Those of us whose careers have included both teaching and research have long found that our students undergo a dramatic transition in ability between their undergraduate years and the end of their first year of graduate school. As undergraduates they would attend lecture-based classes and master course content by listening to their professors and slogging through weekly problem sets. (You know what this is like!) By the end of the semester, most of the class would understand most of the material, but would find it difficult to integrate it into a coherent picture of, say, classical electrodynamics. And a semester after a course had ended, most students would not have retained their mastery of the topic.

But after a year of graduate school—during which students would work on difficult material without the distracting edge effects of 50-minute class periods—their competence at navigating confusing subjects and difficult problems would increase enormously.

Project physics

You've already had some experience with this instructional mode if you've taken Physics 298owl (now Physics 246) from Prof. Gollin. It's different from fighting to stay awake for an hour in lecture, then sifting through the wreckage to extract what you need to do the homework assignment!

This course

If all goes well, you'll find this so captivating that it will be hard to put your work aside to attend to your other academic obligations. We suspect it is this strong engagement with a project that drives the transition from an undergraduate level of skill to the expert mastery typical of graduate researchers.

Prerequisites

You must already know how to program. If you've learned to code in python or C/C++, or Java, or some other language, you'll be fine. A B- or better in CS 101, CS 125, or Physics 298owl are suitable prerequisites. It's also fine if you've learned on your own. But if you've never programmed before, or did poorly in an intro CS course, you should delay enrollment in Physics 371 until after you've done some coding.

You must have a basic working knowledge of introductory physics at the level of Physics 211 and Physics 212. More is better, though not necessary.

We are not building robots

Physics 371 is not a course in building cute robots for the sake of learning to build robots. That would be an engineer thing, and we are physicists, not engineers. We are going to tackle measurements that—if they prove feasible—might make our corner of the world a little bit better. If we did build a cute robot, it would be to accomplish a significant end, for example recognizing the onset of a potentially catastrophic fall by an elderly person.

In Physics 371 you'll construct a hand-held device loaded with inexpensive sensors that are interrogated by an onboard microcontroller—a small computer larded with additional features such as timers and analog-to-digital converters—and write the data acquisition software necessary to perform the measurements associated with your project.

You'll assemble a prototype on a breadboard, construct a final (electrically equivalent) version on a printed circuit board, use a 3D printer to build a case for it, do field work, then write analysis code to understand what conclusions can be drawn from your data. You'll write a report presenting your results and justifying your conclusions, publish it to the web, and perhaps send it to the appropriate recipient—the Illinois Department of Transportation, for example.

Some possible projects

The intellectual tradition in physics is for researchers to build their own instruments (buying off-the-shelf parts when available), ultimately creating sophisticated devices to perform the measurements that will tell us about the physics we are researching. It is not like this in all fields; my wife's background is in bio-inorganic chemistry, and she would assemble reactors from stock components, then run reaction products through spectrometers built by vendors like Varian and Hitachi. So you'll be following the physics tradition, and you will be working in collaboration with three other students.

Some of the projects are probably best imagined as feasibility studies that might inform the design of a more definitive future measurement. We will see how it goes! Here are some that we have in mind. You are free to suggest other possibilities, though we reserve the right to veto anything that we feel is too difficult or too expensive.

Projects for Spring 2023 - final list!

