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4.5Galaxy formation and Evolution


Houjun Mo (UMASS), Xiaohu Yang (SHAO), Yipeng Jing (SHAO)
Overview of galaxy formation in the CDM

There is now much evidence that we live in a flat universe dominated by Cold Dark Matter (CDM) with a total energy density 0~1, a total matter density m,0~0.3, a baryon density B,0~0.025h-2, a Hubble constant (in units of 100 km/s/Mpc) h~0.7, a power-law index of initial perturbation n~1, and an amplitude of the perturbation power spectrum, as specified by the rms of the perturbation field smoothed in spheres of a radius 8Mpc/h, 8~0.85. This `standard' CDM model has been very successful in explaining a variety of observations, such as temperature fluctuations in the cosmic microwave background, the clustering of galaxies on large scales, and the clustering of the Lyman- forest at high redshift (e.g. Spergel et al. 2007 and references therein).


In this paradigm, galaxy formation is believed to be a two-stage process (e.g. White & Rees 1978). First, small perturbations in the density field believed to originate from quantum fluctuations in the inflaton, grow and collapse to give rise to a population of virialized dark matter halos. Second, the baryonic mass associated with these halos accumulates at the halo centers via cooling and cold flows, causing the baryonic densities to become sufficiently high that star formation transforms the baryonic gas into dense aggregates of stars, namely galaxies. Because of the hierarchical nature of structure formation in a CDM cosmogony, dark matter halos merge, giving rise to halos containing multiple galaxies (e.g. clusters), and to galaxy-galaxy mergers that are believed to be the main formation channel of elliptical galaxies.
The first stage of this process, the formation and virialization of dark matter halos, has been studied in great detail using the (extended) Press-Schechter formalism (e.g., Press & Schechter 1974; Bond et al. 1991; Lacey & Cole 1993), spherical and ellipsoidal collapse (e.g., Gunn & Gott 1972; Fillmore & Goldreich 1984; Bertschinger 1985; Sheth, Mo & Tormen 2001; Lu et al. 2006) and, most importantly, numerical simulations (e.g., Efstathiou et al. 1985; Navarro, Frenk & White 1997; Bullock et al. 2001a,b; Springel et al. 2005; Maccio et al. 2007). These studies have provided us with an accurate description of the properties of the CDM halo population, such as their mass function, spatial distribution, formation histories, and internal structure. This can be considered the backbone for the formation of galaxies.
The second stage of the galaxy formation process is far less established, mainly because the baryonic processes involved (cooling, star-formation and feedback) are poorly understood. Although great progress has been made in the past two decades, the theory of galaxy formation and evolution still faces several outstanding problems (see Primack 2009 for an up-to-date review). For example, it remains challenging to fit the faint-end slope of the galaxy luminosity function (e.g. Benson et al 2003; Mo et al. 2005), and the models typically predict disk rotation velocities that are too high, unless adiabatic contraction and/or disk self-gravity are ignored (e.g. Cole et al. 2000; Dutton et al. 2007). In addition, the models have problems matching the evolution of the galaxy mass function with redshift (e.g., De Lucia & Blaizot 2007; Somerville et al. 2008; Fontanot et al. 2009), and typically overpredict the red fraction of satellite galaxies (Baldry et al. 2006; Weinmann et al. 2006; Kimm et al. 2009; Liu et al. 2009). There are three main reasons that underly these problems. First and foremost, it is more than likely that current models miss some vital ingredients and/or the `recipes' used do not properly capture the underlying physics. Secondly, it has recently become clear that the data used to constrain the models leaves significant degeneracies in the model parameters that have thus far not been sufficiently explored (Henriques et al. 2009; Liu et al. 2009; Lu et al. 2009). Thirdly, some of the outstanding problems may actually reflect inconsistencies in the data itself. For example, it has been pointed out that the observed evolution in the stellar mass function is inconsistent with the observed cosmic star formation history (Fardal et al. 2007; Gilmore et al. 2009).
As is the case in virtually every field in science, in order to make progress we need more and better data. During the last decade, there has been a dramatic increase of data on the nearby galaxy population, mainly with the completion of large spectroscopic galaxy redshift surveys, such as the Sloan Digital Sky Survey (SDSS; York et al. 2000; Stoughton et al. 2002) and the 2-degree Field Galaxy Survey (2dFGRS; Colless et al. 2001). Although some spectroscopic redshift surveys out to z~1 have recently become available as well, such as DEEP2 (Davis et al. 2003) and zCOSMOS (Lilly et al. 2007), these surveys are much smaller than their low-redshift counterparts. At redshifts significantly higher than one, very limited spectroscopic data of the entire galaxy population is currently available.
With TMT, deep spectroscopic data will be possible, allowing us to study the galaxy population, its relation to the dark matter component, and the properties of the gas reservoir for galaxy formation for the entire history of the universe. It will allow us to probe the evolution of galaxy mass function up to redshift z~2, to model the mass distribution in nearby galaxies with unprecedented precision, to probe the chemical evolution of galaxies to redshift beyond z~1, to probe the gas state and distribution span a large redshift ranges using QSO absorption lines, to probe the strong gravitational lensing systems to redshift z~1.5, search for the highest redshift galaxies, etc. Below we will address in detail these science cases for TMT.

References:


  1. Baldry I. K., Balogh M. L., Bower R. G., Glazebrook K., Nichol R. C., Bamford S. P., Budavari T., 2006, MNRAS, 373, 469

  2. Benson A. J., Bower R G., Frenk C. S., Lacey C. G., Baugh C. M., Cole S., 2003, ApJ, 599, 38

  3. Bertschinger E., 1985, ApJS, 58, 39

  4. Bond J. R., Cole S., Efstathiou G., Kaiser N., 1991, ApJ, 379, 440

  5. Bullock, J. S., Kolatt, T. S., Sigad, Y., Somerville, R. S., Kravtsov, A. V., Klypin, A. A., Primack, J. R., & Dekel, A. 2001a, MNRAS, 321, 559 (B01)

  6. Bullock, J. S., Dekel, A., Kolatt, T. S., Kravtsov, A. V.,Klypin, A. A., Porciani, C., & Primack, J. R. 2001b, ApJ, 555, 240

