UCSCIPHYL42.5 ECTSEnglishBachelor
Experimental Statistical Mechanics
Faculteit—
NiveauBachelor
Studiejaar2026-2027
Beschrijving
Course goals
After completing this course students are able to:
- use and integrate knowledge from UCSCIPHY25 into experimental research and use this in the analysis and interpretation of his/her results.
- perform a numerical simulation of random processes in a considerably large system in Python as well as to analyse and describe the observed macroscopic behavior.
- use several methods of measuring thermodynamic quantities (such as temperature, pressure and heat) and evaluates the physical performance, accuracy and application of these.
- write an article that meets the standard requirements with regard to form, content and layout and reflect the insights gained in the laboratory work.
Relationship between assessment and learning goals:
| Description of assignment | Weight | Assesses which course aims? |
| 26 % 22 % 30 % 20 % | 1, 2 4 1, 3 4 |
Content
Statistical mechanics describes how the macroscopic behavior of systems consisting of large numbers of constituents (particles) follows from the statistical properties of constituents on a microscopic level. The goal of this course is to apply knowledge of statistical physics and practical skills for experimental and numerical problems in the field in an integrated way.
In the first part of this lab course, you will study the emergence of macroscopic properties from microscopic behavior for model systems with a simulation performed in Python. Topics that are modelled, are energy distribution or phase transitions.
In the second part, you perform experiments that allow you to test the laws that describe macroscopic behaviour.
Format
During the lab course, students work in pairs on their projects. The supervising TA will provide frequent feedback on physical context, skill development and project planning.
There are two group instructions that focus on writing scientific articles, to help students identify the key aspects of writing.
The module is offered in the statistical mechanics laboratory at Utrecht Science Park during Block 1, when this facility is set up for the physics bachelor course NS-204B. This module is created in order to provide physics double degree students with the required laboratory experience for the physics bachelors. The module is also relevant for UCU students completing regular tracks in physics and chemistry.
Schedule
In the first part of this lab course, you will study the emergence of macroscopic properties from microscopic behavior for model systems with a simulation performed in Python. Topics that are modelled, are energy distribution or phase transitions.
In the second part, you perform experiments that allow you to test the laws that describe macroscopic behaviour.
Format
During the lab course, students work in pairs on their projects. The supervising TA will provide frequent feedback on physical context, skill development and project planning.
There are two group instructions that focus on writing scientific articles, to help students identify the key aspects of writing.
The module is offered in the statistical mechanics laboratory at Utrecht Science Park during Block 1, when this facility is set up for the physics bachelor course NS-204B. This module is created in order to provide physics double degree students with the required laboratory experience for the physics bachelors. The module is also relevant for UCU students completing regular tracks in physics and chemistry.
Schedule
The course is organized in UU timeslot D on Wednesday and Friday afternoons (8 contact hours a week) for 8 weeks.
The first four weeks, students work on the simulation project (global planning: 3 weeks of programming and data analysis, 1 week writing the article).
The last four weeks, students work on the experimental project (global planning: 1 week exploration, 2 weeks measurement and data analysis, 1 week writing the article). At the end of each project there is a deadline to hand in deliverables.
The first four weeks, students work on the simulation project (global planning: 3 weeks of programming and data analysis, 1 week writing the article).
The last four weeks, students work on the experimental project (global planning: 1 week exploration, 2 weeks measurement and data analysis, 1 week writing the article). At the end of each project there is a deadline to hand in deliverables.
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