Namrata Intel Trifold

A Spectral Analysis of the Chemical Enrichment
History of Red Giants in the Andromeda Galaxy Field
(M31) Versus its Dwarf Spheroidal (dSph) Satellites
Background
Big Picture Context
•Spiral galaxy similar to our own—results
applicable to Milky Way
Why dSphs?
65
•Small, less chemically
enriched than larger
galaxies, made up of
mostly older stars,
intact
,0
00
lig
ht
ye
ar
s
≈ 65,000 light years
• Small galaxies =
building blocks of
galaxy formation
• Outskirts of
M31—longer
shredding time /
longer memory
preservation
Metallicity graphs
(FeHphot vs. (V-I)0)
generated
Research conducted at UC Santa Cruz
under the guidance of Professor Puragra Guhathakurta and Dr. Evan Kirby
• External yet close-by vantage point—global
but detailed view of galaxy
Radius—20 kiloparsecs
Metallicity Distributions
By Namrata Anand
Why Andromeda?
Traditional view of M312
Methods, continued
Introduction
What are FeHphot
About this study
Galaxies are interesting organisms: they
move, change, grow, and, strangely enough,
consume. In a process known as galaxy
cannibalism, a dwarf satellite galaxy is drawn
towards a larger, more massive galaxy and
shredded by the forces of gravity.
• Analyzed chemical trends as a
function of photometric properties
of stars
• 1st time that cannibalism survivors
(Field) are compared to cannibalism
victims (Dwarf Spheroidals)
• 1st time that coaddition was used to
group LIKE stars strictly and with great
detail
What determines whether a dwarf satellite is
shredded or remains intact? Is it possible to find
dwarf galaxies that are in the midst of being
shredded? What are the chemical differences
between parent galaxies and their surviving
satellites?
Metallicity Graph
([Fe/H] [dex] vs.
(V-I)0 [mag]) for Field
Population
Metallicity Graph
([Fe/H] [dex] vs. (V-I)0
[mag]) for dSph
Population
The Bulge and Inner Disk of the Andromeda Galaxy1
Procedures
Data Collection
Sample Definition
Metallicity Distributions
Binning/Coadding Spectra
Step shows that dSph sample is more anemic than Field
sample (consistent with findings of other researchers)
Analyzing Spectra
Binning and Coadding Spectra
Results
Area analyzed in this
study
…using the Keck
Telescope and other
major telescopes
around the globe…
Field
Ca Triplet
•Sharper, deeper
absorption lines at 6500
[Å] (Hα) and Ca
triplet area (Figure 3)
Program used to coadd
spectra from stars in
each bin
Figure 3: (V-I)0 [1.2, 1.4]
Figure 1: FeHphot [-0.5, 0.0]
…then handled
with software
pipeline and
individual
analysis
•Three FeHphot ranges selected (one
shown above, Figure 1). All three show
consistent trends with (V-I)0
Methods
Figure 1a: Changing Equivalent
Widths [Å] vs. (V-I)0 for Ca Triplet
Average
dSph
1. Zquality 3 or 4: Eliminates background galaxies, isolates stars
with clean spectra from which velocities can be determined
Ca Triplet
2. M31Class 1, 2, or 3: eliminates foreground MW dwarf stars
Graph and
analyze spectra
•Bins only extended
horizontally to preserve
integrity of data.
Figures
1 and 1a
TiO band formation
•Beginnings of TiO band
formation are visible at 7150 [Å]
(Figure 4).
Figure 4a: (V-I)0 [1.2, 1.4]
Figure 4: (V-I)0 [1.2, 1.4]
•Reinforces Field Sample trends
2
dSph
• Sample is a mix of M31 stars, background galaxies, and
foreground Milky Way (MW) stars
•Changes visible
by observing at
6500 [Å]
(Hα) and by
inspecting the
Ca triplet’s
changes
•Bins with less than 10 stars
combined with adjacent bins.