  7. Cole S., Lacey C. G., Baugh C. M., & Frenk C. S., 2000, MNRAS, 319, 168

  8. Colless, M., et al. 2001, MNRAS, 328, 1039

  9. Davis M., et al., 2003, SPIE, 4834, 161

  10. De Lucia G., Blaizot J., 2007, MNRAS, 375, 2

  11. Dutton A.A., van den Bosch F.C., Dekel A., Courteau S., 2007, ApJ, 654, 27

  12. Efstathiou, G.; Davis, M.; White, S. D. M.; Frenk, C. S., 1985, ApJS, 57, 241

  13. Fardal M.A., Katz N., Weinberg D.H., Davé R., 2007, MNRAS, 379, 985

  14. Fillmore J.A., Goldreich P., 1984, ApJ, 281, 1

  15. Fontanot F., De Lucia G., Monaco P., Somerville R.S., Santini P., 2009, MNRAS, 397, 1776

  16. Gilmore R.C., Madau P., Primack J.R., Somerville R.S., Haardt F., 2009, MNRAS, 399, 1694

  17. Gunn J.E., Gott J.R., 1972, ApJ, 176, 1

  18. Henriques B.M.B., Thomas P.A., Oliver S., Roseboom I., 2009, MNRAS, 396. 535

  19. Kimm, T. et al., 2009, MNRAS, 394, 1131

  20. Lacey C., Cole S., 1993, MNRAS, 262, 627

  21. Lilly S. J., et al., 2007, ApJS, 172, 70

  22. Liu L., Yang X., Mo H.J., van den Bosch F.C., Springel V., 2009, in preparation

  23. Lu Y.; Mo H. J., Katz N., Weinberg M.D., 2006, MNRAS, 368, 1931

  24. Lu Y., et al., 2009, in preparation

  25. Macciò A.V., Dutton A.A., van den Bosch F.C., Moore B., Potter D., Stadel J., 2007, MNRAS, 378, 55

  26. Mo, H. J., Yang, X., van den Bosch, F. C., & Katz, N. 2005, MNRAS, 363, 1155

  27. Navarro J. F., Frenk C. S., White S. D. M., 1997, ApJ, 490, 493

  28. Press W. H., Schechter P., 1974, ApJ, 187, 425

  29. Primack J.R., 2009, NJPh, Volume 11, Issue 10, pp. 105029

  30. Sheth, R. K., Mo, H. J., & Tormen, G. 2001, MNRAS, 323, 1

  31. Somerville R.S., Hopkins P.F., Cox T.J., Robertson B.E., Hernquist L., 2008, MNRAS, 391, 481

  32. Spergel D. N., et al. 2007, ApJS, 170, 377

  33. Springel, V., et al. 2005, Nature, 435, 629

  34. Stoughton, C., et al. 2002, AJ, 123, 485

  35. Weinmann S. M., van den Bosch F. C., Yang X., Mo H. J., Croton D. J., Moore B., 2006b, MNRAS, 372, 1161

  36. White S. D. M., Rees M. J., 1978, MNRAS, 183, 341

  37. York, D. G., et al. 2000, AJ, 120, 1579



4.5.1Evolution of galaxy luminosity/mass function


Xiaohu Yang (SHAO), Houjun Mo (UMASS), Yipeng Jing (SHAO)
Key questions:

1. Can one accurately measure the luminosity (stellar mass) functions from low to high redshifts, especially their faint end behaviours?

2. What is their evolutionary trend?

3. What if separated into different colours and morphologies?

4. Can one obtain the luminosity (stellar mass) functions of galaxies in groups and clusters down to very faint (low mass) end, i.e., their environment dependence?
Introduction:

In the current paradigm of galaxy formation, galaxies are formed within cold dark matter halos, i.e. small galaxies in small halos form first, while massive galaxies in massive halos form later. However, observations show that massive galaxies already formed at redshift z~2, and most of the very small galaxies are actually newly formed. This is the so called ‘anti-hierarchical’ problem. To answer this question one may first have a robust measure of the luminosity (stellar mass) functions of galaxies at different redshifts. The luminosity (stellar mass) function describes the average number density of galaxies of given luminosities (stellar masses) in the universe. It tells us the total stars that formed at different epoch of the universe. However, because of the survey magnitude limit, low luminosity galaxies can only be observed at low redshift. To get a clear picture of galaxy formation, any efforts in the accurate measurement of luminosity functions to the very faint end at high redshift are always appreciated. The unprecedented observation ability of TMT surely will promote the research capability in this subject.


Main science areas:
1. Low mass end behaviour of luminosity (stellar mass) functions: from low to high redshifts

In the local Universe, thanks to the large sky coverage and highly completed observations, e.g., by SDSS, we are now able to measure the luminosity function of galaxies to the very faint end [1]. One of the major problems facing models of galaxy formation, however, is that cold dark matter models in general predict larger numbers of low-mass galaxies than locally observed [2]. There are a number of mechanisms have been proposed to suppress the star formation in small halos, e.g., the UV background radiation, the SN and other feedbacks, e.g., the preheating. These processes have different impact on the star formation in small halos at different redshift. Thus a key step to answer this question is to have robust observational measurements of the faint (small) galaxies at high redshifts (e.g. z~3). However so far at higher redshifts, most of the luminosity functions are obtained from photometric redshift surveys where systematic error can be large, or mainly for a specific population of galaxies, e.g., Lyman break galaxies, star forming galaxies or luminous red galaxies.

The TMT/WFOS provides highly multiplexed, moderate resolution, slit spectroscopy in the optical window (0.31– 1m). It is optimal for obtaining identification-quality spectra of the faintest galaxies, and will provide us the opportunity to measure the luminosity function to redshift z~2. At higher redshift, TMT/IRMS may be used: since some of the oldest and most massive galaxies present at redshifts z > 2 are either heavily obscured by dust, or have little or no current star formation, so that they may only be observed in the near-IR (there is no rest-UV flux).
2. Low mass satellite galaxies in groups and clusters

Since low mass satellite galaxies in groups and clusters were central galaxies of small halos before their accretion into the massive halos, thus their population contains both the information about the star formation in small galaxies and halos at higher redshift and their later evolution processes in the massive host halos. Combing the observations of the low mass field galaxies at high redshift, one can probe the evolution of satellite galaxies [3].

Although there are already quite a number of observational work regarding low mass galaxies in clusters, most of them are based on the photometric redshift data. Studies show that the low mass end slope of the cluster galaxies is about -1.3 to -1.4, much steeper than the field galaxies, and varies between individual clusters. It is worth noting that deriving luminosity functions from photometry alone requires background subtraction, an uncertain procedure that may bias one’s estimates toward steep slopes. Popesso et al. [4] have used statistical background subtraction on the photometric catalog to measure the optical luminosity function around X-ray clusters without recourse to determining redshifts and found very steep low mass end slopes -1.6 to -2.1. Using the SDSS observation, Yang et al. have obtained a low mass end slope ~ -1.6 for the stellar mass function of galaxies in clusters [5]. This indicate that at higher redshift, the over abundant problem of small galaxies may be less severe. Again, because of the current shallow observation, these constraints are only carried for the galaxies in the local Universe. It will be a very good project for TMT/WFOS to push this measurement to high redshift z~2.
3. Central massive galaxies in groups and clusters
Group and cluster halos are formed by the merger of smaller halos. The mass of the central galaxies formed within them thus should be an ever increasing function as the increase of the host halo mass. However, observations show that, according to the high mass end luminosity function of galaxies, the most massive cluster galaxies have not grown at all after redshift z~2. Although AGN feedbacks in clusters may prevent the star formation in central massive galaxies, the merge of satellite galaxies into central galaxies will still raise their masses. Before try to solve this problem one shall have a better understanding of the structure, size and luminosity of most massive galaxies at different redshifts. As pointed out in recent studies, there are a significant number of diffused stars around the cluster BCGs, e.g., central galaxies we observed contain only 10% to 20% stars that are really associated with the them [6]. In such a scenario, there is no ‘anti- hierarchical’ problem anymore.

