Course Syllabus
Physics 431 - Advanced Laboratory: Condensed Matter Physics
Experiments in condensed matter physics. Examples are Hall effect, nuclear magnetic resonance, statistics of electronic noise, superconductivity, and the Mössbauer effect.
Instructor
David B. Pengra
Office: Physics/Astronomy Building, Room B256A
Phone: 206-543-4783
email: dbpengra@uw.edu
Hours & Location
Room B248, Physics/Astronomy Building
Section A – Tuesday & Thursday, 1:30–4:20
Section B – Wednesday & Friday, 1:30–4:20
First 30-45 minutes may be used for lecture and general comments.
Required Reading/Viewing Material
Website
http://courses.washington.edu/phys431 (Standard URL links to Canvas page)
Text
There is no required text. Material will be provided through the course website.
Recommended References:
- Experiments in Modern Physics, Adrian C. Melissinos (Academic Press, San Diego, CA, 1966 or 2nd ed, 2003).
- The Art of Experimental Physics, Daryl W. Preston and Eric R. Dietz (John Wiley & Sons, New York, 1991).
- Introduction to Solid State Physics, Charles Kittel (John Wiley & Sons), any edition.
Copies of these books are available in the lab, for reference.
Overview
The 43x series of advanced laboratories are intended to provide a bridge between introductory labs, which are mostly "canned," in the sense that there is a fixed sequence of activities and a fairly rigid analysis to perform, and the kind of open-ended research found in real experiments, where you don't really know what will happen or how you should interpret the results. The physics itself is also more complicated than in the intro labs, both in terms of the underlying phenomena and the operation and interpretation of the experimental apparatus.
Measurement techniques, data analysis, and experiment interpretation form the three main emphases of the advanced labs. The first, measurement techniques, concern the things one usually associates with a lab course: experimental apparatus and its use. Measurement techniques in condensed matter span the range of nearly all experimental physics: techniques of spectroscopy (associated with atomic physics and astronomy) and particle detection (associated with nuclear physics) are used, as are measurements of light, magnetic fields, temperature, pressure, and other thermodynamic quantities. In nearly all cases, such measurements are converted to electrical signals for analysis. The phenomena of condensed matter physics are similarly diverse. This lab course has among its collection experiments in superconductivity, the thermodynamics of 2-d matter, the Hall effect, optical properties of metal films, nuclear magnetic resonance and its use in characterizing material properties, and the amazing energy sensitivity of the Mössbauer effect to measure the magnetic field inside metallic iron.
The advanced labs focus much more on data analysis and experiment interpretation than introductory labs. Data analysis include basic tasks often called data reduction, usually done with a variety of computer programs and computer coding, and further analysis of the reduced data to look at it in different ways, i.e., with different types of graphs, with fits to complex curves, and to consider any calibration steps. Often, the goal of data analysis is to derive final results from the measurements to compare to predictions from theory or to the results of other experiments. In some cases uncertainty calculations must be carried out to complete one's interpretation of the results. This lab will introduce the use of Python coding and useful Python packages in basic data analysis, curve-fitting, and making plots.
Interpretation of experimental results is distinct from data analysis. To interpret the results means to construct a story to explain them within the framework of physical theory, and to note and describe trends, patterns and anomalies in the data. Interpretation also combines the physics of the phenomena being measured (e.g., spin echoes in NMR) with the physics of the apparatus (e.g., the magnet, pulse generator and sequence, and pickup coil). You will be asked to do more than take data and write code: ultimately your goal is to understand and be able to explain the physics of both the experiment technique and the phenomena under study with it.
Learning Goals
"Learning goals" are the most important skills and understanding you should expect to learn by taking this course. At the end of this Condensed Matter Physics Laboratory course, you should be able to
- Explain the basic concepts and operation of a variety of measurement techniques used in the experiments you perform.
- Describe how the measurements reveal the underlying phenomena being studied in terms of the physical operation and chain of cause and effect in each experiment.
