GalMod tutorial

In this tutorial, we explain how to use the GalMod web interface. All parameters and a detailed derivation of the adopted formulation are in three dedicated papers: Pasetto et al. (2016, 2018a,b).

GalMod aims to generate mock catalogs for a specified field of view of our Galaxy (the Milky Way, MW), an external galaxy such as Andromeda (M31), a dwarf galaxy, or a quasi-equilibrium stellar model. Each input set of parameters corresponds to a single output. The output is not unique, being the product of stochastic simulations based on Monte Carlo integration methods. If the user runs GalMod twice (or more) on the same set of parameters, GalMod produces “statistically equivalent” results but not identical.

GalMod requires the user to fill a (basic) input form, containing the minimum requirements for the model to work (or an extended/advanced input form). The preset parameters that the user finds in the GalMod input form are random examples of the field of view based on an MW “optimal model.” The user is free to change those parameters within the indicated range (or accept the preset parameters). Once the user fills all the parameters and provides a correct email address, GalMod produces the simulation and sends an email with a password and a link to download the results (the website is mobile friendly). The timescale for the delivery of a mock catalog depends on the input parameters and the servers’ availability; a minimum time of 10 minutes is preset, and times longer than 10,000 minutes indicate either difficult FoVs or a bug in GalMod. In that case, feel free to contact the support (see below).

The input form requires the user to provide a set of parameters (grouped by background color) referring to a Galactic composite stellar population (CSP). By hovering with the mouse over any box inside these sections, a brief explanation of the parameter appears with a few hints on its possible value. The allowed parameter range (if a real number) is below the input box, written in mathematical notation, e.g., \(x \in \left] {a,b} \right]\) meaning \(a < x \le b\), or \(y = {a..d}\) for integer limits meaning \(y = a \vee y = b \vee y = c \vee y = d\). Each box must contain a single number; no arrays of numbers are allowed as input. The input form comes with preset parameters for the Galaxy to facilitate the use of the model (including a field of view as an example). Selecting a parameter outside the range of allowed values causes the box border to become red to indicate the mistake. By refreshing the web page, GalMod performs a check on the full list of parameter values. Reloading the page resets the preset parameters to their original values.

If the input is accepted, the simulation runs "as soon as possible," and when finished, GalMod sends a communication to the provided email address with a temporary password and a link to download the file from GalMod. The simulations are available for download for a few days.

 

Not all parameters are necessary to run GalMod; the recommended fields to set are:

1. field of view of interest or simulation type,
2. photometric system.

If the user wants to study a direction in the Galaxy, an all-sky mock catalog results in a low-resolution model in the direction of interest. Hence it is strongly recommended to specify the field of view because this allows GalMod to produce a better simulation only in the direction of interest. Full-sky simulations are allowed; there is no limit on the solid angle of the field of view. GalMod informs the user of the correct amount of stars that should fill the desired field of view under the specified parameters.

Choosing a photometric system is also important. Several important photometric systems are available in the drop-down list menu, and the closest to the user’s interest should be set.

Other relevant parameters to set are:

