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Photometry of in the era of the wide-field camera

Enrichetta Iodice INAF- Astronomical Observatory of Capodimonte Napoli, Italy

VST color composite image of NGC1316 Lectures’ outline why study the low-surface brightness universe ? main progresses from theoretical & observational sides task & tools to manage deep and wide-field images: photometry of galaxies observations vs theoretical predictions future perspectives Lectures’ outline

lecture 1 why study the low-surface brightness universe ? main progresses from theoretical & observational sides task & tools to manage deep and wide-field images: photometry of galaxies observations vs theoretical predictions future perspectives Lectures’ outline

lecture 1 why study the low-surface brightness universe ? main progresses from theoretical & observational sides task & tools to manage deep and wide-field images: photometry of galaxies observations vs theoretical predictions future perspectives lecture 2 Why study the low-surface brightness universe?

LCDM formation theories predict that galaxies grow through a combination of in situ formation and accretion of from other galaxies … Pillepich et al. 2018 Intra-cluster light from TNG100 simulations Intra-cluster light from TNG100 simulations Intra-cluster light from TNG100 simulations Intra-cluster light from TNG100 simulations Intra-cluster light from TNG100 simulations Why study the low-surface brightness universe?

Since dynamical timescales are long in the galaxy outskirts, phase-space substructures related to accretion (streams, tails, etc.) can persist over many Gyrs

The structural properties of the outer parts of galaxies and their correlations with stellar mass and other observables might therefore provide ways of testing theoretical predictions of mass assembly Why deep images? Mancillas et al. 2019

2 2 �g ~ 33 mag/arcsec �g ~ 29 mag/arcsec Why wide-field images? Mancillas et al. 2019

stellar halo extends 50 - 100 kpc ICL extends > 100 kpc Why wide-field images? Mancillas et al. 2019

stellar halo extends 50 - 100 kpc ICL extends > 100 kpc this is particularly important for nearby clusters…… DSS image of the cluster DSS image of the Fornax cluster

FOV@ ESO 1.5m Tel 148 x 237 arcsec DSS image of the Fornax cluster

FOV@ ESO 1.5m Tel 148 x 237 arcsec DSS image of the Fornax cluster

FOV@ ESO 1.5m Tel 148 x 237 arcsec

20 arcmin ~115 kpc DSS image of the Fornax cluster

FOV@ ESO 1.5m Tel 148 x 237 arcsec 33 arcmin ~195 kpc

20 arcmin ~115 kpc

Iodice et al. 2016 The era of deep imaging surveys

In the latest 10 years advances in telescopes technology & instrumentations & data analysis allow to map the regions of the stellar halos & ICL

2 LSB optimised small telescope and telescope arrays: �g ~ 29.5 mag/arcsec Burrell Schmidt (Mihos et al. 2017), Dragonfly image array (Abraham & van Dokkum 2014; Merritt et al. 2016) 2 using 3m-class telescope: �g ~ 28.5 - 29 mag/arcsec NGVS@CFHT (Ferrarese et al. 2012); ATLAS3D@CFHT (Duc et al. 2015); CFHT Legacy Survey (Gwyn 2012); FDS&VEGAS@VST (Iodice et al. 2019) 2 using 4m-8m class telescope (wider area): �r ~ 27.5 - 28.5 mag/arcsec DECam@CTIO (Dey et al. 2019); Hyper Suprime-Cam Subaru Strategic Program@Subaru (Aihara et al. 2018) 2 using 10m GTC telescope (FOV=5’): �r ~ 31.5 mag/arcsec (Trujillo & Fliri 2016) using HST: � ~ 31 mag/arcsec2 (ICL in Hubble Frontiers Fields by Montes & Trujillo 2018) Theory Observations explain why natural Set of observables of phenomena natural phenomena occurs

Studying the mass assembly: Observations vs theoretical predictions Theory Observations explain why natural make hypothesis Set of observables of to reproduce natural phenomena phenomena observables occurs

Studying the mass assembly: Observations vs theoretical predictions Theory Observations explain why natural make hypothesis Set of observables of to reproduce natural phenomena phenomena observables occurs

Studying the mass assembly: Observations vs theoretical predictions

It’s a tricky task! Theoretical predictions stellar halo morphology

SB profile shape & color gradients accreted mass fraction in galaxies

ICL properties kinematics & stellar population in stellar halos Theoretical predictions stellar halo morphology

SB profile shape & color gradients deep accreted mass fraction in galaxies imaging

ICL properties kinematics & stellar population in stellar halos Theoretical predictions stellar halo morphology

SB profile shape & color gradients deep accreted mass fraction in galaxies imaging

ICL properties kinematics & stellar population in stellar halos

spectroscopy Theoretical predictions: stellar halo morphology Mancillas et al. 2019

Tidal tails: result from tidal forces acting within the host galaxy, by intermediate-mass merger and major merger events (mass ratios ~ 7:1 and 3:1) Theoretical predictions: stellar halo morphology Mancillas et al. 2019

