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Simulation of High-z Dust Enrichment in Sub-mm Galaxies: Models and Survey Strategy

This study by H. Hirashita and T. Suwa from the University of Tsukuba focuses on simulating the dust enrichment in high-redshift sub-mm galaxies. The research covers topics such as sub-mm galaxies at high-z, N-body simulation models with dust evolution, results from the simulations, and strategies for survey observations. The study examines the relationship between sub-mm galaxies and optical samples, evolutionary scenarios, and the impact of dust content on star formation rates. By incorporating dust evolution models in dark halos and estimating luminosities, the research provides insights into the properties of galaxies at different redshifts.

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Simulation of High-z Dust Enrichment in Sub-mm Galaxies: Models and Survey Strategy

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  1. Simulation of High-z Dust Enrichment H. Hirashita (University of Tsukuba) T. Suwa (Univ. of Tsukuba)

  2. Contents • Sub-mm Galaxies at High-z • Models (N-body + Dust) • Results • Strategy for Survey Observation

  3. 1. Sub-mm Galaxies at High-z Luminosity function at 850 mm (Chapman et al. 2005) A lot of sub-mm luminous galaxies are found up to z ~ 3. z ~ 2.5 z ~ 1

  4. Relation with Optical Samples Number：Lya blobs Thick ○：with sub-mm ~ 5×1012 Lsun Geach et al. (2005) z = 3.1

  5. Galaxy Evolution Scenario in Optical Mori & Umemura (2006) Optical spectra evolve from Lya-emitter-like properties Lyman-break-galaxy-like ones. stars gas How about sub-mm galaxies? ⇒Necessary to include dust evolution.

  6. 150Mpc/h 2. Models (N-body + Dust) • N-body Simulation • LCDM model Cosmological Simulation • Box Size: (150Mpc/h)3 ⇔ 104 arcmin2 • Dust Evolution Model • Increase of Dust Content by SNe II • Evolution of Dust Optical Depth • Evolution of UV and FIR Luminosities • Dust evolution model is applied to dark halos in the simulation to estimate LIRand LUV

  7. Star Formation Rate SFR • SFR(t) = t/M0 exp(–t /) • t: Age of the dark halo • t: Star formation timescale (= R/vcir) • M0: available gas mass for star formation (eMgas) e = 0.1 (t > t) e = 0.5 (t < t) • The above SFR is applied to each halo. t t/t

  8. UV radiation IR radiation Dust grains (~0.1mm) Absorb UV Radiate IR Observer Massive stars 3～100MO LUV and LIR Estimation • LUV ∝ SFR(t) • LIR= (1-[1-exp(-dust)]/dust) LUV - dust: Optical depth of dust, ∝ Mdust/R2 -Mdust is increased by SNe II (0.4MO per SN) - Supernova rate ∝ SFR(t)

  9. 3. Results Data from Chapman et al. (2005) Our prediction at z ~ 3 z ~ 2.5 z ~ 1

  10. Lya Emitters with Sub-mm z = 3: sub-mm luminous Lya emitters (LIR > 5×1012Lsun) Lya emitters are selected by t < 2×108 yr.

  11. Results (LIR>1011LO) at z = 6 497 galaxies (LIR>1011LO) are found in (150Mpc/h)3

  12. Results (LIR>1011LO) at z = 10 30 galaxies (LIR>1011LO) are found in (50Mpc/h)3 ~1000arcmin2

  13. 4. Strategy for Survey Observation • Although the dust opacity is lower at z ~ 6, we can detect ~ 30 galaxies in a 100 arcmin2 survey.← Cosmic variance is large, so we should observe known clustering regions already observed in optical. • We could expect detection of a few z ~ 10 galaxies. (A survey at 220 GHz is favorable.)

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