• Number of stars: GalMod computes a probability distribution function (PDF) and populates it with a number of stars that is fixed in agreement with the multiple-stellar-population consistency theorem (MSP-CT, Pasetto et al. 2018b). If the user knows the number of stars expected in an observation/catalog, GalMod can renormalize the PDF to the requested value. Then, if the number of stars required is lower than that predicted by MSP-CT, GalMod renormalizes the PDF with the number of stars requested, automatically adjusting the relative proportions of the multiple stellar populations to agree with the structural parameters provided. If the number of stars requested is larger than that predicted by GalMod, the user can increase the number of stars by changing the structural parameters of the Galaxy (density profiles, star formation history, cuts). Again, in this case, GalMod automatically adjusts the relative proportions of the multiple stellar populations to agree with the structural parameters provided in agreement with the MSP-CT.
• Photometric system. GalMod is so far equipped with a few photometric systems: Johnson-Cousins, HST/ACS-WFC, HST/ACS-HRC, Gaia, SDSS, 2MASS, etc. (see below for a complete list). The input form changes depending on the photometric system selected. A magnitude/color cut in the output CMD acts on the photometric systems by selecting which filter is on the y-axis of the CMD (called \(1^{st}\) filter). For example, to simulate a field of view with SDSS filters with \(g \in \left[ {13.5,17.5} \right]\) mag and \(g - i \in \left[ { - 1.2,3.2} \right]\) mag, the \(1^{st}\) filter (\(1_{\rm{fltr}}^{st}\)) is \(g\) (bluer filter first), i.e., the second SDSS filter, and the \({2^{nd}}\) filter is \(i\), i.e., the fifth SDSS filter (the SDSS filters are \(\left\{1^{st},2^{nd},3^{rd},4^{th},5^{th} \right\} = \left\{u,g,r,i,z \right\}\). Thus, in the online form, the \(2_{\rm{fltr}}^{nd} = 5\), and then the minimum magnitude considered in the first filter is \({\rm{mag}}_\min ^{1_{\rm{fltr}}^{st}} = 13.5\) mag while the maximum magnitude is \({\rm{mag}}_\max^{1_{\rm{fltr}}^{st}} = 17.5\) mag. The color is the difference between first and second magnitude, i.e., \({\rm{col = 1}}_{\rm{fltr}}^{st} - 2_{\rm{fltr}}^{nd}\) spanning values between \({\rm{co}}{\rm{l}}_\min = - 1.2\) mag and \({\rm{co}}{\rm{l}}_\max = + 3.2\) mag.
• Photometric errors. Every observation comes with errors. We suggest setting an (or accepting the preset) error function while producing your mock observations with GalMod. GalMod uses a Gaussian distribution with magnitude dispersion dependent on the \(1_{\rm{fltr}}^{st}\) magnitude, with the dispersion computed from the following formula \({\sigma _m} = {\left( {\frac{\sigma _{m_\max}}{\sigma _{m_\min }}} \right)^{\frac{m - {m_\min }}{m_\max - m_\min }}}\) where \(\sigma _{m_\max}\) is the error at \({\rm{mag}}_\max^{1^{st}{\rm{fltr}}}\), e.g., \(\sigma _{m_\max}\) = 0.1 mag, and \({\sigma _{\rm{ma}{\rm{g}_\min }}}\)is the error at the brightest magnitude limit \({\rm{mag}}_\min ^{1^{st}{\rm{fltr}}}\), e.g., \({\sigma _{\rm{ma}{\rm{g}_\min }}}\) = 0.01 mag. If \({\sigma _{\rm{ma}{\rm{g}_\min }}} = \sigma _{m_\max} = 0.0\) is set, GalMod introduces no mag errors. If \({\sigma _m} > {\rm{co}}{\rm{l}}_\max - {\rm{co}}{\rm{l}}_\min \) GalMod renormalizes the error function to \({\sigma _m} = {\rm{co}}{\rm{l}}_\max - {\rm{co}}{\rm{l}}_\min \).
• Metallicity limits. These boxes influence the CMD obtained from GalMod. While every CSP spans different metallicity ranges, the resulting CMD of the CSP is filtered by these cuts a posteriori. For example, to study the halo kinematics of the solar neighborhood, a simple cut in metallicity below a threshold limit allows to decontaminate the stars from coherent circular motions.
• Field of view (f.o.v.) definition. This box determines the direction of the GalMod mock catalog as generated from the solar location, or the kind of simulation generated (MW, M31 or semi-equilibrium models). There are six different options, of which the first four limit the sky area considered:
• By setting the four parameters \(\left\{l_\min ,l_\max,b_\min ,b_\max \right\}\), i.e., the minimum and maximum longitude and latitude, respectively. For example, because \(l \in \left[ {0,360} \right[\), the MW central direction is examined by setting \({l_\min } = 350\) deg, \({l_\max} = 5\) deg, \({b_\min } = - 5\) deg, and \({b_\max} = 5\) deg;
• By setting the four parameters \(\left\{l_c,b_c,\Delta l,\Delta b \right\}\), i.e., the central longitude and latitude of the field of view and its opening angle in longitude and latitude. For example, \({l_c} = 180\), \({b_c} = 0\), \(\Delta l = 180\), and \(\Delta b = 180\) returns the 2nd and 3rd Galactic quadrants;
• By setting the three parameters \(\left\{\alpha _c,\delta _c,OA \right\}\), i.e., the central right ascension and declination of the field of view and its opening angle. In this case, the field of view is circular and centered on the equatorial coordinates \(\left\{\alpha _c,\delta _c \right\}\). All inputs are in [deg].
• By setting the four parameters \(\left\{\alpha _c,\delta _c,\Delta \alpha ,\Delta \delta \right\}\) with the same meaning as above, but with the input given in [arcmin].
The last two options activate a set of parameters to model semi-equilibrium systems or a specific M31 field of view:
• Equilibrium systems (experimental). This option activates a GalMod experimental modality to realize the semi-equilibrium collisionless model of spiral galaxies. The CSPs are set coherently with the input provided by the user, but GalMod spreads the total mass of the resulting galaxy among the total number of “star-like” particles (established by the user). GalMod realizes a full sky survey without photometric limits where mass, metallicity, and phase-space are assigned to massive particles as explained in a dedicated paper (Pasetto et al. 2012). A finely tuned code to perform this initial condition generation is freely available upon request to the project P.I.
• Andromeda (M31)/dwarf galaxy field of view. This option activates a group of preset values that allow modeling M31 and its surrounding area as seen from the solar position. This option is equivalent to moving the Sun's location outside the Galaxy and rotating the field of view accordingly. The simulation, in this case, does not model the MW foreground; the user needs to add that with a separate simulation. The location of M31, the inclination of the M31 plane to the line of sight, and the position angle on the celestial sphere are also free parameters, thus allowing GalMod to model virtually any collisionless stellar system as seen from the solar location.
• Field depth. This parameter determines the heliocentric distance reached by the integration of the galaxy potential. To ask for a very deep field (a \({r_{\rm{hel}}}\) as large as 50 kpc is allowed) may require a longer integration time that might not be necessary because of the adopted photometric cuts or because of the presence of external stellar systems that prevent the line of sight to be seen beyond a given limit. For example, if the solar position is outside the MW (e.g., to simulate M31 or another spiral galaxy), GalMod computes possible spiral arm resonance locations up to the nominal 50 kpc or according to the branch cut discontinuity in the complex plane implemented for a given Hypergeometric function. It is up to the user to understand whether physically meaningful results are obtained.
• Velocity space constraints. Because GalMod realizes simulations as a mock catalog in the space of observations, the limitations on the velocity space are applied directly on radial velocities and proper motions. The proper motions are either \(\left\{\mu _\alpha ,\mu _\delta \right\}\) or \(\left\{\mu _l,\mu _b \right\}\) depending on the adopted field of view definition.

