Hong Ou Mandel experiment in graphene
|Contact: ROULLEAU Preden, , email@example.com, +33 1 69 08 73 11|
In this internship, we propose to realize the first two-electron interfetometer in graphene: the Hong Ou Mandel experiment.
|Possibility of continuation in PhD: Oui|
|Deadline for application:10/04/2021 |
|Full description: |
This internship addresses a central topic at the cross between quantum information, quantum transport, and 2D materials: the physics of valleytronics. In addition to the fundamental electronic charge, electron carries spin. The development of spin control has opened and extended a large field, spintronics, which exploits spin to encode information for some applications in data transfer and storage. In graphene, because of the two sublattices, a new internal degree of freedom pops up: the valley isospin. Robustness of the valley isospin against electrostatic noise suggests that valleytronics, which encodes information in the valley isospin, has great potential for tremendous applications in fundamental physics but also high-tech industry. The Graphene Technology and Innovation Roadmap (Graphene Flaqship) describes graphene as a potential platform for valleytronics.
Recently, we succeeded in controlling the degree of the valley scattering at a small side gate on a graphene edge. Using two side gates as a pair of valley beam splitters, we have realized an electronic Mach Zehnder interferometer and demonstrated basic quantum operations of a flying valley qubit, that is, quantum control of the superposition of spatially co-propagating but opposite-valley-isospin channels along a graphene PN junction. We moreover show that the coherence of the flying valley qubit largely surpasses state of the art values of charge qubit in high-mobility 2D semiconductors.
In this internship, we propose to go one step further and to realize the first two-electron interfetometer in graphene: the Hong Ou Mandel experiment.
|Technics/methods used during the internship: |
It is a running experiment The student will analyse and treat the data with Python Discussion about the data treatment with the team
|Tutor of the internship |