Master Projects

MP#1: ALMA observations of the most enigmatic structures in the ISM: the mystery of the Nessie filament

Status: AVAILABLE

Supervisor: Alvaro Hacar (alvaro.hacar@univie.ac.at) + Jouni Kainulainen (Chalmers Univ., Sweden)

Duration: 1 year (max)

Project description: Recent Galactic Plane surveys have revealed the existence of >100pc long filaments, the so-called Giant Molecular Filaments (GMFs). Characterising the origin and evolution of these GMFs is essential to understand how most stars form in spiral galaxies. This project aims to explore one of the most prototypical GMFs in the Milky Way, the Nessie cloud. We have observed this GMF using the ALMA Compact Array (ACA) in Band 3 (93 GHz). Our observations mapped the molecular content of this cloud using a series of dense (N2H+) and diffuse (e.g. HNC) molecular tracers. This project aims to investigate the internal gas structure (integrated intensity maps) and dynamics (spectra) of this paradigmatic Nessie filament across 2 orders of magnitude in scale, between 150 and 0.1 pc.

Specific Goal(s): Obtain a physical description of gas density and motions within the Nessie filament combining some of the different molecular tracers obtained in our ACA observations.

Keywords: ALMA, molecular observations, gas dynamics

Working plan:

  1. ALMA observations of the Nessie region: ACA maps

  2. Dense vs diffuse gas tracers

  3. Comparison with IR/continuum emission

  4. Spectral analysis: turbulence, velocity oscillations, and fragmentation (optional)

  5. Write Master Thesis

Requirements: Basic background in star formation

Supervision: in person + online

References:
https://ui.adsabs.harvard.edu/abs/2010ApJ...719L.185J/abstract

MP#2: HOW accurately can ALMA reveal interstellar Filaments?

Status: AVAILABLE

Supervisor: Alvaro Hacar (alvaro.hacar@univie.ac.at)

Duration: 1 year (max)

Project description: Recent Herschel observations have highlighted the strong filamentary nature of clouds in our Galaxy. Nowadays, ALMA is routinely used to observed filaments across the Milky Way, both in low- and high-mass environments, at high spatial resolutions. Despite the unprecedented ALMA sensitivity, however, the particular and complex morphology of these objects presents fundamental challenges for current interferometric surveys. Given the wide dynamic range of densities between their diffuse envelopes and their densest cores, both ALMA continuum and line observations in filaments can be potentially affected by filtering + sampling effects. Given their potential impact for the star-formation community, it is of fundamental importance to quantify these interferometric effects on the interpretation and analysis of ALMA observations. Combining both real and simulated data, in this technical project the selected Master student will investigate the impact and perils of new ALMA line + continuum observations in filaments under different conditions using the CASA simulator.

Specific Goal(s): Characterize and quantify the filtering effects produced by interferometers such as ALMA during the observations of diffuse and extended gas filaments.

Keywords: ALMA, interferometers, gas dynamics, CASA

Working plan:

  1. Interferometers & ALMA

  2. CASA simulator

  3. Filament models: static, velocity gradient, & oscillations

  4. Discussion and implications for ALMA observations

  5. Write Master Thesis

Requirements: Technical project. Basic knowledge of interferometric observations is preferred.

Supervision: in person + online

References:
https://ui.adsabs.harvard.edu/abs/2018A%26A...610A..77H/abstract

MP#3: Warm vs. cold deuteration in Orion A

Status: AVAILABLE

Supervisor: Alvaro Hacar (alvaro.hacar@univie.ac.at)

Duration: 1 year (max)

Project description: Deuterated molecules are regularly used a probes of the densest phases of early-star formation. Thanks to the increased sensitivity of sub-mm telescopes such as ALMA, deuteration is nowadays employed on the study of both dense cores and massive star-forming regions. The origin of deuterated species in molecular clouds is, however, matter of strong debates. In a recent observational campaign, we have observed a series of deuterated species in the Orion A cloud. Our results show different deuteration levels as function of temperature. This project aims to investigate how the two current chemical scenarios proposed for deuteration in clouds, namely, warm a cold formation routes, can explain the emission distribution observed in this prototypical region.

Specific Goal(s): Compare the distribution of different deuterated molecules (N2D+, DCN, DCO+...) and find their correlation with the gas column densities and temperatures along the Orion A cloud.

Keywords: radioastronomy, molecules, astrochemistry

Working plan:

  1. Obtain maps of different deuterated species in Orion A

  2. Produce line emission ratios

  3. Compare emission maps and ratios with gas/dust column density + temperature

  4. Investigate the origin of both warm + cold deuteration mechanisms

  5. Write Master Thesis

Requirements: Basic knowledge of python.

Supervision: in person + online

References:
https://ui.adsabs.harvard.edu/abs/2018A%26A...616A..45S/abstract

MP#4: Analysis of multi-dimensional Molecular datasets using machine learning techniques

Status: AVAILABLE

Supervisor: Alvaro Hacar (alvaro.hacar@univie.ac.at)

Duration: 1 year (max)

Project description: Molecular astrophysics is entering the Big Data domain. Compared to former single-line studies, the improved sensitivity and large instantaneous band coverage of instruments such as ALMA provide wide spectral maps including dozens (if not hundreds) of molecular transitions from clouds to proto-planetary disks. Given the nature and richness of these complex datasets, it is clear that next ground-breaking discoveries in this field will undoubtedly require the use of novel and advanced analysis strategies. In a recent large-scale survey, we mapped the molecular emission properties of the Orion A cloud using multiple line tracers in the 1mm and 3mm bands. This project will explore the use of machine learning techniques (e.g. classification & clustering algorithms) on the study of N-dimensional molecular datasets similar to those obtained by our group in Orion.

Specific Goal(s): Develop new statistical and machine learning techniques to explore large-scale multi-line molecular surveys of nearby clouds.

Keywords: molecular emission, data-science, machine learning

Working plan:

  1. Molecular diversity in the Orion A cloud

  2. Correlations between line emission vs. dust continuum

  3. Machine learning techniques for the exploration of N-dim datasets

  4. Classification algorithms

  5. Write Master Thesis

Requirements: Previous experience on data-science, mathematical methods, and/or machine learning techniques.

Supervision: in person + online

References: https://ui.adsabs.harvard.edu/abs/2018A%26A...610A..12B/abstract