 

• Solar location This parameter sets the place in the Galactic model where some of the density profiles and velocity normalization profiles are normalized. These values also define the preferred observer location. In the semi-equilibrium model case, this parameter is neglected.
• Solar motion to the Local Standard of Rest (LSR). This value sets the motion of the Sun to the local standard of rest. The value is positive for the direction pointing outside the Galaxy, in the anti-rotation direction, and toward the NGP.

 

The “basic” parameter section influences the way the Galaxy “looks” in the simulation output. Modifying the structural parameters changes the way in which the Galaxy “is,” independently of the possibility of detecting it in the output catalog. This concept can be explained with a few simple examples. Modifying the structure parameters of the bulge components for a small field of view of an MW model pointing toward the anticenter direction rarely results in visible changes in the resulting mock catalog, even though changes to the bulge parameters affect the global potential of the MW. As a less straightforward example, modifying the metallicity/age of a thin disk CSP in the structure section implies a variation in the velocity-dispersion distribution of stars because of the implemented age-velocity dispersion relation for the thin disk CSPs. However, if the user requires a model with a high velocity dispersion for very young thin disk CSPs, the MSP-CT predicts a small probability for this type of CSP to exist, thus reducing this CSP's total mass in favor of other disk CSPs. The MSP-CT “redistributes” the mass onto other more probable CSPs. Conversely, the stellar halo, which is supposed to be old and metal-poor but whose connection with other CSPs is not obvious, is left free to be metal-poor and old as well as metal-rich and young. The GalMod user has responsibility for the simulation inputs as well as the freedom to experiment.

GalMod generates the Galaxy potential, the number of stars in the CMDs and the kinematics of the stars depending on a set of parameters that define the stellar populations, the dark matter and the gas contents of the Galaxy. For each CSP, these parameters are:

