Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Three-body renormalization group limit cycles based on unsupervised
  feature learning   Both the three-body system and the inverse square potential carry a special
significance in the study of renormalization group limit cycles. In this work,
we pursue an exploratory approach and address the question which two-body
interactions lead to limit cycles in the three-body system at low energies,
without imposing any restrictions upon the scattering length. For this, we
train a boosted ensemble of variational autoencoders, that not only provide a
severe dimensionality reduction, but also allow to generate further synthetic
potentials, which is an important prerequisite in order to efficiently search
for limit cycles in low-dimensional latent space. We do so by applying an
elitist genetic algorithm to a population of synthetic potentials that
minimizes a specially defined limit-cycle-loss. The resulting fittest
individuals suggest that the inverse square potential is the only two-body
potential that minimizes this limit cycle loss independent of the hyperangle.

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The categories of this paper are: chem-ph
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The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
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The categories of this paper are: q-fin
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The categories of this paper are: nucl-ex
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The categories of this paper are: eess
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The categories of this paper are: q-alg
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The categories of this paper are: patt-sol
2
The categories of this paper are: math
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The categories of this paper are: atom-ph
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The categories of this paper are: funct-an
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The categories of this paper are: acc-phys
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The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
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The categories of this paper are: alg-geom
14
The categories of this paper are: math-ph