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Scalably learning quantum many-body Hamiltonians from dynamical data

The dataset used in the paper is a collection of measurement outcomes from dynamical data, used to learn families of interacting many-body Hamiltonians.

Data and Resources

Cite this as

F. Wilde, A. Kshetrimayum, I. Roth, D. Hangleiter, R. Sweke, J. Eisert (2024). Dataset: Scalably learning quantum many-body Hamiltonians from dynamical data. https://doi.org/10.57702/sdrnzbip

DOI retrieved: December 16, 2024

Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2209.14328
Author F. Wilde
More Authors
A. Kshetrimayum
I. Roth
D. Hangleiter
R. Sweke
J. Eisert
Homepage https://arxiv.org/abs/2208.04842