COMPUTACIÓN
CIENTÍFICA
Definición: de Wikipedia
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Scientific computing (or computational science) is
the field of study concerned with constructing
mathematical models and numerical solution techniques
and using computers to analyze and solve scientific and
engineering problems. In practical use, it is typically the
application of computer simulation and other forms of
computation to problems in various scientific disciplines.
The field is distinct from computer science (the
mathematical study of computation, computers and
information processing). It is also different from theory
and experiment which are the traditional forms of
science and engineering. The scientific computing
approach is to gain understanding, mainly through the
analysis of mathematical models implemented on
computers.
Alcances
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Scientists and engineers develop computer programs,
application software, that model systems being studied
and run these programs with various sets of input
parameters. Typically, these models require massive
amounts of calculations (usually floating-point) and are
often executed on supercomputers (computer that leads
the world in terms of processing capacity, particularly
speed of calculation) or distributed computing platforms.
Numerical analysis is an important technique
used in scientific computing. Numerical
simulations have different objectives depending
on the nature of the task being simulated
Objetivos concretos en otras disciplinas
distintas de computación:
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Reconstruct and
understand known events
(e.g., earthquake,
tsunamis and other
natural disasters).
Optimise known scenarios
(e.g., technical and
manufacturing
processes).
Predict future or
unobserved situations
(e.g., weather, sub-atomic
particle behaviour).
Algorithms and mathematical methods used in
scientific computing are varied.
Commonly applied methods include:
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Numerical analysis
Application of Taylor series as convergent and asymptotic series
Computing derivatives by Automatic differentiation (AD)
Computing derivatives by finite differences
High order difference approximations via Taylor series and
Richardson extrapolation
Methods for integration on a uniform mesh: rectangle rule,
trapezoid rule, midpoint rule, Simpson's rule
Runge Kutta method for solving ordinary differential equations
Monte Carlo methods
Numerical Linear Algebra
Computing the LU factors by Gaussian elimination
Choleski factorizations
Discrete Fourier transform and applications.
Newton's method
Time stepping methods for dynamical systems
Algorithms and mathematical methods used in
scientific computing are varied.
Commonly applied methods include:
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Numerical analysis
Application of Taylor series as convergent and asymptotic series
Computing derivatives by Automatic differentiation (AD)
Computing derivatives by finite differences
High order difference approximations via Taylor series and
Richardson extrapolation
Methods for integration on a uniform mesh: rectangle rule,
trapezoid rule, midpoint rule, Simpson's rule
Runge Kutta method for solving ordinary differential equations
Monte Carlo methods
Numerical Linear Algebra
Computing the LU factors by Gaussian elimination
Choleski factorizations
Discrete Fourier transform and applications.
Newton's method
Time stepping methods for dynamical systems
Lenguajes
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Programming languages commonly used
for the more mathematical aspects of
scientific computing applications include
Fortran, MATLAB, GNU Octave, NumPython, Sci-Python and PDL.
The more computationally-intensive
aspects of scientific computing will often
utilize some variation of C or Fortran.
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Computational science application programs often model real-world
changing conditions, such as:
 weather,
 air flow around a plane,
 automobile body distortions in a crash,
 the motion of stars in a galaxy,
 an explosive device, etc.
Such programs might create a 'logical mesh' in computer memory
where each item corresponds to an area in space and contains
information about that space relevant to the model.
For example, in weather models, each item might be a square
kilometer; with land elevation, current wind direction, humidity,
temperature, pressure, etc.
The program would calculate the likely next state based on the
current state, in simulated time steps, solving equations that
describe how the system operates; and then repeat the process to
calculate the next state.
Contexto
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The term computational scientist is used to describe someone skilled
in scientific computing. This person is usually a scientist, an
engineer or an applied mathematician who applies highperformance computers in different ways to advance the state-ofthe-art in their respective applied disciplines in physics, chemistry or
engineering. Scientific computing has increasingly also impacted on
other areas including economics, biology and medicine.
Computational science is now commonly considered a third mode of
science, complementing and adding to experimentation/observation
and theory. This thesis has been propounded by many, including
Stephen Wolfram (most notably in his book A New Kind of Science),
and Jürgen Schmidhuber
Revistas
Scientific Computing World
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SIAM Journal on Scientific
Computing
Scientific Computing World is Europe's
premier magazine devoted to the
computing and information technology
needs of those in science, engineering,
technology and medicine. It reports on
research, development, testing, and
laboratory analysis (including QA/QC).
Particularly known for its authoritative
reviews of maths/stats software, the
magazine also covers Laboratory
Information Management Systems
(LIMS), and computing in chemistry,
physics, and life sciences.
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The SIAM Journal on Scientific
Computing contains research articles
on numerical methods and techniques
for scientific computation. Papers
address computational issues relevant
to the solution of scientific or
engineering problems and generally
include computational results
demonstrating the effectiveness of the
proposed techniques.
