Quantum Wasserstein distance of order 1
- 2020年12月16日13:00 - 14:30 (JST)
- via Zoom
The Wasserstein distance is an indicator for the closeness of two probability distributions and is applied to various fields ranging from information theory to neural networks . It is particularly useful to treat the geometry of the underlying space, such as tensor-product structures. In this journal club, I talk about one of the recent proposals on quantum extension of the Wasserstein distance . After reviewing basic properties of classical Wasserstein distance, e.g., its relation to concentration phenomena, I discuss how they might be generalized to quantum realm.
*Detailed information about the seminar refer to the email.
- Boucheron, Stéphane, Gábor Lugosi, and Pascal Massart. "Concentration inequalities: A nonasymptotic theory of independence." Oxford university press, 2013.
- De Palma, Giacomo, et al. "The quantum Wasserstein distance of order 1." arXiv preprint arXiv:2009.04469 (2020).