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MARK KRUMHOLZ OPEN PROBLEMS IN STAR FORMATION OUTLINE OUTLINE: THE BIG QUESTIONS Regulation of the star formation rate Global vs. local regulation Universal versus variable efficiency Bound clusters versus unbound associations


  1. MARK KRUMHOLZ OPEN PROBLEMS IN STAR FORMATION

  2. OUTLINE OUTLINE: THE BIG QUESTIONS ▸ Regulation of the star formation rate ▸ Global vs. local regulation ▸ Universal versus variable efficiency ▸ Bound clusters versus unbound associations ▸ What is special about stars that stay bound? ▸ What sets transition between bound and unbound stars? ▸ The origin of the IMF ▸ Where does it come from? ▸ Is it universal?

  3. REGULATION OF THE SFR Figure 1. Theorist who has been asked to talk about JWST.

  4. DEPLETION TIME ≈ 100 × FREE-FALL TIME Compilation: Krumholz (2014) TIGHT SFR-GAS CORRELATION AT ~500 PC SCALES Data: Leroy+ (2013), Bolatto+ (2010), Schruba+ (2010)

  5. REGULATION OF THE SFR ORIGIN OF THE CORRELATION: THE TOP-DOWN VIEW ▸ One model: tight correlation comes from momentum balance between gravity and SN feedback (Ostriker+ 2010, 2011, Hopkins+ 2011, 2012; Faucher-Giguere+ 2013) ▸ If SN inject momentum per unit mass of stars formed <p/M * >, SFR obeys P mp ≈ 2 𝜌 G Σ gas ( Σ gas + Σ * ) ≈ <p/M * > Σ SFR ▸ Depletion time long and SF inefficient because each SN injects a lot of momentum ⇒ ε ff ≡ SFR / (M gas / t ff ) = t ff / t dep ≪ 1 ▸ Important point: SFR regulated in scales of order galactic scale height — on smaller scales, SF can be efficient, ε ff ≈ 1

  6. All simulations MW_10_8_hr: ε =0.35% Low � int High � int MW_10_7_hr: ε =1.5% MW_10_9_hr: ε =6.0% 10 • yr -1 ] SFR [M O 1.0 0.1 10 − 4 10 − 3 10 − 2 10 − 1 10 0 10 1 0.0 0.2 0.4 0.6 � ff, 50 Hopkins+ 2011 Grudic+ 2018 NUMERICAL EXPERIMENTS Left: large-scale SFR independent of small-scale SF efficiency Right: huge variation in SF efficiency in ≲ 100 pc clouds

  7. REGULATION OF THE SFR THE BOTTOM-UP VIEW ▸ Alternate model: galaxy- scale correlation is just counting the # GMCs / beam, with each GMC forming stars at ~same rate / unit mass (Krumholz+ 2005, 2012, 2018, Padoan+ 2011, 2012; Federrath+ 2012, 2015) ▸ ε ff ≈ 0.01 within clouds due to turbulence, B-fields, jets Federrath 2015

  8. REGULATION OF THE SFR OBVIOUS TEST: IS THE CLOUD-SCALE SF EFFICIENCY UNIFORMLY LOW? σ ≈ 0.3 DEX Cloud-to-cloud variation in ε ff (Krumholz 2014) Intra-cloud variation in ε ff (Pokhrel+ in prep)