Publication Information
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Computational Results for Scientific and
Engineering Problems
ISSN
Print: 1064-8275
Electronic: 1095-7197
SCIENTIFIC COMPUTING: An Introductory Survey,
Second Edition
by Michael T. Heath, published by McGraw-Hill, New York,
2002
Table of Contents
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Scientific Computing
Systems of Linear Equations
Linear Least Squares
Eigenvalue Problems
Nonlinear Equations
Optimization
Interpolation
Numerical Integration and Differentiation
Initial Value Problems for Ordinary Differential Equations
Boundary Value Problems for Ordinary Differential Equations
Partial Differential Equations
Fast Fourier Transform
Random Numbers and Stochastic Simulation
Bibliography
Educación
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Scientific computation is most often studied through an applied
mathematics or computer science program, or within a standard
mathematics, sciences, or engineering program. However, there are
increasingly many B.S. programs in computational science, notably
at SUNY-Brockport (Capital University of Ohio offers a well-known
minor program in computational studies that was one of the first
NSF-funded programs in the field). There are also master's degrees
in computational science or scientific computation, including the
Sloan Foundation's professional science master's programs . The
University of Waterloo in Canada offers a B.Math in computational
mathematics and a Master's program in scientific computing as well.
Some schools also offer the Ph.D. in computational science,
computational engineering, computational science and engineering,
or scientific computation, such as the University of Texas at Austin
Institute for Computational Engineering and Sciences (ICES),
McMaster University School of Computational Engineering and
Science, Purdue University, and UCSB. At some institutions a
specialization in scientific computation can be earned as a "minor"
within another program (which may be at varying levels).
There are also programs in areas such as computational physics,
computational chemistry, etc.
Campos relacionados
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Bioinformatics
Cheminformatics
Chemometrics
Computational chemistry
Computational biology
Computational mechanics
Computational physics
Computational Electromagnetics
Computational fluid dynamics
Computational economics
Environmental simulations
Financial modeling
Geographic information system (GIS)
Numerical weather prediction
Chemometrics
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Chemometrics is the science of relating measurements
made on a chemical system or process to the state of
the system via application of mathematical or statistical
methods.
Chemometric research spans a wide area of different
methods which can be applied in chemistry. There are
techniques for collecting good data (optimization of
experimental parameters, design of experiments,
calibration, signal processing) and for getting information
from these data (statistics, pattern recognition,
modeling, structure-property-relationship estimations).
Chemometrics tries to build a bridge between the
methods and their application in chemistry.
Computational Chemistry
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Computational chemistry is a branch of chemistry
that uses the results of theoretical chemistry
incorporated into efficient computer programs to
calculate the structures and properties of molecules and
solids, applying these programs to real chemical
problems. Examples of such properties are structure (i.e.
the expected positions of the constituent atoms), energy
and interaction energy, charges, dipoles and higher
multipole moments, vibrational frequencies, reactivity or
other spectroscopic quantitities, and cross sections for
collision with other particles. The term computational
chemistry is also sometimes used to cover any of the
areas of science that overlap between computer science
and chemistry. Electronic configuration theory is the
largest subdiscipline of computational chemistry.
Cheminformatics
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Cheminformatics is the use of computer
and informational techniques, applied to a
range of problems in the field of
chemistry. Also known as
chemoinformatics and chemical
informatics. These in silico techniques
are used in pharmaceutical companies in
the process of drug discovery.
Bioinformatics
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Bioinformatics and computational biology
involve the use of techniques including applied
mathematics, informatics, statistics, computer
science, artificial intelligence, chemistry and
biochemistry to solve biological problems usually
on the molecular level. Research in
computational biology often overlaps with
systems biology. Major research efforts in the
field include sequence alignment, gene finding,
genome assembly, protein structure alignment,
protein structure prediction, prediction of gene
expression and protein-protein interactions, and
the modeling of evolution.
Information Technology
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IT is concerned with the use of technology in managing and
processing information, especially in large organizations.
In particular, IT deals with the use of electronic computers and
computer software to convert, store, protect, process, transmit, and
retrieve information. For that reason, computer professionals are
often called IT specialists or Business Process Consultants, and the
division of a company or university that deals with software
technology is often called the IT department. Other names for the
latter are information services (IS) or management information
services (MIS), managed service providers (MSP).
Information and
Communication Technology
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In the United Kingdom education system, information technology
was formally integrated into the school curriculum when the
National Curriculum was devised. It was quickly realised that the
work covered was useful in all subjects. With the arrival of the
Internet and the broadband connections to all schools, the
application of IT knowledge, skills and understanding in all subjects
became a reality. This change in emphasis has resulted in a change
of name from Information Technology to Information and
Communication Technology (ICT). ICT in Education can be
understood as the application of digital equipment to all aspects of
teaching and learning. It is present in almost all schools and is of
growing influence.
The growth of use of Information and Communications Technology
and its tools in the field of Education has seen tremendous growth
in the recent past. Technology has entered the classroom in a big
way to become part of the teaching and learning process.