Tidal tails: result from tidal forces acting within the host galaxy, by intermediate-mass merger and major merger events (mass ratios ~ 7:1 and 3:1) Theoretical predictions: stellar halo morphology Mancillas et al. 2019

Stellar streams in the first series of consecutive minor mergers (mass ratios larger than 7:1) Theoretical predictions: stellar halo morphology Mancillas et al. 2019

Stellar streams in the first series of consecutive minor mergers (mass ratios larger than 7:1) Theoretical predictions: stellar halo morphology Mancillas et al. 2019

Shells shell formation is associated with both intermediate-mass mergers and major mergers (mass ratios ~ 7:1 and 3:1) Theoretical predictions: stellar halo morphology

Method: To date, the LSB features in the galaxy outskirts are done by visual inspection Theoretical predictions: stellar halo morphology

Method: To date, the LSB features in the galaxy outskirts are done by visual inspection

Let’s do an interactive exercise LEDA087331

HCC020 LEDA087331 which kind of features?

shells ?

tidal tails ?

streams ?

HCC020 LEDA087331 which kind of features?

✔ shells ?

X tidal tails ?

X streams ?

HCC020 ABELL 1060: 340

ABELL 1060: 341 ABELL 1060: 340 which kind of features?

shells ?

tidal tails ?

streams ?

ABELL 1060: 341 ABELL 1060: 340 which kind of features?

✔ shells ?

✔ tidal tails ?

X streams ?

ABELL 1060: 341 NGC3316 NGC3316 which kind of features? NGC3316 shells ?

tidal tails ?

streams ? which kind of features? NGC3316 ✔ shells ? ✔ tidal tails ?

X streams ? PGC031447 PGC031447 which kind of features?

shells ?

tidal tails ?

streams ? PGC031447 which kind of features?

X shells ?

✔ tidal tails ?

X streams ? ????

???? Ultra???? diffuse galaxy

???? Theoretical predictions: SB profiles Cooper et al. (2013)

The global stellar halo density profile depends on the accretion history of the galaxy Theoretical predictions: SB profiles Cooper et al. (2013)

Thein situ global & relaxed stellar accreted halo density density profiles profile are well depends reproduced on by the a Sersic r1/n law n~2 for the inaccretion situ component history of the galaxy unrelaxed envelope ~ exponential decline Theoretical predictions: stellar populations in the galaxy outskirts Cook et al. (2016)

stellar population gradients at large radii can be used to infer basic properties of galactic accretion histories Theoretical predictions: stellar populations in the galaxy outskirts Cook et al. (2016)

At fixed mass, galaxies that accreted little of their stellar halo material tend to have steeper metallicity and SB profiles (Re~2–4 ) stellar population gradients at large radii can be used to Metallicity and SB profiles in the stellar halo typically flatten from z=1 toinfer the present basic —> properties accretion of of stars galactic into the accretion stellar halo histories Theoretical predictions: total accreted mass fraction Pillepich et al. (2018)

Massive galaxies: 12 15 10 - 10 M⦿ Theoretical predictions: total accreted mass fraction Pillepich et al. (2018)

facc ~ 80-100 % for R> 100 kpc!

Massive galaxies: 12 15 10 - 10 M⦿ Theoretical predictions: total accreted mass fraction Pillepich et al. (2018) Tacchella et al. (2019)

facc ~ 80-100 % for R> 100 kpc!

Less massive galaxies: 9 11 10 - 10 M⦿

Massive galaxies: 12 15 10 - 10 M⦿ Theoretical predictions: total accreted mass fraction Pillepich et al. (2018) Tacchella et al. (2019)

facc ~ 80-100 % for R> 100 kpc!

Less massive galaxies: 9 11 facc strongly depends10 on- 10 Mstar M ⦿

10.5 facc ~ 0 at Mstar ~ 10 M⊙ Massive galaxies: 11.5 facc ~ 0.7 when Mstar ~ 10 M⊙ 12 15 10 - 10 M⦿ Theoretical predictions: ICL formation & properties

ICL forms by stellar stripping of satellites galaxies relaxation processes during galaxy mergers Theoretical predictions: ICL formation & properties

Contini et al. (2014)

The predicted fICL in groups and clusters ~ 10 - 40 % Theoretical predictions: ICL formation & properties

Contini et al. (2014)

The predicted fICL in groups and clusters ~ 10 - 40 % Theoretical predictions: ICL formation & properties

Contini et al. (2014)

The predicted f in groups ICL ICL formed very late z≾1 and clusters ~ 10 - 40 % Theoretical predictions: ICL formation & properties Contini et al. (2014)

The predicted fICL correlates with the BCG stellar mass, depending on the ICL formation process In summary: To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

which are the requirements of the real data? In summary: To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

which are the requirements of the real data?

2 deep (�g ~ 27-33 mag/arcsec ) multi-band imaging

large covered area (several square degrees)

arcsec-level angular resolution (pixel scale < 0.3 arcsec/pixel) In summary: To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

which are the requirements of the real data?

