5 papers
Operator Learning for efficient Quantum Computation
Paul Over, Sergio Bengoechea, Leonardo Borello Busilacchi +3
An efficient implementation of quantum algorithms is often hindered by the lack of efficient primitives for operators and state preparation. This limits both the ability of near-te…
Quantum time-marching algorithms for solving linear transport problems including boundary conditions
Sergio Bengoechea, Paul Over, Thomas Rung
This article presents the first complete application of a quantum time-marching algorithm for simulating multidimensional linear transport phenomena with arbitrary boundaries, wher…
Towards Variational Quantum Algorithms for generalized linear and nonlinear transport phenomena
Sergio Bengoechea, Paul Over, Dieter Jaksch +1
This article proposes a Variational Quantum Algorithm to solve linear and nonlinear thermofluid dynamic transport equations. The hybrid classical-quantum framework is applied to pr…
Quantum-Inspired Tensor-Network Fractional-Step Method for Incompressible Flow in Curvilinear Coordinates
Nis-Luca van Hülst, Pia Siegl, Paul Over +5
We introduce an algorithmic framework based on tensor networks for computing fluid flows around immersed objects in curvilinear coordinates. We show that the tensor network simulat…
Quantum Algorithm for the Advection-Diffusion Equation by Direct Block Encoding of the Time-Marching Operator
Paul Over, Sergio Bengoechea, Peter Brearley +2
A quantum algorithm for simulating multidimensional scalar transport problems using a time-marching strategy is presented. A direct unitary block encoding of the explicit time-marc…