Make instructions and questions more clear

Author: duboism

Challenge/README.md

@@ -9,8 +9,7 @@ Data files may be downloaded from [DCC G2300818](https://dcc.ligo.org/LIGO-G2300
 * [challenge3.gwf](https://dcc.ligo.org/public/0187/G2300818/001/challenge3.gwf)
 * [challenge3_2048hz.gwf](https://dcc.ligo.org/public/0187/G2300818/001/challenge3_2048hz.gwf)   <-- Downsampled version of Challenge 3 file
 
-Workshop participants may [submit solutions via thinkific](https://learn.gwosc.org) as individuals or in teams of up to 3 people.
-Check for the deadline date on the Thinkific website.
+Workshop participants may [submit solutions via the online course](https://learn.gwosc.org/courses/odw2026) as individuals or in teams of up to 3 people (check for the deadline date on the website).
 
 Challenges are ordered by difficulty. Entries will be rewarded a number of
 points that scales with the difficulty of the challenge.
@@ -19,78 +18,88 @@ Good luck to all!
 
 ## Challenge 1 (1 point) -- Novice
 
-Identify a loud binary black hole signal in white, Gaussian noise.
+Identify a loud binary black hole signal in white, Gaussian noise:
 
 * Use the data file `challenge1.gwf`. The channel name is `H1:CHALLENGE1`.
 * The data are white, Gaussian noise containing a simulated BBH signal.
 
 Instructions:
-1. Load the data into memory. What are the sampling rate and duration of the data?
-2. Plot the data in the time-domain.
-3. Plot a spectrogram (or q-transform) of the data, and try to identify the signal.
 
-Question:
-* What is the time of the merger (in seconds from the start of the segment)?
+* Load the data into memory. What are the sampling rate and duration of the data?
+* Plot the data in the time-domain.
+* Plot a spectrogram (or Q-transform) of the data, and try to identify the signal.
+
+Question for Challenge 1:
+
+1. What is the time of the merger (in seconds from the start of the segment)?
 
 ## Challenge 2 (2 points) -- Rookie
 
-Signal in colored, Gaussian noise.
+Signal in colored, Gaussian noise:
 
 * Use the data file `challenge2.gwf`, with channel name `H1:CHALLENGE2`.
 * The data contain a BBH signal with m1 = m2 = 30 solar masses, spin = 0.
 
-Question A:
-
-* What is the approximative time of the merger? (Hint: a plot of the q-transform could help)
-
-Next steps:
-1. Generate a time-domain template waveform using approximate `SEOBNRv4_opt`.
-   with the same parameters as above. Plot this waveform.
-2. Calculate a PSD of the data, and plot this on a log-log scale.
-   Use axes ranging from 20 Hz up to the Nyquist frequency.
-3. Use the template waveform and PSD to calculate the SNR time series. Plot the SNR time-series.
+Instructions:
 
-Question B:
+* Plot a Q-transform of the data.
+* Generate a time-domain template waveform using approximate `SEOBNRv4_opt`.
+  with the same parameters as above. Plot this waveform.
+* Calculate a PSD of the data, and plot this on a log-log scale.
+  Use axes ranging from 20 Hz up to the Nyquist frequency.
+* Use the template waveform and PSD to calculate the SNR time series. Plot the SNR time-series.
 
-* What is the matched filter SNR of the signal?
+Questions for Challenge 2:
 
+2. From the Q-transform, what is the approximative time of the merger?
+3. What is the matched filter SNR of the signal?
 
 ## Challenge 3 (4 points) -- Intermediate
 
+Search for a loud event in realistic data:
+
 * Use the data file `challenge3.gwf` with channel `H1:CHALLENGE3`.
 * These are real LIGO data from O2, though we've adjusted the time labels and
   added some simulated signals.
 * The data contain a loud simulated signal with m1 = m2 = 10 solar masses.
 
-Questions:
+Instructions:
+
+* Use the template waveform `SEOBNRv4_opt` and PSD to calculate the SNR time series.
 
-A. What is the merger time of this signal?
+Questions for challenge 3:
 
-B. What is the matched-filter SNR of this signal?
+4. What is the merger time of the loud signal?
+5. What is the matched-filter SNR of the loud signal?
 
 **Note:** it's not needed to use bilby for this challenge.
 
 ## Challenge 4 (8 points) -- Advanced
 
-* Use the data file `challenge3.gwf` with channels `H1:CHALLENGE3` and `L1:CHALLENGE3`.
+Realistic search and parameter estimation:
+
+* We will use the same realistic data set `challenge3.gwf` with channels `H1:CHALLENGE3` and `L1:CHALLENGE3`.
 * These are real LIGO data from O2, though we've adjusted the time labels and
   added some simulated signals.
-* Any simulated signals have been added to both the H1 and L1 data
-* All simulated signals have spin = 0 and m1 = m2, with m1 somewhere in the range 10-50 solar masses
+* All simulated signals have been added to both the H1 and L1 data.
+* All simulated signals have spin = 0 and m1 = m2, with m1 somewhere in the range 10-50 solar masses.
+* Watch out! These are real data, and so glitches may be present.
 
 Questions:
-A. Identify as many signals as you can. Watch out! These are real data, and so glitches may be
-present. Any correct detection is +1 point but any false alarms will count -1 point
+
+6. Identify as many signals as you can. Any correct detection is +1 point but any false alarms will count -1 point
 against your score. For each signal you find, list:
 
  * The merger time
  * The SNR
  * Your estimate of the component masses
 
-B. Identify as many glitches as you can. Make a spectrogram of each one.
+7. Identify as many glitches as you can. Make a spectrogram of each one.
+8. For the earliest event you found, use bilby to compute the posterior distribution for the mass.
+   Hint:
 
-C. For the earliest event you found, use bilby to compute the posterior distribution for the mass.
-   Fix the spin and mass ratio to make this run faster.
+   - Fix the spin and mass ratio to make this run faster.
+   - You can also fix other angular parameters to zero, while leaving at least the chirp mass, sky position, time and distance free. This will still give an approximately correct posterior for the chirp mass.
 
 ### Useful notes