- Carry out complete numerical analysis of experimental data using Python and common computer libraries (numpy, LMFit, matplotlib, etc.)
- Explain features in experimental data in terms of known physics, and point out features of data that may not be captured by the expected models.
Rules
The following are rules. The first two may be subject to modification by the instructor, depending on circumstance. The second two are safety rules which cannot be violated.
- Experimental groups must be no larger than three persons. With four persons or more, there is not enough to do to keep everyone busy.
- No food or drink may be consumed in the lab. Washington State Law forbids the consumption of food or drink in these labs because they are officially "radiation laboratories:" there are radioactive substances in the lab.
- No students may work in the lab without the presence of lab staff.
Every person is welcome in this course. Instances of discrimination (e.g., shunning, belittling, bullying, harassment) for any reason (e.g., ethnicity, religion, sexual orientation, gender identity, different-ability, or political beliefs) will incur thorough investigation and possible sanction through University approved processes. If you believe you have been subject to such discrimination, please contact the instructor directly, or see University Policies for information on how to contact University officials.
Course Structure
The experiments will duplicate some foundational discoveries in condensed matter (CM) physics. All are associated with Nobel-Prize winning research, and the techniques used in them continue to be used in current research. This means that each experiment will give only a brief introduction to a deep, rich and complex sub-field in CM physics; indeed, one could easily spend 10 weeks on any one of the experiments and its related phenomena.
Each experimental cycle will include between 3 and 4 class meetings (i.e., be 2 weeks in length). All assignments associated with an experiment should be completed before starting a new experiment. The first meetings of a cycle will mostly involve learning the apparatus and making measurements; later meetings will mostly involve data analysis and interpretation.
Grades will be derived from (1) Daily Participation (Day X), (2) the Group Notebook (GN), (3) the Data Analysis (DA), and (4) the Individual Report (IR). More details on each of these is given elsewhere, but briefly, the Group Notebook is the group's data collection and analysis record. It includes information about the apparatus, links to/copies of data sets, and copies of hand-written notes or calculations, and may pull items from members' Individual Analysis. The Group Notebook will consist of a document prepared on Google Docs, submitted for grading as a PDF. The Data Analysis is a Jupyter Notebook written in Python, and submitted as a PDF for grading. The Individual Report is a brief written answer to specific questions concerning the interpretation of the experiment, also submitted as a PDF to Canvas.
Daily Participation credit is awarded as you show up to class, in person, to work with your partners. Students who are more than 15 minutes late to class will receive a lower grade.
There is no final exam (or any exam). Your grade is based on the work submitted.
Working Groups
Research is a collaborative process. Most scientific work is done in teams, some quite large. Even if you are a solo theorist, you need to talk to others to refine your ideas, brainstorm and challenge assumptions. Thus, learning how to work in a group is essential. In experimental research, projects are broken down into specific tasks to be accomplished by subject experts (e.g., coding, hardware, sample preparation) and those who may be learning the field (e.g., grad students).
You will be expected to form a group of 2-3 persons in your section. Group membership will be discussed during the first class meeting. You may already know people in the class you would like to work with.
After class, you should join a group by adding your name to a Google Doc linked on the main page. Ideally, you should communicate with possible group members before you form a group. The group memberships will be posted on the main page. Any students not in a group by the time of the second class meeting will be assigned to a group by the instructor.
Group members are not bound to the same group for the duration of the course, but if possible, those groups working well together will be preserved.
What Your Group Should Do
At minimum, your group must decide which members are primarily responsible for which tasks to complete the Group Notebook. Other members will be expected to review the work entered into the Group Notebook, comment on it and correct it, if necessary.
For each experiment there will be a set of tasks assigned to the group. For example, to create a diagram of the apparatus, to record and plot a data set, to perform basic data reduction, to carry out a particular calculation. Your group should decide who is primarily responsible for a particular task.
Members should also plan to rotate tasks from experiment to experiment. In other words, do not always have the same person draw the apparatus diagram, or carry out basic data reduction coding.
