日時
2020年12月16日13:00 - 14:30 (JST)
講演者
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 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) Edit
会場
via Zoom
言語
英語

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).

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