Collective Bootstrap for Matrix Quantum Mechanics

Abstract

We develop a collective bootstrap framework for large N matrix quantum mechanics formulated directly in the loop space of single trace coordinate moments. Loop joining and splitting operations organize the kinetic constraints systematically and avoid treating momentum containing moments as independent variables. Employing the virial theorem, a Schur complement, and a relaxation of quadratic products of loops, we recast the nonlinear constrained optimization of the collective energy into a semidefinite program, which yields a lower bound on the planar ground state energy at every truncation. A sequential semidefinite optimization heuristic then searches for configurations satisfying planar factorization and estimates the ground state energy and loop expectation values. Applications to one-, two-, and three-matrix models exhibit close agreement with analytic solutions and master field optimization. By working exclusively with coordinate moments, the framework permits truncations at higher word length and offers a promising approach to models with more matrices, including the bosonic sectors of the BFSS and BMN models.

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BibTeX RIS

BibTeX

@misc{liu2026collective,
  title = {{Collective Bootstrap for Matrix Quantum Mechanics}},
  author = {Xianlong Liu},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.38716},
  eprint = {2610.38716},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.38716},
}

RIS

TY  - UNPB
TI  - Collective Bootstrap for Matrix Quantum Mechanics
AU  - Xianlong Liu
PY  - 2026
DA  - 2026/10/28
PB  - arXiv
DO  - 10.48550/arxiv.2610.38716
UR  - https://arxiv.org/abs/2610.38716
AB  - We develop a collective bootstrap framework for large N matrix quantum mechanics formulated directly in the loop space of single trace coordinate moments. Loop joining and splitting operations organize the kinetic constraints systematically and avoid treating momentum containing moments as independent variables. Employing the virial theorem, a Schur complement, and a relaxation of quadratic products of loops, we recast the nonlinear constrained optimization of the collective energy into a semidefinite program, which yields a lower bound on the planar ground state energy at every truncation. A sequential semidefinite optimization heuristic then searches for configurations satisfying planar factorization and estimates the ground state energy and loop expectation values. Applications to one-, two-, and three-matrix models exhibit close agreement with analytic solutions and master field optimization. By working exclusively with coordinate moments, the framework permits truncations at higher word length and offers a promising approach to models with more matrices, including the bosonic sectors of the BFSS and BMN models.
ER  -

Abstract

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