Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Identifying Topological Phase Transitions in Experiments Using Manifold
  Learning   We demonstrate the identification and classification of topological phase
transitions from experimental data using Diffusion Maps: a nonlocal
unsupervised machine learning method. We analyze experimental data from an
optical system undergoing a topological phase transition and demonstrate the
ability of this approach to identify topological phase transitions even when
the data originates from a small part of the system, and does not even include
edge states.

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The categories of this paper are: patt-sol
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The categories of this paper are: hep-lat
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The categories of this paper are: hep-ph
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The categories of this paper are: atom-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: solv-int
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The categories of this paper are: chem-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: math-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: hep-th
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The categories of this paper are: q-fin
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The categories of this paper are: econ
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The categories of this paper are: adap-org
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The categories of this paper are: eess