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ABSTRACT We combine parallax distances to nearby O stars with parsec-scale resolution three-dimensional dust maps of the local region of the Milky Way (within 1.25 kpc of the Sun) to simulate the transfer of Lyman continuum photons through the interstellar medium (ISM). Assuming a fixed gas-to-dust ratio, we determine the density of ionized gas, electron temperature, and H$$\alpha$$ emissivity throughout the local Milky Way. There is good morphological agreement between the predicted and observed H$$\alpha$$ all-sky map of the Wisconsin H$$\alpha$$ Mapper. We find that our simulation underproduces the observed H$$\alpha$$ emission while overestimating the sizes of H ii regions, and we discuss ways in which agreement between simulations and observations may be improved. Of the total ionizing luminosity of $$5.84 \times 10^{50}~{\rm photons \, s^{-1}}$$, 15 per cent is absorbed by dust, 64 per cent ionizes ‘classical’ H ii regions, 11 per cent ionizes the diffuse warm ionized medium, and 10 per cent escapes the simulation volume. We find that 18 per cent of the high-altitude ($$|b| > 30{}^{\circ }$$) H$$\alpha$$ arises from dust scattered rather than direct emission. These initial results provide an impressive validation of the three-dimensional dust maps and O-star parallaxes, opening a new frontier for studying the ionized ISM’s structure and energetics in three dimensions. 

High-resolution 3D maps of interstellar dust are critical for probing the underlying physics shaping the structure of the interstellar medium, and for foreground correction of astrophysical observations affected by dust. We aim to construct a new 3D map of the spatial distribution of interstellar dust extinction out to a distance of kpc from the Sun. We leveraged distance and extinction estimates to 54 million nearby stars derived from the Gaia BP/RP spectra. Using the stellar distance and extinction information, we inferred the spatial distribution of dust extinction. We modeled the logarithmic dust extinction with a Gaussian process in a spherical coordinate system via iterative charted refinement and a correlation kernel inferred in previous work. In total, our posterior has over 661 million degrees of freedom. We probed the posterior distribution using the variational inference method MGVI. Our 3D dust map has an angular resolution of up to $ $ ($$N_ side =256$$), and we achieve parsec-scale distance resolution, sampling the dust in $516$ logarithmically spaced distance bins spanning pc . We generated 12 samples from the variational posterior of the 3D dust distribution and release the samples alongside the mean 3D dust map and its corresponding uncertainty. Our map resolves the internal structure of hundreds of molecular clouds in the solar neighborhood and will be broadly useful for studies of star formation, Galactic structure, and young stellar populations. It is available for download in a variety of coordinate systems online and can also be queried via the publicly available dustmaps Python package.