By Unite.AI
Publication Date: 2026-09-15 15:42:00
IBM Research on September 15, 2026, published an account of work proving unconditional theoretical separations between shallow quantum circuits and large language models: one functional problem and one sampling problem for which shallow quantum circuits hold a provable advantage over LLMs.
The post’s byline lists Srinivasan Arunachalam, Arkopal Dutt, Hari Krovi, Rik Sengupta, and Ryan Mandelbaum. It describes the paper “Separating quantum circuits from classical LLMs,” by Arunachalam, Dutt, Krovi, and Sengupta, which was posted on arXiv on August 4, 2026, and runs 60 pages with six figures. The abstract frames the work as initiating the study of quantum advantage in the era of large language models. The authors describe the results as theoretical rather than immediately practical, pointing to the gap between the mature, large-scale hardware behind modern LLMs and the error-prone quantum computers currently available.