The TMT/IRIS integral-field spectroscopy over contiguous regions can provide near-IR spectral information on physical scales as fine as 50 – 70 pc at any redshift in the range z = 1 – 6. Together with the high resolution deep image of most massive galaxies either observed by LSST, KDUST or other resources, will provide us the opportunity to have a better decomposition of the total stars that associated with them to high redshift z~6 depending on the quality of the image.


4. Luminosity functions for galaxies of different colour, morphology and spectral types

Galaxies of similar masses at the same redshift may still differ in their colours, spectra, morphologies, etc. These quantities hold important information regarding the status of the galaxies, e.g., their ages, gas reservoirs, star formation rates, evolution histories, etc. Luminosity functions for galaxies of different colour, morphology and spectral types in the local Universe has been carried out for almost all the large redshift surveys, e.g., in 2dF [7] and SDSS [8]. Obviously in the TMT observation, such kind of measurement can be carried for galaxies at higher redshifts. Combined with high resolution AO imaging and redshift measurement, one may also investigate the evolution of Hubble consequence.

These measurements can be used in semi-analytical models to constrain the galaxy formation processes and various feedbacks to higher redshifts, or adopted by the conditional luminosity function models to constrain the colour dependent relation between galaxies and dark matter halos.

Possible TMT programs:


  1. Together with the high resolution AO imaging provided by other resources like CFHT, Subaru, LSST or KDUST, TMT can be used to trace the morphological studies of galaxies to high redshift and to understand how the Hubble consequence arise.

  2. A few deep pencil beam surveys of galaxies to high redshifts with highly completed spectroscopic observations carried out using WFOS and IRMS are needed for the accurate luminosity function measurements to the very faint end.

  3. Spectroscopic measurements for those potential member galaxies at the locations of some candidate groups and clusters which will be identified from LAMOST or BIGBOSS project.


China’s strengths and weakness in this area:

There are already quite a number people and groups working in this area, at SHAO, NAOC, USTC, PMO, and TJNU. In theoretical modelling, image processing, spectra analysis of galaxies, we are already internationally competitive. Our weakness is the lack of the first hand observational data and quite weak in building/running the state-of-the-art facilities. In addition, we do not have telescope which can provide us the high resolution wide field image, unless the KDUST is launched.



We still need many more students or stuff members that are willing to deal with those raw data, doing image processing, spectroscopic analysis etc.
References:

  1. Blanton M. R., Lupton R. H., Schlegel D. J., Strauss M. A., Brinkmann J., Fukugita M., Loveday J., 2005, ApJ, 631, 208

  2. Mo H.J., Yang X., van den Bosch F.C., Katz N.S., 2005, MNRAS,363, 1155

  3. Yang X., Mo H.J., van den Bosch F.C., 2009, ApJ,693, 830

  4. Popesso P., Böhringer H., Romaniello M., Voges W., 2005, A&A, 433, 415

  5. Yang X., Mo H.J., van den Bosch F.C., 2009, ApJ,695, 900

  6. Gonzalez A. H., Zaritsky D., & Zabludoff A. I. 2007, ApJ, 666, 147

  7. Madgwick D.S, et a., 2002, MNRAS, 333, 133

  8. Nakamura O., Fukugita M., Yasuda N., Loveday J., Brinkmann J., Schneider D.P., Shimasaku K., SubbaRao M., 2003. AJ, 125, 1682

4.5.2Probing the evolution of galaxies with kinematic studies


Zuhui Fan (PKU)
Key questions:

  1. What are the kinematic properties of galaxies of different types in clusters of galaxies?

  2. What are the environmental effects on the transformation of galaxies between different types, and possible kinematic signatures of different formation mechanism of red sequence galaxies in clusters?

  3. How do the Tully-Fisher relation for rotation dominated galaxies and fundamental plane for velocity dispersion dominated galaxies evolve as a function of redshift?


Introduction
From the evidence of the existence of dark matter to the discovery of the Tully-Fisher relation for spiral galaxies and the Fundamental Plane for elliptical galaxies, kinematic studies have played important roles in our studies of the formation and evolution of large-scale structures in the Universe. Concerning gravities, the kinematic properties of dynamical tracers of a galaxy depend on its mass distribution, and thus are excellent probes in studying the dark matter distribution of its host halo [1]. Furthermore, as galaxies evolve, the kinematics of the galaxies are expected to change accordingly. Therefore in addition to photometric and spectroscopic information, kinematic analyses can provide important clues in understanding the physical mechanism underlying the galaxy evolution. The recent advances in 3D spectroscopic observations have shown the exciting potentials in probing relatively high redshift galaxies kinematically [2,3]. The much larger light collecting area of TMT comparing to the existing facilities offers an excellent opportunity for us to study detailed kinematics of high redshift galaxies, which in turn will improve greatly our knowledge about how galaxies are shaped during their evolutionary history.
Main science areas


  1. Kinematic studies of lening galaxies in conjunction with strong lensing studies

Kinematic studies offer important complementary information to strong lensing studies. The joint analyses of the two can provide much better constraints on the mass distribution of the lensing galaxies, and further shed lights on probing the nature of dark matter particles. Meanwhile, the dynamical evolution of the galaxies, such as the evolution of the Tully-Fisher relation and the Fundamental Plane can be probed for lensing galaxies up to high redshift z~2 with much higher signal-to-noise than unlensed galaxies. This will be an integrated part of the strong lensing studies with TMT (see 4.5.5).




  1. Kinematic studies of galaxy transformations in clusters of galaxies.

While majority of the knowledge is currently obtained from the photometric observations of light distribution and color information, and the spectroscopic studies concerning physical processes related to star formation, it has been realized that kinematic studies can provide additional and important complementary information in understanding the physics behind the galaxy evolution. One of the most notably example is the discovery of large disks around high redshift star forming galaxies from 3-D spectroscopic analyses [2]. For nearby galaxies, the SAURON project has done extensive integral field spectroscopic studies, aiming at understanding the formation and evolution of elliptical and S0 galaxies from the kinematic point of view. It is shown that kinematically, these red galaxies can be divided into two categories of fast rotators and slow rotators. Some elliptical galaxies can be fast rotators. To some extent, these kinematic differences may reflect the differences in their formation process more directly than that of the visual classifications purely based on light distribution of images [4]. For high redshift galaxies, such detailed kinematic studies regarding the galaxy transformation are less explored due to the limited observing power of the current facilities. TMT will be superb in making up this shortage.


