Table 1
Model parameters, their priors, and their functional forms for the three different models presented in this work.
| Prior/functional form | |||
|---|---|---|---|
| Parameter | Frozen means model on [M/H]−vϕ plane | Evolving means model on [M/H]−vϕ plane | Evolving means model on [M/H]–η plane |
![]() |
Dirichlet(0.5 2) | Dirichlet(0.5 2) | Dirichlet(0.5 2) |
| σmean, GP | − | 𝒰(50 km s−1, 200 km s−1) | 𝒰(0.1, 0.9) |
| ℓGP | − | 𝒰(0, 1) | 𝒰(0, 1) |
| αGP | − | 𝒰(0, 4) | 𝒰(0, 4) |
![]() |
− | 𝒩(80 km s−1, covspin up) | 𝒩(0.3, covspin up) |
| σ1, knots | − | ℋ𝒩(150 km s−1) | ℋ𝒩(0.3) |
| σ2, knots | − | 𝒯𝒩(100 km s−1, 50 km s−1.; 50 km s−1, 150 km s−1) | 𝒯𝒩(0.4, 0.2; 0.4, 0.7) |
| w | ![]() |
![]() |
![]() |
| μ1 | 𝒩(0 km s−1, 150 km s−1) | ![]() |
![]() |
| σ1 | ![]() |
𝒮interp([M/H] | ) |
𝒮interp([M/H] | ![]() |
| μ2 | 𝒩(0 km s−1, 150 km s−1) | Fixed, 0 km s−1 | Fixed, 0 |
| σ2 | ![]() |
![]() |
![]() |
| w · 𝒩(μ1, σ1)+ | w · 𝒩(μ1, σ1)+ | w · ℱ𝒩(μ1, σ1;−1, 1)+ | |
| vϕ or η | (1-w) · 𝒩(μ2, σ2) | (1-w) · 𝒩(μ2, σ2) | (1-w) · ℱ 𝒩(μ2, σ2;−1, 1) |
Notes. Abbreviations: ℋ𝒩= half-normal distribution, 𝒯𝒩= truncated normal distribution, 𝒮interp= spline interpolation, ℱ𝒩= folded normal distribution. The parameters of 𝒯𝒩 and ℱ𝒩 are (μ, σ; min, max). The subscript 1 and 2 stands for the disc-like and halo-like components, respectively, with μ and σ as the Gaussian mean and standard deviations in vϕ or η, conditioned on the value of [M/H]. w stands for the relative contribution of the disc-like component with the relative contribution of the halo-like component defined as (1−w). knot sw and knot sμ stands for the [M/H] spline knots location for the relative contribution parameter (w) and the velocity/circularity means and standard deviations (μ, σ) respectively. The graphical representation of the models are shown in Figure 5.
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![$\mathcal{S}_{{interp}}\left([M / H] \mid \overrightarrow{{knots}_{w}}, \overrightarrow{w_{{knots}}}\right)$](/articles/aa/full_html/2025/11/aa53063-24/aa53063-24-eq5.png)
![$\mathcal{S}_{{interp}}\left([M / H] \mid \overrightarrow{{knots}_{w}}, \overrightarrow{w_{{knots}}}\right)$](/articles/aa/full_html/2025/11/aa53063-24/aa53063-24-eq6.png)
![$\mathcal{S}_{{interp}}\left([M / H] \mid \overrightarrow{{knots}_{w}}, \overrightarrow{w_{{knots}}}\right)$](/articles/aa/full_html/2025/11/aa53063-24/aa53063-24-eq7.png)
![$\mathcal{S}_{{interp}}\left([M / H] \mid \overrightarrow{{knots}_{\mu}}, \overrightarrow{\mu_{1, {knots}}}\right)$](/articles/aa/full_html/2025/11/aa53063-24/aa53063-24-eq8.png)
![$\mathcal{S}_{{interp}}\left([M / H] \mid \overrightarrow{{knots}_{\mu}}, \overrightarrow{\mu_{1, {knots}}}\right)$](/articles/aa/full_html/2025/11/aa53063-24/aa53063-24-eq9.png)




![$\mathcal{S}_{{interp}}\left([M / H] \mid \overrightarrow{{knots}_{\mu}}, \overrightarrow{\sigma_{2, {knots}}}\right)$](/articles/aa/full_html/2025/11/aa53063-24/aa53063-24-eq14.png)
![$\mathcal{S}_{{interp}}\left([M / H] \mid \overrightarrow{{knots}_{\mu}}, \overrightarrow{\sigma_{2, {knots}}}\right)$](/articles/aa/full_html/2025/11/aa53063-24/aa53063-24-eq15.png)