[<] [>]

# Physics projects for Y3 and Y4 students

## Writing a good report or paper

### Writing a good report or paper

After the experimental and theoretical work is done, it is important to write things up to make sure others don't need to reinvent the wheel. Instead you will want them to acknowledge your genius. Hence you have to write in a way to ensure that:

Provide a self-contained and clear title and abstract.
• readers who are familiar with the field but not with the particular problem treated by you can still benefit from your work:
Write an introduction section covering relevant literature and useful theory. It should also make clear why you consider the problem worthwhile working on. If there is a lot of theory, you may consider a separate theory section.
In your experimental section, describe all relevant facts that may have influenced your results and all your operations during the experiment. Mention only experimental facts that relate to the results you show. If you have changed or improved the setup before taking data, you do not need to report your considerations that caused the change - somebody who plans to follow up on your work needs to start where you have finished.
Show plots of your results. Results are the immediate data you have recorded as a function of the experimental parameters. In this section, no derived quantities should be displayed. However, you can (and should) plot the data in a way that helps the analysis. For example, if you want to determine the exponent of a power law, plot the data logarithmically. Generally, plots are better than tables, and the same information should not be presented twice. It is important to guide the reader through your results, so write some text pointing to the important features in the plot: the position of a maximum, the linewidth, signal-to-noise, change in slope - whatever is important. But do not draw any conclusions at this stage. Quantify all errors in primary measured results and parameters. If you have to process your raw data (filtering, background subtraction, smoothing etc.), describe it here, quantify the errors introduced by the processing, and show an example of how it affects your raw data. State all your data to a precision commensurate with the error margin - only the final significant digit should be affected by the stated error. Use present tense whenever implying reproducibility (i.e. most of the time). Past tense is more appropriate when referring to one-off events that cannot be repeated, such as an astronomical observation.
In a separate discussion section, derive qualitatively and quantitatively any properties or quantities from your data using the formulae given in the introduction or theory section. Refer to the equations rather than repeating them. A Mathcad script is not acceptable - you must describe in words what you do and why you do it. Analyse the propagation of errors quantitatively. The purpose of error analysis is not to blame the kit/yourself/the technician but to provide a level of confidence with the data. There are papers with horrendous error bars in the journals, but if nobody else can measure it more accurately then this is perfectly acceptable! If you can/want to derive a generalised model from your results, do it in this section; and make it accessible by drawing a sketch of its main features.
• readers will remember the key points:
Provide a short Conclusions section. This is a summary without reference to literature, figures and tables, and will not normally contain formulae.
• people who have helped you will find their contribution acknowledged
Finally, give a short list of people (if any) who have helped you, and how. Only include those in the Acknowledgements who really did - there is no need to be over-polite.

Some further points you should keep in mind:

• Plot figures on an appropriate scale. Ensure that different data sets are clearly distinguishable. If you plot lines to connect points, state in the caption whether these represent theory functions or merely guides to the eye. In the latter case - do you really need them? Fig.1 gives an example of well-presented data: Both data sets are shown on a scale which allows to discern the detail of the pattern, and plotting them together in one graph allows to spot correlations. Error bars help distinguish real fluctuations from random noise. Axes are labelled, and the data fill the frame with little empty space.
• Make sure that all figures and tables are enumerated and have a caption describing what is on display and what the different markers stand for. Increase signal-to-noise by avoiding sentences like "a graph to show" - people know that it's a graph; and graphs are usually meant to show something. Use the figure numbers to refer to figures in the text. No figure should go without mentioning in the text!
• When referring to other people's work, you can use either of two formats, but be consistent with it. Either enumerate references[1] or refer to the papers by using the name of the first author (Author 2002a). Then list the references at the end of the papers like this:
[1] A.N. Author, A.N. Other, J. Irrepr. Res. 23 (2002) 456
Author 2002a; A.N. Author, A.N. Other, J. Irrepr. Res. 23 (2002) 456
In the example, 23 is the volume, 456 the number of the first page, and 2002 the year of publication. In the second format, distinguish different papers by the same author from the same year by a,b,... after the year of publication. You can also cite books, other people's lab reports or scientific gossip:
[3] HC van de Hulst, Light Scattering by Small Particles, Dover Publ., New York 1981, p.123
[4] ER van Hoek, Gravel, Mud, and Avalanches, UWA group project report, 2001
[5] MY Colleague, unpublished
The latter makes sense e.g. if you want to make clear that a group who did the experiment earlier has given you a vital clue. When citing from a book, always refer to the particular page or section that is relevant in the context.
• Use appendices wisely and sparely. Anything that is essential to your project should really be in the report itself, where it can be referred to and explained properly. However, appendices can be useful to add background information such as source code of programs you've written or data images of similar samples where you have already shown and discussed a typical image in your report. There is no need to reproduce data tables of every measurement you've taken during your project. In the majority of cases, material considered for an appendix should either be in the report itself or could be left out completely without detriment.
• Before you submit your report or paper, read it, sleep a night, and read it once again. Incomplete sentences and misguided formatting can easily be avoided this way. These really are important issues - if you make yourself easily understood people will be more receptive of the point you're making.
It's your work - be proud of it!

Here is a research paper from Phys Rev Lett. Because it is a short paper, it doesn't have section headings like Introduction or Results etc, but it follows the same structure. See if you can identify the different sections.

Content updated: ruw/190613