Figure 3a: Ca Triplet for (V-I)0 [1.2, 1.4]
dSph sample showed non-monotonic changes in absorption lines
Distinguishing between the dSph and Field Samples
Overall Criteria
Weight the spectra in
each bin according to
the assigned value
Adjustable
Binning Process
•Metal absorption lines
in between Ca lines
become stronger at
8460, 8560, 8675,
and 8690 [Å] (Figure
3a; left)
•(Figure 1a) Change in strength of
Calcium (Ca) triplet absorption lines
(8498 [Å], 8542 [Å], and 8662 [Å]) is not
monotonic
W. M. Keck Observatory on Mauna Kea, HI4
Data
collected
over several
years…
•Titanium oxide
(TiO) bands
appear at 7100 [Å]
for top six spectra, at
7600 [Å] for
multiple spectra, and
at ≈8200 [Å] for
top spectrum
FeHphot= [-0.5, 0.0]
4
Field
Data Collection and Processing
Assign each spectra
an ivar value (“inverse
of the variance”)
TiO Bands
≈ 600,000 light years
3
Equal-sized bins (0.2
mag x 0.5 dex) used to
grid Metallicity graphs
Analysis of Spectral Changes for Each Sample
As a function of (V-I)0 at a given FeHphot range:
As a function of FeHphot at a given (V-I)0 range:
Radius—200 kiloparsecs
FeHphot ([Fe/H]):
photometric metallicity
estimate; iron to
hydrogen ratio in a star;
log unit [dex] relative to Sun
(V-I)0: measure representing
a star’s
and (V-I)0 ? temperature
•Ca band trends (Figure 4a):
spectral lines become deeper,
sharper, and wider
3
1
Figures 3 and 3a
The Mean and Median Values (with Root Mean Square Deviation) of Metallicity vs.
Color for the Coadded Spectra of Each Bin of the M31 Field Sample
Figure 2: FeHphot [-1.5, -1.0]
dSph vs. Field
Criteria
Two ‘flavors’ of telescope pointing during data collection:
• Towards M31 dSph Satellites
• Away from M31 dSph Satellites (“non-dSph pointing”)
dSph vs. Field Single Bin Spectral Comparison
•Bins outlined in Table 1 selected for Single Bin
comparison (only Bin 2 detailed in poster, other
bins reflected same results)
When telescope is pointed towards dSph, collected sample is
a mix of dSph AND field stars:
• Stars from initial dSph
Sample not within
stringent Vcorr range
selected as part of Field
Sample (see figure)
(V-I)0
[mag]
FeHphot
[dex]
Number of
Number of
Stars in
Stars in Field
dSph Sample
Sample
Bin 1 [1.2, 1.4] [-2.0, -1.5]
Bin 2 [1.2, 1.4] [-1.5, -1.0]
168
84
47
88
Bin 3 [1.4, 1.6] [-1.0, -0.5]
21
81
1
Ca triplets and Weaker Metal Absorption Lines for Bin 2
Field Sample is slightly more chemically
enriched than the dSph Sample.
The Mean and Median Values (with Root Mean Square Deviation) of Metallicity vs.
