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Enrique Vázquez-SemadeniInstituto de Radioastronomía y Astrofísica, UNAM
IRyA
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Collaborators:
Pedro ColínU (IRyA)
Marina Kounkel (WWU)
Manuel Zamora-Avilés (INAOE-
LMT)
Postdoc:
Alejandro González-Samaniego
(IRyA)
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• Outline:
– Global hierarchical collapse (GHC) context
• Acceleration of SF
• Filament formation
• Accretion at all scales
– The simulations
• Simplified prescriptions
– Effects of feedback:
• Triggering vs. quenching
• Cluster expansion
• Indirect feedback-cluster coupling via the gas
• Regulation of the SFR and SFE.
– Young cluster evolution (time permitting)
• Age histograms
• Delayed massive-star formation
• Age-mass correlation
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I. The Global Hierarchical
Collapse (GHC) Scenario(VS+19, MNRAS, 490, 3061)
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• Mounting evidence of multi-scale infall flows, in
particular via filaments, in MCs.
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• The GHC scenario (VS+09, ApJ, 707, 1023; VS+19, MNRAS, 490, 3061):
– Solar-neighborhood-type clouds form by compression-triggered phase
transition WNM CNM (Hennebelle & Perault 99; Koyama & Inutsuka 02; Heitsch+05;
VS+06).
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• Turbulence in the diffuse ISM forms clouds as much as it shakes
them (BP+99, ApJ, 515, 286):
An SPH simulation of
decaying solenoidal
turbulence with initial
Ms = 2 in the
thermally bistable
WNM with self-gravity(Heiner+15, MNRAS, 452,
1353).
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• The GHC scenario (VS+09, ApJ, 707, 1023; VS+19, MNRAS, 490, 3061):
– Solar-neighborhood-type clouds form by compression-triggered phase
transition WNM CNM (Hennebelle & Perault 99; Koyama & Inutsuka 02; Heitsch+05;
VS+06).
• Self-consistent moderate turbulence inside cloud driven by various instabilities.
• r 100x r; T T/100
– Jeans mass (~ r-1/2 T3/2) drops precipitously (x104) by cooling/compression
and cloud begins to collapse (Gómez & VS 14).
• As cloud contracts, average Jeans mass decreases (Hoyle 53).
As time proceeds, turbulent fluctuations of ever lower mass go into collapse.
• Cloud gradually turns molecular (Hartmann+01; Heiner+15, MNRAS, 452, 1353).
• Large-scale collapse becomes filamentary because Pth becomes negligible.
Collapse (and cloud) become strongly anisotropic (Lin+65).
– Collapse is multi-scale: small-scale collapses within and falling into larger-
scale ones.
– All scales accrete from their parent scale.
• Filaments are the accretion flow from clouds to hubs (Gómez & VS 14).
• With durations ~ free-fall time of the parent structure. ( Pamela’s talk)
• Conveyor-belt (Longmore+14) type of flow.
• For simulations: crucial to couple to the larger scale. ( Hosokawa’s talk)
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• Filament formation:
– Due to nearly pressureless collapse (Lin+65), not to strongly supersonic turbulence.
Gómez & VS
2014, ApJ,
791, 124.
Produces
“Conveyor-belt”-
like (Longmore+14)
filamentary flow
onto hubs.
Hubs grow in
mass and density.
Secondary, low-
mass SF in
filaments.
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• SF accelerates in a contracting cloud (Zamora-Avilés+12, ApJ, 751, 77,
ZA & VS 14, ApJ, 793, 84; VS+18, MNRAS 479, 3254. See also Hartmann+12;
Burkert & Hartmann 13; Völschow+17; Burkhart18):
– Because mass fraction of dense gas increases in time due to
gravitational contraction and accretion.
– Massive stars appear late, when the accretion rate onto a hub and
the SFR are large (~ 103 Msun Myr-1).
• When massive stars appear (a few Myr after the first stars), they
disperse the cloud (Leisawitz+89).
SFR increases first by contraction, then decreases again due to
feedback.
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II. The simulations
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– LAF1: Simulation of molecular cloud formation, evolution and
cluster formation by converging flows (Robi’s talk) including self-
gravity, photoionizing feedback and a realistic IMF (imposed).
• ART+HD code (Kravtsov+97; Kravtsov03)
• Box size: 256 pc; maximum resolution: 0.06 pc.
