Universal scaling framework for parameterized quantum evolutions at criticality
Abstract
Variational ans\"atze are a cornerstone of quantum many-body physics, providing compact approximations to complex ground states using finite resources. Recent quantum-technology advances have introduced a new class based on layered parameterized evolutions. Assessing whether they can represent critical ground states is challenging: correlations span all length scales, while finite circuit depth limits how far they extend. Building on finite-resource scaling from tensor networks, we assign each ansatz an emergent correlation length , the longest range over which it faithfully captures critical correlations. Its growth with refinement parameter , , defines an exponent measuring how efficiently an architecture converts resources into long-distance correlations. Applying this framework to the critical transverse-field Ising model, with the circuit depth of parameterized evolutions, we compare ans\"atze with nearest-neighbor and long-range generators, and layers where generators act separately or combined. All ans\"atze are compatible with algebraic growth, but fitted exponents range from to . Exponential interactions give the largest exponents, while power-law interactions stay close to nearest-neighbor behavior, showing long-range support alone gives no scaling advantage. Combined-generator layers generally outperform separable ones, so layer organization matters alongside interaction range. Finally, a quasiparticle analysis shows finite depth leaves an unresolved window of width around the low-energy modes responsible for long-distance correlations. The emergent correlation length thus acts as an infrared resolution scale, providing a benchmark for critical-state preparation and a guide for designing resource-efficient variational architectures.
Cite
@article{arxiv.2607.22863,
title = {Universal scaling framework for parameterized quantum evolutions at criticality},
author = {Jan T. Schneider and Cristian Tabares and Alejandro González-Tudela and Luca Tagliacozzo},
journal= {arXiv preprint arXiv:2607.22863},
year = {2026}
}
Comments
24 pages, 9 figures