Particularly, TMT can target at clusters of galaxies. It is well known that clusters of galaxies nurture the transformation of their residing galaxies, and thus are the best ones to be investigated to probe the evolutionary path of galaxies [5]. Many important ‘downsizing’ related phenomena, such as the morphology-density relation, the color-magnitude relation for red sequence galaxies, the deficiency of faint red galaxies in high redshift clusters comparing to that in local ones, were revealed firstly from the studies of clusters of galaxies of different masses and at different redshifts [6,7]. Extending the observations to the surrounding area of a massive cluster can also allow us to probe the environmental effects on galaxy evolution at different conditions, from field, to group and to high density environments [8]. The main questions we particularly concern here include when and where the star formation activity is efficiently suppressed and the galaxy starts its journey to reach the red elliptical end; How the morphology of a galaxy changes during its evolution; the possible different mechanisms involved in the formation of luminous red galaxies and the formation of the faint red galaxies. Besides the ability that TMT can detect fainter galaxies, red or k+a, it can make detailed kinematic maps for a subsample of galaxies of different types at different places around clusters. It is expected that different processes involved in galaxy transformations, such as major mergers, minor mergers, or interactions with intracluster medium, should result distinctly kinematic signatures. Therefore such kinematic information from TMT will improve our understanding on the galaxy transformation tremendously.
Possible TMT programs:
The Spitzer Adaptation of the Red-sequence Cluster Survey (SpARCS) has yielded hundreds of z >1 cluster candidates [9]. Potential clusters for TMT observations can be chosen from this catalogue. As examples, SpARCS J163435+402151 and SpARCS J163852+403843 are the two spectroscopically confirmed clusters in northern hemisphere ([10], see Figure 4 and Figure 5). The following two figures are taken from [10]). The redshifts of the two clusters are z=1.1798 and z=1.1963, respectively. The corresponding masses are ~1014 Msun and 2x1014 Msun. At redshift z ~1.2, the angular extend of of a cluster including surrounding regions is about a few arcminutes, and the light distribution of a typical galaxy is ~1.2 arcsecond (10kpc). They are ideally suited to the observations of IRMS and IRIS (imaging and IFU) mounted on TMT. Much larger number of faint galaxies are expected to be detected with TMT in comparison with current 10m-level observations, which will help to understand the problem of the deficiency of red galaxies at faint end. It will also be very important to detect faint k+a galaxies to learn the evolutionary path from a blue galaxy to a red one. The current observations seem to see fewer k+a galaxies than expected, indicating some channels other than through k+a phase for galaxy evolution might be needed [11]. TMT can go much fainter magnitudes, and will help pin down the problem in a much more solid ground. Kinematic mappings are needed for a subsample of galaxies of different types (blue, k+a, S0 and ellipticals) and at different densities within the observed field. It is expected that such kinematic observations will provide us a comprehensive picture about the transformation of galaxies in clusters of galaxies, so that to improve considerably our knowledge on the underlying physics.


Figure 4: Left: Rz ~ 3.6 μm color composite of the cluster SpARCS J163435+402151 at z = 1.1798. The R and z-images have been convolved to match the 3.6 μm PSF. The FOV of the image is ∼3.5 arcmin across. Right: same as left panel but with spectroscopically confirmed cluster members marked as white squares and spectroscopically confirmed foreground/background galaxies marked as green circles. Taken from [10].





Figure 5: Same as Figure 4, but for cluste SpARCS J163852+403843 at z=1.1963. The FOV of the image is 4.5 arcmin across. Taken from [10].


China's strength and weakness
There are a handful of people working in this field, and having experiences in IFU analyses. Numerical simulations to explore the kinematic signatures related to different physical processes can be pursued in China or through international collaborations. Kinematic studies are starting, but need to be strengthened considerably.
References:

[1] Binney, J., Tremaine, S. 2008, Galactic Dynamic, 2nd edition, Princeton University Press

[2] Genzel, R. et al. 2006, Nature, 442, 786

[3] Wright, S. A. et al. 2009, ApJ, 699, 421

[4] Emsellem, E. Et al. 2007, MNRAS, 379, 401

[5] White, S.D.M. et al. 2005, A&A, 444, 36

[6] De Lucia, G. et al. 2007, MNRAS, 374, 809

[7] Tanaka, M. et al. 2008, A&A, 489, 571

[8] Patel, S. G. et al., 2009, ApJ, 694, 1349

[9] SaARCS: http://www.faculty.ucr.edu/~gillianw/SpARCS/

[10] Muzzin, A. et al. 2009, ApJ, 698, 1934

[11] De Lucia et al. 2009, arXiv: 0907.3922



4.5.3Chemical evolution of galaxies


Chenggang Shu (SNU), Xu Kong (USTC)
Key questions:


  1. How do star formation and chemical evolution of high-z bright galaxies proceed?

  2. What are the early stages of galaxy formation and chemical evolution?

  3. How do chemical enrichments take place in quiescent objects and what is the enrichment history of the inter-galactic and intra-cluster media (IGM/ICM)?


Introduction:
Chemical abundances of galaxies provide us important clues to the evolution of galaxies. They are crucial to understanding the current star formation activities, star formation history, gas processes including inflows and outflows, and the environments of galaxies, which are of primary interests of galaxy formation and evolution theories.
From observational point of view, there are two ways to obtain the chemical information of galaxies. The first is by observing galaxies are intrinsically bright so that their spectrum can be easily obtained. The second (indirect) method, is by studying absorption features of bright background sources induced by intervening galaxies that are by themselves too faint to observe directly.
Currently, there have been many observational results available, mainly for bright galaxies in the local universe. But we still lack sufficient and accurate data for galaxies at redshift z>1 and faint galaxies at low z (such as low surface brightness galaxies) to establish a global picture of the chemical (hence the dynamical) evolution of galaxies in the hierarchical structure formation picture (see the Introduction). TMT, with its large aperture and high-resolution, will play a key role in this field in many different ways.
Main science areas:


  1. The chemical evolution of high-redshift “bright” galaxies

“Color dropouts” has been a very successful method to find galaxies at high-z (Chapman et al 2005; Shapley et al 2005; van Dokkum et al 2006; Bouwens et al 2007; Casey et al 2009) as demonstrated by the pioneering work by Steidel at al (1995) for Lyman Break galaxies at z~3. Since these galaxies are active, they provide important clues to the chemical and dynamical evolution of present day massive galaxies. For example, several studies have been outflows of several hundreds km/s are common with important implications for chemical enrichment of the intergalactic medium. Unfortunately, few observations have been done and no systematic sample with chemical information are available, except a few that have been gravitationally lensed (CB58, Pettini et al. 2001). Currently it is difficult to measure their chemical composition because they are too faint (usually R~23.5) to obtain a sample of high resolution spectra even by Keck (Teplitz et al 2000; Matsuoka et al 2009). Since thousands of these galaxies have already been identified in imaging survey, a relatively complete sample with chemical information of these galaxies can be establish by TMT down to magnitude R~25.5, which is very important to understanding their chemo-dynamic evolution.