• Density defining parameters. Each CSP is specified by a set of parameters extensively described in Pasetto et al. (2016) Sec. 4 to 6 and Pasetto et al. (2018a) Sec. 3 and Appendix A.
• Kinematics parameters. Some of the CSP components contain free parameters not directly related to the potential. These are typically second order moments of the unknown phase-space distribution function of the unperturbed component. A complete description of the implemented model is given in Sec. 7 of Pasetto et al. (2016). These parameters normalize the velocity dispersion profiles at the solar location set by the user.
• Age parameters. The age of the stars is a free parameter. GalMod uses parametric profiles of star formation rate (SFR) and \(\psi \left( t \right)\), from which the stars are sampled. Four SFR profiles are available:
• Constant star formation rate. The stellar age is randomly sampled from a constant SFR profile, \(\psi \left( t \right) = {\rm{const}}{\rm{.}}\) between \(t_\min \) and \(t_\max\). The constant is determined coherently from the density profiles and initial mass function by the MSP-CT.
• Exponential star formation rate. The stellar age is randomly sampled from an exponential SFR profile, \(\psi \left( t \right) = {\rm{const}}{\rm{.}} \times {e^{\frac{t}{h_\tau }}}\) between \(t_\min \) and \(t_\max\). The constant is determined coherently from the density profiles and initial mass function set in agreement with the MSP-CT. \({h_\tau }\) is the timescale of the profile (it can be both a positive or a negative value).
• Linear star formation rate. The stellar age is randomly sampled from a linear SFR profile of the type \(\frac{t - t_\min }t_\max - t_\min = \frac{\psi \left( t \right) - \psi \left( {t_\min } \right)}{\psi \left( {t_\max} \right) - \psi \left( {t_\min } \right)}\) between \(t_\min \) and \(t_\max\). In the case of \(\psi \left( t_\max \right) = \psi \left( t_\min \right)\) GalMod will switch to the \(\psi = {\rm{const}}{\rm{.}}\) case treated above.
• Rosin-Rammler. This SFR is taken from Chiosi et al. (1981) with the aim of offering a more realistic SFR profile over a broad temporal range between \(t_\min \) and \(t_\max\). The profile is bi-parametric \(\psi \left( t \right) = {\rm{const}}{\rm{.}} \times {t^\zeta }{e^{ - \frac{t}{h_\tau }}}\) with both \(\zeta \) and \({h_\tau }\) strictly positive. Note how the profile uses a look-back time where \(t \to t_\max - t\). Depending on the galaxy, the user needs to set the input accordingly.
• Metallicity range. The stellar metallicity is a free parameter sampled uniformly between \({Z_\min }\) and \({Z_\max}\). An age-metallicity relation on a single stellar population (CSP) is not implemented but can be obtained by implementing sequential metallicity ranges over the five CSPs.

The thin disk CSP-I, green background section is modeled as a spiral arm CSP and smoothly connects with the bar structure. The code will return information on whether the Galaxy component happens to have stars or is empty (e.g., this can occur if the input number of stars is too low and the density is low). The code will output the number of stars of each CSP. All the CSPs are always considered in the potential computation even if their result is empty based on the input number of stars. For example, when inputting 1000 stars in the anticenter direction, the bulge mass distribution is considered in the total potential even though probably zero bulge stars will ultimately be produced. Note that the dark matter component automatically accounts for the hot coronal gas in the outermost layer of the MW (\(R > 40kpc\)). For the specific case of M31 simulations, or any other spiral or S0 galaxy, the user is supposed to set the parameters of interest manually. GalMod will then provide kinematics and photometry according to the input and return feedback information on the resulting galaxy potential, i.e., rotation curve, total mass, Oort constants, and so forth at the normalization location for the density and velocity profiles (the location of a virtual Sun on M31).

 

The interstellar medium (ISM) component is considered in the total Galaxy density to obtain the total potential and to determine the extinction that will affect the simulated CMDs. The ISM distribution follows the spiral arm parameters adopted for the first stellar population distribution (i.e., thin disk CSP-I), but it perturbs the density profile of the ISM and is dimmed by the “reducing factor” (see Pasetto et al. 2016). In the case of M31 simulations, the extinction of the stars is computed from the solar location excluding the MW extinction that the user must account for in a separate simulation. The ray-tracing technique is a spin-off of the ray-tracing 3D dust radiative transfer code DART-Ray by Natale et al. (2017).

If the generation of the model is successful, the user receives a second email containing a password and a link to download the catalog of data containing the results of the simulation. The file contains an initial section that recaps the chosen input parameters, including the version of GalMod used and references to the sections of Pasetto et al. (2016, 2018a,b).

The first section of the output file looks like the following:

GalMod rel. XX.XX

GalMod is presented in Pasetto et al. (2016a, 2018a,b), and references therein.

The section numbers here quoted refer to the sections in those papers.

