Physics 307: Science and Computers I, aka Computational Physics

At a glance:

  • Tuesdays and Thursdays, 5:00-6:20, Life Sciences Building 215
  • Instructors:
  • Office hours: Wednesdays 2-4PM and Friday 10-12AM or by appointment. Note that these office hours are shared with AST101 students, and there are a lot more of them than there are of you. If you would like to work intensively on PHY307 material with me, I’d be happy to arrange a session for you outside these times.
  • Course website: http://walterfreeman.github.io/phys307/ (you are likely here now)
  • Email address for homework submissions: suphysics307@gmail.com
  • Slack team for questions and conversation: suphysics.slack.com
    • Slack is the best way to ask technical questions and get a quick answer.
  • Course computer: phy-compphysclass.syr.edu

Asking for help

Please contact any of us with questions that arise outside of class; you will often get a prompt response. The best way for you to get help is to send a message to the #physics307 channel on the Slack team; otherwise, you can email me at wafreema@syr.edu or stop by my office at Physics Building 215. Please don’t email questions to suphysics307@gmail.com, since we generally only check that when we go to grade your work.

I encourage you to ask us to help you debug your programs once you’ve made an effort to figure it out yourself; while learning to debug code is important, I don’t want you to waste six hours trying to track down a missing minus sign or curly brace. We are here to help you! As a general rule, if your program isn’t compiling, write to us after five to ten minutes of trying to figure out what is wrong; if there is a bug of another sort, email us after fifteen to thirty minutes of trying to figure it out on your own. To encourage you to ask for help, there’s a participation component for the class – and asking questions out of class will earn you points as well as helping you learn things!

We will be covering a great deal of ground in this course, so if you don’t understand something or fall behind, ask for help; that’s what I am for. Learning computational physics often involves a lot of personal coaching and messy practice – it is more like learning to play the guitar than learning geography. (We will learn something about guitars in our class, in fact!)

Office hours

  • Wednesdays and Fridays, 9:30-11:30, and others to be added
  • I’m also often around – feel free to email me and set up an appointment at other times!
  • I can also hold “virtual office hours”. If I’m at home and you have a question, I’m very willing to help you by teleconference using your favorite tool (Google Hangouts, Discord, Skype, etc.), so long as it runs on Linux.

Course overview:

This course is an introduction to the art of using computers to aid in solving problems in physics and other sciences. You will learn the basics of programming a computer to do computations and physical simulations, as well as the equally important skill of interpreting the results that the computer gives. In this course we will teach you to use the C programming language (and possibly also Python) on a Linux system, but what you learn here will apply to many other languages and architectures. In fact, any of you who know another serious programming language are welcome to use it instead of C in my class; this list includes Fortran, Python, Julia, Java, Perl, and probably some others that I haven’t heard of.

First we’ll study the basics required to get around a Linux environment and learn some simple C programming. Then we will learn how to use those skills to accomplish some mathematical tasks, e.g. integrating functions. As part of our study of numerical integration, we will develop the tools required to answer questions like “How well can I trust a numerical calculation?” and “On what things does the numerical result depend?” We will then apply these skills to model various physical situations, picking up new programming and computational skills along the way. One of the most important is knowing how to interpret results from the computer, and when to suspect that your simulation isn’t accurately reproducing what you want it to reproduce. Along the way, you’ll discover how readily you can use computers to uncover insight about physics that aren’t widely known.

While we will study computer programming and the Linux environment, and these things are important aspects of this course, these are only tools; /the emphasis in this course will always be on the computational aspect/, even though you will spend a lot of time programming. However, the C-on-Linux environment we will be using is the gold standard for scientific computing. The tools you will learn in my class are the same tools used to program ten-thousand-processor supercomputers, and you can transfer these skills to other environments and languages (such as Python) if that’s what you use in your research.

Course philosophy:

This class is going to be a significant amount of work; I have high standards for what I want you to accomplish. However, you have a team of people on your side to help you: myself, the TA, the learning assistants, and your classmates. This class is emphatically not a class in which you attend lecture, learn things, go home and work by yourself, and submit a fully-formed clean result. Computational physics, and especially the process of learning it, is messy. You should ask questions – early and often. The teaching staff and I will all be happy to answer your questions in class. Help session hours are a good time to work on your projects, when folks are around to answer your questions.

In this class you will begin by learning basic skills needed to program and control a computer in a Linux/Unix environment. You will then use those skills to implement basic computational algorithms (in particular, numerical integration) and study their accuracy, and in the process learn about visualizing and intepreting data.

