Lecture 1 Flashcards
What is Scientific Computing?
What are typical problems for scientific computing?
What are the formula’s for absolute and relative error?
Note: these may be negative, but usually only absolute values are quoted
What are the two types of errors?
- Input errors
- Computational errors
What are three examples of input errors?
What are three examples of computational errors?
How can the total error be split into the two types of errors?
What is a trunctation error and a rounding error?
What are the forward and backward errors?
When is a problem well-posed?
What is the condition number?
How can the condition number approximated?
What does the concept stability mean?
What does the concept of accuracy imply?
How are floating point number stored?
What is the concept of normalization?
What is the number of floating points numbers that exist in a system?
What is the meaning and formula of an overflow and underflow level of a floating point system?
What are the two rounding methods?
What is the unit roundoff? What does it imply?
What is the specific definition for Python?
epsilon_mach
What are subnormal floating point systems? Are they better?
How are the different floating point operations managed?
How can floating points operation errors be rewritten?
What are cancellation errors?
What are overflow errors?
What is the IEEE double precision format?
