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Gauge-invariant theory of truncated quantum light-matter interactions in arbitrary media

Published 24 Aug 2022 in quant-ph | (2208.11796v2)

Abstract: The loss of gauge invariance in models of light-matter interaction which arises from material and photonic space truncation can pose significant challenges to conventional quantum optical models when matter and light strongly hybridize. In structured photonic environments, necessary in practice to achieve strong light-matter coupling, a rigorous model of field quantization within the medium is also needed. Here, we use the framework of macroscopic QED by quantizing the fields in an arbitrary material system, with a spatially-dependent dispersive and absorptive dielectric, starting from a fundamental light-matter action. We truncate the material and mode degrees of freedom while respecting the gauge principle by imposing a partial gauge fixing constraint during canonical quantization, which admits a large number of gauges including the Coulomb and multipolar gauges. We also consider gauge conditions with explicit time-dependence, enabling us to unambiguously introduce phenomenologically time-dependent light-matter interactions in any gauge. Our results allow one to derive rigorous models of ultrastrong light-matter interactions in structured photonic environments with no gauge ambiguity. Results for two-level systems and the dipole approximation are discussed, as well as how to go beyond the dipole approximation for effective single-particle models. By comparing with the limiting case of an inhomogeneous dielectric, where dispersion and absorption can be neglected and the fields can be expanded in terms of the generalized transverse eigenfunctions of the dielectric, we show how lossy systems can introduce an additional gauge ambiguity, which we resolve and predict to have fundamental implications for open quantum system models. Finally, we show how observables in mode-truncated systems can be calculated without ambiguity by using a simple gauge-invariant photodetection model.

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