14 papers
A fidelity metric for quantum annealing benchmarked by extreme scaling quantum Monte-Carlo simulations
Gabriel Gouraud, Miha Srdinsek, Xavier Waintal
Quantum annealers are supposed to follow adiabatically the ground state of a system as its Hamiltonian slowly interpolates between a trivial phase and a non-trivial one; the non-tr…
Who can compete with quantum computers? Lecture notes on quantum inspired tensor networks computational techniques
Xavier Waintal, Chen-How Huang, Christoph W. Groth
This is a set of lectures on tensor networks with a strong emphasis on the core algorithms involving Matrix Product States (MPS) and Matrix Product Operators (MPO). Compared to oth…
A multilevel tensor network compression technique for simulating Lindblad dynamics in superconducting circuits
Adrien Moulinas, Xavier Waintal
Designing superconducting quantum hardware requires simulation tools that can account for various deviations from ideal scenarios. This, in turn, requires approaches that automatic…
Electrostatics in semiconducting devices II: Solving the Helmholtz equation
Antonio Lacerda-Santos, Xavier Waintal
The convergence of iterative schemes to achieve self-consistency in mean field problems such as the Schrödinger-Poisson equation is notoriously capricious. It is particularly diff…
Replica Tensor Train
Miha Srdinsek, Gabriel Gouraud, Xavier Waintal
We describe a numerical many-body technique that is based on both tensor networks and quantum Monte Carlo. The variational ansatz is a tensor network that can harvest volume-law en…
Hybrid between biologically and quantum-inspired many-body states
Miha Srdinšek, Xavier Waintal
Deep neural networks can represent very different sorts of functions, including complex quantum many-body states. Tensor networks can also represent these states, have more structu…