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Accurate photometric redshift (photo-$z$) estimates are essential to thecosmological science goals of the Vera C. Rubin Observatory Legacy Survey ofSpace and Time (LSST). In this work we use simulated photometry for mock galaxycatalogs to explore how LSST photo-$z$ estimates can be improved by theaddition of near-infrared (NIR) and/or ultraviolet (UV) photometry from theEuclid, WFIRST, and/or CASTOR space telescopes. Generally, we find that deeperoptical photometry can reduce the standard deviation of the photo-$z$ estimatesmore than adding NIR or UV filters, but that additional filters are the onlyway to significantly lower the fraction of galaxies with catastrophicallyunder- or over-estimated photo-$z$. For Euclid, we find that the addition of${JH}$ $5{\sigma}$ photometric detections can reduce the standard deviation forgalaxies with $z>1$ ($z>0.3$) by ${\sim}20\%$ (${\sim}10\%$), and the fractionof outliers by ${\sim}40\%$ (${\sim}25\%$). For WFIRST, we show how theaddition of deep ${YJHK}$ photometry could reduce the standard deviation by${\gtrsim}50\%$ at $z>1.5$ and drastically reduce the fraction of outliers tojust ${\sim}2\%$ overall. For CASTOR, we find that the addition of its ${UV}$and $u$-band photometry could reduce the standard deviation by ${\sim}30\%$ andthe fraction of outliers by ${\sim}50\%$ for galaxies with $z<0.5$. We alsoevaluate the photo-$z$ results within sky areas that overlap with both the NIRand UV surveys, and when spectroscopic training sets built from the surveys'small-area deep fields are used.

Photometric Redshifts with the LSST II: The Impact of Near-Infrared and Near-Ultraviolet Photometry