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PHYS 130B

Quantum Physics II

Schedule of Classes

  • Lecture: Mon, Wed, Fri. 3:00 PM - 3:50 PM, MOS 0204

  • Discussion session: Thu. 6:30 PM - 7:20 PM, WLH 2204

  • Instructor: Yi-Zhuang You (尤亦庄) (sounds like EACH-ONE, YOU) (He/Him/His)

  • Teaching Assistants: Shuhan Zhang. Email: shz091@ucsd.edu

Assessment Components

1. Preview Reports

Before each unit (§x.y), students use AI to preview the upcoming material. Each lesson page contains a Prompts box with guiding questions designed to help students engage AI productively. Students submit a preview report — their chat history with AI about the unit — before class starts.

  • Grading: Completion-based (graded on submission, not content).
  • Purpose: Arrive at class already familiar with the landscape, with questions that AI couldn’t fully resolve.

2. Homework

Each of the 60 lessons (§x.y.z) includes a Homework block with 5–10 problems. Choose 5 problems per unit (§x.y) to finish. You are welcome to use AI assistance.

  • Grading: Graded on timely submission, not correctness — since AI assistance makes correctness grading meaningless. Late submissions receive decaying credit.
  • Numbering: Problems are numbered 1, 2, 3, … within each lesson. Cross-references use format HW x.y.z.k (e.g., HW 1.1.1.3 = problem 3 of lesson §1.1.1).
  • Connection to final exam: The same problems will appear on the in-person final exam with possible slight variations, so students who genuinely engage with the homework — rather than passively copying AI output — will be well prepared.

3. Research Projects

Each student completes two research projects during the quarter, with AI assistance. Each of the 21 units (§x.y) in the lecture notes includes a research project at the frontier of physics research. Choose 2 projects to finish and submit project reports. Projects require genuine scientific inquiry — literature survey, computational exploration, and scientific writing — not just extended calculation.

  • Scope: Each project is designed to be achievable in approximately 2 weeks with AI assistance.
  • Deliverable: A written research report. Oral presentations to the class if enrollment permits.
  • Grading: Evaluated on correctness, novelty, and presentation quality (potentially with AI-assisted grading).
  • AI policy: AI can help with implementation (code, writing, calculations), but the student must drive the scientific inquiry and demonstrate understanding.

4. Final Exam (In-Person, No AI)

The final exam is held in person with no AI access. Problems are drawn directly from the homework assignments, with possible slight variations. This is the primary test of whether students have internalized the physical worldview and problem-solving skills — not merely copied AI-generated solutions.

  • Format: In-person, closed-book, closed-AI. 5 problems.
  • Content: Problems selected from the homework sets across all six chapters.
  • Philosophy: Students who genuinely learned from working with AI throughout the quarter — who built intuition, checked AI answers against physical reasoning, and developed their own understanding — will succeed.

Grading Breakdown

Component Weight Workload Grading Basis
Preview Reports 10% 1 report × 20 units Completion
Homework 40% 5 problems × 20 units Timely submission
Research Projects (x2) 20% 1 report Correctness, novelty, presentation
Final Exam 30% 5 problems Accuracy and understanding

Submission

AI Policy

Students are encouraged to use AI (ChatGPT, Claude, etc.) for all coursework except the final exam. This is not a concession — it is a core part of the pedagogical design. The course teaches students how to use AI effectively: how to ask good questions, how to evaluate AI-generated answers against physical reasoning, and how to spot hallucinations. The final exam, taken without AI, ensures that genuine understanding has been internalized.

Textbooks

[1] David Tong, Quantum Mechanics (Lectures on Theoretical Physics Volume 3). Cambridge University Press. DOI: 10.1017/9781009594806

Some other books for reference:

[2] J. J. Sakurai, Modern Quantum Mechanics. Addison-Wesley Publishing Company. (1994)

[3] R. Shankar, Principles of Quantum Mechanics. Plenum Press, New York. (1994)

[4] Arjun Berera and Luigi Del Debbio, Quantum Mechanics. Cambridge University Press, New York (2021).

Lecture Notes

/teaching/PHYS130B/notes/
Jupyter Book notes following David Tong's Quantum Mechanics, with consolidated lecture content, equations, and figures. Prepared with assistance from Claude Code and Cursor AI; all material has been reviewed by the instructor.

The course covers 6 chapters, 20 units (§x.y), and 60 lessons (§x.y.z). Each lesson corresponds roughly to one lecture’s worth of material. Two project periods (~2 weeks each) are distributed across the quarter for students to work on their chosen research projects.

Chapter 1 — Qubit (Tong §4)

  • Unit 1.1 — States and Observables (§4.1)
  • Unit 1.2 — Measurement (§4.2)
  • Unit 1.3 — Time Evolution (§4.3)

Chapter 2 — Identical Particles (Tong §8)

  • Unit 2.1 — Bosons and Fermions (§8.1)
  • Unit 2.2 — Angular Momentum (§8.2)
  • Unit 2.3 — Anyons (§8.3)

Chapter 3 — Path Integral (Tong §15)

  • Unit 3.1 — Quantization (§15)
  • Unit 3.2 — Propagator (§15.1)
  • Unit 3.3 — Stationary Phase (§15.2)
  • Unit 3.4 — Imaginary Time (§15.3)

Chapter 4 — Phase and Gauge (Tong §9, §11)

  • Unit 4.1 — Gauge Field (§9.1)
  • Unit 4.2 — Berry Phase (§9.4, §11.1)
  • Unit 4.3 — Landau Level (§9.2)
  • Unit 4.4 — Spin and Monopole (§9.3, §9.5)

Chapter 5 — Perturbation Theory (Tong §10, §11)

  • Unit 5.1 — Time-Independent Perturbation (§10.1)
  • Unit 5.2 — Time-Dependent Perturbation (§11.3)

Chapter 6 — Quantum Foundations (Tong §16)

  • Unit 6.1 — Density Matrix (§16.3)
  • Unit 6.2 — Entanglement (§16.1, §16.2)
  • Unit 6.3 — Generalized Measurement (§16.4)
  • Unit 6.4 — Open Quantum Systems (§16.5)