Physics II

PHY102 — Calculus-based, Notebook-enhanced

📚 Dr. Arif Solmaz
📅 Spring 2026-27
⏱ 14 weeks · 3 hrs/week
📧 arif.solmaz@istun.edu.tr
"I can analyze any circuit or field and predict its behavior"

Course Information

Course Code
PHY102
Semester
Spring 2026-27
Credits / Hours
3 hours/week
Format
Google Colab Notebooks
Methodology
Configuration → Law → Equation → Prediction → Verify
Office Hours
Wednesday, 09:00–11:00 AM

Course Description

This calculus-based physics course covers electricity, magnetism, circuits, and optics through Python-enhanced simulations. Given any electromagnetic system (charges, fields, circuits, waves, light), students learn to identify the configuration, choose the right law (Coulomb, Gauss, Kirchhoff, Ampere, Faraday), write the equation, predict the measurable quantity, and verify with simulation.

The course follows a consistent methodology: Configuration → Law → Equation → Prediction → Verify. Each week uses one notebook containing the lecture and problem activities, delivered via Google Colab.

Learning Outcomes

Upon successful completion of this course, the student will be able to:

  1. Calculate electric fields and forces using Coulomb's law and the superposition principle.
  2. Apply Gauss's law to predict electric fields for symmetric charge distributions.
  3. Analyze DC circuits using Kirchhoff's rules and predict voltages, currents, and time behavior in RC circuits.
  4. Predict magnetic forces on moving charges and current-carrying conductors using the Lorentz force law.
  5. Apply Ampere's law to predict magnetic fields from symmetric current configurations.
  6. Use Faraday's and Lenz's laws to predict induced EMF and current direction in changing magnetic flux scenarios.
  7. Analyze RLC circuits for resonance conditions, natural frequency, and damping behavior.
  8. Apply geometric optics (Snell's law, lens equation) and wave optics (interference, diffraction) to predict light behavior.

Weekly Schedule

Week Topic Key Content Weekly notebook
Phase 1 · Electric Fields & Energy (Weeks 1-3)
01
The Invisible Force: Charge, Coulomb & Electric Field
Superposition, point charge fields, 2D field vectors Week 1 notebook
02
Energy Landscape: Electric Potential
Potential-field relationship, work/energy, potential surfaces Week 2 notebook
03
The Symmetry Shortcut: Gauss's Law
Symmetry, closed surface flux, symmetric field distributions Week 3 notebook
Phase 2 · Storing & Moving Charge (Weeks 4-6)
04
Storing Energy: Capacitors & Dielectrics
Capacitance calculation, energy storage, series/parallel Week 4 notebook
05
Predicting Circuits: Ohm & Kirchhoff
Junction/loop analysis, circuit solving, voltage divider Week 5 notebook
06
Time Behavior: RC Circuits
Charge/discharge, time constant τ=RC, low-pass filter concept Week 6 notebook
Phase 3 · Magnetism & Induction (Weeks 7-9)
07
The Other Force: Magnetic Fields & Lorentz
Moving charges in B fields, circular orbits, velocity selector Week 7 notebook
08
Creating B Fields: Ampere's Law
Long wire, solenoid, toroid, right-hand rule Week 8 notebook
09
Change Creates Current: Faraday & Lenz
Induced EMF, direction, generator model Week 9 notebook
Phase 4 · AC & Resonance (Week 10)
10
Resonance: RL & RLC Circuits
RL step response, RLC natural frequency, damping, Q factor Week 10 notebook
Phase 5 · Unification — Maxwell (Week 11)
11
The Grand Unification: Maxwell & EM Waves
Fields creating each other, EM wave concept Week 11 notebook
Phase 6 · Light — Fields You Can See (Weeks 12-13)
12
Tracing Light: Geometric Optics
Reflection/refraction, Snell's law, lenses, image formation Week 12 notebook
13
Light as a Wave: Interference & Diffraction
Double slit, grating, diffraction patterns Week 13 notebook
Phase 7 · Proving Mastery (Week 14)
14
Capstone: Configuration → Law → Predict → Verify
Full project: EM system analysis + verification Week 14 notebook

Course Delivery & Learning Contract

What Students Can Expect Every Week

  • Protected class time: the 3-hour session starts and finishes according to the official timetable, with a visible agenda and planned breaks.
  • Clear explanation: each major idea follows explain → worked example → prediction → test → interpretation.
  • Questions and voice: questions are welcome throughout; checkpoints reserve explicit time for think-pair-explain, misconceptions, and open questions.
  • Professional purpose: the course is designed for Mechatronics and Computer Engineering students and repeatedly connects concepts to circuits, fields, sensing, communications, optics, and computing hardware.
  • Exam alignment: notebooks label the reasoning moves rehearsed on assessments. Exams use the same verbs and standards with new values or contexts.
  • Materials: weekly notes, runnable examples, core practice, feedback checkpoints, optional extensions, and references are provided from the start of the term.

Assessment & Grading

ComponentWeightDescription
Midterm Exam 25% Written/practical exam covering Weeks 1-7 concepts
Final Exam 50% Comprehensive exam covering all 14 weeks
In-Class Project Demonstration & Technical Explanation 25% Live demonstration or presentation during scheduled class time, scored with the published rubric; weekly notebooks are private practice

In-Class Demonstration Rubric

  • Completeness: Core functionality demonstrated during the scheduled class
  • Correctness: Solutions produce expected physical predictions for given configurations
  • Methodology: Evidence of Configuration → Law → Equation → Prediction → Verify approach
  • Verification: Simulation results compared with analytical predictions

Course Policies

Attendance

Regular attendance is expected. Students who miss more than 30% of classes may be denied the right to take the final exam, per university regulations. Weekly notebooks are private practice and are not used as an attendance record.

Academic Honesty

All assessed exams and live demonstrations must represent your own understanding. You may discuss general approaches with classmates, but you must be able to explain and adapt the solutions you demonstrate. The following are considered violations:

  • Copying solutions from another student or external source without attribution
  • Sharing your exercise solutions with other students
  • Presenting AI-generated work that you cannot explain, test, or modify

AI Tool Usage

AI assistants (ChatGPT, Copilot, etc.) may be used as learning aids to understand concepts. However, you must be able to explain and modify any work you demonstrate. Exercises are designed to build your physics intuition progressively — bypassing them with AI defeats the purpose and will leave you unprepared for exams.

Communication

For course-related questions, email arif.solmaz@istun.edu.tr with your course code (PHY102) in the subject line. Office hours: Wednesday, 09:00–11:00 AM.

References & Resources