The Maxwell-Bloch equations for a two-level system are solved in a particular case. The example follows that of P. Siddons, "Light propagation through atomic vapours," Journal of Physics B: Atomic, Molecular, and Optical Physics 47, 093001 (2014). In the reference, the optical intensity, population of the upper state and coherence are given for light with a carrier frequency which is on resonance. Here, the same example is worked, but the result is given at intermediate times as well as at the entrance and exit faces as in the example. The solution is found using Mathematica's NDSolve for the time dimension and the Method of Lines for propagation in space.

This data set consists of both measured and simulated optical intensities scattered off periodic line arrays, with simulations based upon an average geometric model for these lines. These data were generated in order to determine the average feature sizes based on optical scattering, which is an inverse problem for which solutions to the forward problem are calculated using electromagnetic simulations after a parameterization of the feature geometry. Here, the array of features measured and modeled is periodic in one-dimension (i.e., a line grating) with a nominal line width of 100 nm placed at 300 nm intervals, or pitch = 300 nm; the short-hand label for the features is "L100P300." The entirety of the modeled data is included, over two thousand simulations that are indexed using a top, middle, and bottom linewidth as floating parameters. Two subsets of these data, featuring differing sampling strategies, are also provided. This data set also contains angle-resolved optical measurements with uncertainties for nine arrays which differ in their dimensions due to lithographic variations using a focus/exposure matrix, as identified in a previous publication (https://doi.org/10.1117/12.777131). We have previously reported line widths determined from these measurements based upon non-linear regression to compare theory to experiment. Machine learning approaches are to be fostered for solving such inverse problems. Data are formatted for direct use in "Model-Based Optical Metrology in R: MoR" software which is also available from data.nist.gov. (https://doi.org/10.18434/T4/1426859). Note: Certain commercial materials are identified in this dataset in order to specify the experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement by the National Institute of Standards and Technology, nor is it intended to imply that the materials are necessarily the best available for the purpose.

Data for "Nanosecond time-resolved dual-comb absorption spectroscopy." Each file contains the data behind the figure in its title.

This dataset contains the code to run the reference case in Walsh et al "Pulse interaction induced systematic errors in dual comb spectroscopy". The code simulates dual combs interferograms at the field level using a generalized non-linear Schrödinger equation to account for non linear propagation is a fiber.

This dataset contains the code to run the reference case in Walsh et al "Pulse interaction induced systematic errors in dual comb spectroscopy". The code simulates dual combs interferograms at the field level using a generalized non-linear Schrödinger equation to account for non linear propagation is a fiber.

Experimental and modeling data from the manuscript: 'Integrating planar photonics for multi-beam generation and atomic clock packaging on chip', C. Ropp, et.al., accepted for publication in Light: Science & Application, 2023.

The mode structure fully describes a light field and contains the information about the source of light without a direct access to the source. Here we offer the tool to extract this information from the measured photon number resolved (PNR) distribution. We present a software package aimed at simulating photon-number probability distributions of a range of naturally occurring classical and non-classical states of light. This software can generate arbitrary probability distributions based on the known mode structure of a light field. It also can solve the reverse problem, i.e. reconstructing the mode structure of a light field based on a given probability distribution.

This is the data underlying "Sub-Doppler spectroscopy of quantum systems through nanophotonic spectral translation of electro-optic light" https://arxiv.org/abs/2309.16069 which is to be published in Nature Photonics.

Data presented is part of the journal manuscript "Optically Distributing Remote Two-node Microwave Entanglement using Doubly Parametric Quantum Transducers." Data includes graphical plots generated from numerical models and computations for various network topologies which illustrate their thresholds for achieving quantum information transfer.