  9. � - � S º p a º s ▸ Mean value and dispersion of ε ff depend on method and targets: a = + � 20 ) ▸ Nearby clouds, SFR from YSO � counting: ε ff ≈ 0.01, σ ≈ 0.3 dex ▸ Distant clouds, SFR from matching HII regions to clouds: ε ff ≈ 0.1, σ ≈ 1 dex YSO counting Cloud matching O+17 � O+17 log ✏ ff = − 1 . 7 +0 . 45 log ✏ ff = − 1 . 3 +0 . 61 − 0 . 33 S µ S t PDF [arbitrary units] − 0 . 44 � H+16 log ✏ ff = − 1 . 8 +0 . 40 LMDM16 − 0 . 44 log ✏ ff = − 1 . 7 +0 . 77 − 0 . 92 log ✏ ff = − 2 . 1 +0 . 37 EHV14 S − 0 . 33 � S µ S t � log ✏ ff = − 2 . 5 +0 . 46 VEH16 − 0 . 70 log ✏ ff = − 2 . 2 +0 . 30 L+13 � − 0 . 33 − 4 . 0 − 3 . 5 − 3 . 0 − 2 . 5 − 2 . 0 − 1 . 5 − 1 . 0 − 0 . 5 0 . 0 − 4 . 0 − 3 . 5 − 3 . 0 − 2 . 5 − 2 . 0 − 1 . 5 − 1 . 0 − 0 . 5 0 . 0 log ✏ ff log ✏ ff � OBSERVERS CAN’T AGREE! Top: Lee+ 2016 Bottom: Krumholz+ 2019, ARA&A S �

  10. REGULATION OF THE SFR THIS IS WHERE JWST COMES IN ▸ Right now can only count ~1 M ⨀ YSOs within ~1 kpc of Earth; JWST will push this out to the Magellanic Clouds ▸ Two possible explanations for discrepancy: ▸ Nearby cloud sample missing efficient star-formers that account for most of SF budget of galaxy ▸ Assigning clouds to HII regions based on proximity doesn’t work well, and returns bogus SFRs sometimes ▸ JWST test: count YSOs in more distant sources, particularly those proposed to have very high ε ff

  11. ORIGIN OF STAR CLUSTERS Figure 2. Epicycles: simpler and cleaner than most models of star cluster formation.

  12. NGC 1313 M > 20 M ⨀ , t life < 5 Myr M = 8-20 M ⨀ , t life = 5-25 Myr M < 8 M ⨀ , t life > 25 Myr MOST STARS DISPERSE FROM BIRTH SITE BY ~20 MYR Pellerin+ 2007

  13. ORIGIN OF STAR CLUSTERS CASE STUDY: ORION ▸ Most stars form in a diffuse, extended (~30 pc) dynamically-unrelaxed region ▸ Bound cluster formation sites (e.g. the ONC) are the densest parts of these regions, distinguished by: ▸ Extended age distribution (t 90 ≳ 5 t ff ) (da Rio+ 2014, Krumholz+ 2019) ▸ Little sub-structure (Hillenbrand+ 1998, da Rio+ 2017) ▸ Velocities close to virial equilibrium (Kim+ 2019) Data: Kounkel+ 2018 Figure: Krumholz+ 2019

  14. ORIGIN OF STAR CLUSTERS FORMATION SCENARIOS ONC, Kounkel+ (2018) 1 . 0 t 90 ≈ 10 t ff ▸ “Conveyor belt”: mass accretes onto a 0 . 8 dp ∗ /d log t ∗ quasi-static star-forming clump for several 0 . 6 t ff (e.g., Longmore+ 2014, Lee + t ff = 0 . 6 Myr 0 . 4 Hennebelle 2016) 0 . 2 ▸ “Global hierarchical collapse”: large 0 . 0 structure collapses on its (longer) t ff , bound CB NGC 6530, Prisinzano+ (2019) stuff fell to current position (e.g., GHC 1 . 0 IE t 90 ≈ 6 t ff Kuznetsova+ 2018, Vazquez-Semadeni+ 0 . 8 2019) dp ∗ /d log t ∗ 0 . 6 ▸ “Increasing efficiency”: ε ff rises over time — t ff = 0 . 5 Myr 0 . 4 slow start allows long SF history, but then most stars form late (e.g., Murray & Chang 0 . 2 2015, Caldwell & Chang 2018) 0 . 0 − 1 . 0 − 0 . 5 0 . 0 0 . 5 1 . 0 log t ∗ [Myr]

