A note on improved stochastic trace estimation for fermionic string fluctuations
Valentina Forini, Bjoern Leder, Nils Wauschkuhn

TL;DR
This paper introduces an improved stochastic trace estimation method using mutually unbiased bases for lattice superstring simulations, demonstrating reduced variance compared to traditional Gaussian estimators.
Contribution
The paper presents a novel stochastic trace estimator based on mutually unbiased bases, enhancing accuracy in lattice superstring computations.
Findings
Reduced variance in trace estimates compared to Gaussian methods
Effective for discretized superstring worldsheet operators
Potentially applicable to other lattice simulation contexts
Abstract
We report on the use of a stochastic trace estimator algorithm, based on mutually unbiased bases, for evaluating the trace of a matrix differential operator appearing in the context of lattice simulations for the discretized superstring worldsheet. A study of the variance, in a setup which is slightly modified with respect to the original one, confirms advantages with respect to more traditional methods like the Gaussian estimator.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsPhysics of Superconductivity and Magnetism · Theoretical and Computational Physics · Opinion Dynamics and Social Influence