  1. Star formation and gas process of emission-line galaxies at z>5

As mentioned above, there are many emission-line galaxies found at very high redshifts (z>5), e.g., Lyman-alpha emitters (Willis & Courbin 2005; Kovac et al 2007; Stanway et al 2007; Fernandez & Komatsu 2008; Ota et al 2008; Goto et al 2009; Overzier et al 2009; Taniguchi et al 2009). Although it is still difficult to have an unbiased sample, they display very special physics properties such as active star formation activities, diverse morphologies, high velocities in kinematics, ionization stages, etc, which are important to understanding the early stage of galaxy formation and how the universe becomes re-ionised. Currently both ground-based and space telescopes are not easy to obtain high signal-to-noise ratio spectra of these objects in order to probe their chemical compositions and kinematics, TMT will be a suitable telescope to do the required deep observations.




  1. Chemical evolution of faint galaxies

From the modern cosmological theory and from observations, there exist small galaxies whose number is several orders of magnitudes larger than ordinary galaxies (such as the Milky Way). These faint galaxies have low star formation and other physical activities so that the chemical evolution should be slow. Low surface brightness galaxies (LSBs) (Roberts et al 2004; Kuzio et al 2006; Coccato et al 2008; Pizzella et al 2008; Adami et al 2009) and QSO absorption systems (such as Ly-alpha forests and damped Ly-alpha systems) are typical (Rao & Turnshek 1998; Chen et al 2000; Pettini et al 2001; Chen & Lanzetta 2003; Pettini & Pagel 2004; Bowen et al 2005; Wild et al 2006; Curran et al 2007, 2009; Pettini et al 2008). Since they are the neutral gas reservoir in our universe and relatively quiescent, they provide good laboratory for us to understanding the physical prescriptions we adopt for bright galaxies. Nerveless, because of their relatively shallow gravitational potential wells, they are the dominating sources that may provide most of the metals to the IGM/ICM metal enrichments. As one of the key projects of HST, QSO absorption systems have been observed with chemical compositions and kinematics data available. But we are still far from fully understanding their evolution especially the chemical evolution. For LSB galaxies, there are still very few observations available. TMT can provide us a relative complete sample of LSBs and more accurate measurements of the QSO absorption systems (such as the internal kinematics, chemical abundances and dust properties).


Possible TMT Program


  1. A spectroscopic survey to establish a complete sample of chemical abundance of high-redshift bright galaxies and a detailed study of star formation and chemical evolution for these galaxies.

  2. A detailed spectroscopic study of the Lyman-alpha emitters found at z>5 to provide their chemical compositions and kinematics. Combining observations in other wavelengths such as radio, sub-mm, this sample can be used to investigate the early evolutionary stage of galaxies and probe the re-ionization epoch.

  3. An ambitious program to accurately measure the kinematics and metallicity of LSBs and QSO absorption systems (especially damped Ly-alpha systems) using TMT and to investigate their chemo-dynamic evolution (hence the enrichments of IGM/ICM).



Chinese strengths and weakness in this area:
There are several groups at NAOC, SHAO, PKU, USTC and SNU, working in this field. The research activities are mainly theoretical (numerical simulations and semi-analytical studies), and internationally competitive. Form the observational side, few people are familiar with the data reduction. So, more expertise in this area is urgently required; joint student training with internationally-leading centers will be particularly useful.
References:


  1. Adami, C., Pello, R., Ulmer, M. P., et al 2009, AA, 495, 407

  2. Bowen, D. V., Jenkins, E. B., Pettini, M., Tripp, T. M., 2005, ApJ 635, 880

  3. Bouwens R. J., Illingworth, G. D., Franx, M., Ford, H., 2007, ApJ 670, 928

  4. Casey, C. M., Chapman, S. C., Beswick, R. J., et al, 2009, MNRAS 399, 121

  5. Chapman S. C., Blain, A. W., Smail, I., Ivison, R. J., 2005, ApJ 622, 772

  6. Chen, H-.W., Lanzetta, K. M., 2003, ApJ 597, 706

  7. Chen, H-.W., Lanzetta, K. M., Fernandez-Soto, A., et al, 2000, ApJ 533, 120

  8. Coccato, L., Swaters, R. A., Rubin, V. C., et al 2008, AA 490, 589

  9. Curran, S. J., Tzanavaris, P., Darling, J. K., et al, 2009, MNRAS accepted, (astro-ph/0910.3742)

  10. Curran, S. J., Tzanavaris, P., Pihlström, Y. M., Webb, J. K., 2007, MNRAS 382, 1331

  11. Fernandez, E. R., Komatsu, E., 2008, MNRAS 384, 1363

  12. Goto, T., Utsumi, Y., Furusawa, H., et al 2009, MNRAS accepted (astro-ph/0908.4079)

  13. Haberzettl, L., Bomans, D. J.,Dettmar, R.-J., Pohlen, M., 2007, AA 465, 95

  14. Haehnelt, M. G., Steinmetz, M., 1998, MNRAS 298, L21

  15. Kovac, K., Somerville, R. S., Rhoads, J. E., et al, 2007, ApJ 668, 15

  16. Kuzio de N., R., McGaugh, S. S., de Blok, W. J. G., Bosma, A., 2006, ApJS 165, 461

  17. Matsuoka, K., Nagao, T., Maiolino, R., et al 2009, AA 503, 721

  18. Overzier, R. A., Shu, X., Zheng, W., et al, 2009, ApJ 704, 5480

  19. Ota, K., Iye, M., Kashikawa, N., et al, 2008, ApJ 677, 120

  20. Pettini, M., Zych, B. J., Murphy, M. T., Lewis, A., Steidel, C. C., 2008, MNRAS 391, 1499

  21. Pettini, M., Pagel, B. E. J., 2004, MNRAS 348, L59

  22. Pettini, M., Ellison, S. L., Schaye, J., et al, 2001, ApSS 277, 555

  23. Pizzella, A., Corsini, E. M., Sarzi, M., et al 2008, MNRAS 387, 1099

  24. Rao, S. M.,Turnshek, D. A., 1998, ApJ 500, L115

  25. Roberts, S., Davies, J., Sabatini, S., et al 2004, MNRAS 352, 478

  26. Shapley, A. E., Steidel, C. C., Erb, D. K., et al 2005, ApJ 626, 698

  27. Stanway, E. R., Bunker, A. J., Glazebrook, K., et al 2007, MNRAS 376, 727

  28. Steidel, C. C., Pettini, M., Hamilton, D., 1995, AJ 110, 2519

  29. Taniguchi, Y., Murayama, T., Scoville, N. Z., et al 2009, ApJ 701, 905)

  30. Teplitz, H. I., Malkan, M. A., Steidel, C. C., et al , 2000, ApJ 542, 18

  31. van Dokkum P. G., Quadri, R., Marchesini, D., et al 2006, ApJ 638, L59

  32. Wild, V., Hewett, P. C., Pettini, M., 2006, MNRAS 367, 211

  33. Willis, J. P., Courbin, F., 2005, MNRAS 357, 1348



4.5.4The intergalactic medium


Renyue Cen (Princeton)
Key questions:

