Research Statement
Sarah Bosman
Probing the Early Universe with Quasar Spectroscopy
In recent years, quasars spectroscopy has become established as a prime tool for observational cosmology. The
ever-increasing number of high redshift quasars detected by surveys has led to a proliferation of techniques
aiming to extract information about the intergalactic medium (IGM) around and along the lines of sight to
these objects. High redshift quasars have provided insights into the early Universe ranging from the metal
enrichment and feedback processes in early galaxies – through line-of-sight metal absorbers – to the large scale
structure and ionisation fraction of Universe as Reionisation ends – by making use of the Lyman-α forest.
My research interests span topics in Reionisation and early galaxy formation brought together by the use
of quasar spectroscopy as the main tool. This has consisted of obtaining and analysing spectra using a a wide
variety of of techniques, as well as working with simulated quasar spectra in post-processing. I am in the
final year of a three-year PhD program at the Institute of Astronomy, University of Cambridge, under the
supervision of Dr. George Becker (UCR) and Prof. Martin Haehnelt.
Past work
Neutral fraction of Hydrogen from the Lyman-α emission line
The profile of the Lyman-α emission line at 1215 Å in quasars is extremely homogeneous across cosmic time,
which has led to the interpretation of deviations at high redshift as consequences of the surrounding medium
rather than the objects themselves. The first quasar at z > 7, J1120+0641 (J1120) discovered by Mortlock
et al. (2011) displayed one such anomalous Lyman-α line profile, which was well fit by the combination of
a composite of ‘typical’ quasar Lyman-α emission superimposed with a highly neutral absorber. This lead
to claims that either the surrounding IGM or a damped Lyman-α system in front of the object were & 10%
neutral. I worked with Dr. Becker in support of the opposing view that the profile is instead consistent with
being fully intrinsic.
Using the SDSS DR7 quasar catalog, I devised a technique to select a sub-sample of objects which match
the properties of C IV, a broad quasar emission line which is also anomalous in J1120 by being excessively
blueshifted while still strong (Bosman & Becker 2015). The rarity of low redshift objects presenting this feature
means they have been under-used in composite and reconstruction techniques; however we found that among
this subsample J1120’s Lyman-α emission was not an outlier at 1σ significance. By finding quasars displaying
anomalous Lyman-α emission lines even though they are not located in a neutral medium, we confirmed a
known strong correlation between quasar emission features, and casted doubt on the interpretation of Lyman-α
emission at high redshift.
Metal Enrichement up to z = 7 with line-of-sight absorbers
By acting as background sources of blackbody radiation, high redshift quasars allow for the detection of
foreground objects through imprinting of absorption lines from ionised metal transitions. The early galaxies
around which this absorption originates are challenging to study in emission at z > 5.5, yet through the
use of the ionic ratios and velocity dispersions of their absorption lines information has been gained on their
ionisation states and in/outflow mechanisms. In addition this technique allows the measurement of the cosmic
abundances of metals, and their evolution across time (D’Odorico et al. 2010, Becker et al. 2015).
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Research Statement
Sarah Bosman
Figure 1: (Left) Lyman-α transmission from two quasars z = 5.923 and z = 6.016, illustrating the extreme variation
of transmission morphologies between lines of sight over 5.3 < z < 5.7. The absorption trough in ULAS J0148+0600
is 110 Mpc/h in length. (Right) Probability distribution functions of Lyman-α opacities from in Becker et al. (2015)’s
sample of 26 quasars (red) and our sample of ∼ 80 (black, preliminary). We produce smoother constraints at z < 5.7
and statistically significant constraints up to z = 6.1.
A extremely high quality (30h) X-Shooter spectrum of the z = 7.1 quasar J1120 allowed me to extend
the study of metal absorbers beyond z = 6 for the first time (Bosman et al. submitted). I wrote a code to
automatically detect intervening absorbers in quasar spectra and assess their significance based on machine
learning techniques. The confirmed detections were analysed using a mixture of old and new statistical
methods, including for the first time a binning-free maximum likelihood statistic which homogenises previous
studies. Our most unexpected result was the discovery of a significant (at 3σ) overdensity of weak Mg II
absorbers at 5.5 < z < 7.0 compared to lower redshifts (Matejek & Simcoe 2012), a signature of the ultraviolet
background (UVB) being less sharp and more accommodating to low-ionised metals at those early epochs
despite lower cosmic metal abundances. The immediate vicinity of the quasar was also shown to contain either
an absorber partially covering the line of sight, or multiple cold and dense absorbers; making the interpretation
of Lyman-α emission from the object more complex than previously thought.
