Scientific computing (Computational science)

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 study of algorithms for approximate numerical calculations.
C) The study of advanced mathematical theories.
D) The analysis of flaws in computer networks.

2. Which programming language is commonly used in scientific computing?

A) Java
B) Python
C) HTML
D) C++

3. What is a supercomputer?

A) A computer that can only perform basic arithmetic operations.
B) A computer that runs on solar power.
C) A powerful computer used for high-performance scientific and engineering applications.
D) A computer designed specifically for playing video games.

4. What is a simulation in scientific computing?

A) Drawing scientific illustrations
B) Writing fiction novels
C) Building physical prototypes
D) Creating a virtual model to imitate the behavior of a real-world system.

5. What is the role of reproducibility in scientific computing?

A) To hide data from other researchers
B) To keep research methods secret
C) To ensure that research results can be independently verified.
D) To change results based on personal beliefs

6. What is the main difference between interpolation and extrapolation?

A) Interpolation estimates values outside the known data range, while extrapolation estimates values within the known data range.
B) Interpolation involves guessing, while extrapolation involves direct calculations.
C) Interpolation estimates values within the known data range, while extrapolation estimates values outside the known data range.
D) There is no difference between interpolation and extrapolation.

7. What is the purpose of error propagation analysis in scientific computing?

A) To introduce errors intentionally
B) To increase the size of data sets
C) To study how errors in input data propagate through calculations to affect the accuracy of the final result.
D) To ignore errors altogether

8. What is the objective of time stepping in numerical simulations?

A) To reverse the order of calculations
B) To slow down computation speed
C) To introduce random errors
D) To advance the solution from one time level to the next.

9. Which type of error occurs due to limitations in the numerical representation of numbers by a computer?

A) Round-off error
B) Speed error
C) Color error
D) Direction error

10. What is a numerical algorithm in scientific computing?

A) A type of geometric shape
B) A collection of random numbers
C) An ancient form of numerical writing
D) A step-by-step procedure for solving a computational problem.

11. What is a sparse matrix in numerical computing?

A) A large matrix with non-zero numbers
B) A matrix with many zero elements
C) A matrix with only positive elements
D) A small matrix

12. What does PDE stand for in the context of scientific computing?

A) Perfect Data Entry
B) Public Domain Encyclopedia
C) Partial Differential Equation
D) Programming Development Environment

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