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ABSTRACT A search of the first Data Release of the VISTA Variables in the Via Lactea (VVV) Survey discovered the exceptionally red transient VVV-WIT-01 (H − Ks = 5.2). It peaked before March 2010, then faded by ∼9.5 mag over the following 2 yr. The 1.6–22 μm spectral energy distribution in March 2010 was well fit by a highly obscured blackbody with T ∼ 1000 K and $$A_{K_s} \sim 6.6$$ mag. The source is projected against the Infrared Dark Cloud (IRDC) SDC G331.062−0.294. The chance projection probability is small for any single event (p ≈ 0.01–0.02), which suggests a physical association, e.g. a collision between low mass protostars. However, blackbody emission at T ∼ 1000 K is common in classical novae (especially CO novae) at the infrared peak in the light curve due to condensation of dust ∼30–60 d after the explosion. Radio follow-up with the Australia Telescope Compact Array detected a fading continuum source with properties consistent with a classical nova but probably inconsistent with colliding protostars. Considering all VVV transients that could have been projected against a catalogued IRDC raises the probability of a chance association to p = 0.13–0.24. After weighing several options, it appears likely that VVV-WIT-01 was a classical nova event located behind an IRDC. 

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown.Euclidis a medium-class mission in the Cosmic Vision 2015–2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14 000 deg²of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance.