Molecular Hamiltonian Learning Extracts Parameters From Stm-Iets Data For Single Molecules

TL;DR


Summary:
- This article discusses a new technique that can extract the Hamiltonian, a mathematical model that describes the energy of a quantum system, from scanning tunneling microscopy (STM) data.
- The method allows researchers to obtain the electronic structure of materials at the atomic scale, which is crucial for understanding and designing new quantum materials.
- By using this approach, scientists can gain valuable insights into the fundamental properties of materials without the need for complex theoretical calculations, paving the way for advancements in quantum technology.

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