Half-Wormholes and Ensemble Averages

TL;DR

This paper investigates half-wormhole saddle points in spectral correlators across various models, improving approximation methods, identifying new saddle contributions, and clarifying their roles in ensemble averages.

Contribution

It introduces a modified approximation scheme for half-wormholes applicable to non-Gaussian distributions and identifies new saddle points in generalized SYK models.

Findings

Improved accuracy of half-wormhole approximations for non-Gaussian distributions.

Discovery of new saddle points in generalized 0d SYK models.

Clarification that certain non-trivial saddles should be excluded after Lefschetz-thimble analysis.

Abstract

We study "half-wormhole-like" saddle point contributions to spectral correlators in a variety of ensemble average models, including various statistical models, generalized 0d SYK models, 1d Brownian SYK models and an extension of it. In statistical ensemble models, where more general distributions of the random variables could be studied in great details, we find the accuracy of the previously proposed approximation for the half-wormholes could be improved when the distribution of the random variables deviate significantly from Gaussian distributions. We propose a modified approximation scheme of the half-wormhole contributions that also work well in these more general theories. In various generalized 0d SYK models we identify new half-wormhole-like saddle point contributions. In the 0d SYK model and 1d Brownian SYK model, apart from the wormhole and half-wormhole saddles, we find new non-trivial saddles in the spectral correlators that would potentially give contributions of the same order as the trivial self-averaging saddles. However after a careful Lefschetz-thimble analysis we show that these non-trivial saddles should not be included. We also clarify the difference between "linked half-wormholes" and "unlinked half-wormholes" in some models.