Ongoing work
Follow-up of line-of-sight detections with MUSE
In the past few years, it has become possible to detect large amounts of early galaxies at 5 < z < 10 through
their Lyman-α emission and characteristic photometric colors. However, no object so far has been observed
in both emission and as absorption towards a high-z quasar. This has become achievable with the MUSE
instrument, an integral field spectrograph sensitive enough to detect the expected Lyman-α emission from
these objects. Such a detection will carry significant implications for models of galaxy formation, as (a) the
distance of Lyman-α emission from the line-of-sight is a direct measure of the size the metal enriched regions
for different ions, and (b) the kinematics of the various components will tell us about the prevalence of metalenriched winds. This information is crucial for current computational models of galaxy growth, which struggle
to reproduce the observed occurrences of metallic ions such as Mg II and C IV(eg. Keating et al. 2015).
To achieve this, I am the P.I. of a Proposal to use the MUSE instrument to target the field around a
particularly rich quasar line-of-sigth, J0100+2802. Its spectrum reveals 16 intervening systems with z > 4.5,
with 6 at z > 5.7. As prepartion for the Proposal, I analysed existing MUSE observations and produced
simulated data to design an optimal observational strategy.
In addition, a successful HST proposal on which I was a Co-I will soon obtain deep imaging of the field
around the z = 7 quasar J1120 in an attempt to identify the galaxies associated with the intervening systems
discovered towards the object.
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Research Statement
Sarah Bosman
Lyman-α forest opacity at 5.3 < z < 6.1
Studies of the Lyman-α forest at low z have provided a wealth of information about Hydrogen in the IGM,
from its ionised fraction to its temperature. As soon at the neutral fraction reaches [HI]/[H] ∼ 0.1% however,
the Lyman-α forest saturates and individual components cannot be isolated any more. Fan et al. (2006)
and Becker et al. (2015) have used large samples of z > 5.7 quasars to obtain the distribution functions of
Lyman-α opacities as a function of redshift up to z = 5.9, as another way to track the increasing neutrality of
the IGM. The samples they had access to were of modest size, especially considering the spread in line-of-sight
morphology: at z ∼ 5.5, some show uninterrupted, completely dark troughs of lengths up to ∼ 110 Mpc,
while others display continuous peaks of transmission at the same redshift. This has proven a challenge for
numerical models to reproduce (see Figure 1).
I am working with Prof. Xiaohui Fan to assemble the largest catalog of z > 5.7 quasars to date, which
will allow for a far more precise determination of opacity distributions and extend the exercise to z = 6.1
and beyond (Bosman et al. in prep). My catalog currently contains ∼ 80 quasar spectra out of 122 alltime spectroscopically confirmed objects, up from 26 in previous studies. This is a cross-collaboration effort
between SDSS, DES and SHELLQs, and includes spectra taken by myself with the ESI spectrograph on the
Keck telescope. By providing the first robust measurements of average opacity but also spread, this allows
us to test the predictions from numerical simulations which output simulated lines of sight. Ultimately, we
will determine which models of IGM temperature, density, mean free path and mean neutral fraction fits the
observations best.
Future Work
Lyman-α transmission spike statistics
While the mean opacity of Lyman-α transmission is a good measure of the state and evolution of the IGM on
scales of 50 Mpc/h and more, it does not carry information about smaller scales. The z > 5 Lyman-α forest
displays transmitted flux as individual peaks rather than a constant level. Different models of Reionisation
predict varying degrees of clustering and strength distributions of those peaks, for instance by distributing the
contributions to Reionisation among galaxies and quasars or including mean free path and temperature effects
(eg. Chardin et al. 2015; D’Aloisio et al. 2015; Davies & Furlanetto 2015).
Working with Prof. Martin Haehnelt and Dr. Jonathan Chardin I have started developing a new technique
to extract information from the z > 5 Lyman-α forest using transmission spike statistics, which provide a new
metric to compare simulations to data. While the above-mentioned sample of quasars contains ∼ 80 Lyman-α
forest lines-of-sight spanning 5.3 < z < 7.0, those spectra are of a wide variety of signal-to-noise ratios (SNRs)
and wavelength resolutions. This poses a challenge since not all instruments are sensitive to a given threshold
of transmission spike flux. We solve this problem by full forward modelling the simulated spectra, degrading
them to a range of SNRs and resolutions mimicking observed data. Preliminary results are intriguing, as they
hint that even the more extreme – quasar-heavy – models under-predict the observed clustering of transmission
spikes.
References: Becker et al. 2015, MNRAS, 447, 3402 Becker et al. 2015, PASA, 32, e045 Bosman & Becker 2015,
MNRAS, 452, 1105 Bosman et al. 2015, MNRAS submitted Bosman et al. in prep Chardin et al. 2015, MNRAS,
453, 2943 D’Odorico et al. 2010, MNRAS, 401, 2715 D’Aloisio et al. 2015, 813, L38 Davies & Furlanetto 2016,
MNRAS, 460, 1328 Fan X. et al. 2006, AJ, 132, 117 Keating et al. 2016 MNRAS, 461, 606 Matejek & Simcoe
2012, ApJ, 761, 112 Mortlock et al. 2011, Nature, 474, 616
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