Color for the Coadded Spectra of Each Bin of the dSph Sample
Highlighted portions of graphs above are ideal locations
for ladder plots of coadded spectra
Conclusions/Future Plans
Benefits of the Coaddition Process
Example Histogram of Corrected
Velocities [km/s] for Stars in dSph
Andromeda 3 (bin size = 5 [km/s])
•Individual stellar spectra have low signal-tonoise—coaddition suppresses noise while
preserving actual absorption features
•Trends as a function of FeHphot or (V-I)0 were
seen
For non-dSph pointing, no velocity cuts necessary (not
shown)
(Methods Continued on Right Panel)
Before Coaddition (only
After Coaddition (full
blue half of spectrum shown)
spectrum shown)
Figure 2
Figures 4
and 4a
Field Eq. Width 54.51 [Å] 22.15 [Å] 20.36 [Å] 20.36 [Å] 20.25 [Å]
Bin 2 Coadded Spectra
3
2
Table 2: Equivalent Widths for Ca Triplets and Weaker Metal Absorption
Lines for Bin 2
1
2
3
4
Average
Ca
(8468(8512- (8660(8690Triplet 8472 [Å]) 8520 [Å]) 8670 [Å]) 8697 [Å]
dSph Eq. Width 44.47 [Å] 10.96 [Å] 16.46 [Å] 19.87 [Å] 19.74 [Å]
1. Stringent Velocity Cuts: histograms of corrected velocities
(Vcorr) generated for
each dSph
• Stars in main
histogram peak
selected as part of
dSph Sample
Table 1: Bins for Single Bin dSph vs. Field Comparisons
•Field spectrum seems to have larger equivalent widths at
each absorption line
(See Results/Discussion Section)
Spectral Analysis
Future Plans
•Changes in Metallicity and Temperature have effect
on star’s spectrum and result in systematic trends
•Field and dSph populations show similar trends, but
Field Sample is chemically richer on average
•Chemical properties of M31’s stellar halo are
consistent with the halo’s formation by merger and
dissolution of dSph satellites
•Interesting to see whether cannibalism victims are
similar to cannibalism survivors in terms of their
distinct chemical properties
•Compare detailed absorption line strengths in
spectra to comprehensive computer models of
stars with range of known chemical properties
•Based on comparison, determine [Fe/H] and
[X/Fe] for various elements (X=Ca, Mg, Ti, etc)
•Compare individual dSphs with each other, Field
to tidal streams, dSphs to tidal streams, etc
•Take Metallicity Distribution Function (MDF) of
dSphs into account to study star formation and
chemical enrichment history of galaxy
References
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Cote, P., O ke, J. B., Cohen, J. G., 1999, Astronomical Journal, 118, 1645-1656
Cox, T. J., Loeb, A., 2007, arXiv:07051170v2
Forgan, D., 2 008, arXiv:astro-ph/08102222
Gilbert, K. M., Font, A. S., Johnston, K. V., Guhathakurta, P. 2009, Astrophysics Journal.
Gilbert, K. M., Fardal, M., Kalirai, J. S., Guhathakurta, P., Geha, M. C., Isler, J.,
Majewski, S. R., Ostheimer, J. C., Patterson, R. J., R eitzel, D. B., Kirby, E. N. 2 007, A pJ. a rXiv: astro-ph/09081111
Gilbert, K. M., Guhathakurta, P., K alirai, J. S., Rich, R. M., M ajewski, S. R.,
Ostheimer, J. C., R eitzel, D. B., Cenarro, A. J., Cooper, M. C., L uine, C., & Patterson, R. J. 2 006, ApJ, arXiv:astro ph/0605171v2
Guhathakurta e t al., 2006, a rXiv:astro-ph/0502366v5
Kalirai, J.S. et al. 2009, ApJ, arXiv: astro-ph/09093298
Kirby, E. N., G uhathakurta, P., Bolte, M., S neden, C., & Geha, M. C. 2009, ApJ, in press, arXiv:astro-ph/09093092
Kirby, E. N., G uhathakurta, P., & Sneden, C. 2008, ApJ, 682, 1217
Lagutin, V. I., Pchelina, I.Z., 1985, Springer New York, 28, 49-51
Lee, Y. S., et al. 2008, Astronomy Journal, 136, 2022
Majewski, S.R. et. al, 2007, ApJ, arXiv:astro-ph/0702635v2
Morossi, C., F ranchini, M., D i Marcantonio, P. & Malagnini, M. L. 2007, n.p., 3, 504-505
Smecker-Hane, T. & M cWilliam, A. 1999, a rXiv: astro-ph/9910211v1
Walker, M. G., Mateo, M., Olszewski, E. W., Gnedin, O. Y., Wang, X., Sen, B., & Woodroofe, M. 2007, ApJ, 667, L53
Yin, J ., H ou, J . L., Prantzos, N ., Boissier, S ., Chang, R. X., S hen, S . Y ., & Zhangh, B., 2009, a rXiv: astro-ph/09064821
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