2020年12月16日(水)13:00 - 14:30 (JST)

• 濱崎 立資 (数理創造プログラム 上級研究員 / 理化学研究所 開拓研究本部 (CPR) 濱崎非平衡量子統計力学理研白眉研究チーム 理研白眉研究チームリーダー)

• 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 [1]. 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 [2]. 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.

## References

1. Boucheron, Stéphane, Gábor Lugosi, and Pascal Massart. "Concentration inequalities: A nonasymptotic theory of independence." Oxford university press, 2013.
2. De Palma, Giacomo, et al. "The quantum Wasserstein distance of order 1." arXiv preprint arXiv:2009.04469 (2020).