1. Where are the missing baryons and how do galaxies and the IGM interact?

2. How do we use the Lyα forest to obtain cosmological information?
Introducton:
In the remarkably successful standard cosmological model (Krauss & Turner 1995; Bahcall et al.1999; Spergel et al.2007) most of the mass-energy density in the universe is in dark energy and dark matter. At present neither of these two unknowns with the astronomically inferred amounts can be explained by fundamental theories. While the exact nature of dark matter and dark energy remains enigmatic, in the simplest models baryons and dark matter are tightly coupled on large scales under the common action of gravity, with the overall temporal evolution also depending on the nature of dark energy. Since the evolution of the intergalactic medium (IGM) is directly observable over a long timeline to high redshift, it potentially provides a powerful probe of dark matter and dark energy. In the past one and a half decade our understanding of the evolution of the IGM has been dramatically enhanced with steadily improving cosmological hydrodynamic simulations. Briefly stated, the evolution of the IGM is consistent with the growth of structure seen in the formation and distribution of galaxies. That is, gravitational instability plays the dominant dynamic role on large scales (r > 1 Mpc), while other physical processes, including hydrodynamics, microphysics and galaxy formation feedback, become increasingly important on smaller scales. Among notable successes, hydrodynamic simulations helped establish the current working theory for the Lyα forest (Cen et al.1994; Zhang et al.1995; Hernquist et al.1996; Miralda-Escude et al.1996) and have successfully predicted the existence the Warm-Hot Intergalactic Medium (WHIM; Cen & Ostriker 1999; Dave et al. 2001) to account for the missing baryons.
Main science areas:
1. Where are the missing baryons and how do galaxies and the IGM interact?
Most of the ordinary, baryonic matter, which altogether makes up about 10-20% of the total matter in the universe (as observed, for example, in clusters of galaxies), seems to be unaccounted for in the present-day universe. At the last scattering (z 1000) the latest cosmic microwave background experiments (Komatsu et al. 2009) indicate
Ωb,CMB(z 1000) (0.02265 ± 0.00059)h2 = 0.046 ± 0.001, (1)
where Ωb,CMB(z 1000) is the baryonic density in units of the critical density extrapolated to z = 0 and a Hubble constant h ≡ H0/(100km/s/Mpc) = 0.70 is adopted throughout. At redshift z = 23, the amount of gas contained in the Lyman  forest (Rauch et al.1997; Weinberg et al.1997) is
Ωb,Lyα(z = 23) 0.017h2 = 0.035, (2)
in units of the critical density extrapolated to z = 0. Independently, the observed light-element ratios (in particular, the deuterium to hydrogen ratio) in some carefully selected absorption line systems at z = 23, interpreted within the context of the standard light element nucleosynthesis theory, yield the total baryonic density (Burles & Tytler 1998; Kirkman et al. 2003)
Ωb,D/H(z = 23) = (0.019 ± 0.001)h2 = 0.039 ±0 .002, (3)
again in units of the critical density evaluated at z = 0. The agreement between these three completely independent measurements is remarkable. But, at redshift zero, after summing over all well observed contributions, the baryonic density appears to be far (by a factor of three) below that indicated by equations (1), (2) and (3) (e.g., Fukugita, Hogan, & Peebles 1997):
Ωb(z = 0)|seen = Ω HI H2Xray,cl 0.0068 0.011 (2σ limit), (4)
where Ω, ΩHI, ΩH2 and ΩXray,cl are the baryonic densities contained in stars, neutral atomic hydrogen, molecular hydrogen and hot X-ray emitting gas in rich cluster centers, respectively, in units of the critical density. Thus, unless three independent errors have been made in the arguments that led to equations (1), (2) and (3), there is a sharp decline of the amount of observed baryons from high redshift to the present-day; i.e., most of the baryons in the present-day universe are yet to be detected.

Cosmological hydrodynamic simulations suggest that a warm-hot intergalactic medium (“WHIM”) in the temperature range 1057 Kelvin may contain most of the “missing baryons” (Cen & Ostriker 1999; Dave et al. 2001). It is therefore of fundamental importance to probe this gas and make an accurate and reliable interpretation in the current cosmological context. The reality of the WHIM, at least the low temperature portion of it (T ≤ 106 K), has now been fairly convincingly confirmed by a number of observations from HST and FUSE, through the O VI λλ1032, 1038 absorption line doublet in the FUV portion of QSO spectra (e.g., Tripp & Savage, 2000; Danforth & Shull, 2008) and Ne VIII (e.g., Savage et al., 2006).



