Pith. sign in

REVIEW 2 cited by

A Comprehensive Survey of Brane Tilings

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1702.03958 v1 pith:TWAFJ2PX submitted 2017-02-13 hep-th math-phmath.AGmath.COmath.MP

A Comprehensive Survey of Brane Tilings

classification hep-th math-phmath.AGmath.COmath.MP
keywords branetilingsgaugetoriccalabi-yauclassificationcomprehensived3-branes
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

An infinite class of $4d$ $\mathcal{N}=1$ gauge theories can be engineered on the worldvolume of D3-branes probing toric Calabi-Yau 3-folds. This kind of setup has multiple applications, ranging from the gauge/gravity correspondence to local model building in string phenomenology. Brane tilings fully encode the gauge theories on the D3-branes and have substantially simplified their connection to the probed geometries. The purpose of this paper is to push the boundaries of computation and to produce as comprehensive a database of brane tilings as possible. We develop efficient implementations of brane tiling tools particularly suited for this search. We present the first complete classification of toric Calabi-Yau 3-folds with toric diagrams up to area 8 and the corresponding brane tilings. This classification is of interest to both physicists and mathematicians alike.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 2 Pith papers

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

  1. Learning to Trace Seiberg Dualities

    hep-th 2026-07 accept novelty 6.0

    Hybrid graph-transformer networks guiding A* and beam search find Seiberg-duality paths between ~10-node quivers more efficiently than BFS or pure physics heuristics, with a measured complexity breaking point.

  2. Machine Learning Toric Duality in Brane Tilings

    hep-th 2024-09 unverdicted novelty 5.0

    Neural networks classify Seiberg dual classes on Z_m x Z_n orbifolds with R^2=0.988 and predict toric multiplicities for Y^{6,0} with mean absolute error 0.021 under fixed Kasteleyn representative.