Please see and cite those documents if you use GalMod.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Some infos about the GalMod simulation you realized are here summarized:

Total number of stars is automatically fixed

Photometric system adopted: extended JOHNSON-COUSINS

fltr no{1st,2nd}, Mag{min,max}, Col{min,max} [mag,mag,mag,mag]: {1, 2},{6.00, 22.00},{.00, 4.00}

ErrMag{min,max} [mag,mag]: {.01, .05}

Z{min,max} [mass fraction]: {.00004, .03000}

Binary fraction: .300

Squared FoV in Galactic coordinates

{lmin,lmax,bmin,bmax} [deg,deg,deg,deg]: {.00, 359.90, -90.00, 90.00}

{rhelmin,rhelmax} [kpc,kpc]: {.01, 25.00}

{mu_1 min,mu_1 max} [mas/yr,mas/yr]: {-700.00, 700.00}

{mu_2 min,mu_2 max} [mas/yr,mas/yr]: {-700.00, 700.00}

{Vrhelmin,Vrhelmax} [km/s,km/s]: {-700.00, 700.00}

{R,phi,z}@Sun [kpc,deg,kpc]: {8.00, .00, .02}

{VR,Vphi,Vz}@Sun-->LSR [km/s,km/s,km/s]: {-10.90, -5.20, 7.20}

Bulge CSPs parameters (P18b Sec. 3.3.3) + tilted bar (P18b, Sec. 3.3.2.)

Etc…

The order of this first metadata block is the same order used by the current output writer: code release and references, the user-visible input summary, the binary fraction, the FoV definition and cuts, the Sun position and velocity, and then the CSP, dark-matter, and interstellar-medium parameters. If \({r_ \odot } < 50\) kpc, these first lines are followed by a set of parameters obtained as a solution of the Poisson equation with the input density parameters. For example:

Some structural values from the density profiles:

• the total CSP mass inside 100 kpc: \(M_\rm{CSP}\left( r \leq 100{\rm{kpc}} \right)\left[ M_ \odot \right] = 0.27 \times 10^{11}\);
• the rotation curve at the solar position: \({V_c}\left( R_\odot,\phi_\odot,z_\odot \right)\left[ {km\;{s^{ - 1}}} \right] = 218.7\);
• the rotation curve profile: \({V_c}\left( {R = \left\{1.0,2.0,3.0,5.0,8.0,13.0,21.0 \right\}} \right)\left[ km\;{s^{ - 1}} \right] = \left\{164.0,183.8,201.5,215.5,218.7,214.3,207.7 \right\}\);
• normalized vertical force: \(\frac{F_z\left(R_\odot,\phi_\odot,z=\left\{1.0,2.0\right\}{\rm{kpc}}\right)}{2\pi G}\left[ M_\odot{\rm{pc}}^{-2} \right] = \left\{ -55.7, -86.4 \right\}\);
• the Oort constants: \(\left\{O^+,O^-\right\}_\odot \left[ {km\;{s^{ - 1}}\;kp{c^{ - 1}}} \right] = \left\{13.8, -13.5 \right\}\);
• the radial epicyclic frequency: \({\kappa _R}\left( R_\odot,\phi_\odot,z_\odot \right)\left[ {km\;{s^{ - 1}}\;kp{c^{ - 1}}} \right] = 38.4\);
• the angular frequency: \({\Omega}\left( R_\odot,\phi_\odot,z_\odot \right)\left[ {km\;{s^{ - 1}}\;kp{c^{ - 1}}} \right] = 27.3\);
• the resonance locations computed for the spiral-arm component: \(R_{\rm{res}}\left[ {\rm{kpc}} \right] = \left\{1.20,10.46\right\}\);
• the resulting proportionality factor to the slope of the velocity ellipsoid: \(\lambda \left( R_\odot,\phi_\odot,z_\odot \right) = 0.72\).

The structural block is followed by the selection-function Monte Carlo diagnostics. Since the binary implementation can represent an unresolved binary as one catalogued system, this section now reports unresolved systems rather than only single stars. It gives the total number of unresolved systems expected before any observational cuts, the number of trial systems generated by the Monte Carlo selection-function estimator, the number accepted after the magnitude, color, metallicity, distance, proper-motion, and radial-velocity cuts, the estimated selection probability, the expected number of unresolved systems after cuts, and an approximate upper value. For example:

Selection-function Monte Carlo diagnostics:

pre-cut expected unresolved systems: 41839764287

generated trial unresolved systems: 99995

accepted unresolved systems after all cuts: 9833

selection probability estimate: 9.8335E-02

expected unresolved systems after cuts: 4.1143E+09 +/- 3.9398E+07

approximate 95 pct upper value: 4.1915E+09

The final section contains the synthetic catalog after the selection cuts have been applied. The table starts with three header rows: the column names, the column numbers, and the units. The number of photometric and extinction columns changes with the selected photometric system. In the Johnson-Cousins example above the table has 48 columns. Each row is one accepted unresolved system, which can be a single star or a binary system, and the first columns are:

\(t\left[ {yr} \right]\): age of the star,

\({\log _{10}}\left( {L/{L_ \odot }} \right)\): logarithm of the stellar luminosity normalized to the solar luminosity,

\(\log _{10}\left( T_\rm{eff}\left[ {^\circ K} \right] \right)\): logarithm of the effective temperature,

\(\log _{10}\left( {g\left[ m\;s^{ - 2} \right]} \right)\): logarithm of the stellar gravity at the stellar surface,

\(M\left[ M_ \odot \right]\): current mass of the source represented in the HR diagram,

\(Z\left[ {\rm{frac}} \right]\): stellar metallicity mass fraction,

\(Y\left[ {\rm{frac}} \right]\): helium mass fraction.

