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December 10, 2025SciPost Physics3 citationsOpen Access

Sparsity in the numerical six-point bootstrap

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SHSebastian Harris

Key Points

  • This approach allows for more efficient computations of six-point bootstrap problems, enhancing scalability.
  • Key findings indicate the application of semidefinite programming results in novel bounds on critical CFT data.
  • Analysis utilizes techniques to transform problems into two-dimensional formats, improving computational feasibility.
  • These insights potentially open up new avenues for research in conformal field theory and related areas.

Abstract

The paper contributes to an ongoing effort to extend the conformal bootstrap beyond its traditional focus on systems of four-point correlation functions. Recently, it was demonstrated that semidefinite programming can be used to formulate a six-point generalisation of the numerical bootstrap, yielding qualitatively new, rigorous bounds on CFT data. However, the numerical six-point bootstrap requires solving SDPs involving infinite-dimensional matrices, which has so far limited its applicability and hindered scalability in early implementations. This work overcomes the challenges by using sparse matrix decompositions to exploit the banded structure of the underlying SDP. The result is a rewriting of one-dimensional six-point bootstrap problems as effectively two-dimensional standard mixed correlator four-point bootstrap computations. As application, novel bounds whose extremal correlators interpolate between the six-point functions of the generalised free fermion and boson are derived. The extremal interpolations are matched with perturbative deformations of the massive free boson in AdS ₂ 2.

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Cite This Study

Sebastian Harris (2025) studied this question.

synapsesocial.com/papers/69401b372d562116f28f7fe4https://doi.org/10.21468/scipostphys.19.6.151
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