The fundamental link between galaxy formation and the IGM lies in the WHIM, which provides a conduit for exchange of matter and energy. This galaxy-IGM interaction is extremely complex and difficult to pin down theoretically. Therefore, mapping out the physical state of the ISM/IGM from central regions of galaxies to the WHIM regions of several hundreds of kpcs will be a key observational challenge in the next decade. A coordinated campaign to probe the multi-phase medium will be required that provides diagnostics for gas at different temperatures, from X-rays, UV to optical. TMT will play three keys roles on this. First, TMT will be able to detect galaxies to very low luminosities, which is important for associating interesting IGM features (such as metal enrichment) with responsible galaxies. Second, TMT will be able to provide a much denser sample of background quasars that will then provide an essentially 3-dimensional absorption grid of cold material (such as Mg II line) around galaxies, which, when combined with other complementary measures of warm gas by HST/COS and of hot gas by X-ray observations, will form a quantitative and much more complete picture of the galaxy-IGM interaction regions in the present universe. Third, TMT will be able to do map out the galaxy-IGM interaction essentially throughout the entire moderate redshift universe, for example, with C IV, O VI and other absorption lines. In summary, TMT will provide a panoramic view of the galaxy-IGM interaction history, which will help us understand the evolution of the IGM and formation of galaxies, and find the missing baryons.
2. How do we use the Lyα forest to obtain cosmological information?
The standard theory is that the observed Lyα forest is a natural consequence of the gravitational growth of small-scale density perturbations (Cen et al.1994; Zhang et al.1995; Hernquist et al.1996; Miralda-Escude et al.1996). TMT observations will provide the next quantum leap in the study of the Lyα forest, over what SDSS and Keck observations have provided us, in two ways. First, it will provide a much larger quasar sample than Keck has. Second, it will provide a quasar sample that will cover a larger redshift range and much higher spectral resolution than SDSS III will. Essentially, we will have a 3-dimensional Lyα forest as well as the forests for various prominent metal lines, such as C IV, N V and O VI lines, over the entire redshift range up to z 6. While numerous cosmological and astrophysical applications will be performed, we highight two important cosmological applications.
First, CMB experiments (e.g., WMAP and Planck) do not have the necessary leverage to precisely constrain the slope of the power spectrum, because of the lack of accurate normalization points at small scales. The Lyα forest flux distribution provides the only competitively accurate measurement of the matter ower spectrum at small scales (Croft et al.1999). The statistical accuracies to determine the amplitude, slope and curvature of the density power spectrum using Lyα forest from large SDSS QSO samples have reached unprecedented 1-3% level (e.g., Mandelbaum et al.2003), complementary to WMAP and in the future PLANCK. Thus, with Lyα forest observations by TMT and CMB observations one may be able to jointly nail down the matter power spectrum to a sub-percent level that may test inflationary theories (Seljak et al.2005).
Second, observations by Type Ia supernovae (e.g., Riess et al., 1998; Perlmutter et al., 1998; Astier et al., 2006) and Cosmic Microwave Background (CMB; (e.g., Komatsu et al., 2009)) both suggest an accelerating expansion of the universe, driven by the mysterious “dark energy”. Characterizing the nature of Dark Energy (determining its w — ratio of pressure to energy density) is perhaps the most exciting problem in cosmology today. Baryon oscillations are believed to be the method “least affected by systematic uncertainties” (Dark Energy task Force report: (Albrecht et al., 2006)). The baryonic acoustic oscillaton (BAO) in the early universe provides a unique and precise scale that should remain little changed with time until the present and can be used as a standard ruler, tightly constrained by the WMAP CMB observation. The overall expansion history of the universe depends on w. If one can measure the sizes of the universe at a few different redshifts precisely, one will be able to place important constraints on w. The extremely valuable improvement of the Lyα forest provided by TMT over what SDSS III BOSS survey is a much higher spectral resolution, a larger redshift coverage and a denser quasar sample. If expectation comes true, BOSS will be able to yield absolute distance measurements with statistical precision of 23% at z 2.5. TMT is likely to achieve significantly better constraints. Is w different from 1? TMT will help answer this fundamental question.
Possible TMT programs:


  1. TMT/WFOS observations of selected fields with known Lyman-break galaxies or quasars, to study the metal enrichment of the IGM, and to map the small-scale power-spectrum.

  2. TMT/HROS observations of selected quasars with very high resolutions.


China’s strengths and weakness in this area:
There are limited expertise (NAOC, SHAO, and USTC) in China in this important area for TMT. We need to significantly strengthen both in terms of observational expertise on large telescopes, and theoretical modelling. Joint PhD training with international centres of excellence in this area will be highly desirable.
References:


  1. Albrecht, A., et al. 2006, ArXiv Astrophysics e-prints, Report of the Dark Energy Task Force

  2. Astier, P. et al. 2006, A&A, 447, 31

  3. Danforth, C. W. & Shull, J. M. 2008, ApJ, 679, 194

  4. Komatsu, E et al. 2009, ApJS, 180, 330

  5. Perlmutter, S. et al. 1998, Nature, 391, 51

  6. Riess, A. G et al. 1998, AJ, 116, 1009

  7. Savage, B. D., Lehner, N., Wakker, B. P., Sembach, K. R., & Tripp, T. M. 2006, in Astronomical ociety of the Pacific Conference Series, Vol. 348, Astrophysics in the Far Ultraviolet: Five Years of Discovery with FUSE, ed. G. Sonneborn, H. W. Moos, & B.-G. Andersson, 363

  8. Tripp, T. M. & Savage, B. D. 2000, ApJ, 542

  9. Cen, R., & Ostriker, J.P. 1997, ApJ, 489, 7

  10. Cen, R., & Ostriker, J.P. 1999, ApJ, 514, 1

  11. Cen, R., Miralda-Escude, J., Ostriker, J. P., & Rauch, M. 1994, ApJ, 437, L9

  12. Croft, R.A.C., Weinberg, D.H., Pettini, M., Hernquist, L., & Katz, N. 1999, ApJ, 520, 1

  13. Danforth, C.W., & Shull, J.M. 2007, eprint arXiv:0709.4030

  14. Dave, R., Cen, R., Ostriker, J.P., Bryan, G.L., Hernquist, L., Katz, N., Weinberg, D.H., Norman, M.L., & O’Shea, B. 2001, ApJ, 552, 473

  15. Hernquist, L., Katz, N., Weinberg, D.H., & Miralda-Escude 1996, ApJL, 457, L51

  16. Kirkman, D., Tytler, D., Suzuki, N., O’Meara, J.K., & Lubin, D. 2003, ApJS, 149, 1

  17. Krauss, L., & Turner, M.S. 1995, Gen. Rel. Grav., 27, 1137

  18. Mandelbaum, R., McDonald, P., Seljak, U., & Cen, R. 2003, MNRAS, 344, 776

  19. Miralda-Escude, J., Cen, R., Ostriker, J. P., & Rauch, M. 1996, ApJ, 471, 582

  20. Rauch, M., Miralda-Escude, J., Sargent, W.L.W., Barlow, T.A., Weinberg, D.H., Hernquist, L., Katz, N., Cen, R., & Ostriker, J.P. 1997, ApJ, 489, 7

  21. Seljak, U. et al., 2005, PRD, 71, 103515

  22. Tytler, D., et al. 2004, ApJ, 617, 1



4.5.5Strong gravitational lensing


Shude Mao (Manchester/NAOC)
Key questions:


  1. How can we identify the highest redshift galaxies using strong lensing clusters?

  2. Are the flux ratio anomalies in gravitational lenses due to substructures?

  3. How do the internal structures of lensing galaxies evolve as a function of redshift out to z~1.5?

  4. What are the chemical abundances of Galactic bulge dwarf stars?


Introduction:

Strong gravitational lensing refers to the fact a background source is multiply imaged, strongly distorted or magnified by a foreground lens. Microlensing, multiply-imaged quasars/galaxies and giant arcs are manifestations of strong lensing by stars, galaxies and clusters respectively. Strong lensing has diverse applications [1], ranging from the discovery of extrasolar planets (with microlensing), determining the cosmological parameters (such as the Hubble constant from time delays), and mass distributions in the Milky Way, external galaxies and clusters. The determination of mass profiles for moderate redshift (z~0.5-1.5) galaxies is likely the most important application of strong lensing in the next decades. Notice that TMT, with its limited field of view, may not be very competitive in the area of weak lensing.