The following columns change depending on the stellar photometry selected:

1. Johnson-Cousin \(m_{1..8} = \left\{U, B, V, R, I, J, H, K \right\}\),
2. HST/ACS-WFC \(m_{1..13} = \left\{ F_{435W},F_{475W},F_{502N},F_{550M},F_{555W},F_{606W},F_{625W},F_{658N},F_{660N},F_{775W},F_{814W},F_{850LP},F_{892N} \right\}\)
3. HST/ACS-HRC \(m_{1..17} = \left\{ F_{220W},F_{250W},F_{330W},F_{344N},F_{435W},F_{475W},F_{502N},F_{550M},F_{555W},F_{606W},F_{625W},F_{658N},F_{660N},F_{775W},F_{814W},F_{850LP},F_{892N} \right\}\)
4. Gaia \(m_{1..3} = \left\{ G_{BpDR2},G_{DR2}, G_{RpDR2}, G_{MAWb},G_{MAWf}, G_{MAW}, G_{RpMAW},G_{BpEDR3}, G_{EDR3},G_{RpEDR3} \right\}\)
5. SDSS \(m_{1..5} = \left\{ u, g, r, i, z \right\}\)
6. 2MASS \(m_{1..3} = \left\{J, H, K_s \right\}\)
7. CFHT \(m_{1..5} = \left\{u, g, r, i, z\right\}_{CFHT}\)
8. DECam \(m_{1..6} = \left\{u, g, r, i, z, y\right\}_{\rm{DECam}}\)
9. GALEX \(m_{1, 2} = \left\{F_{UV},N_{UV}\right\}\)
10. JWST \(m_{1, 29} = \left\{ \begin{array}{l}{F_{070W},F_{090W},F_{115W},F_{140M},F_{150W2},F_{150W},F_{162M},F_{164N},F_{182M},F_{187N},\\ F_{200W},F_{210M},F_{212N},F_{250M},F_{277W},F_{300M},F_{322W2},F_{323N},F_{335M},F_{356W}, \\ F_{360M},F_{405N},F_{410M},F_{430M},F_{444W},F_{460M},F_{466N},F_{470N},F_{480M}}\end{array}\right\}\).
11. LSST \(m_{1..6} = \left\{u,g,r,i,z,y\right\}_{\rm{LSST}}\)
12. Pan-STARRS \(m_{1..7} = \left\{g,r,i,z,y,w,open\right\}_{\rm{Pan - STARRS}}\)
13. SkyMapper \(m_{1..6} = \left\{u,v,g,r,i,z\right\}_{\rm{SkyMapper}}\)
14. Spitzer \(m_{1..4} = \left\{F_{3.6},F_{4.5},F_{5.8},F_{8.0}\right\}_{\rm{IRAC}}\)
15. Swift \(m_{1..6} = \left\{UVW2,UVM2,UVW1,U,B,V\right\}_{\rm{Swift}}\)
16. UKIDSS \(m_{1..5} = \left\{Z,Y,J,H,K\right\}_{\rm{UKIDSS}}\)
17. Washington \(m_{1..4} = \left\{C,M,{T_1,T_2}\right\}\)
18. Stromgren \(m_{1..4} = \left\{u,v,b,y\right\}\)
19. WISE \(m_{1..4} = \left\{W_1,W_2,W_3,W_4\right\}\)
20. Kepler \(m_{1..2} = \left\{K_p,D51\right\}\)
21. Hipparcos + Tyco \(m_{1..3} = \left\{B,H_p,V\right\}\)
22. HST-WFC3 \(m_{1..57} = \left\{ \begin{array}{l}{F_{200LP},F_{218W},F_{225W},F_{275W},F_{280N},F_{300X},F_{336W},F_{343N},F_{350LP},F_{373N}, \\ F_{390M},F_{390W},F_{395N},F_{410M},F_{438W},F_{467M},F_{469N},F_{475W},F_{475X},F_{487N}, \\ F_{502N},F_{547M},F_{555W},F_{600LP},F_{606W},F_{621M},F_{625W},F_{631N},F_{645N},F_{656N}, \\ F_{657N},F_{658N},F_{665N},F_{673N},F_{680N},F_{689M},F_{763M},F_{775W},F_{814W},F_{845M}, \\ F_{850LP},F_{953N},F_{098M},F_{105W},F_{110W},F_{125W},F_{126N},F_{127M},F_{128N},F_{130N},\\ F_{132N},F_{139M},F_{140W},F_{153M},F_{160W},F_{164N},F_{167N}}\end{array}\right\}\).
23. HST-WFPC2 \(m_{1..13} = \left\{ \begin{array}{l}{F_{218W},F_{255W},F_{300W},F_{336W},F_{439W},F_{450W},F_{555W},F_{606W},F_{622W},F_{675W}, \\ F_{791W},F_{814W},F_{850LP}}\end{array}\right\}\).
24. Subaru Hyper Suprime-Cam \(m_{1..7} = \left\{g, r, i, z, y, NB816, NB921 \right\}\)
25. INT Photometric H-alpha \(m_{1..3} = \left\{gR, Ha, gI \right\}\)
26. SDSS-PLUS \(m_{1..7} = \left\{g, r, i, z, y, NB816, NB921 \right\}\)
27. UVIT \(m_{1..9} = \left\{F_{148W}, F_{154W}, F_{169M}, F_{172M}, N_{242W}, N_{219M}, N_{245M}, N_{263M}, N_{279N}\right\}_{\rm{UVImgTel}}\)
28. VISTA \(m_{1..5} = \left\{Z, Y, J, H, K\right\}\)
29. Roman/RST (option 30) \(m_{1..8} = \left\{F062,F087,F106,F129,F158,F184,F213,F146\right\}_{\rm{Roman/RST}}\)

