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Abstract:

The arrival of the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), Euclid-Wide and Roman wide-area sensitive surveys will herald a new era in strong lens science in which the number of strong lenses known is expected to rise from to. However, current lens-finding methods still require time-consuming follow-up visual inspection by strong lens experts to remove false positives which is only set to increase with these surveys. In this work, we demonstrate a range of methods to produce calibrated probabilities to help determine the veracity of any given lens candidate. To do this we use the classifications from citizen science and multiple neural networks for galaxies selected from the Hyper Suprime-Cam survey. Our methodology is not restricted to particular classifier types and could be applied to any strong lens classifier which produces quantitative scores. Using these calibrated probabilities, we generate an ensemble classifier, combining citizen science, and neural network lens finders. We find such an ensemble can provide improved classification over the individual classifiers. We find a false-positive rate of 10-3 can be achieved with a completeness of 46 per cent, compared to 34 per cent for the best individual classifier. Given the large number of galaxy-galaxy strong lenses anticipated in LSST, such improvement would still produce significant numbers of false positives, in which case using calibrated probabilities will be essential for population analysis of large populations of lenses and to help prioritize candidates for follow-up.

Abstract:

The MAJIS (Moons And Jupiter Imaging Spectrometer) instrument on board the ESA JUICE (JUpiter ICy moon Explorer) mission is an imaging spectrometer operating in the visible and near-infrared spectral range from 0.50 to 5.55 μm in two spectral channels with a boundary at 2.3 μm and spectral samplings for the VISNIR and IR channels better than 4 nm/band and 7 nm/band, respectively. The IFOV is 150 μrad over a total of 400 pixels. As already amply demonstrated by the past and present operative planetary space missions, an imaging spectrometer of this type can span a wide range of scientific objectives, from the surface through the atmosphere and exosphere. MAJIS is then perfectly suitable for a comprehensive study of the icy satellites, with particular emphasis on Ganymede, the Jupiter atmosphere, including its aurorae and the spectral characterization of the whole Jupiter system, including the ring system, small inner moons, and targets of opportunity whenever feasible. The accurate measurement of radiance from the different targets, in some case particularly faint due to strong absorption features, requires a very sensitive cryogenic instrument operating in a severe radiation environment. In this respect MAJIS is the state-of-the-art imaging spectrometer devoted to these objectives in the outer Solar System and its passive cooling system without cryocoolers makes it potentially robust for a long-life mission as JUICE is. In this paper we report the scientific objectives, discuss the design of the instrument including its complex on-board pipeline, highlight the achieved performance, and address the observation plan with the relevant instrument modes.

Abstract:

<jats:p>The composition, evolution, distribution, structure, and dynamics of Jupiter&amp;#8217;s atmosphere are of interest to the scientific community. The JUICE (JUpiter ICy moons Explorer) mission from the European Space Agency (ESA) launched in April 2023, will make detailed observations to characterize Jupiter&amp;#8217;s atmosphere that are complementary to those from Juno. In preparation for its arrival to the Jovian System in July 2031, we would like to assess the visible and near-infrared (VIS-NIR) capabilities of the Moons And Jupiter Icy Moons Spectrograph (MAJIS), onboard JUICE. This is only possible by knowing the actual performances of the MAJIS VIS-NIR channel implemented in a radiometric model, and by simulating the radiative processes of Jupiter&amp;#8217;s atmosphere in a Radiative Transfer (RT) model. Here we discuss the radiative transfer model, which was validated against observational data from Jupiter&amp;#8217;s Great Red Spot (GRS) taken by the Visible and Infrared Mapping Spectrometer (VIMS), on board the Cassini mission, during its journey to Saturn. The line-by-line RT software ASIMUT-ALVL developed by BIRA-IASB, has been extensively used for the study of the atmospheres of Venus, Mars and Earth (Vandaele et al., 2006), and now has been upgraded for the modelling of Jupiter&amp;#8217;s atmosphere. Since Jupiter&amp;#8217; upper atmosphere is mainly composed of hydrogen (H2), helium (He), and minor traces of other gases such as methane (CH4), water (H2O) and ammonia (NH3), its VIS-NIR spectrum is dominated by the absorption bands due to the CH4, H2O and NH3; Rayleigh scattering due to the dominant atmospheric species (H2 and He); Mie scattering due to aerosols and haze; and Collision-Induced Absorption (CIA) due to H2-H2 and H2-He molecular systems (Lopez-Puertas et al., 2005). We included the typical temperature profile from Moses et al. (2005) in our model, which covers data down to a pressure level of 1 bar, supplemented with data from Seiff et al. (1998) for pressure levels down to 20 bar. The initial atmospheric composition was obtained from Gonz&amp;#225;lez et al. (2011) and extrapolated with constant values below the pressure level of 1 bar. The required spectroscopic line lists were implemented as Look Up Tables (LUTs) for different pressure and temperature values, using data from Chubb et al. (2021), after realizing that the HITRAN 2020 database does not extend in the visible spectral range for all species. In the case of CH4 and NH3, the LUTs have been derived from the band models of Karkoschka et al. (2010) and Coles et al. (2018), respectively. Finally, to model the atmospheric aerosols and hazes, including the chromophores, the microphysical parameters were obtained as described by Baines et al., (2019) for the Cr&amp;#232;me Brul&amp;#233;e model. Additionally, aerosols and hazes as defined by Lopez-Puertas et al., (2005) are also available. It is already possible to perform inverse models and retrieve physical parameters. Moreover, the RT model can now be used in combination with the radiometric model of MAJIS to assess the optical performances of the VIS-NIR channel.</jats:p>