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Computational Astronomy

Code: AST3007     Acronym: AST3007

Keywords
Classification Keyword
OFICIAL Astronomy

Instance: 2019/2020 - 1S Ícone do Moodle

Active? Yes
Responsible unit: Department of Physics and Astronomy
Course/CS Responsible: First Degree in Physics

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
L:B 0 study plan from 2016/17 3 - 6 56 162
L:CC 0 Plano de estudos a partir de 2014 2 - 6 56 162
3
L:F 9 study plan from 2017/18 2 - 6 56 162
3
L:G 0 study plan from 2017/18 2 - 6 56 162
3
L:M 1 Plano estudos a partir do ano letivo 2016/17 2 - 6 56 162
3
L:Q 1 study plan from 2016/17 3 - 6 56 162

Teaching Staff - Responsibilities

Teacher Responsibility
Mário João Pires Fernandes Garcia Monteiro
Jorge Filipe da Silva Gameiro

Teaching - Hours

Theoretical and practical : 1,00
Laboratory Practice: 3,00
Type Teacher Classes Hour
Theoretical and practical Totals 1 1,00
Jorge Filipe da Silva Gameiro 0,30
Mário João Pires Fernandes Garcia Monteiro 0,70
Laboratory Practice Totals 1 3,00
Mário João Pires Fernandes Garcia Monteiro 2,00
Jorge Filipe da Silva Gameiro 1,00

Teaching language

Portuguese

Objectives

The course aims to provide the student with basic skills to solve problems in different areas of computational astronomy, covering both, the methods used and the astronomy issues being addressed. To achieve this, the student acquires experience on how to use the methods and tools, as well as on developing computer applications to analyze and solve some specific problems of modern astronomy. The aim of the laboratory component is to provide the student with the opportunity to use the techniques and develop the skills needed to solve, computationally a wide range of astronomical problems. There is also the aim to provide the stduent with the expertise on validatinng and on the interpretation of the numerical results by using astronomical observations relevant for the problems being addressed.

Learning outcomes and competences

Some of the most common methods used in computational astronomy (as interpolation, differentiation, function setting, solving differential equations, Monte Carlo simulations, N-body simulation, optimization, characterizing time series, etc.) are used in order to allow the student to formulate the approach that should be implemented in order to find the solution of each problem being considered. Through application to concrete problems of astronomy, the curricular unit aims at strengthening the student's ability to plan, validate algorithms and implement codes, as well as to evaluate the relevance of the numerical solution being obtained. The choice of problems is made to ensure that the student can use the numerical results to construct the physical interpretation of the specific astronomical problem being addressed, supporting the consolidation of fundamental concepts in astronomy related to the problems being studied.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Basic astronomy concepts, numerical methods and some experience with numerical calculation of physical models.

Program

The CU includes a theoretical approach in the formulation of the numerical solution, the computer implementation of the algorithm and specific applications to concrete cases, through a portfolio of problems in astronomy whose answer is obtained by the student using a computer. The organization of the contents is:

  • Concepts of numerical calculus in astronomy (numerical methods, statistics, Monte Carlo simulations)
  • Stellar interior models (sun, low-mass or massive stars, energy production)
  • N-body simulations and applications in astronomy (planetary systems, stellar clusters, galaxy, galaxy clusters)
  • Fitting models to different systems using spectroscopic or photometric data (synthesis of stellar populations, fitting spectral lines and measuring equivalent widths)
  • Applications of time domain Astronomy (astro-dynamics of stellar binaries and planetary systems, radial velocities in planetary systems, determination of oscillations in stars, planetary transits)

Mandatory literature

Monteiro, M. J. P. F. G.; Astronomia Computacional, 2017

Complementary Bibliography

Bajpai A. C.; Numerical methods for engineers and scientists. ISBN: 0-471-99542-8

Comments from the literature

Relevant material (articles, web references, presentations and book chapters) are made available through the Moodle for the curricular unit.

Teaching methods and learning activities

The course is organized using the theoretical lectures and laboratory work. The theoretical analysis of the issues being addressed is discussed to allow the student to follow the construction of the physic-mathematical description of the various items covered and to do the definition of the computational approach to be implemented. In the laboratory (computer) the student works in structuring of algorithms and implementing the codes in compute, in order to obtain the required results for concrete applications in astronomy (using observational data).

The methodology used aims at enhancing the student's ability to formulate and implement a numerical approach to solve specific problems in astronomy. This is done by ensuring that the student identifies the problem and the desired solution, identifies the method for its resolution, which can then be implemented to study specific astronomical problems/questions. For reaching this goal, the student works on the computer, under the guidance of lecturer, in order to plan and implement the codes needed to produce a valid solution. The student also develops the procedures required to optimize and validate the code as well as the procedures necessary to characterize the solution being calculated (in terms of relevance/physical applicability and determination of uncertainties).

The methodology used ensures that the student develops a critical approach in the analysis and interpretation of numerical results, understanding that these are a simplified representation of a particular physical behaviour for a complex phenomena.

Software

Python
FORTRAN (opcional)
LaTeX

keywords

Physical sciences > Astronomy
Physical sciences

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation Weight (%)
Exame 30,00
Participação presencial 10,00
Trabalho escrito 60,00
Total: 100,00

Amount of time allocated to each course unit

designation Time (hours)
Elaboração de relatório/dissertação/tese 30,00
Estudo autónomo 76,00
Frequência das aulas 56,00
Total: 162,00

Eligibility for exams

In order to qualify for evaluation the student must:

  • attend a minimum of 50% of the lectures,
  • submit a minimum of one report.

Calculation formula of final grade

The final grade is obtained by combined the result on different components of the evaluation. These are:

1) 60% a minimum of three writen reports on specific study cases developed during the semester,

2) 10% - participation in all activities through interaction in the lectures and presentation of preliminary results, including also a short presentation (10 minutes) of the results of one project,

3) 30% - a final written exam (access to supporting material and/or equipmentr is allowed).

Examinations or Special Assignments

Due to the specific characteristics of this course unit it is not possible to request and additional evaluation test.

Classification improvement

The classifications in most of the components of the evaluation can be improved, namely in any of the reports (item 1) and the final exam (item 3).

Observations

It is recomended that students install the recomended open source software for the curricular unit in their personal computer, should it exist.

The jury of the curricular unit includesi:
   - Mário João P. F. G. Monteiro
   - Jorge Filipe S. Gameiro
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