1. How many beetles are in a corn field? Or in traps disseminated through them? Or on single cobs? Prof. Nick Seiter and his collaborators at ACES are interested in these questions. Maybe we can help them!
   • Using mockup targets (cobs, traps, leafs etc..) with fake beetles in the lab, we can try to develop a device capable of acquiring images of the target (also surveying the neighboring environment) and counting the number of beetles on the target via pattern recognition techniques. If this part of the project is accomplished successful, we can think about how to acquire data in fields! 
2. Mapping crowd flow across Loomis: can we instrument a device to measure the macroscopic flux of people through the (labyrintic) Loomis corridors? What about typical room's typical hourly occupancy? This may be useful for crowd control and optimization of social distancing measures!
   • What about pairing a movement sensor with associated picture acquisitions at ground level, to then count # of shoes? 
3. Live portable monitoring system for detector tests at accelerators! Every time we test a detector with a beam at an accelerator, it is crucial to keep track of the environment around the setup. Let's build a device to monitor and record this information. In this way, it will be possible to disentangle effects due to the tested detector from those induced by changes in the neighbouring environment. Standard (temperature, pressure, humidity etc.) parameters should be monitored and recorded, along with more complex quantities (electronic noise, magnetic field variations, etc.). The device should be easy to transport and setup, complemented by a user friendly DAQ and also equipped with a series of alarms that can trigger on certain measured quantities. If all of this is accomplished, it may be possible to instrument an alignment survey feature? 
4. Resuspension of particles can be used to study contamination after nuclear fallouts on a microscopic level (more info can be found here). Dr. Kaminsky and Illinois GS Nico Santiago are carrying out research on this topic at Argonne. We can help them by carrying out studies on resuspension generated by pedestrian and vehicles! 
   • Project 1: replicate the functionality of commercially available air quality monitors as well as expand upon them. One such sensor is the Purple Air PA-II which monitors concentration of dust particles in the air as well as temperature, pressure, and humidity. Additionally, we would like to have measurements of wind speed and direction. If time permits, this project would be made into a self-contained, portable, weather resistant, low power, Internet of Things (IoT) device that transmits its data to a central server.
   • Project 2: Study pedestrian resuspension of particles on sidewalk surfaces. This project would look to create a data pool that does not currently exist for resuspension studies. A Plantower sensor would be attached to a follow pedestrian, walking a set distance behind the first pedestrian. The 2 should measure a constant distance between them, while the measurement is taking place. The purpose of this experiment is to study how many particles are kicked up during a walking cycle over a set distance by various types of at different speeds.
5. Are water fountains in Loomis equally powerful? If I am in a hurry, shall I choose a particular one? How do they compare to other buildings? Let's find it out with a PHYS371-built device! 
6. Smart jacket for cyclists: can we instrument that to display, on the biker's back, turning signals and brake lights? We can also try to track the biker's heart rate, distance traveled, etc. We can extrapolate these quantities into different measurements, such as total calories burned.
7. Lab Room Temperature Distribution Analysis: the FORGE Lab would like to know how the temperature changes across our lab room, as it significantly affects some of our experiments. We have an understanding of how it changes in one spot, but there may be better spots to place our experiments that need temperature control. In particular, understanding what happens directly underneath vents and far away from them will help us prepare experiments for these conditions.
8. Macroscopic Collider: The measurements of cross sections are of great importance in particle physics. Can we design a setup to measure the (differential) cross section of a macroscopic collision, for example two air hockey pucks colliding with different impact parameters. What other physics phenomena can we measure with this apparatus?
9. The Mpemba Effect: does hot water actually freeze faster than cold water?
10. Predictive seismometry: Can we recognize seismic noise on a perimeter surrounding a sensitive device, and use this to predict the vibrations that will be experienced by the device? A possible application would be the stabilization of final-focus beam optics in a high energy linear electron-positron collider.
11. Daytime bovine methanogenesis measurements in a UIUC Animal Sciences barn. In the United States livestock generate more methane than nearly all other sources. Methane is an important, incredibly harmful contributor to climate change caused by greenhouse gas emission. Let's install a string of methane sensors, all read by an Arduino that is radio-linked to a WiFi-enabled base station.
12. Solar cell performance comparisons: control an NPN-based current source with an Arduino, see what various solar cells can do. I'm starting to use these in an agriculture technology project, and there are surprises in what I find. So let's scope this out in more detail.
13. Inertial navigation: how well can we integrate the rotations and accelerations of a Roomba autonomous vacuum cleaner to figure out where the device actually is?
14. An initial feasibility study of a rotating-mirror arthroscope. Orthopedic surgeons use an optical instrument called an arthroscope to view the surgical field during procedures such as joint repair. The typical field of view of an arthroscope can vary from 75° to 115°. Could we expand this to greater than 200° by synchronizing image capture with the orientation of a rotating mirror?
15. Spectral properties of African percussion instruments: Djembe vs. Conga. How (and why) does the sound change with technique?
16. Predictive shock mitigation on Illinois Central passenger trains. Amtrak rails are a mess just south of Kankakee. Could the bumps felt in one car be radio'd to a device in a car further towards the rear? It might allow an active suspension supporting a crate of delicate devices to better protect its cargo.
17. Noise produced by wind turbines. We want to do this in the time domain, not frequency domain.
18. Multiple-head IR non-contact thermometer. What would it take to measure the temperatures of a dozen subjects simultaneously? How fast can we do this?
19. Foot pressure profiles for users of standing desks. I like my standing desk, but should I be wearing protective footgear?
20. Airborne particulate concentrations in agricultural settings (outside/inside tractor and/or combine cabins)
21. Microphone-based, radio-linked vector anemometers (Prof. Gollin's invention!): could a sound engineer use these to correct (in real time) for wind-induced phase errors between towers of speakers in a large outdoor concert venue?
22. Pulse oximetry calibration issues. A pulse oximeter uses the relative absorption of light from 660 nm and 940 nm LEDs to determine the degree to which blood is oxygenated. The commercially available devices are calibrated for light-skinned subjects and can yield systematically incorrect results for subjects with darker skin. A Fall 2022 group investigated how to correct for this; we'd like to continue their work.

The style in which we will work

So what's this "Design Like a Physicist" business? It's a reasonably descriptive term for how we will go about things. Here is what we mean. If you took Physics 298owl from Prof. Gollin you'll remember that he had you hand-code a lot of algorithms—integrators, Fourier transforms—that could also be found in professionally produced libraries. For pedagogical purposes, he had you reinventing a lot of wheels.

That's not how we've gone about our own research. If there's a pre-coded numerical algorithm that we can use, we'll appropriate it, generally putting proper attribution to its source in comments in our own code. If there's a circuit we need that's described in an engineering web site, we'll use it, identifying its source on the schematic diagram.

You will keep track of your efforts in a physical paper notebook in which you describe your work, useful revelations, and calculations. You should put notes about techniques you find (or invent) into your noebook so you can find them later. We're not going to collect or inspect your notebooks, but we want to see them out, and open, during all of our class meetings.

Real physicists are fearless, and sometimes confused

You will be working with things for which your understanding will often be really blurry. That's OK, and in fact that's the usual state of things in research. Taking the time to understand every last detail about an IDE is a waste of time: it is better to focus your efforts on getting by, on muddling through. You will get more done this way than you would if you spent the time to understand everything completely. There is too much to do, and far more interesting things to consider than the arcane details of SPI and I2C interfaces. You will want to understand them well enough to work with them, that's all.