Ph 2B Winter 2025

Physics 2B - Intro to Quantum Physics, Jan-Mar 2025

Physics 2B is a 10-week introduction to quantum physics for students not planning to major in physics or applied physics.

from https://twitter.com/JuliaCramer/status/1625120134393102336/photo/1

Instructor: Brad Filippone
Office: 360 Lauritsen Lab;  Mail Code: 356-48; Phone: x4517; E-mail: bradf AT caltech.edu

Course assistant:  Leona Kershaw (lkershaw at caltech.edu)

Prerequisites:
Math 1abc or equivalent (differential equations, complex numbers, ...)
Physics 1abc or equivalent (mechanics, special relativity, electromagnetism)

Lectures:
Tuesdays and Thursdays, 11:00-11:55, 201 E. Bridge
Any changes will be announced well in advance

Textbook for Phys 2b:
David Griffiths, Introduction to Quantum Mechanics, 3rd ed; (Amazon)

Other resources: Liboff, Introductory Quantum Mechanics, 4th ed;
Also French & Taylor, Eisberg & Resnick, Feynman lectures
There are many other good introductory QM textbooks.

Class Notes:

Week 1:  Lecture Notes + Bonus Content: NOVA - Einstein's Quantum Riddle   (full video),  Black-Body_Radiation_Handout
(math details FYI - not required reading)  Photoelectric_Effect_Handout
(exp details FYI - not required reading)
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
Week 8
Week 9
Week 10

Problem Sets:
Due at 9pm on date listed in Syllabus. Solution sets will be posted shortly after on the web (see syllabus). You are strongly encouraged to study your returned set and be sure to understand any parts that lost points.  Problem sets are essential for mastering the material in this class!

Exams:
There will be two Quizzes and a Final Exam. All will be take-home and "limited" open-book (only the text and class notes allowed). The final exam will be comprehensive.

Grading: 50% Problem Sets, 25% Quizzes, 25% Final Exam

TA Contact info: 

• Head TA: Dariel Mok
• GTA 1: Francesco Calisto
• GTA 2:  Akiyoshi Park
• GTA 3:  Guangyi Zhang

There will also be 2 undergraduate graders.

• Guangyi Zhang: 10 am, Friday (except for 1/10 at 10 am on ZoomGuangyi Zhang: 10 am, Friday (except for 1/10 at 10 am on Zoom https://caltech.zoom.us/j/4336776873?omn=89362525053)
•  Akiyoshi Park: 3:30 pm, Friday @ 114 E Bridge
•  Francesco Calisto: 9 am, Thursday @ 4th floor Downs-Lauritsen (except for first two weeks: 1/10 (Fri, 10 am) &  1/15 (Wed, 10 am), on Zoom - see link under Recitation)

Graders: Jacob Chang (HW 1, 4, 7), Emily Hu (HW 2, 5, 8), Luke Lamitina (HW 3, 6, 9)

Course Ombuds

Extensions:

• There is a 5 min grace period for turning in assignments/exams; after this it will be considered late. If you have technical issues during the submission process that cause your set to be submitted a couple of minutes late, please notify the Head TA immediately.
• OFFICIAL policy: Work (the entire problem set) will be accepted late, with a 10% penalty for each day that it is submitted late (e.g. 0-24 hours late = 90% credit, 24-48 hours late = 80% credit, etc.). Please put a note at the top of your problem set if it is late. Exams will not be accepted late unless you have a valid extension before the due time.
•  Free extensions (so-called "sleep-days") for up to 8 days are allowed without question (like a silver bullet). For example you can submit 8 sets up to 24 hrs late or one set up to 8 full days late. Please put a note at the top of your problem set that you are using your sleep day(s). You cannot use sleep-days for Exams.
• Additional extension requests (to Head TA) can be granted for a good excuse (eg, major illness).  Please try to request extensions prior to the deadline.  Depending on the situation (e.g. for longer requests, extensions on exams, requests after the deadline), you may be asked to provide some sort of letter/proof with your request.  Extension requests for planned travel (e.g. attending a conference, etc) will not be accepted since they are planned well in advance.
• Sets and exams will be submitted via Gradescope.
• Late papers make far more work for the graders, who have their own set of pressures and deadlines as matriculating students. There is no entitlement to extensions, so please do not be demanding.