\(m_{X,\rm{app}}\left[ {mag} \right]\): apparent magnitude in photometric band \(X\), after distance modulus, extinction, photometric errors, and the unresolved-binary photometric contribution have been applied. For rows with \({\rm{Binary}}=1\), the listed magnitude is the unresolved system magnitude used by the selection cuts;

\(A_X\left[ {mag} \right]\): absorption in photometric band \(X\) for the source along the l.o.s.

The following columns contain the position and velocity-space description of each accepted system:

\(r_{\rm{hel}}\left[ {kpc} \right]\): heliocentric distance,

\(\left\{\alpha,\delta\right\}\left[ \deg \right]\) or \(\left\{l,b\right\}\left[ \deg \right]\): angular coordinates, depending on the selected FoV definition,

\(\left\{R,z,\phi+\phi_\odot\right\}\left[ {kpc,kpc,\deg} \right]\): Galactocentric cylindrical position,

\(v_{r,\rm{hel}}\left[ {km\;s^{ - 1}} \right]\): heliocentric radial velocity, including the binary radial-velocity perturbation where applicable,

\(\left\{\mu_\alpha,\mu_\delta\right\}\) or \(\left\{\mu_l,\mu_b\right\}\)\(\left[ mas\;yr^{ - 1} \right]\): proper motions in the two angular coordinates, including the binary photocentre-motion perturbation where applicable,

\(\left\{V_R,V_z,V_\phi\right\}\left[ {km\;s^{ - 1}} \right]\): Galactocentric cylindrical velocity components.

The final columns contain stellar-evolution, compact-object, binary, and CSP identifiers:

\(M_{\rm{ini}}\left[ M_\odot \right]\): initial stellar mass,

\(C/O\): carbon-to-oxygen value associated with the stellar-evolution stage,

\(K_{\rm{CO}}\): compact-object type flag,

\({\rm{Binary}}\): binary flag, equal to 1 for unresolved binary systems and 0 for single-star systems,

\(q_{\rm{bin}}\): binary mass ratio \(q=M_2/M_1\),

\(\left\{M_{1,\rm{now}},M_{2,\rm{now}}\right\}\left[ M_\odot \right]\): current primary and secondary masses,

\(\beta_{\rm{bin}}\): dimensionless binary photocentre/light parameter used by the kinematic correction,

\(P_{\rm{bin,d}}\left[ day \right]\): binary orbital period in days,

\(\Delta v_{r,\rm{bin}}\left[ {km\;s^{ - 1}} \right]\): binary-induced radial-velocity offset,

\(\left\{\Delta \mu_{1,\rm{bin}},\Delta \mu_{2,\rm{bin}}\right\} \left[ mas\;yr^{ - 1} \right]\): binary-induced proper-motion offsets along the two output angular coordinates,

\({\rm{CSP}}\): composite stellar population type. For single-star systems, the binary-specific quantities are set to zero.

