I am a PhD student at University College London, working on Galaxy Evolution and Active Galactic Nuclei (AGN) under the supervision of Dr. Amélie Saintonge. My research interests are the characterization of dust properties of nearby galaxies, the link between dust and molecular gas content and the study of powerful AGN in the nearby Universe.
I am currently visiting ESO Garching as part of a one year PhD Studentship program. At ESO I am working with Dr. Vincenzo Mainieri and Dr. Chris Harrison on the characterization of dust properties of AGN at redshift ~2.

Research

Here is a summary of my research.

Dust properties of nearby galaxies: JINGLE survey

For the main project of my PhD, I used data from the JMCT dust and gas In Nearby Galaxies Legacy Exploration Survey (JINGLE) . Dust observations can be used to probe galaxy evolution, serving as a less time consuming tool to measure the gas content of galaxies. This has a great potential for the study of dwarf galaxies and objects at z>2, where molecular gas measurements through classical CO emission line observations are hard. In order to use dust to trace the gas content of galaxies, it is necessary to understand how dust properties vary across the galaxy population. The JINGLE survey is a JCMT large program which aims to characterize the dust properties of nearby galaxies, study their relation with the gas content and how they vary as a function of other key galaxy properties.
Below you can find a link to the JINGLE survey website and to the paper describing the survey.

JINGLE website Saintonge et al. 2018: JINGLE I


Relation between the dust temperature and dust emissivity index (T-β relation) for the JINGLE sample derived with non- hierarchical (upper panel) and hierarchical (bottom panel) Bayesian methods. Using the hierarchical method,the T-β anti-correlation is reduced.

As part of the JINGLE survey, I developed a method to fit the far-IR to submm SED of the JINGLE galaxies using modified black-body models (MBB). The main limitation of the MBB model is the intrinsic degeneracy between the dust temperature and the dust emissivity index β. To solve this problem, I used a hierarchical Bayesian approach, which helps to reduce the T- β degeneracy . After applying this technique to the JINGLE sample, the T-β anti-correlation is strongly reduced and I obtain better estimates of the dust parameters.
I also derive scaling relations between dust properties and global galaxy properties which can be used to estimate the dust temperature and emissivity index β in galaxies for which there are not enough photometric data available to measure them directly through SED fitting.

Here you can find a link to my paper published in MNRAS JINGLE V: Dust properties of nearby galaxies derived from hierarchical Bayesian SED fitting :

Lamperti et al. 2019: JINGLE V

CO(3-2) as a tracer of dense molecular gas

The most commonly used tracer of molecular hydrogen in galaxies is the CO molecule. The CO(J=1-0) emission line traces both the dense and diffuse molecular gas. The higher level CO(J=3-2) transition instead traces denser molecular gas, which is thought to be more directly related to star-formation.
In this project, we investigate the relation between the r31=LCO(3-2)/LCO(1-0) luminosity line ratio and the star-formation efficiency (SFE=SFR/M(H2) in a sample of star-forming galaxies and AGN hosts from xCOLD GASS (Saintonge et al. 2011a, 2017), BASS (Koss et al. 2017) and SLUGS (Yao et al. 2003). We find a trend for the r31 line ratio to increase with star-formation efficiency. If we interpret the r31 as a tracer of the gas density, we can infer that the star-formation efficiency is not only related to the amount of molecular gas present in the galaxy but also on the fraction of the molecular gas which is in the dense phase.
Using the photon-dissociation region (PRD) code UCL-PDR, I model the CO(3-2)/CO(1-0) line ratio for different gas conditions and conclude that the main parameter affecting this line ratio is indeed the gas density, while the UV radiation field and the cosmic rays play only a minor role.

Upper panel: r31=LCO(3-2)/LCO(1-0) luminosity line ratio as a function of star-formation efficiency. We observe a trend for the line ratio to increase with star-formation efficiency. We do not observe any significant different in the r31 values of AGN and star-forming galaxies.
Bottom panel: r31 line ratio as a function of gas density modelled using the UCL-PDR code. According to the model, the main parameter driving variation in the r31 in the gas density, which is related to the SFE.
This work is be presented in Lamperti et al. (2019b, in press.):

Lamperti et al. 2019b: CO(3-2)/CO(1-0) luminosity line ratio

BASS: BAT AGN Spectroscopic Survey

During my Bachelor and Master at ETH Zürich, I worked on projects related to the BASS survey. The BASS survey is the spectroscopic follow-up of the AGN detected in the hard X-rays by the Neil Gehrels Swift/BAT telescope. The goal of the survey is to obtain emission line measurements, black hole masses and X-ray observations for a large sample of the brightest nearby AGN. As part of my Bachelor projects, I worked on the emission line fitting and black hole mass measurements from the velocity dispersion of ~600 AGN spectra for the first data release DR1 (Koss et al. 2017). For more information about the BASS survey, here you can find a link to the website:

BASS survey website


Example of optical (upper) and NIR (bottom) spectrum of a Sy 1.9 galaxy from the BASS sample. The optical spectrum shows only a weak broad component in Hα, which may be difficult to distinguish from an outflow signature. In the NIR the broad Paschen α component is more prominent and clearly detected.

For my Master Thesis, I focused on the analysis of the near-infrared (NIR) spectra of a sub-sample of ~100 BAT AGN. The NIR part of the spectrum is less susceptible to obscuration than the optical, and this allows us to study hidden broad line region that not visible in the optical. The NIR broad lines can be used to estimate the mass of the supermassive black hole. I also investigate the possibility to use NIR spectroscopy to identify AGN that are missed from optical emission line diagnostics. The presence of NIR coronal lines is an indicator of AGN activity, due to their high-ionization potential ( > 100 eV), and they can be used as an AGN selection criterion. I detect coronal lines in 43% of the AGN in our sample.
If you are interested in my work on the NIR properties of BAT AGN, here you can find a link to my paper:

Lamperti et al. 2017: BASS IV

Curriculum vitae

Here is a short summary of my CV:

  • PhD studentship project , European Southern Observatory, Garching, Germany, Sept. 2019 - present
  • PhD in Astrophysics, Department of Physics and Astronomy, University College London, United Kingdom, Nov. 2016 - present
  • Research Project, Center for Astrophysics and Supercomputing, Swinburne University of Technology, Melbourne, Australia, August - October 2016
  • M.Sc. in Physics, ETH Zürich, Switzerland, 2014-2016
  • B.Sc. in Physics, ETH Zürich, Switzerland, 2010-2014
The full version of my CV can be downloaded at this link: Full CV

Contact information

E-mail address:

i.lamperti.16[at]ucl.ac.uk

Postal address:

European Southern Observatory
Karl-Schwarzschild-Strasse 2
85748 Garching bei München
Germany