DOE OSTI · 3002409
Deployed quantum link characterization via Bayesian ancilla-assisted process tomography
Abstract
The development of large-scale quantum networks requires reliable quantum channels, the quality of which can be quantified by the framework of quantum process tomography. Here, in this work, we leverage ancilla-assisted process tomography (AAPT) and Bayesian inference to probe a 1.6 km deployed fiber-optic link. We send one of the two polarization-entangled photons at Alice in one building to Bob in another, exploiting the local qubit as an ancilla system to characterize the corresponding quantum channel. Monitoring over a 24 h period returns a steady process fidelity of 97.6(1)%, while controllable spectral filtering with passbands from 0.025 to 4.38 THz finds fidelities that first increase, and then level off with bandwidth, suggesting both stable operation with time and minimal polarization mode dispersion. To our knowledge, these results represent the first AAPT of a deployed quantum link, revealing a valuable tool for in situ analysis of entanglement-based quantum networks.
Keep this discovery
Explore connections, maps & timelines
Rahman, Arefur [Arizona State Univ., Tempe, AZ (United States)] (ORCID:0009000179434260), Wasserbeck, Noah I. [Arizona State Univ., Tempe, AZ (United States)], Goisman, Zachary [Arizona State Univ., Tempe, AZ (United States)], Fernandes, Rhea P. [Arizona State Univ., Tempe, AZ (United States). Dept. of Physics], Kirby, Brian T. [Army Research Laboratory, Adelphi, MD (United States); Tulane Univ., New Orleans, LA (United States)] (ORCID:0000000226989887), Alshowkan, Muneer [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000264293450), Kurtz, Chris [Arizona State Univ., Tempe, AZ (United States)], Lukens, Joseph M. [Arizona State Univ., Tempe, AZ (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Purdue Univ., West Lafayette, IN (United States)] (ORCID:0000000196504462). 2025-04-02. Deployed quantum link characterization via Bayesian ancilla-assisted process tomography. https://doi.org/10.1364/ol.545625
Cite the original work for its findings. Save a collection to share your selection of sources.