We will then apply these skills to model various physical situations, picking up new programming and computational skills along the way. One of the most important is knowing how to interpret results from the computer, and when to suspect that your simulation isn’t accurately reproducing what you want it to reproduce. Along the way, you’ll discover how readily you can use computers to uncover insights about physics that aren’t widely known.

While we will study computer programming and the Linux environment, and these things are important aspects of this course, these are only tools; /the emphasis in this course will always be on the computational aspect/, even though you will spend a lot of time programming. However, the C-on-Linux environment we will be using is the gold standard for scientific computing. The tools you will learn in my class are the same tools used to program ten-thousand-processor supercomputers, and you can transfer these skills to other environments and languages (such as Python) if that’s what you use in your research.

If you are comfortable with any other programming languages (Python, Fortran, Java, Julia, Perl…) you may use those for my class as well. All of the graphics tools we will be using don’t care what language generated the data.

Also, I want to make sure you all know that my door is always (figuratively) open to help you with whatever other issues arise this semester. If you need help in another class or if you just have a question about physics in general, please ask me. I am a teaching professor, so it is my full-time job to help students!

A project-based course?

This course has no textbook, as few lectures as I can get away with, and a nonstandard/optional final exam. Instead, the bulk of your opportunity to learn computational physics and to demonstrate what you’ve learned will come from the computational projects you will complete throughout the semester. You will have time during class to begin your projects, but you will also work on them outside.

After completing each project, you will write a report (in prose, not in code) describing what you did. This report should focus on computational science, algorithms, and physics – not mostly on programming nuts and bolts. (A little discussion of programming is okay.) Your report should address questions like:

  • What are you trying to study? What questions are you trying to answer?
  • What algorithms are you using? How are you modeling the system in question?
  • Were there any particularly thorny issues in writing your simulation? How did you address them?
  • What data did you generate? (Graphs, animation captures, and the like…)
  • What do your data mean? Why do they look the way they do, and how do you interpret them?
  • What’s the answer to the question you posed in the beginning?
  • What insights into computational science and physics did you develop along the way?

You should invest a substantial amount of time into writing your report. In general, the time in your projects will fall in three categories:

  1. Write some code that calculates or simulates something
  2. Use that code to calculate or simulate, study its behavior, and interpret your results
  3. Write the report that describes your findings.

Don’t underestimate the effort it will take to do (2) and (3) well; in this class, writing your code is only the first step.

We will grade the project reports and give you a grade, and give them back to you with comments. If you get a low grade, you should meet with the teaching staff and arrange to revise and resubmit your report for a higher grade.

Grading philosophy:

Many classes have the following pattern:

  • There are lectures and homework, where you spend a lot of time learning stuff (we hope)
  • There are exams, where you have a little time to do sutff
  • If you are able to do the stuff, you get a high grade; if not, you get a low grade
  • The difficulty of the exams is set so that some students, but not all, can do the stuff well

This class, instead, has a different pattern:

  • There are short lectures, where I introduce some stuff
  • You spend a lot of time doing stuff, and we help you along the way
  • You write about the stuff and what you learned from it
  • Your grade is based on the stuff you did and the insight you get from it

We expect your grades to be quite high as a result, since your grade is based on the things that you learn and achieve, not a high-stakes exam that you either pass or fail.

This class is a significant amount of work, but we will support you as you do it. If you feel like you’re getting behind, please come talk to me; in the past, we’ve had multiple students fall behind and catch up.

Grading

Most of your grade will come from the project reports.

If you will be late turning in a project, let us know in advance and request an extension. Otherwise, late reports may receive a 10% penalty. This is just to encourage you all to stay current with what we’re introducing in class.

You will receive a participation grade based on both in-class and out-of-class participation. “Out-of-class participation”, you say? Remember that since this is a project-based class, I expect you to spend lots of time outside class working on your projects and/or helping your peers with theirs.

Your score will be computed as follows:

  • Projects: 80%
  • Participation: 10%
  • Exit interview: 10%

The final exam for this class will be unconventional. There is no regularly-scheduled final. Instead, you will schedule 20-minute “exit interviews” with me during finals week, where you will come talk to me about what you’ve done in class. This is not an exam, and we don’t expect you to study for it; instead, I may ask you about the work you’ve done, and what you thought about the course.

