Numerical methods in chemistry

Numerikus matematika vegyészeknek


4 credits – 2 contact hours weekly

code: nummatk20em (En/Hu)

programme: MSc in Chemistry from year 2020/21, status: semi-optional

The course is integrated to Canvas

Language: English/Hungarian*

*(spring semester 2020/21: officially it is English, but on request we might switch to Hungarian. Online materials, books and the Canvas-study module are in English)


Aim of the course: An overview is given on numerical methods applied in chemistry with special focus on theoretical chemistry. The theoretical knowledge is coupled to a practical introduction of Python in order to use it in simple data evaluation and in post evaluation of data obtained in extensive computations.**

**(This new MSc in Chemistry course integrates three previous MSc courses: Numerical methods in chemistry lecture (A. Császár and G. Tóth), Numerical methods in chemistry practice (G. Tóth) and Scripting (G. Magyarfalvi))


Practical part (60% Gábor Magyarfalvi, 40% Gergely Tóth)

Basics of Python – self and common-study tasks integrated to Canvas. Application of numerical methods on chemical/physico chemical tasks by writing Python (or other) codes.


Lecture part (40% Attila Császár, 60% Gergely Tóth)

Online lectures weekly, if the number of active students is at least 5. or

Online consultations-tutorials every second week, if there are less students

Topics: Linear equations, Ordering, Random numbers, Non-linear set of equations, Roots of polynomials, Search for minima and maxima, Numerical differentiates, integrals, interpolation techniques, Parameter fitting, Eigenvalues, Differential equations, Fourier transformation, Search for global minima, Neural networks.



50% practice during the semester time (self- and common-study module, coding)

50% lecture part (written/oral exam at the end of the semester)

It is necessary to pass both parts separately.


Workload in hours

24 - lecture

32 – self-study on theory

  2 – consultation for lecture

  2 – exam

30 – self-study Python

10 – common-study Python

16 – coding tasks

  4 - consultation

sum: 120 hours