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The role of large-scale structure on galaxy properties Joss Bland-Hawthorn University of Sydney Galaxy studies are an environmental science: but are there observed environmental dependencies? They struggle to find a strong environmental dependence beyond cluster vs. field. Why ? This may reflect (i) difficulty of defining environment; (ii) influence is washed out – evolution, projection, complexity; (iii) inadequacy of existing data; What is environment? Muldrew+ 2012 Statistical environment – a measure of "crowding" Physical environment – I How do we define physical structures? Ideally these would be defined in terms of EUV/x-ray emissivity, CMB SZ or weak lensing signal. Dietrich+ 12 But while useful for dense groups & cluster mass scales, these are much less sensitive to large-scale structure at lower densities. For the foreseeable future, we are limited to galaxy redshift surveys. Physical environment – II "A collection of connected points having the same environmental attributes." 1. Double pass friends of friends (Murphy+ 2011) 2. Multiscale mapping (Barrow+ 1985; Aragon-Calvo+ 2007; Smith+ 2012) 3. Geometric classifiers (Lemson & Kauffman 1999; Sousbie+ 2008) 4. Dynamic classifiers (Hahn+ 2007; Hoffman+ 2012) Dynamic classifiers – Gravitational tidal tensor, Velocity shear tensor – are the most physical but have not been demonstrated on data yet. V G Projection effects in a multi-component galaxy Cappellari 2016 Effects of dust ? I can't find any discussion on this point in measuring, say, kinematic parameters. Integral field spectroscopy is giving us a new angle on environmental effects. But we need “cosmological” samples across large-scale structure at high density, cf. Stripe 82. STRIPE 82: 16000 galaxies to rp ~ 17.7 (3o thick) The technological evolution continues… Near field – ATLAS3D, CALIFA, SAMI, MaNGA, MUSE, Hector… By 2025, we may have 100,000+ galaxies with spatially resolved optical and HI kinematics. We need virtual IFS observations for ~105 galaxies from ~10 x 1003 Mpc3 simulations that reach to z~0. improved sampling where Φ(r) varies rapidly SAMI survey @ AAT (2017) 2016 SAMI has so far obtained masses, low & high order kinematics, specific angular momenta on ~1200 galaxies, ~2000 by mid 2017, ~3600 by end 2018. Hector: “cosmologically motivated IFS survey” across large-scale structure (all galaxies, M ≥ 109 M) SAMI: 3600 gals in 0.6 x 1003 Mpc3 (1dF: 2015-18) Hector-1: 12000 gals in 2 x 1003 Mpc3 (2dF: 2018-23) Hector-2: 60000 gals in 6 x 1003 Mpc3 (3dF: unfunded) our first “true” hexabundle (88% fill) N ~ 60,000 galaxies to detect spin alignment with LSS at z=0 Dark matter only: see also Bailin & Steinmetz; Hahn; 1003 Mpc3 includes gas, AGN etc. (RAMSES: Teyssier et al) Critical mass where it switches over decreases with redshift (~1012 M today) Most of the action at high z but signature frozen in down to z ~ 0. Codis+12,15; Dubois+14; Laigle+15; Chisari+16 LSS connection goes back to: Katz+03; Birnboim & Dekel 03; Keres+05; Ocvirk+08 ω= Δ Vorticit y xv ω ~ 100 km s-1 Mpc-1 Codis+12: helical motion down filament in co-moving frame generates spin. Local | to filament. vorticity sets up in plane __ Galactic accretion with vorticity (Codis+12, 15; Laigle+15) Spinning up haloes Spin-aligned galaxies Early onset of vorticity due to shear flows This is not the same as TTT which was long thought to dominate spin. Vorticity may dominate over TTT in the final analysis (Libeskind+13). New work from Sadrine Codis A (see also Codis+15) Signatures at z~1, want to extend to z~0. A: galaxy spin aligns with tidal tensor (e1 points down filament) for low mass galaxies, opposite for high mass. B: blue galaxies align, red galaxies not so much. C: tensor contribution mostly < 3 Mpc but detectable to 10 Mpc. Same volume as SAMI but 20x more galaxies; some cosmic variance. If true, some galaxy properties are affected by largest scales. B C Australia’s major investment: important element of the Hector survey Gas supply – missing ingredient in all surveys: Deep 21cm (≤1019 cm-2) maps of nearby galaxies & groups only exist for small samples. Deepest to date: M31-M33 map reaches ~1017 cm-2 (Wolfe+16). ASKAP 36 dishes Wallaby, Dingo surveys Milky Way “analogue” – M83 Koribalski 2016 Huge HI disks appear to be normal for Galaxy, M31, M33, LMC, SMC... Summary A case is proposed for physical environment over statistical environment. We must distinguish between filaments in voids ( .v > 0) and filaments in dense regions ( .v < 0)… We need to reach down to void galaxies while retaining enough filaments, groups and clusters for intercomparisons. A full treatment takes us to a Hector survey of ~105 galaxies ultimately down to mass limit ≥ 109 M . 2-4m class telescopes, supported by all-sky HI and photometric surveys, are needed into the next decade to tackle these issues. Simulations must extract “Hector IFS observations” of ~105 galaxies and measure key parameters (e.g. slow/fast fraction, high order kinematics). Dubois+ 14