Incompletes: A grade of “incomplete” is a provisional grade given to any student who is unable to complete the coursework during the semester due to unavoidable personal problems. In general, a student is eligible for an incomplete if they are substantially unable to come to class or study for a period of two weeks or more, or one week in the last month of class, due to personal illness or injury, illness or injury in the family (including significant others), legal involvement, or international issues. Please contact me if you feel that you might need to take an incomplete in my class, and we can discuss your options.

Computing environment:

As you might expect, you will be using computers quite extensively in my class. There is a course computer running Linux which you can access via ssh to phy-compphysclass.syr.edu. You are welcome to use the machines in the classroom to do this at any time, or you may connect from your personal laptops (running any OS; you will need a few pieces of free software if you are on Windows).

You are encouraged to instead do all of your computing on your personal machines. You are welcome to bring your personal laptops to class and use those in lieu of the machines provided; this is probably the better solution if you have a Mac or a laptop you want to install Linux on. If you need any help getting things working on your own machines, please ask.

Macs will be usable without much hassle, since OSX is quite similar to Linux under the hood. If you have a Windows machine, it is generally not that difficult to set up a dual-boot Linux environment or a virtual machine; I can help you with this, and can provide you with the graphics software installed on the course system. You are welcome to use any other C-on-Unix environment you have access to.

If you have a Mac or a Linux system, you will likely get smoother graphical performance if you run things locally, especially if you live off campus, once we start making 2D and 3D animations.

Learning objectives

After this class, students will be able to:

  • model physical systems in ways suitable for computational attack
  • make and defend an informed choice of a numerical algorithm to simulate these models
  • implement these algorithms using tools like those used in professional research, such as C, Linux, and gnuplot
  • visualize the data from their simulations in ways that contribute to “data storytelling”
  • validate and interrogate simulation results, since numerics often involve many approximations
  • synthesize insights about general principles of physics from their simulations

Students with disabilities:

If you believe that you need accommodations for a disability, please contact the Office of Disability Services (ODS), located in Room 309 of 804 University Avenue, or call (315) 443- 4498 for an appointment to discuss your needs and the process for requesting accommodations. ODS is responsible for coordinating disability-related accommodations and will issue students with documented disabilities Accommodation Authorization Letters, as appropriate. Since accommodations may require early planning and generally are not provided retroactively, please contact ODS as soon as possible.

More informally, if there is anything I can do for you, please ask me. I am around to help you, whether that is with a disability, disruption due to illness, personal issues, or anything else. I have an excellent working relationship with ODS, and am willing to do anything in my capability to ensure that my class is accessible and welcoming to all.

Academic Integrity:

I encourage you to work on your projects in groups, and to receive help from and offer help to your peers. You must write your own code, with the exception of “pair programming” exercises in which you will collaborate with another student to get started on projects. I encourage you to get assistance from your peers with your work, although substituting someone else’s understanding for your own constitutes academic dishonesty. In the event that you receive substantial help from another student in writing your code, please acknowledge their help in the code comments. If you actually copy-and-paste code from another source, you must

  • understand how it works and what every piece of it does
  • tell me explicitly which code you copied and where you copied it from

Some of your later projects may be group projects. In this case, obviously, you will share code/data/etc. and write your report jointly, but everyone in the group is responsible for understanding everything the group submits.

The complete Syracuse University code of academic integrity can be found online, and its requirements are incorporated by reference.

Religious observances:

(The following is common to all SU classes)

SU’s religious observances notification and policy recognizes the diversity of faiths represented among the campus community and protects the rights of students, faculty, and staff to observe religious holidays according to their tradition. Under the policy, students are provided an opportunity to make up any examination, study, or work requirements that may be missed due to a religious observance provided they notify their instructors before the end of the second week of classes. An online notification process is available for students in My Slice / StudentServices / Enrollment / MyReligiousObservances / Add a Notification.

(The following is specific to this class)

I believe SU’s religious observance policy discriminates against nonreligious people by privileging religious observances over secular events of equal importance. Thus, events of equal solemnity to major religious observances, occurring on inflexible dates, will be given the same deference as religious observances. This includes weddings and commitment ceremonies of immediate family members, funerals, caregiving duties for sick family members, other family emergencies or singularly-important events, job interviews, and the like. Note that I treat exceptionally close friends and romantic partners as family members.

Additionally, participation in political activity occurring on inflexible dates – attending a demonstration, canvassing for a campaign, or the like – will be given this same deference, regardless of affiliation.

If you need to miss class for such a reason, please notify Dr. Freeman as far in advance as practical to discuss arrangements.