- Open Access
Eigenvalue distribution from bootstrap estimates
Phys. Rev. D 112, 126021 – Published 23 December, 2025
DOI: https://doi.org/10.1103/m812-s3hr
Abstract
The bootstrap method has proven useful for a wide range of matrix models. Here, we show that the computed moments can be used to reconstruct the underlying eigenvalue probability distribution, which, in turn, allows us to compute the free energy of the model—a necessary quantity for identifying the thermodynamically preferred solution. We verify the method on the well-studied quartic potential model and then apply it to a recently analyzed asymmetric multitrace model. We consider an extended class of possible solutions and demonstrate that free-energy analysis reliably selects the correct one, making it an essential tool for studying models with a complex solution structure.
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References (36)
- B. Eynard, T. Kimura, and S. Ribault, Random matrices, arXiv:1510.04430.
- R. G. Jha, Introduction to monte carlo for matrix models, SciPost Phys. Lect. Notes 46, 1 (2022).
- X. Han, S. A. Hartnoll, and J. Kruthoff, Bootstrapping matrix quantum mechanics, Phys. Rev. Lett. 125, 041601 (2020).
- P. D. Anderson and M. Kruczenski, Loop equations and bootstrap methods in the lattice, Nucl. Phys. B921, 702 (2017).
- H. W. Lin, Bootstraps to strings: Solving random matrix models with positivity, J. High Energy Phys. 06 (2020) 090.
- M. Khalkhali, N. Pagliaroli, A. Parfeni, and B. Smith, Bootstrapping the critical behavior of multi-matrix models, J. High Energy Phys. 25 (2020) 158.
- S. Tchoumakov and S. Florens, Bootstrapping Bloch bands, J. Phys. A 55, 015203 (2022).
- H. Hessam, M. Khalkhali, and N. Pagliaroli, Bootstrapping Dirac ensembles, J. Phys. A 55, 335204 (2022).
- V. Kazakov and Z. Zheng, Analytic and numerical bootstrap for one-matrix model and unsolvable two-matrix model, J. High Energy Phys. 06 (2022) 030.
- Y. Aikawa, T. Morita, and K. Yoshimura, Bootstrap method in harmonic oscillator, Phys. Lett. B 833, 137305 (2022).
- D. Berenstein and G. Hulsey, Bootstrapping more QM systems, J. Phys. A 55, 275304 (2022).
- J. Bhattacharya, D. Das, S. K. Das, A. K. Jha, and M. Kundu, Numerical bootstrap in quantum mechanics, Phys. Lett. B 823, 136785 (2021).
- M. J. Blacker, A. Bhattacharyya, and A. Banerjee, Bootstrapping the Kronig-Penney model, Phys. Rev. D 106, 116008 (2022).
- D. Berenstein and G. Hulsey, Bootstrapping simple QM systems, arXiv:2108.08757.
- D. Berenstein and G. Hulsey, Anomalous bootstrap on the half-line, Phys. Rev. D 106, 045029 (2022).
- S. Khan, Y. Agarwal, D. Tripathy, and S. Jain, Bootstrapping PT symmetric quantum mechanics, Phys. Lett. B 834, 137445 (2022).
- Y. Nakayama, Bootstrapping microcanonical ensemble in classical system, Mod. Phys. Lett. A 37, 2250054 (2022).
- Z. Zheng, Bootstrap method in theoretical physics, Ph.D. thesis, Ecole Normale Supérieure, Paris, 2023, arXiv:2401.00350.
- M. Khalkhali and N. Pagliaroli, Coloured combinatorial maps and quartic bi-tracial 2-matrix ensembles from noncommutative geometry, J. High Energy Phys. 05 (2024) 186.
- V. Kazakov and Z. Zheng, Bootstrap for finite N lattice Yang-Mills theory, J. High Energy Phys. 03 (2025) 099.
- S. Lawrence, B. McPeak, and D. Neill, Bootstrapping time-evolution in quantum mechanics, arXiv:2412.08721.
- Z. Huang and W. Li, Bootstrapping periodic quantum systems, arXiv:2507.02386.
- C. W. J. Beenakker, Random-matrix theory of quantum transport, Rev. Mod. Phys. 69, 731 (1997).
- R. J. Szabo, Quantum field theory on noncommutative spaces, Phys. Rep. 378, 207 (2003).
- D. Karabali and V. P. Nair, Quantum Hall effect in higher dimensions, matrix models and fuzzy geometry, J. Phys. A 39, 12735 (2006).
- A. P. Balachandran, S. Kurkcuoglu, and S. Vaidya, Lectures on fuzzy and fuzzy SUSY physics, arXiv:hep-th/0511114.
- B. Ydri, Lectures on Matrix Field Theory (Springer, New York, 2017), Vol. 929.
- J. Tekel, Phase strucutre of fuzzy field theories and multitrace matrix models, Acta Phys. Slovaca 65, 369 (2015), http://www.physics.sk/aps/pub.php?y=2015&pub=aps-15-05.
- M. Šubjaková and J. Tekel, Fuzzy field theories and related matrix models, Proc. Sci., CORFU2019 (2020) 189 [arXiv:2006.12605].
- J. Tekel and L. Cohen, Constructing and estimating probability distributions from moments, in Automatic Target Recognition XXII (SPIE, Bellingham, WA, 2012), Vol. 8391, pp. 114–123.
- K. Ramda, On random multitraces matrix models, Int. J. Theor. Phys. 61, 160 (2022).
- B. Bukor and J. Tekel, Cubic asymmetric multitrace matrix model, J. Phys. A 58, 255203 (2025).
- G. Livan, M. Novaes, and P. Vivo, Introduction to Random Matrices (Springer International Publishing, Berlin, 2018).
- G. Szegö, Orthogonal Polynomials (American Mathematical Society, Providence, RI, 1975).
- B. Simon, The classical moment problem as a self-adjoint finite difference operator, Adv. Math. 137, 82 (1998).
- https://github.com/KatkaMagdolenova/Eigenvalue_distribution_from_bootstrap_estimates.