The other main purpose of the group is to work together to accomplish the data analysis tasks that should be completed by every member. Such tasks are important enough that these will be assigned to all students. However, it is expected that your group may work together and help each other solve these problems.
Videos
Course materials include two different types of videos.
Theory Lectures are about 15-40 minutes in length. These are voice-over-slide videos that discuss the important theoretical ideas behind the week's experiments. The focus of the "theory" is to help you make sense of the experiments themselves. The longer videos are copies of Zoom sessions from a previous version of the class.
Experiment Operation and Data Collection videos show an experiment in detail: what the apparatus is, how it is assembled, how the electronics are configured and connected together, and any other important physical detail you would need to know in order to operate it. The videos will also show how data are collected, plus other measurements needed for calibration or analysis. Experiment videos will be broken up into sections of variable length, typically between 5 and 25 minutes each. For example, one video may give an overview of the apparatus, another may delve into its setup and calibration, and a third may show how data are collected.
Not all experiments have the same number and/or duration of videos. Some experiments do not have any videos associated with them. Experiments that have less or no video material will have more in-person instruction.
Weekly Tasks
Attend class every scheduled session. Lectures will be given at the beginning of most sessions, especially at the beginning of each cycle. You also need to meet with your group to carry out the measurements as well as work on data analysis and discuss your interpretations. It is expected that students will work approximately 9 hours/week on this course, 6 hours/week in the lab and 3 hours/week at home. A full experimental cycle should take about 18 hours to complete, sometimes less, other times more. Over each experimental cycle, students should plan to accomplish the following tasks during the course sessions and at home.
- Watch any videos associated with the current experiment. These give overview of the experiment and how the apparatus is to be used. Not all experiments will have videos; for these you will get more direct instruction in the lab. (0-2 hours, depending on experiment)
- Do the experiment: assemble and learn to operate apparatus, take data, document the experiment in your Group Notebook. (2-6 hours, depending on experiment)
- Carry out data reduction and analysis in your Jupyter notebook for the Data Analysis. (5 hours)
- Annotate, discuss, and check each other's contributions to the Group Notebook (4-5 hours)
- Write your Individual Report, based on assigned prompt and consultation session. (2 hours)
Class Meetings
The first 1-2 class meetings of each experimental cycle will begin with a lecture on topics of importance for the whole class (course structure, overview of experiments, general principles of data analysis and uncertainty analysis). Depending on needs, lectures may be brief or take up to an hour. When groups begin working on experiments, those with instructional videos should review them. In-person instruction will be prioritized to experiments without videos and/or those with hazardous or challenging operations.
During most of the meeting time students will work with their group on the experiment and data analysis. See Working Groups above for details. You are expected to attend the full scheduled period.
Participation credit will be awarded based on an attendance record taken by the instructor or TA. Late arrival or early departure may result in a lower participation grade.
Remote Participation
In the event that you are unable to attend in person, you may coordinate with your group and the instructor to attend remotely and work with your group via a Zoom session. This might happen, for example, if you contracted a mild or asymptomatic case of COVID-19 or needed to quarantine but could otherwise attend to your courses. The instructor will assist the group members in the lab to set up a video link, but otherwise the session will be up to the group to manage and conduct.
Group Notebooks
The "group notebook" is the primary product of the working group. It should be created with a collaboration platform such as Google Docs. The group document should be made accessible to the TAs and instructor so that they can view and comment on it during the course of the experiment. The easiest way to do this is create such a document on Google Docs (or Microsoft OneDrive) and share it.
What Goes in the Group Document?
To complete the group document, use the notebook template posted on the experiment page. It lists tasks to be completed and some information on how to accomplish them.
Each person must indicate their contribution by initials and date. Every member must contribute to the notebook in an equitable amount. If a member has few or no credited entries, that person's grade will be lowered relative to the whole. This is standard scientific record-keeping practice. Do not "back-date" entries into the notebook, but be honest. Entries need to be made roughly equally by every member of the team.