Honor Code and Collaboration policy:

• All assignments are governed by the honor system.
• For assignments, you may not use sources that contain the answer to a problem or to a very similar problem (more details below)
  
  • In particular, do not use solution sets from previous years, problem/solution books, or internet searches at any time. Exams and their solutions from past years are not to be used in any fashion.
• Discussion with others is encouraged, but then you should go off alone and write it up; the work you hand in must be your own.
• Mathematica may be used in problem sets, or in exams for getting past some mathematical chore (not for gaining knowledge of the physics). It should never be necessary; it is much better to master the mathematical analysis yourself without help from Mathematica. If you choose to use Mathematica anyway, make sure you simplify the result as much as possible, so that it is easy to see what the math is telling you.
• Please attend class and section meetings!
• Please ask questions of the TA's and the prof.
• Please clearly write your name, date, assignment number on all of your assignments and exams.
• Clearly mark the problem numbers and answers.
• Please write as neatly as possible. A human being is trying to read your work well enough to give credit!

Feedback:
I greatly appreciate student feedback; providing feedback prior to the end-of-term evaluations allows the instructor to modify the class to fit your needs. I also welcome any comments in person, by email to bradf AT caltech.edu, or talk to your:

Ombudspeople:
Ombudspeople are student volunteers who represent the students of each of the undergrad houses. They collect suggestions, comments, complaints, etc, and present them to the instructor at a mid-term meeting (free lunch!). Talk to your ombudsperson!

Handouts, Exams, Solutions, etc: Access to this material is restricted to Caltech (i.e. VPN)

PMA guidance on the usage of artificial intelligence, internet resources, and online tutoring in
classes

A primary goal of education is to learn how to approach and how to think about problems.
Rapidly evolving generative artificial intelligence tools (e.g. ChatGPT, Bard, etc), online tutoring
services (e.g. Chegg) and internet resources (e.g. Google) have the potential to be powerful
companions for learning. On the other hand, they also provide tempting shortcuts to solutions
that can be seriously detrimental to student learning. The course policies below serve to ensure
that artificial intelligence (AI), internet resources (IR) and online tutoring (OT) usage in our class
is carried out responsibly and ethically.

Permissible Uses of AI, IR & OT
• Augmenting learning: AI, IR & OT can be used as a virtual TA to help clarify concepts
learned in class, to provide example problems/solutions that supplement course material,
and to inquire about advanced topics beyond the scope of the course.
• Brainstorming: If the instructor explicitly allows use of AI for a particular class
assignment, AI may be used to as a virtual classmate to provide criticism of the student's
ideas or to help seed new ideas/hypotheses.

Prohibited Uses of AI, IR & OT
• Generating solutions: Unless explicitly allowed by the instructor, AI, IR & OT cannot
be used to generate answers to any class assignment (e.g. problem sets, quizzes, exams),
even if the student revises or recreates the content. If there is any confusion about AI, IR
& OT policy, the student should seek clarification before using them for any assignment.
• Plagiarizing: AI models are trained on large amounts of data, some of which may consist
of other people's work or even copyrighted material. It is the student's responsibility to
make sure that original creators are properly credited.
Guidelines for Using AI, IR & OT in Permissible Cases
• Transparency: Students must be transparent about their use of AI. This means that on
any assignment submitted for grading, they must disclose what parts were generated or
edited by AI. If there is any confusion about AI policy, the student should err on the side
of more disclosure.
• Academic integrity: If a student includes material generated by an AI program, it should
be cited like any other reference material. Any plagiarism or other form of cheating are
considered a Caltech Honor Code violation.
• Understanding and Learning: Students may use AI, IR & OT to enhance their learning.
However, these should not replace primary methods of learning, such as attending
lectures, reading assigned textbooks, participating in sections and office hours, and
practicing independent problem-solving. Students should take advantage of the unique
opportunities associated with being enrolled in-person at Caltech.
• Critical thinking: Students should note that material generated by AI, IR & OT may be
inaccurate, incomplete, or otherwise problematic. Students should ensure they arelearning from reliable sources. Beware that over-reliance on these tools may also stunt the development of independent thinking and creativity.

Consequences of Violating the AI, IR & OT Use Policy. Any student who violates the AI, IR
& OT use policy for their class are subject to the same disciplinary actions as they would face for
a Caltech Honor Code violation.