 

Binary-star photometric and observed-kinematic corrections are generated statistically from the input binary fraction and the current GalMod binary prescription. Simulations are made at one's own risk. The authors are not responsible for wrong applications of their model. For further information, please contact Galaxy.Model@yahoo.com.

The support team can be reached at Galaxy.Model@Yahoo.com. GalMod is hosted by a cloud service; the support team does not have access to either the user’s email or to the produced simulations. If support on a simulation is needed, please contact the support email and include the first 100 lines of the file received. These contain the GalMod version and the parameters introduced in the form, and this will enable us to regenerate a simulation with the same version of GalMod.

Jun 2018 release (ver. 17.10): bug fixed on the azimuthal velocity written in the output table.

Oct 2018 release (ver. 17.20): bug fixed on the M31/dwarf-galaxies velocity field and FoV definition. New faster extinction and gravitational potential computation algorithms.

Dec 2018 release (ver. 18.01): numerous bugs evidenced by a larger GalMod community of users. Bug fixed on the M31/dwarf-galaxies FoV definition. Bug fixed on the M31/dwarf-galaxies FoV radial velocity computation. Bug fixed on the number of stars computed beyond the Galactic center in the (l,b)=(0,0) direction. Bug fixed on the vertical velocity dispersion for some young stellar populations. Bug fixed on the HR diagram for masses of 0.6 Msun. Bug fixed for the random generator of the age/metallicity distribution. Minor bugs fixed on the kinematics computation. Furthermore, in the semi-equilibrium model initial-condition generator mode, GalMod no longer uses the database of simulations (in this way, every time the user runs a simulation, new, different i.c. are generated). Use of co-arrays (and other Fortran 2018 features) has been implemented to speed up the computations.

Feb 2019 release (ver. 18.06): bug fixed on the position angle for the M31/dwarf-galaxies simulation mode.

Mar 2019 release (ver. 18.06): Simplified web-page with Basic and Advanced input form. Implemented encryption with SSL Certificate Management System.

Apr 2019 release (ver. 18.09): bug fixed to handle crashes gracefully.

Jul 2019 release (ver. 18.15): Introduction of parallel tempering technique to sample the posterior probability distribution functions more efficiently. Introduction of the small-FoV approximation to the solution of the star count equation to speed up the computation of very small FoV. Bug fixed in the bulge dispersion velocity computation of external galaxy models and/or MW bulge.

Aug 2019 release (ver. 18.19): Subaru Hyper Suprime-Cam photometry added to the synthetic CMD generator, extinction model, and webpage access. Bugs fixed on selection cuts.

Sep 2020 release (ver. 18.20): Speed up extinction computation. Bugs fixed.

Dec 2020 release (ver. 18.21): Bugs on the AI memory database fixed. Extinction computing bug fixed.

Nov 2021 release (ver. 18.22): New spherical frustum definitions.

Dec 2022 release (ver. 18.23): Bugs on M31-FoV generation fixed.

Jan 2024 release (ver. 19.01): Multiple thin disk stellar populations, new hardware, new webpage.

Feb 2024 release (ver. 19.03): Bug fixed on stellar halo total mass computation. New extinction map calibrated.

Mar 2024 release (ver. 19.04): Delivering up to 1e6 stars in .tgz output format.

Jun 2024 release (ver. 19.05): webpage bug fixed, new input/output reader, bugs on the number of stars computed fixed.

Jun 2024 release (ver. 19.06): M31 FoV model bugs reported and fixed.

Feb 2026 release (ver. 20.02): bugs in the number-of-stars normalization fixed.

Apr 2026 release (ver. 21.25): new MIST-based photometry, including AGB and white-dwarf sequences; new bolometric corrections from the MIST photometric tables; five new photometric systems added (INT Photometric H-alpha, S-PLUS, UVIT, VISTA, and Roman/RST), with Gaia DR3 photometry updated; optimized performance for faster catalog generation.

May 2026 release (ver. 22.07): binary-star support added to the online GalMod workflow and to the synthetic-catalog engine. The web interface now includes a Binary Fraction input, allowing the user to set the fraction of generated systems treated as binaries directly from the basic form. Binary systems are now propagated through the Hertzsprung-Russell and color-magnitude diagram generation, so unresolved binary contributions are included in the synthetic photometry and in the photometric selection cuts. The catalog generation also carries binary-state information into the velocity-space stage, including companion-related quantities and binary-induced radial-velocity and proper-motion perturbations where applicable.