More information on what should go into Group Notebooks, such as expectations for graphs, apparatus diagrams and annotations, discussion of data and results, inclusion of calculations and computer code, etc., are in Getting Started with Group Notebooks.
Data Analysis Assignments
All students should carry out data analysis individually. You may think of these like "homework" for a lecture class, but distinct from the writing focus of the Individual Reports.
There are two reasons for making everyone go through the coding and data analysis.
First, such assignments usually concern core concepts, such as creating a calibration, or finding an important quantity with a line fit. Everyone in the class should know how to do these things, not just the one person who might be assigned to that task in the group.
Second, among the learning goals of this course is building skills with computation as applied to experimental physics. Data analysis tasks will be carried out with Python on Jupyter Notebooks. This is part of an overall department effort to teach computation within the physics major. The use of Python is based upon current trends in physics research, data science generally, and the growth and maturation of collaborative tools associated with Python. See Python and Jupyter Notebooks for more information.
Consultations & Individual Reports
Consultations
The instructor (or TA) will meet with each group for about 15-30 minutes at some point in the experiment cycle to consult with the group members about questions concerning their experiment. Some questions are posted on each experiment page. Other questions may come up during the consultation. Based on the consultation, each member will be assigned to write about one of the questions for their individual report, although the consultation session will involve all group members.
Reports
Each group member writes and submits their Individual Report, as a PDF uploaded to a Canvas assignment. The content of each member's report will be discussed and agreed upon during the consultation, but there are a few common aspects:
- It must conform to strict formatting rules and length limits. Typically, a report must be between 1 and 3 pages, be typed, single-spaced, and use 11 or 12 point font and 1 inch margins.
- It must be written well, with complete, grammatically correct sentences and structured paragraphs.
- It must address the assigned writing prompt: typically questions about the experiment.
- It should have an opening paragraph to provide context so that the reader can understand what the report is about without having read the question (or done the experiment). This opening may contain summary of the experiment and results.
Experiments
The experiments available in this term are
Johnson and Shot Noise and Fundamental Constants
The Hall effect
Mössbauer spectroscopy
Surface plasmon resonance
Continuous-wave Nuclear Magnetic Resonance (CWNMR)
Pulsed NMR
Physical adsorption of gases
Low-temperature superconductivity
Groups may sign up for any experiment they have not already done. Links to information about these experiments are posted on the main course page.
Grading
Overall grade portions are 10% Participation, 40% Group Notebook, 20% Data Analysis, 30% Individual Reports. These are further broken down as described below.
Participation (10%)
Class attendance is required because you need to be in the lab to do the experiment and work with your partners. You also need to learn about any important aspects of the experiments and how to conduct them that may be described in lecture, and you need to be present for the consultation sessions. Participation is graded according to the A-F scale described below, where lower grades are assigned to students who are 15 minutes or more late to the lab session.
Lateness penalty: 15+ minutes: B, 45+ minutes: C, 60+ minutes: D, 120+ minutes: F
Group Notebook (40%)
Group document grading will reflect "real-world" assessments: the kinds of assessments that are typical in work environments and active research. Notebook assessments will be listed as letter grades A, B, C, D, F which correspond to numerical grades 4, 3, 2, 1, 0, (or 100%, 75%, 50%, 25%, 0%) and are based on the typical workplace assessments outstanding, exceeds expectations, meets expectations, does not meet expectations, nothing to assess. These may also have +/- refinements ("+" adds 0.3 to the numerical grade, "–" subtracts 0.3, i.e., +/- 7.5%).
Although the group notebook is nominally the product of the group, students will also be graded according to their own contributions.
Grades will depend on
- Credit: Entries / sections / contributions must be credited to one individual. All partners are expected to contribute substantially to the notebook (i.e., in roughly equal amounts of effort). Entries that are not credited may not count towards the notebook grade.
- Timeliness: Add information to the notebook as you do the experiment. Date the entries. A notebook mostly created after the experiment is done will get a lower grade. Missing dates will get a lower grade
- Context: Entries should explain what is recorded and what it means. Lack of context is the main reason notebooks receive low grades.
