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Research Skills

Useful templates (LaTeX, Python, ROOT) and general guidance here: JTS Public Dropbox

Reading Papers

Telling A Story

  • Guidance on writing abstracts is here
  • Sample presentations:
  • How to start writing a talk/presentation
    • General guidance on the structure of the narrative is here: 2022-03-01-hints-how-to-scientific-presentations-jts
    • Presentations should be 1 slide per minute (roughly and this includes the title slide and conclusion slide)
    • Pass 1: The title of each slide should be a complete sentence (with proper grammar and punctuation) that indicates the main take away message for that slide that is suitable for the intended audience
    • Pass 2: Think about the figure (see below) that best illustrates that sentence and put in a placeholder
    • Pass 3: Add supporting text
    • Pass 4+: iterate with constructive feedback and revise for legibility and visibility

Publication Quality Figures

  • Learn a tool for making publication quality figures (diagrams and plots)
  • A diagram shows how the experiment was carried out
  • A plot shows the data extracted from the experiment
    • ROOT and Python+matplotlib are both free and excellent tools
    • Save the diagram in EPS or SVG format so that it does not look pixelated when changing sizes and can be manipulated in an illustrattion software (see above)
    • Basic required elements of a 2D plot:
      • x-axis title label and units in parentheses, units should be chosen such that the x-values are between -100 and +100
      • x-axis labels values are large and legible, should be the same size
      • y-axis title label and units in parentheses, units should be chosen such that the y-values are between -100 and +100
      • y-axis labels values are large and legible, should be the same size
      • title of plot should describe the relevant conditions under which the data was taken and possibly include the timestamp of the dataset
      • data markers should be closed red circles
        • if the data density is high (the points overlap), then the data markers should be open red circles
        • if there are two data sets, then the second data set should be blue crosses
        • if there are multiple data sets, then the color of each data set should encode information about the variable that was varied between data sets
      • data markers should include uncertainties in the y-values and possibly the x-values if relevant
      • data markers should not be connected with lines just to guide the eye
      • if you use curve fitting to model the data, then you must plot both the (data vs fit) as well as the residual (data-fit)
      • example Python code is here: Python Curve Fitting
      • examples ROOT code are here: ROOT example
research_skills.1685206553.txt.gz · Last modified: 2023/05/27 12:55 by singhj