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arXiv · 2605.25647

Endpoint formulation and Molien--Weyl structure for the \(N=2\), large--\(d\) BFSS/BMN models

Abstract

We study the \(N=2\), large--\(d\) sector of BFSS/BMN-type matrix quantum mechanics on the lattice in the Gaussian regime. We develop a radial endpoint formulation in which the bulk, gauge, and longitudinal degrees of freedom are integrated out, leaving transverse endpoint variables governed by an effective holonomy potential. We show that this planar endpoint formulation is equivalent to the angular Molien--Weyl description of the gauge-projected partition function, up to a universal spectator factor. This relation allows the low-temperature expansion of the endpoint partition function to be obtained from the Molien--Weyl result, whose quadratic coefficient \(d(d+1)/2\) counts Gaussian singlet states above the vacuum. We then analyze the continuum limit of the quadratic coefficient and show that it separates into a Gaussian contribution, a \(D\)-channel, and a \(β\)-channel. The naive Gaussian term becomes trivial, while the exact holonomy kernel generates finite continuum contributions through singular dependence on the endpoint Gaussian width and anisotropic coupling. We then study the geometry of the holonomy potential and show that its relevant saddle is a constrained boundary saddle on the aligned branch, rather than an unconstrained critical point. The associated transverse expansion captures the local saddle geometry, but any finite polynomial truncation has a trivial continuum limit. Finally, we introduce a non-polynomial toy model based on \(V_{\rm toy}(B)=-\log\cosh B\), which provides a completion of the transverse expansion and reproduces exactly the continuum \(D\)-channel contribution \(-2d\). This prepares the geometric interpretation of the \(D\)-channel as a Wishart--Stiefel entropy associated with an emergent four-dimensional geometry embedded \(\mathbb R^d\) in the endpoint formulation.

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BibTeXRIS

Badis Ydri. 2026-05-25. Endpoint formulation and Molien--Weyl structure for the \(N=2\), large--\(d\) BFSS/BMN models. https://arxiv.org/abs/2605.25647

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