String theory for the curious / 数理物理学 (2026)


Overview

I revived the slot with the title Mathematical Physics / 数理物理学 in the Graudate School of Physics in 2024, and use it to give a lecture on basic algebraic topology aimed for theoretical physicists for two years. This year I'm going to discuss string theory instead.

This will be a course to introduce string theory for those who do not intend to become string theorists themselves but are curious about what string theory actually tells us at the graduate school level. For example, you might have heard that string theory is a prime candidate for quantum gravity and that string theory has been a source of new mathematics.

What do these statements actually mean? I intend to answer these and other questions you might have in the lectures, not just at the level of books for the general public, but hopefully in a way convincing to those who already understand physics at the undergraduate and the basic graduate level. I would welcome the participants to pre-submit the questions from this web form so that I can prepare better in advance. And here are the submitted questions so far. Please keep them coming!

It so happened that the ability of LLMs became equal to or above that of average graduate students, just before this class. I think it is a good opportunity for us to discuss the implications toward graduate school educations. I would welcome your feedback.

Misc info

Plan of the lectures

Lecture 1: What do you want to know about string theory?
After giving a general overview of the course, we'd like to have an open question session, to assess what the audience members want to know about string theory. Honest and direct questions will be appreciated, and you can pre-submit the questions from the web form. I will not be able to answer all the questions on the spot, but will try to answer them over the course of the lectures.
Lecture 2 & 3: What is so hard about quantum gravity?
I would like to review which theoretical aspects of quantum gravity are harder than quantum versions of other parts of the real world.
Lecture 4 and onward:
The content will be chosen depending on the questions I received during the lecture 1.

To get credits

In the past I usually suggested a list of problems for you to work on as your term-end project paper, and gave credits according to that. But with powerful LLMs now available, any such problems would be very easily solvable by just paying $100 to either OpenAI or Anthropic. That said, confining you for 90 minutes for a written exam, and watching over you during the exam so that none of you use smartphones to cheat, also sounds absurd for this type of lectures.

So I don't really know what to do. Any suggestions?

Date and time

Autumn semester, 2nd slot of Thursdays, from 10:25 to 12:10.

Date Summary Comments
1. Oct. 8 General introduction to the course
2. Oct. 15
3. Oct. 22
4. Oct. 29
5. Nov. 5
6. Nov. 12
7. Nov. 19
* Nov. 26 no class due to university schedule
8. Dec. 3
9. Dec. 10
10. Dec. 17
11. Dec. 24
* Dec. 31 no class due to holidays
12. Jan. 7
13. Jan. 14
* Jan. 21 no class due to university schedule
14. Jan. 28

email: yuji.tachikawa_at_ipmu.jp