  15. ORIGIN OF STAR CLUSTERS FORMATION SCENARIOS: OTHER CONSTRAINTS ▸ IE: hard to reconcile model with variable ε ff with observed narrow distribution from YSO counting ▸ GHC: possible budget problem — ATLASGAL found ~10 7 M ⊙ in proto-ONC-like dense clumps with t ff ≈ 0.5 Myr; if these collapse in ~t ff , MW SFR should be ~20 M ⊙ yr − 1 ▸ CB: no obvious problems, but needs testing: in still- embedded clusters, younger stars (t ≲ t ff ) should be non- virialized, while older stars are virialized: can test with JWST proper motions

  16. ORIGIN OF STAR CLUSTERS WHAT UNBINDS THE REMAINING STARS? ▸ To understand cluster formation, need to understand what clears the remaining gas, so that star formation stops before lower density regions have a chance to virialize ▸ Candidate mechanisms ▸ Photoionization ▸ Radiation pressure (direct or indirect) ▸ Massive star winds ▸ Supernovae

  17. ORIGIN OF STAR CLUSTERS PHOTOIONIZATION ▸ Ionization heats gas to 10 4 K, producing pressure-driven wind ▸ Able to eject ~70% of the mass in clouds with v esc ≲ 10 km s − 1 Kim, Kim, & Ostriker 2018

  18. ORIGIN OF STAR CLUSTERS DIRECT RADIATION PRESSURE ▸ Radiation force > gravitational force on any gas column with Σ < Σ crit = (L/M) / 4 𝛒 Gc ~ 300 M ⨀ pc − 2 (Fall+ 2010) ▸ In a turbulent medium with a PDF of Σ ’s, low Σ regions ejected even if mean Σ > Σ crit (Thompson & Krumholz 2016) ▸ Net effect is to eject ~50% of mass for Σ ≲ 10 Σ crit Wibking+ 2018

  19. ORIGIN OF STAR CLUSTERS 30 Dor (Lopez+ 2011) Blue = x-ray, green = Ha, red = 8 μ m MASSIVE STAR WINDS Contours = CO ▸ Key issue with winds is leakage: how much hot gas escapes without exerting significant forces? ▸ Can measure directly by x-rays ▸ Compare to other pressures: P dir − 7 P IR photoionized gas (from radio free- P HII free), direct radiation (from log P (dyn cm − 2 ) − 8 P X bolometric luminosity), IR radiation (from dust SED) − 9 ▸ Winds not observed to be dominant − 10 1 2 10 10 R (pc) Figure 11. All pressures vs. radius from the center of R136. Regions with

  20. ORIGIN OF STAR CLUSTERS SUPERNOVA FEEDBACK ▸ First SNe do not explode until ≳ 4 Myr after star formation ▸ Dynamical time is 4 Myr for densities n ≈ 100 cm − 3 ; at ε ff = 1%, 50% of gas used before first SN if n ≳ 3 x 10 5 cm − 3 ▸ Thus SNe probably only important for SF regulation in low- density regions — this may provide the boundary between clustered and non-clustered SF (Kruijssen 2012)

  21. ORIGIN OF STAR CLUSTERS UNBINDING THE STARS: SUMMARY AND PROSPECTS ▸ Different feedback mechanisms suggest different thresholds separating bound and unbound stars: ▸ Photoionization : escape speed, v esc ≈ 10 km s − 1 ▸ Radiation pressure : surface density, Σ ≈ 3000 M ⊙ pc − 2 ▸ Winds : ??? ▸ Supernovae : density (free-fall time), n ≈ 10 5 cm − 3 ▸ At present not clear how to differentiate between these mechanisms; dependence of cluster demographics on environment may provide a clue (c.f. Adamo’s talk)

  22. THE IMF Figure 3. Theorist who has been asked to explain the IMF.

  23. ORIGIN OF THE IMF THE OBSERVED IMF ▸ In all resolved stellar populations, IMF is a power law at high mass with a turnover at lower mass ▸ Some evidence that the turnover may vary weakly with environment: ▸ Near Galactic center (Hosek+ 2019) ▸ In early-type galaxies (van Dokkum & Conroy+ 2010, Cappellari +2012) ▸ Other claims (IMHO) mostly unconvincing Data: Bastian+ 2010 Plot: Krumholz 2015

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