• Parameterized cooling functions (Koyama & Inutsuka 2002).
• A “PMRT” (“poor man’s radiative transfer”) scheme:
– For each grid cell i compare its distance to star s, di,s to the Strömgren
radius Rsgiven by
where
– If di,s < RS, heat cell to 104 K.
Numerical simulation (Colín+2013, MNRAS, 435, 1701;
Vázquez-Semadeni+17, MNRAS, 467, 1313)
iSnnn LOS
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– The stars have lifetimes
– Each star radiates according to its mass.
• A probabilistic SF scheme:
– When maximum refinement level has been reached, if ni > nth, have
probability p of forming a stellar particle.
– If no star forms, no further refinement accretion occurs onto cell.
– When star forms, acquires half of the cell’s mass. No accretion onto
stellar particle.
– Produces power-law, stellar-mass sink IMF, with p-dependent slope:
“Winds”
“UV radiation”
Salpeter for p = 0.003
Minimum stellar mass:
0.3 Msun
Can trust cluster
dynamics.
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pc
x104 yr
“Cluster 2”
Self-consistent turbulence,
cloud evolution and
energy-injection locations.
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Qualitative behavior consistent with full-RT FLASH 2.5
simulations (Zamora-Avilés+19, MNRAS, 487, 2200)
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III. Effect of the
feedback on cluster
structure(González-Samaniego & VS 2020, to be subm.)
– Compare feedback run (LAF1) to a non-feedback one (LAF0).
1822.5 Myr 29.1 Myr27.5 Myr25 Myr
LAF1
LAF0
15
pc
15
pc
– Cluster is assembled hierarchically from the cloud’s hierarchical
collapse.
• Secondary subgroups appear in filaments.
– Gas dispersal dominated by the most massive star.
• Subgroup expansion and gas dispersal occurs at later times for more
distant clumps.
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Plots of individual stars’ distances to cluster’s center of mass vs. time.
• Triggered or primordial neighboring SF?
– Most peripheral SF is primordial, from secondary collapses in
filaments.
– Only one instance of triggered SF.
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– Gas mass increases by accretion faster than SFR.
• Keeps observed SFE low even before cloud dispersal.
• At tage = 7 Myr, SFELAF0 ~ 6.5% SFELAF1 ~ 4%
• But LAF0 keeps going, LAF1 shuts off, so final M*,LAF0 >> M*,LAF1
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)()(
)()SFE(
*g
*
tMtM
tMt
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• Evolution of virial parameter:
– Clouds have virial parameters a ~ 1 before SFR becomes large.
Then massive stars form and disrupt the clouds, with a >> 1:
Viria
lpara
mete
r a
Massive stars
form, unbind cloud.
Colín+13, MNRAS,
435, 1701
SFR
*max,gas
*SFEMM
M
Final SFE ~ 7%
Mcloud
Most (~90%) of
cloud’s mass
dispersed. The
“unbound” clouds?
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– SFEff within every volume:
– Consistent with observations.
– Feedback-star coupling via the gas:
2422.5 Myr 29.1 Myr27.5 Myr25 Myr
LAF1
LAF0
15
pc
15
pc
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– Prevents excessively large group infall speeds (Krumholz+19).
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IV. Cluster Formation and
Structure(VS+17, MNRAS, 467, 1313)
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– SFR increases by collapse, then decreases by feedback.
Stellar age histograms peak at a certain age.
Quantitatively
consistent with
observed embedded
cluster age
histograms (e.g.,
Palla & Stahler 2000;
daRio+10).
Vázquez-Semadeni+17, MNRAS, 467, 1313
1.5 Myr since
onset of SF.
3.5 Myr 5.7 Myr 6.7 Myr
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Cluster 1 @ 11 Myr (synth)
Cluster 1 @ 11 Myr (raw))
Age histograms
Synthetic and observed age histograms for Cluster 1 (11
Myr after the formation of its first star) and Orion D from
Kounkel+18. (González-Samaniego+20, in prep.)
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• Massive-star population builds up over time
– As clumps become denser and more massive by accretion...
Cu
mu
lative
ma
ss fra
ctio
n
Vázquez-Semadeni+17, MNRAS, 467, 1313
... and SFR is high,
> 103 Msun Myr-1
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3. Mass-age correlations and radial gradients.
