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Scientific computing (Computational science)
Contributed by: Haigh
  • 1. Scientific computing, also known as computational science, is the interdisciplinary field of study that involves constructing mathematical models and quantitative analysis techniques to solve complex problems in various scientific disciplines. It utilizes advanced computing techniques and algorithms to simulate, analyze, and visualize complex systems and phenomena. Scientific computing is widely used in areas such as physics, chemistry, biology, engineering, and economics to gain deeper insights, make predictions, and optimize systems. By leveraging high-performance computing resources, scientific computing enables researchers and scientists to tackle large-scale problems that were previously impossible to solve using traditional methods. Overall, scientific computing plays a crucial role in advancing scientific knowledge, driving innovation, and solving real-world challenges.

    What is numerical analysis in scientific computing?
A) An analysis of numerical symbols in ancient texts.
B) The analysis of flaws in computer networks.
C) The study of algorithms for approximate numerical calculations.
D) The study of advanced mathematical theories.
  • 2. Which programming language is commonly used in scientific computing?
A) C++
B) HTML
C) Java
D) Python
  • 3. What is a supercomputer?
A) A computer designed specifically for playing video games.
B) A powerful computer used for high-performance scientific and engineering applications.
C) A computer that can only perform basic arithmetic operations.
D) A computer that runs on solar power.
  • 4. What is a simulation in scientific computing?
A) Building physical prototypes
B) Creating a virtual model to imitate the behavior of a real-world system.
C) Writing fiction novels
D) Drawing scientific illustrations
  • 5. What does PDE stand for in the context of scientific computing?
A) Public Domain Encyclopedia
B) Partial Differential Equation
C) Perfect Data Entry
D) Programming Development Environment
  • 6. What is the main difference between interpolation and extrapolation?
A) Interpolation estimates values within the known data range, while extrapolation estimates values outside the known data range.
B) Interpolation estimates values outside the known data range, while extrapolation estimates values within the known data range.
C) There is no difference between interpolation and extrapolation.
D) Interpolation involves guessing, while extrapolation involves direct calculations.
  • 7. What is a numerical algorithm in scientific computing?
A) A type of geometric shape
B) An ancient form of numerical writing
C) A collection of random numbers
D) A step-by-step procedure for solving a computational problem.
  • 8. What is the objective of time stepping in numerical simulations?
A) To advance the solution from one time level to the next.
B) To slow down computation speed
C) To reverse the order of calculations
D) To introduce random errors
  • 9. Which type of error occurs due to limitations in the numerical representation of numbers by a computer?
A) Direction error
B) Color error
C) Speed error
D) Round-off error
  • 10. What is the role of reproducibility in scientific computing?
A) To hide data from other researchers
B) To ensure that research results can be independently verified.
C) To change results based on personal beliefs
D) To keep research methods secret
  • 11. What is the purpose of error propagation analysis in scientific computing?
A) To ignore errors altogether
B) To increase the size of data sets
C) To introduce errors intentionally
D) To study how errors in input data propagate through calculations to affect the accuracy of the final result.
  • 12. What is a sparse matrix in numerical computing?
A) A small matrix
B) A matrix with only positive elements
C) A matrix with many zero elements
D) A large matrix with non-zero numbers
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