Main science areas:
1. The discovery of highest redshift galaxies

An effective way to search for high-redshift galaxies is to identify faint objects close to the critical curves where the galaxies are highly magnified. For example, systematic searches for gravitationally lensed Lyman break “dropouts” can be conducted via very deep imaging through foreground clusters. A recent survey undertaken with the Hubble and Spitzer space telescopes has yielded 10 z-band and two J-band dropout candidates beyond redshift 7 [2]. This method can be extended to TMT to search for the highest redshift galaxies, in particular IRIS and IRMS can be used to provide spectroscopic confirmations of these galaxies.


Such a systematic search may be attractive for another reason: if we can confirm the membership of the foreground cluster with LAMOST, then we can combine gravitational lensing and kinematics to constrain the cluster mass distribution, in addition to identify the highest redshift galaxies.
2. Substructures in lensing galaxies

Substructures are a generic prediction of the cold dark matter (CDM) hierarchical structure formation theory. In this theory, galaxies are surrounded by massive dark matter haloes. Big haloes are formed by the merging of smaller ones. In this process, the cores of smaller haloes often survive the tidal disruption and dynamical friction, which then manifest as subhaloes (substructures). The number of subhaloes appears to exceed the number of observed satellite galaxies in a Milky-Way type halo by a factor of ~10 (e.g. [3]). One solution is that many of the substructures may be dark due to the suppression of star formation, and so may escape detection from any light-based method.


Gravitational lensing provides a promising way to detect these since lensing does not depend on whether the lens is luminous or dark. In particular, substructures may affect flux ratios in lenses, which has been called “anomalous flux ratio problem.” A detailed study of the highest resolution simulation using AQUARIUS seems to indicate CDM models actually under-predict the substructures required by the CLASS survey (see [3] and references therein), although this under-prediction may be due to small number statistics (22 lenses in the survey).
Equally puzzling, many of the anomalous lenses seem to host faint luminous satellite galaxies. So far, these satellite galaxies (I~24.5) are too faint for spectroscopic observations even by KECK. So it is unclear whether they are associated with the main lens, or lie along the line of sight [4]. TMT will be able to securely determine the redshift of these faint galaxies and thus their nature. Such observations will not only solve the anomalous flux ratio problems, but also provide insights on the formation of satellite galaxies.

Evolution of dynamical properties in lenses out to z ~ 1.5

The HST lens survey SLACS have found ~100 new gravitational lenses. This sample, combined with kinematics from KECK, provides the strongest kinematical constraints at moderate redshift (out to z~0.7). A recent study found that these lensing galaxies are well modelled with singular isothermal spheres [5]. In the next decade, many large-area photometric surveys, using, e.g. Pan-STARRS and LSST, will discover orders of magnitudes more gravitational lenses. These new lenses can potentially reach redshift of 1.5 to 2.

An IRIS IFU survey of a representative sample of lenses out to z~1.5-2 will offer us a chance to have detailed studies of kinematics of lenses (extending the current limit of z~0.7), and thus provide key insights in how the mass profiles change as a function of redshift: does the isothermal sphere model still hold for these higher redshift lenses? The epoch of z~1.5 may be particularly interesting because of the significant star formation and AGN activities at this epoch (see Section 4.4.2) that may provide vital clues for the establishment of dynamical entities.

3. Spectroscopy of highly magnified lenses in the Galactic bulge

In the next decade, upgraded survey networks will discover several thousand microlensing events per year; most of these will be discovered in real-time. Some of these may reach a magnification as high as of ~3000. Target-of-opportunity observations of such highly lensed stars will make the TMT as a telescope with an effective aperture of ~1500m! Building on earlier attempts [6], KECK and Magellan high-resolution spectroscopies of microlensed targets already revealed potential surprises in the stellar evolution [7, 8], although the sample is still too small. TMT observations of highly microlensed stars may provide extremely high S/N ratio spectra for a sample of bulge stars. WFOS/IRMS can also obtain the spectra of many other stars within the field simultaneously, and thus establish a significant sample of stars with chemical abundance of faint dwarf stars (rather than mostly giants as in the current samples), potentially provide important clues about the different formation histories of the Galactic bulge and disk.



Possible TMT programs:

  1. A detailed study of a sample of cluster lenses at moderate redshift to search for lensed, very high redshift background galaxies; detailed membership classification (z~0.2) may be obtained with LAMOST.

  2. A spectroscopic survey of known anomalous flux ratio lenses with IRMS IFUs to obtain the kinematics of the central lens, and obtain redshifts of the faint luminous satellite galaxies. This will provide a definitive solution to the anomalous flux ratio problem.

  3. Target-of-opportunity observations of a sample of microlensed bulge stars in the Galactic centre to obtain extremely high S/N ratio spectra with IRMS/WFOS, which can be used to obtain detailed abundance patterns of faint stars in the Galactic centre.


China’s strengths and weakness in this area:

There are already several people working in this area at NAOC, PKU, SHAO and SNU. In theoretical (statistical) studies of galaxy-scale and cluster-scale lenses, we are already internationally competitive, although in observations, we still lag behind due to the lack of access to state-of-the-art observing facilities.

We still need to train more PhD students, especially in the area of detailed modelling of complex cluster lenses in order to identify highest redshift galaxies; some promising work in this area has been performed at SNU. Another area that we require substantially more expertise is in dynamical modelling that can combine integral field unit and gravitational lensing data (through either the Schwarzschild method or the made-to-measure method, see also Section 4.5.2).

References:


  1. Kochanek C. S., Schneider P., Wambsganss J. 2003, Gravitational lensing: strong, weak and micro. Saas-Fee Advanced Course 33.

  2. Richard J., Stark D. P., Ellis R. S., George M. R., Egami E., Kneib J.-P., Smith G. P., 2008, ApJ, 685, 705

  3. Xu D. D., Mao S., Wang J., Springel V., Gao L., White S. D. M., Frenk C. S., Jenkins A., Li G. L., Navarro J. F. 2009, MNRAS, 398, 1235

  4. Metcalf, B. 2005, ApJ, 629, 673

  5. Koopmans L. V. E. et al. 2009, ApJ, 703, L51

  6. Lennon D. J., Mao S., Fuhrmann K., Gehren T. 2006, ApJ, 471, L23

  7. Cohen J. G., Huang W., Udalski A., Gould A., Johnson J. A., 2008, ApJ, 682, 1029

  8. Cohen J. G., Thompson I. B., Sumi T., Bond I., Gould A., Johnson J. A., Huang W., Burley G., 2009, ApJ, 699, 66

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