Table A.1
Priors applied to the two models, ℳ1 and ℳ2.
| Component | Parameter | Distribution |
|---|---|---|
| Power law | log(APL) | 𝒩(−10,5)b |
| α | 𝒩 (3,2) | |
| Lorentzian 1 | log(ALor,1) | 𝒩(−5,5) |
| log(vmid,1) | 𝒰(log(0.0049), log(10))c | |
| log(Q1) | 𝒰(log(0.01), log(2)) | |
| Lorentzian 2a | ALor,2 | 𝒰(0,1.0) |
| log(vmid,2) | 𝒰(log(0.0049), log(10) | |
| log(Q2) | 𝒰(log(2), log(50)) | |
| Counting noise | log(C) | 𝒩 (log(µn), log(µn/5))d |
Notes. (a) This component is only present in ℳ2. (b) 𝒩(µ, σ2) defines a normal distribution with a mean of µ and a variance of σ2 (c) 𝒰(a, b) defines a uniform distribution with lower bound a and upper bound b.(d) For simplicity, and because the noise in GBM is generally well-behaved, the prior for the white noise component is set using the mean power µn of the last 100 frequencies in the periodogram.
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