How were you exposed to probability theory in physics?

In summary, many physicists who are active in research do not keep up with the literature on probability theory, but many do.
  • #1
StatGuy2000
Education Advisor
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Hi everyone.

As a graduate student in statistics, I had taken a graduate course in measure-theoretic probability theory. In a conversation with the professor, he had remarked that if I wanted to pursue further research on some of the topics covered, it may be wise to do background reading or auditing some physics courses.

Indeed, the more I've looked into this, the more I've found that researchers in probability theory often either have double majors in math and physics, or else have been exposed to physics as a math student.

This prompted to me ask those of you who are either physicists or are current physics students the following:

1. When were you first introduced to probability in your college/university curricula? Was it during your first course in quantum mechanics? Or in statistical mechanics? Or did you take probability as an elective?

2. I'm curious how many of you who are actively working on physics research keep up with the literature on probability theory. To what extent does it inform your research?
 
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  • #2
Hopefully what I post won't derail the thread, but I wonder if it doesn't start earlier.

Where I am from my first contact with probability (in combination with combinatorics, things like calculation of probability of winning the lottery and drawing blue ball from a bag filled with only black and red ones :wink: ) was when I was about 17-18, which in US would put me somewhere in High School.
 
  • #3
Either in a modern physics course wrt nuclear cross sections or in thermodynamic wrt to free paths in transport processes.. I don't remember which came first.
 
  • #4
Probabilities might have been treated in the first semester lecture "Methods of theoretical physics", I don't remember it exactly. I think that the main introduction happened during short lectures which took place in advance of all lab courses. Afterwards, they popped up here and there in the excercises of various courses. In statistical mechanics, a few gaps were closed.
 
  • #5
I was exposed to probability theory in high school and first year of college, before being exposed to quantum mechanics and statistical physics.
 
  • #6
StatGuy2000 said:
Hi everyone.

1. When were you first introduced to probability in your college/university curricula? Was it during your first course in quantum mechanics? Or in statistical mechanics? Or did you take probability as an elective?

2. I'm curious how many of you who are actively working on physics research keep up with the literature on probability theory. To what extent does it inform your research?

I was never exposed to 'probability' as a specific topic, it was always added 'as needed' (how to calculate and report experimental uncertainties, or as broad background for statistical mechanics/quantum mechanics). I consider this to be a deficit in my training and try to get my students more exposure.

That said, I don't follow the probability literature, either. I try to regularly read the "Points of Significance" column in Nature Methods and am considering sitting in on a Bayesian statistics class.
 
  • #7
Probability theory, statistics and hypothesis testing took up a significant portion of my final year of math in high school, i.e. well before learning any actual undergraduate level physics whatsoever.
 

FAQ: How were you exposed to probability theory in physics?

1. How does probability theory apply to physics?

Probability theory is used in physics to study and predict the behavior of physical systems that are governed by random events or uncertain outcomes. It allows scientists to make statistical predictions about the likelihood of certain events occurring within a system, which can be used to better understand and describe the behavior of complex physical systems.

2. What are some real-world examples of probability theory in physics?

One example of probability theory in physics is the use of quantum mechanics to describe the behavior of subatomic particles. The probabilistic nature of these particles allows scientists to make predictions about their position and momentum, rather than exact measurements. Another example is the use of statistical mechanics to predict the behavior of large systems, such as gases or fluids, where individual particles may behave randomly but the overall behavior can be described by statistical laws.

3. How does probability theory contribute to the understanding of uncertainty in physics?

In physics, there are many phenomena that cannot be predicted with certainty due to their inherent randomness or complexity. Probability theory allows scientists to quantify this uncertainty and make predictions based on the likelihood of certain outcomes. It also provides a framework for understanding and analyzing the behavior of complex systems that may be affected by multiple random variables.

4. What are some challenges of applying probability theory to physics?

One of the main challenges of using probability theory in physics is the need for accurate and precise measurements. In order to make reliable predictions, scientists must have a thorough understanding of the system they are studying and be able to measure the relevant variables with high precision. Additionally, the use of probability theory may also introduce some level of subjectivity, as different scientists may interpret and apply it differently in their research.

5. How has the use of probability theory in physics evolved over time?

The use of probability theory in physics has evolved significantly over time, with many developments and advancements made in the field. Early applications of probability theory in physics focused on classical mechanics and statistical thermodynamics, while more recent developments have incorporated quantum mechanics and statistical mechanics. With the increasing complexity of physical systems being studied, the use of probability theory has become essential in making accurate predictions and understanding the behavior of these systems.

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