Welcome to PHYS 276!!

1. Welcome to PHYS 276!! • Instructor: Johnpierre Paglione, Assistant Prof. • Started Jan 2008 • Area of Research: Condensed Matter Physics

2. Exotic Metals, Magnets and SuperconductorsProfessor Johnpierre Paglione high magnetic field experiments exploration of new phases of matter ultra-low temperature thermoelectric transport measurements new materials exploration see http://www.vector.umd.edu

3. My Office: 1367 – CNAM 2nd floor

4. Teaching Assistant: Introduction: Nightvid Cole

5. Introductions Name, class, major?

6. PHYS 276: E & M experiments

7. PHYS 276: E & M experiments • Learn experimental techniques and equipment for studying electricity and magnetism • Reinforce understanding of E&M and electronics gained last semester in lecture course through hands-on experience • Learn importance of proper recording keeping and scientific writing for experimental science: learn how to write a lab report • Further develop skills in error analysis, beyond that gained in 174, 275 web page: http://www.physics.umd.edu/courses/Phys276/

8. PHYS 276: Syllabus Our contract: let’s go through it.

9. ELMS/Blackboard Will use to turn in our in-class spreadsheets and our Lab reports. Will try it out at the end of this class, after we do a little refresher exercise

10. Lab Reports See pgs. 2-3 of lab manual and “rubric” on class web page lab reports for 4 labs: #1 - Ohm’s Law #2 - Magnetic Fields #4 - RC/LR Circuits #6 - LRC Circuits (6a and 6b – combined report)  please hand in hard copy AND upload doc/pdf/tex to ELMS Note: figures from lab manual available on 276 web page. REPORTS DUE: 1 week after lab @12PM (first one to my office)

11. Schedule  XLS spreadsheet due after EACH LAB

12. Schedule FORMAL REPORT DUE

13. Lab 0 (today!) • Error Analysis and Oscilloscope Refresher • Remember error calculation… • practice doing linear fits • practice measuring signals with the scope

14. Lab 1 • Electric Circuit Basics • Remember what current, voltage, resistance are. • Remember the basic symbols used for common circuit elements • Measure the internal resistance of a battery • learn how to take into account imperfections in meters when doing data analysis • practice doing linear fits • learn about diodes and LEDs FORMAL REPORT

15. Lab 2 • Magnetic Fields due to Currents • Remember the Biot and Savart law and Ampere’s Law • learn how to use a Hall probe to measure magnetic fields • remember the field due to a current loop, a coil, and a toroid FORMAL REPORT

16. Lab 3 • Force on charged particle due to electromagnetic fields • Remember the Lorentz Force • use an electron gun • learn how to take into account the earth’s magnetic field when doing magnetic experiments Will not do!

17. Lab 4 • RC and LR circuits driven by a DC/step source • remember what capacitance and inductance are • remember what the time constant is for circuits containing RC and RL elements • use WAVESTAR to transfer data from an oscilloscope to a computer

18. Lab 5 • RC Circuits driven by an AC source • Remember “AC” circuits • Remember about phases in AC circuits FORMAL REPORT

19. Lab 6 • LRC Circuits driven by a sine wave voltage generator (2 parts) • Observe resonance • LRC circuits driven by a square wave voltage generator FORMAL REPORT

20. Lab 7 • Diode and Rectifier Circuits • more on diodes • building a crude AC to DC converter

21. Lab 8 • Transistor circuits (new lab) • basic stuff – IV characteristics, amplification • building a simple oscillator • help us debug!

22. Goals • further develop skills in error analysis, beyond that gained in 174, 275 • propagation of error • chi-squared Introduction to Error Analysis, J. Taylor, Unversity Science Books, 1997 Use it!

23. Review: Estimating Errors • 1. Systematic errors: sources of error that have the same size effect on every measurement that is made (or a correlated effect) • a ruler that was not manufactured correctly • a consistently delayed reaction when using a stop watch • your inability to perfectly estimate the size of a stray magnetic field from your computer that leaks into your experimental area • 2. Random errors: sources of error whose effect varies with each measurement • precision of your measuring device • when using a stop watch, a reaction time that sometimes anticipates the event, some times is in retard of the event.

24. Systematic Errors Usually estimated using information from the manufacturer of the measuring device or by making measurements of a calibrated standard. “Mistakes” are not systematic errors. They are mistakes. Do not use data that has known mistakes, if the data can not be reliably corrected for the mistake. If you have made a mistake, you need to correct the data or retake the data. For example, failing to take into account the resistance of your ammeter when testing ohm’s law is a mistake, not a systematic error. Uncertainties on its resistance, because your ability to measure its value is limited, do lead to a systematic error. Systematic errors instead come from your limits on your ability to assess the accuracy of the device, even when it is being used correctly.

25. Random Errors Usually distributed according to a Gaussian Distribution 68% of data within 1 “sigma” 95% within 2 “sigma” (s) What were some random errors from 174? How did you estimate them?

26. Review: Error Propagation You have taken a measurement, which has an error (uncertainty), and want to use it in a calculation. What is the uncertainty on the result of the calculation due to the uncertainty on the measurement?

27. Error Propagation: Example Length of a table is 2 m ± 0.01 m Width is 1 m ± 0.005 m What is the area? What is the error on the area? x x x L

28. Error Propagation: Example You take 3 independent measurements of the period of a pendulum. You get 15 +/- 0.1 s, 14.8 +/- 0.1 s, and 14.9 +/- 0.1 s. What is the average of these 3 measurements? …which is smaller than 0.1s – make sense?

29. EXERCISE: Error Propagation Calculate this in EXCEL. You will submit your work at the end of class. We’ll move on when all of you are done. You drop a ball (initially at rest) and it falls 3 m +- 0.01 m in 0.785+-0.002 s. What is g? I Strongly suggest you put each number in a separate cell, the formula for each partial derivative in a cell, and then multiply, square and add them up. It makes it easier to spot errors!

30. Review: Chi^2 You’ve made a measurement and want to compare it to theory. How do you do this? How far is the data from the theory in natural units (size of the error)? If the data is in good agreement with the theory, what should the value of chi^2 be? N= Degrees of freedom: number of data points – number of parameters in the theory that are determined using the data “Reduced chi^2” = chi^2/N

31. Review: Chi^2 Estimating the chi^2 for this data to the theory curve by eye (no fitting parameters). Put the result in your spreadsheet.

32. Fitting: Review Have some data points. What straight line curve best “fits” the data? -> what values of m and b minimize the chi^2 between the line and the data. “perfect fit” z would be zero. Theory is that z is zero. Have 2 fitting parameters. m and b. Measurements are x and y z=y-(mx+b)

33. Practice linear fitting Use XLS template to plot and fit given data: “linear_fitter_276.xls” in folder “shortcut to p276” on your desktop. Calculate the chi^2 and calculate the probability to get a chi2 this big or bigger due to random errors.