MAVIS: science case, imager, and spectrograph

Ellis, S. C.; McDermid, Richard M.; Cresci, G.; Schwab, Christian; Rigaut, François; Chin, T.; Horton, Anthony; Mohanan, Mahesh; McGregor, Helen; Pember, Jacob; Robertson, David J.; Waller, Lew; Zhelem, Ross; Monty, Stephanie; Mendel, J. Trevor; Aliverti, Matteo; Agapito, Guido; Antoniucci, S.; Balestra, Andrea; Baruffolo, A.; Bergomi, Maria; Bianco, Andrea; Bonaglia, Marco; Bono, G.; Bouret, Jean-Claude; Brodrick, David; Busoni, Lorenzo; Carolo, Elena; Chinellato, Simonetta; Cranney, Jesse; Silva, Gayandhi De; Esposito, Simone; Fantinel, D.; Farinato, Jacopo; Fusco, Thierry; Gausachs, Gaston; Gilbert, James; Gratadour, Damien; Gerggio, Davide; Gullieuszik, Marco; Haguenauer, Pierre; Haynes, Dionne; Korkiakoski, Visa; Magrin, Demetrio; Magrini, L.; Marafatto, Luca; Neichel, Benoît; Pedichini, Fernando; Pinna, Enrico; Plantet, Cédric; Portaluri, Elisa; Radhakrishnan, Kalyan; Ragazzoni, Roberto; Salasnich, Bernado; Ströbele, Stefan; Thorn, Elliott; Vaccarella, Annino; Vassallo, Daniele; Viotto, Valentina; Zamkotsian, Frédéric; Zanutta, Alessio; Zhang, Hao

doi:10.1117/12.2561930

Cited by 5 publications

(1 citation statement)

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“…Most of the work has been done through, in particular, sensitivity analysis to different parameters, error terms, with a few different tools. These tools that have also been used to compute synthetic PSFs to support the design of the MAVIS imager and spectrograph modules, 2,3 are presented in the next section, 2. Then, the article continues with the description of the parameters of the baseline configuration of the MAVIS AO module 4 in Sec.…”

Section: Introductionmentioning

confidence: 99%

MAVIS: system modelling and performance prediction

Agapito,

Vassallo,

Plantet

et al. 2020

Preprint

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The MCAO Assisted Visible Imager and Spectrograph (MAVIS) Adaptive Optics Module has very demanding goals to support science in the optical: providing 15% SR in V band on a large FoV of 30arcsec diameter in standard atmospheric conditions at Paranal. It will be able to work in closed loop on up to three natural guide stars down to H=19, providing a sky coverage larger than 50% in the south galactic pole. Such goals and the exploration of a large MCAO system parameters space have required a combination of analytical and endto-end simulations to assess performance, sky coverage and drive the design. In this work we report baseline performance, statistical sky coverage and parameters sensitivity analysis done in the phase-A instrument study.

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Section: Introductionmentioning

confidence: 99%

MAVIS: system modelling and performance prediction

Agapito,

Vassallo,

Plantet

et al. 2020

Preprint

Self Cite

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The role of gas kinematics in setting metallicity gradients at high redshift

Sharda

Wisnioski

Krumholz

et al. 2021

Monthly Notices of the Royal Astronomical Society

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In this work, we explore the diversity of ionised gas kinematics (rotational velocity vφ and velocity dispersion σg) and gas-phase metallicity gradients at 0.1 ≤ z ≤ 2.5 using a compiled data set of 74 galaxies resolved with ground-based integral field spectroscopy. We find that galaxies with the highest and the lowest σg have preferentially flat metallicity gradients, whereas those with intermediate values of σg show a large scatter in the metallicity gradients. Additionally, steep negative gradients appear almost only in rotation-dominated galaxies (vφ/σg > 1), whereas most dispersion-dominated galaxies show flat gradients. We use our recently developed analytic model of metallicity gradients to provide a physical explanation for the shape and scatter of these observed trends. In the case of high σg, the inward radial advection of gas dominates over metal production and causes efficient metal mixing, thus giving rise to flat gradients. For low σg, it is the cosmic accretion of metal-poor gas diluting the metallicity that gives rise to flat gradients. Finally, the reason for intermediate σg showing the steepest negative gradients is that both inward radial advection and cosmic accretion are weak as compared to metal production, which leads to the creation of steeper gradients. The larger scatter at intermediate σg may be due in part to preferential ejection of metals in galactic winds, which can decrease the strength of the production term. Our analysis shows how gas kinematics play a critical role in setting metallicity gradients in high-redshift galaxies.

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