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Trapped Ion Quantum Computing
Quantum Machine Learning
Classification of dynamical Lie algebras for translation-invariant 2-local spin systems in one dimension
arXiv
Authors: Roeland Wiersema, Efekan Kökcü, Alexander F. Kemper, Bojko N. Bakalov
Year
2023
Paper ID
54967
Status
Preprint
Abstract Read
~2 min
Abstract Words
146
Citations
N/A
Abstract
Much is understood about 1-dimensional spin chains in terms of entanglement properties, physical phases, and integrability. However, the Lie algebraic properties of the Hamiltonians describing these systems remain largely unexplored. In this work, we provide a classification of all Lie algebras generated by translation-invariant 2-local spin chain Hamiltonians, or so-called dynamical Lie algebras. We consider chains with open and periodic boundary conditions and find 17 unique dynamical Lie algebras. Our classification covers some well-known models such as the transverse-field Ising model and the Heisenberg chain, and we also find more exotic classes of Hamiltonians that cannot be identified easily. In addition to the closed and open spin chains, we consider systems with a fully connected topology, which may be relevant for quantum machine learning approaches. We discuss the practical implications of our work in the context of quantum control, variational quantum computing, and the spin chain literature.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2023 reference point for readers tracking recent quantum research.
- Much is understood about 1-dimensional spin chains in terms of entanglement properties, physical phases, and integrability.
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