• Stars form in hub and filaments over large-scale collapse duration
(tff), not local.
• SF accelerates in hub as mass and density grow by accretion.
– Massive stars form later, when SFR is high (> 103 Msun Myr-1).
• Older stars are more scattered and less massive on average,
younger stars more concentrated and up to higher mass.
~
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Age
Scarcity of young stars
at large distances.
Vázquez-Semadeni+17, MNRAS, 467, 1313
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Age
A flyby.
Vázquez-Semadeni+17, MNRAS, 467, 1313
Mass gradient Mass-age relation
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V. Conclusions
– GHC is synonymous with cloud and SFR evolution.
• Flow regime consists of multi-timescale collapses within collapses...
• ... and accretion at all scales from parent structures.
– Need to include accretion onto system at least from next larger scale.
• Accretion onto massive-SF cores via clumpy filaments. (CCCs?)
• Clumps grow in mass and density SF accelerates.
• Clumps definitely not spheroidal (important for simulation initial conditions).
– Effect of UV feedback on cluster:
• Dominated by most massive star.
• Some momentum imparted to stars via the gas they form from.
• Most peripheral star-forming clumps were pre-existing, not triggered.
• Hub’s gas mass increases by accretion faster than stellar mass.
– Keeps instantaneous apparent SFE low even without feedback for a while.
(Can’t model this without coupling to the next larger scale.)
– This structure/evolution is imprinted on forming clusters.
• Massive stars begin to form when clumps are massive and SFR is large.
• When sufficiently massive stars appear, clumps and filaments are quickly
destroyed SFR decreases again.
• Most stars have age of SFR peak. 35
• Provocative questions/food for thought:
– Having self-consistent conditions is at least as important as
extremely detailed modeling of the physical processes.
• Appropriate level of self-consistently-driven turbulence.
• Appropriate cloud geometry (flattened/filamentary rather than
spherical clumps?)
• Self-consistently-generated magnetic fields.
– How much can we learn from light simulations that capture the
essentials without extreme detail and power?
– When do we really need the full power?
• To generate the self-consistent environment? ( Aake’s question)
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THE END
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Fundamental fact for production of density
enhancements:
A density enhancement requires an accumulation of initially
distant material into a more compact region. A convergingflow.
(d/dt is the Lagrangian, or material, derivative)
Not optional!
udt
d r
r
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• Filamentary flow akin to rivers funneling material from high to low
potential levels (Gómez & VS 14, ApJ, 791, 124):
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• Flow smoothly changes
direction from perpendicular
to longitudinal (Gómez & VS
14, ApJ, 791, 124):
– No strong shocks form at
the filament’s axis.
– Strong shocks only form at
central hub if infall is
supersonic.
– Shocks in filament, if any,
are weak.
• Filaments in turn accrete
from parent cloud
– The large-scale collapse
flow.
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Position-velocity diagram:
High velocity dispersion at
local collapse centers.
Column density
Red: n < 103 cm-3
Green: n > 103 cm-3
Gómez & VS 2014, ApJ, 791, 124
Longitudinal velocity:
Acceleration and shocks
at collapse centers.Hacar+17
Compare to
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• In the presence of
subdominant magnetic
field (Gómez et al. 18, MNRAS, 480,
2939):
– Magnetic field lines draggedalong by the collapse.
• Not controlling the flow.
– Thus nearly perpendicular to
main filament...
– ... although with curvature
induced by flow along
filament.
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Compare to Planck XXXV
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Hierarchical collapse of cloud implies several properties of
cluster (Vázquez-Semadeni+17, MNRAS, 467, 1313):
1. Hierarchical-collapse structure of cloud imprinted on cluster
structure.
Groups identified by a
friends-of-friends
algorithm, varying the
linking parameter l.
l = 0.5
l = 1 l =2
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4. Comparison with observations (González-Samaniego+19, in prep.):
– Kounkel+18 (AJ, 156, 84): spectroscopic and astrometric study of Orion.
– Discussed 5 star-forming regions: Orion A, B, C, D and l Ori.
– Process on simulation stars:
(age,mass) (color,magnitude) place in HR diagram synthetic (age,mass)
Orion D
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Cluster 1
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Simulation
HII region expansion test:
– Within 30% of analytic solution.
Colín +13
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