Publications (12)
Polynomial-reproducing spline spaces from fine zonotopal tilings
Hélène Barucq, Henri Calandra, Julien Diaz +1
Given a point configuration A, we uncover a connection between polynomial-reproducing spline spaces over subsets of conv(A) and fine zonotopal tilings of the zonotope Z(V) associat…
Velocity estimation via registration-guided least-squares inversion
Hyoungsu Baek, Henri Calandra, Laurent Demanet
This paper introduces an iterative scheme for acoustic model inversion where the notion of proximity of two traces is not the usual least-squares distance, but instead involves reg…
On high-order multilevel optimization strategies
Henri Calandra, Serge Gratton, Elisa Riccietti +1
We propose a new family of multilevel methods for unconstrained minimization. The resulting strategies are multilevel extensions of high-order optimization methods based on q-order…
Practical Quantum Computing: solving the wave equation using a quantum approach
Adrien Suau, Gabriel Staffelbach, Henri Calandra
In the last years, several quantum algorithms that try to address the problem of partial differential equation solving have been devised. On one side, "direct" quantum algorithms t…
Minimod: A Finite Difference solver for Seismic Modeling
Jie Meng, Andreas Atle, Henri Calandra +1
This article introduces a benchmark application for seismic modeling using finite difference method, which is namedMiniMod, a mini application for seismic modeling. The purpose is…
Simulations of intermittent two-phase flows in pipes using smoothed particle hydrodynamics
Thomas Douillet-Grellier, Florian De Vuyst, Henri Calandra +1
Slug flows are a typical intermittent two-phase flow pattern that can occur in submarine pipelines connecting the wells to the production facility and that is known to cause undesi…
On the approximation of the solution of partial differential equations by artificial neural networks trained by a multilevel Levenberg-Marquardt method
Henri Calandra, Serge Gratton, Elisa Riccietti +1
This paper is concerned with the approximation of the solution of partial differential equations by means of artificial neural networks. Here a feedforward neural network is used t…
To quantum or not to quantum: towards algorithm selection in near-term quantum optimization
Charles Moussa, Henri Calandra, Vedran Dunjko
The Quantum Approximate Optimization Algorithm (QAOA) constitutes one of the often mentioned candidates expected to yield a quantum boost in the era of near-term quantum computing.…
Matrix probing: a randomized preconditioner for the wave-equation Hessian
Laurent Demanet, Pierre-David Létourneau, Nicolas Boumal +3
This paper considers the problem of approximating the inverse of the wave-equation Hessian, also called normal operator, in seismology and other types of wave-based imaging. An exp…
Function Maximization with Dynamic Quantum Search
Charles Moussa, Henri Calandra, Travis S. Humble
Finding the maximum value of a function in a dynamic model plays an important role in many application settings, including discrete optimization in the presence of hard constraints…
On the iterative solution of systems of the form
Henri Calandra, Serge Gratton, Elisa Riccietti +1
Given a full column rank matrix (), we consider a special class of linear systems of the form with $x, c \in \mathbb{…
Tabu-driven Quantum Neighborhood Samplers
Charles Moussa, Hao Wang, Henri Calandra +2
Combinatorial optimization is an important application targeted by quantum computing. However, near-term hardware constraints make quantum algorithms unlikely to be competitive whe…