanks to the reservoir technique. The reservoir technique is a method designed to avoid artificial diffusion generated by first order finite volume methods approximating hyperbolic systems of conservation laws. For some class of hyperbolic systems, namely those with constant matrices in several dimensions, we show that the combination of i) the reservoir method and ii) the alternate direction iteration operator splitting approximation, allows for the derivation of algorithms only based on simple unitary transformations, thus perfectly suitable for an implementation on a quantum computer. The same approach can also be adapted to scalar one-dimensional systems with non-constant velocity by combining with a non-uniform mesh. The asymptotic computational complexity for the time evolution is determined and it is demonstrated that the quantum algorithm is more efficient than the classical version. However, in the quantum case, the solution is encoded in probability amplitudes of the quantum register. As a consequence, as with other similar quantum algorithms, a post-processing mechanism has to be used to obtain general properties of the solution because a direct reading cannot be performed as efficiently as the time evolution.Keywords First order hyperbolic systems, quantum algorithms, quantum information theory, reservoir method.
IntroductionQuantum computing is a new paradigm in information science which benefits from quantum mechanics to perform some computational tasks. In the last few decades, it has attracted a lot of attention because it promises efficient solutions to a large class of problems deemed unsolvable on classical computers. Shor's algorithm, for the prime number factorization of integers, is the foremost example of the strength of quantum computing [52]. This algorithm runs in polynomial time, i.e. the computation time scales like a polynomial function of the input size, while the same task runs in (sub-)exponential time on a classical computer. This quantum speedup has motivated the development of many other algorithms for the solution of problems in the BQP complexity class but outside the P class, i.e. problems with bounded error for which the amount of quantum resources is a polynomial function and having an exponential speedup over classical computations [47,56].One of the promising applications of quantum computing is the simulation of quantum systems. Inspired from Feynman's quantum simulator [24], it has been demonstrated that universal quantum F. Fillion-Gourdeau