Quantum computing and its applications in chemistry and physics
- Datum: 10.11.2020
- Uhrzeit: 14:30 - 14:30
- Vortragende(r): Dr. Ivano Tavernelli
- IBM Quantum, IBM Research - Zurich
- Gastgeber: Omar Valsson
- Kontakt: valsson@mpip-mainz.mpg.de
Quantum computing is emerging as a new paradigm for the solution of a
wide class of problems that are not accessible by conventional high
performance classical computers. Quantum computers can in principle
efficiently solve problems that require exponential resources on
classical hardware, even when using the best known classical algorithms.
In the last few years, several interesting solutions with potential
quantum speedup have been brought forward in the domain of quantum
physics, like the quantum phase estimation and the hybrid variational
quantum eigensolver [1] for the solution of optimization problems. The
original idea that a quantum computer can potentially solve many-body
quantum mechanical problems more efficiently than classical computers
is due to
R. Feynman who proposed the use of quantum algorithms to
investigate the fundamental properties of nature at the quantum scale.
In particular, the solution of the electronic structure and statistical
mechanics problems is a challenging computational task as the number of
resources increases exponentially with the number of degrees of freedom.
Thanks to the development of new quantum technologies witnessed over
the last decades, we have now the possibility to address this class of
problems with the help quantum computers. To achieve this goal, new
quantum algorithms able to best exploit the potential quantum speedup of
state-of-the-art noisy quantum hardware have also been developed [2,3].
In this talk, I will first introduce the basics of quantum computing
using superconducting qubits, focusing on those aspects that are crucial
for the implementation of quantum chemistry and physics algorithms. In
the second part, I will highlight the potential advantages of the new
generation of quantum algorithms for applications in electronic
structure calculations for ground [4] and excited states [5], molecular
dynamics [6], and statistical physics [7].
[1] A. Peruzzo et al., Nature Communications 5, 4213 (2014).
[2] N. Moll, et al., Quantum Sci. Technol. 3, 030503 (2018).
[3] A. Kandala et al., Nature, 549, 242 (2017).
[4] P. Baroutsos, et al., Phys. Rev. A, 98 022322 (2018).
[5] M. Ganzhorn,, et al., Phys. Rev. Appl., 11 044092 (2019); P. Ollitrault et al.
arXiv:1910.12890 (2019).
[6] I. O. Sokolov, P. Kl Barkoutsos, L. Moeller, et al., arXiv:2008.08144 (2020).
[7] A. Robert et al., arXiv:1908.02163 (2019).