- Completeness: Everything produced by the group that the group needs should be in the notebook: raw data, apparatus diagrams, pictures of the setup, plots, equipment settings or operations you would need to duplicate the measurements. But: you should NOT copy Python code from the Jupyter Notebook unless you specifically discuss it in the context of some point you want to make. For example, you may copy code snippet to show how you did a particular calculation, but you should not reproduce the entire code block.
- Discussion and interpretation: Take some time to write down how you understand the experiment and what it means. Make your discussion quantitative and based on clear physics reasoning.
- Corrections and comments: Did you get a different result from your partner? If so, you should notice it and say so. Do you think that an entry needs more context? If so, provide that context, and initial/date it. All partners are responsible for all parts of the notebook.
Data Analysis (20%)
Data analysis calculations will be done in Jupyter notebooks on the JupyterHub for the course, converted to HTML, and uploaded to canvas for grading. They will be graded according to the letter scale used for the Group document (A-F).
Individual Report (30%)
The Individual Report will be graded according to the following criteria
- Length and formatting. Does the report conform to the required length and formatting criteria?
- Content - topic. Does the report discuss the assigned topic as determined during the consultation session?
- Content - correctness. Is the discussion correct in terms of physics theory and experimental facts, and is interpretation supported by argument?
- Writing quality. Are complete sentences used? Do paragraphs concern a single topic or related set of ideas? Are words, both technical and ordinary used correctly? Is the structure logical and easy to follow?
The Individual Report will be graded on the A-F scale, as described above.
If the report is turned in by the due date (or a mutually agreed upon extension of the due date) and it received a grade of B+ or lower, it may be revised and resubmitted once. Exceptions to the submission process may occur if there is not enough time to grade, return, and resubmit, such as at the end of the term.
Resubmissions are due within 1 week of the initial grade decision. The last report of the term will only be graded once, unless you have arranged with the TA or instructor on acceptable due dates.
If it is turned in past the due date, even if submitted within the grace period (see below), it may be graded only once.
ONLY INDIVIDUAL REPORTS many be resubmitted for regrading. Group Notebooks and Data Analysis are submitted and graded once.
To summarize:
| Contribution | Percent of total |
|---|---|
| Participation | 10% |
| Group Notebooks | 40% |
| Data Analysis | 20% |
| Individual Reports | 30% |
Due dates & Extensions
- There is one due date for the final version of the Group Notebook and Data Analysis: midnight (i.e., 11:59 pm) on the last class day of the experiment cycle (typically Thursday or Friday night, depending of section).
- The due date for the Individual Report is at midnight (11:59 pm) on the first class day of the following experiment cycle, e.g., Tuesday or Wednesday night, depending on section.
- There is an automatic grace period of 24 hours following all due dates. Think of this as an automatic extension, should you need to talk to the TA or instructor. You do not need to ask for this extension.
- Extensions beyond the grace period will be granted, but they must be requested before the end of the grace period. A new date will be assigned to work granted an extension. New dates will be decided by the TA or instructor. These will typically be set to 2-3 days following the request. There is no grace period attached to an extension; the only thing that will change is the availability date.
- Each student must individually request an extension for each assignment. Extensions must be requested in writing by email through Canvas. One student may not request an extension for other members of the group, except the lead who will turn in the Group Notebook.
- Without an extension granted and set in Canvas, the assignment will become unavailable following the grace period.
If you need an extension on the Individual Report and you want to have it subject to revise/resubmit grading, you must ask for the extension before the due date. Extensions requested after the due date will make the paper be graded once.
Grade Calculation
The final grade will be calculated according to the formula
| Grade | = |
|
× 4.2 |
Thus, to earn a 4.0, you need about 95%.
Writing ("W") Option
A writing "W" credit will be awarded to any student who earns at least 4 grades of B+ or higher on their Individual Reports.
University Policies
A number of University of Washington policies pertain to this course. See University Policies.
Course Summary:
| Date | Details | Due |
|---|---|---|