2 deep (�g ~ 27-33 mag/arcsec ) multi-band imaging ➥ to study the galaxy structure out to region of the stellar halos + detect the LSB features & ICL + hints on the stellar populations of progenitors from colors large covered area (several square degrees)

arcsec-level angular resolution (pixel scale < 0.3 arcsec/pixel) In summary: To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

which are the requirements of the real data?

2 deep (�g ~ 27-33 mag/arcsec ) multi-band imaging ➥ to study the galaxy structure out to region of the stellar halos + detect the LSB features & ICL + hints on the stellar populations of progenitors from colors large covered area (several square degrees) ➥ map the extended stellar envelope of BCG & ICL in nearby clusters of galaxies (< 50 Mpc) arcsec-level angular resolution (pixel scale < 0.3 arcsec/pixel) In summary: To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

which are the requirements of the real data?

2 deep (�g ~ 27-33 mag/arcsec ) multi-band imaging ➥ to study the galaxy structure out to region of the stellar halos + detect the LSB features & ICL + hints on the stellar populations of progenitors from colors large covered area (several square degrees) ➥ map the extended stellar envelope of BCG & ICL in nearby clusters of galaxies (< 50 Mpc) arcsec-level angular resolution (pixel scale < 0.3 arcsec/pixel) ➥ characterise the LSB features (tidal tails, shells, streams & UDGs) In summary: To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

which are the observables that can be derived? In summary: To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

which are the observables that can be derived? morphology azimuthally-averaged SB profiles color gradients fraction of ICL In summary: To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

which are the observables that can be derived? morphology ➥ to constraints the processes in the mass assembly history (i.e. detection of diffuse halos vs fine LSB features) azimuthally-averaged SB profiles color gradients fraction of ICL In summary: To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

which are the observables that can be derived? morphology ➥ to constraints the processes in the mass assembly history (i.e. detection of diffuse halos vs fine LSB features) azimuthally-averaged SB profiles ➥ to set the scales of the different components in the galaxy (in-situ vs ex-situ) color gradients fraction of ICL In summary: To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

which are the observables that can be derived? morphology ➥ to constraints the processes in the mass assembly history (i.e. detection of diffuse halos vs fine LSB features) azimuthally-averaged SB profiles ➥ to set the scales of the different components in the galaxy (in-situ vs ex-situ) color gradients ➥ to derive hints on the metallicity in the galaxy outskirts fraction of ICL In summary: To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

which are the observables that can be derived? morphology ➥ to constraints the processes in the mass assembly history (i.e. detection of diffuse halos vs fine LSB features) azimuthally-averaged SB profiles ➥ to set the scales of the different components in the galaxy (in-situ vs ex-situ) color gradients ➥ to derive hints on the metallicity in the galaxy outskirts fraction of ICL ➥ to constraint the look-back time of the mass assembly in the cluster and/or group of galaxies In summary: To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

which are the observables that can be derived? morphology ➥ to constraints the processes in the mass assembly history (i.e. detection of diffuse halos vs fine LSB features) azimuthally-averaged SB profiles ➥ to set the scales of the different components in the galaxy (in-situ vs ex-situ) color gradients ➥ toContent derive hints on the metallicity of the in the galaxylecture outskirts 2! fraction of ICL ➥ to constraint the look-back time of the mass assembly in the cluster and/or group of galaxies Concluding remarks To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

Is it feasible? M31: Andromeda’s violent past

Gilbert et al. 2018 D~0.8 Mpc data from Keck 10m Tel M81: the most detailed study of a stellar halo yet obtained outside of the Local Group Smercina et al. 2019 D~3.6 Mpc data from Subaru HSC M81: the most detailed study of a stellar halo yet obtained outside of the Local Group Smercina et al. 2019 D~3.6 Mpc data from Subaru HSC M81: the most detailed study of a stellar halo yet obtained outside of the Local Group Smercina et al. 2019 D~3.6 Mpc data from Subaru HSC The extended halo of CenA CrnojeviĆ et al. 2016 D~3.8 Mpc data: MegaCam@Magellan 6.5m Tel The extended halo of CenA CrnojeviĆ et al. 2016 D~3.8 Mpc data: MegaCam@Magellan 6.5m Tel The extended halo of CenA CrnojeviĆ et al. 2016 D~3.8 Mpc data: MegaCam@Magellan 6.5m Tel ICL in the

Mihos et al. 2015 D~ 16.5 Mpc data: Burrel Schimdt Tel Stellar halos in the core of the Fornax cluster Iodice et al. 2016 D~ 20 Mpc data: VST

Stellar halos in the SW group of the Fornax cluster Iodice et al. 2017 D~ 20 Mpc data: VST

ICL in the high-redshift clusters Montes & Trujillo 2019 z ~ 0.3-0.5 data: HST Concluding remarks To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

Is it feasible? Concluding remarks To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

Is it feasible? ye! Concluding remarks To trace the mass accretion at all scales, i.e. in galaxies & clusters, from observations:

Is it feasible? ye! but, sudying t LSB universe i a chaleng! ➥ let’s see how in the next lecture on February 10