4 code implementations • 5 Nov 2020 • Jakob S. Kottmann, Sumner Alperin-Lea, Teresa Tamayo-Mendoza, Alba Cervera-Lierta, Cyrille Lavigne, Tzu-Ching Yen, Vladyslav Verteletskyi, Philipp Schleich, Abhinav Anand, Matthias Degroote, Skylar Chaney, Maha Kesibi, Artur F. Izmaylov, Alán Aspuru-Guzik
As in classical computing, heuristics play a crucial role in the development of new quantum algorithms, resulting in high demand for flexible and reliable ways to implement, test, and share new ideas.
Quantum Physics Chemical Physics Computational Physics
1 code implementation • 6 Aug 2020 • Jakob S. Kottmann, Philipp Schleich, Teresa Tamayo-Mendoza, Alán Aspuru-Guzik
We present a basis-set-free approach to the variational quantum eigensolver using an adaptive representation of the spatial part of molecular wavefunctions.
Quantum Physics Chemical Physics Computational Physics
1 code implementation • 22 Nov 2017 • Teresa Tamayo-Mendoza, Christoph Kreisbeck, Roland Lindh, Alán Aspuru-Guzik
Automatic Differentiation (AD) is a powerful tool that allows calculating derivatives of implemented algorithms with respect to all of their parameters up to machine precision, without the need to explicitly add any additional functions.
Chemical Physics
