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Geometry of Complexity in Conformal Field Theory

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arxiv 2005.02415 v3 pith:4ETEYUOY submitted 2020-05-05 hep-th quant-ph

classification hep-thquant-ph
keywords complexitycircuitsconformalcasediscussequationsfieldgeometry
verification ladder T0 review T1 audit T2 compute T3 formal
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We initiate quantitative studies of complexity in (1+1)-dimensional conformal field theories with a view that they provide the simplest setting to find a gravity dual to complexity. Our work pursues a geometric understanding of complexity of conformal transformations and embeds Fubini-Study state complexity and direct counting of stress tensor insertion in the relevant circuits in a unified mathematical language. In the former case, we iteratively solve the emerging integro-differential equation for sample optimal circuits and discuss the sectional curvature of the underlying geometry. In the latter case, we recognize that optimal circuits are governed by Euler-Arnold type equations and discuss relevant results for three well-known equations of this type in the context of complexity.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. The Geometry of Quantum Complexity in Open Systems

    quant-ph 2026-07 conditional novelty 7.0 of 10

    Open-system quantum complexity is governed by a sub-Finslerian geometry whose curvature depends on the cost penalties for unitary and dissipative controls.

  2. CFT Complexity and Penalty Factors

    hep-th 2025-07 conditional novelty 6.0 of 10

    A submersion-based method turns weighted generator costs into state-complexity metrics for CFTs, giving analytic formulas in simple limits and constraints on which weight choices are viable.

  3. Probing the self-coherence of primordial quantum fluctuations with complexity

    hep-th 2025-02 conditional novelty 5.0 of 10

    Complexity of formation, unlike complexity of purification, shows distinct and timescale-matching signatures of both decoherence and recoherence in a Gaussian two-field de Sitter model.

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