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Astrocook

Absorbers cookbook

Table of contents

  1. New systems from likelihood
  2. Complete systems from likelihood
  3. New systems from line list
  4. Complete systems
  5. Find candidate systems
  6. Improve systems
  7. Fit systems
  8. Clean system list
  9. Recreate the models
  10. Estimate SNR of systems
  11. Select systems
  12. Extract systems based on components
  13. Merge a system into the current system

New systems from likelihood

Method CookbookAbsorbers.systs_new_from_like
Parameters
  • series: Series of transitions
  • z_start: Start redshift
  • z_end: End redshift
  • dz: Threshold for redshift coincidence
  • modul: Modulation of the error function
  • thres: Threshold for accepting likelihood
  • distance: Distance between systems in pixels
  • logN: Guess (logarithmic) column density
  • b: Guess Doppler broadening
  • resol: Resolution
  • chi2r_thres: Reduced chi2 threshold to accept the fitted model
  • dlogN_thres: Column density error threshold to accept the fitted model
  • refit_n: Number of refit cycles
  • chi2rav_thres: Average chi2r variation threshold between cycles
  • max_nfev: Maximum number of function evaluation
  • append: Append systems to existing system list
JSON template 
{
  "cookbook": "cb",
  "recipe": "systs_new_from_like",
  "params": {
    "series": "'Ly-a'",
    "z_start": "0",
    "z_end": "6",
    "dz": "0.0001",
    "modul": "1",
    "thres": "0.997",
    "distance": "10",
    "logN": "14",
    "b": "10",
    "resol": "null",
    "chi2r_thres": "inf",
    "dlogN_thres": "inf",
    "refit_n": "0",
    "chi2rav_thres": "0.01",
    "max_nfev": "1000",
    "append": "true"
  }
}

TBD

Complete systems from likelihood

Method CookbookAbsorbers.systs_complete_from_like
Parameters
  • series: Series of transitions
  • series_ref: Reference series of transitions
  • z_start: Start redshift
  • z_end: End redshift
  • binz: Bin size to group existing redshifts
  • dz: Threshold for redshift coincidence
  • modul: Modulation of the error function
  • thres: Threshold for accepting
  • distance: Distance between systems in pixels
  • logN: Guess (logarithmic) column density
  • b: Guess Doppler broadening
  • resol: Resolution
  • chi2r_thres: Reduced chi2 threshold to accept the fitted model
  • dlogN_thres: Column density error threshold to accept the fitted model
  • refit_n: Number of refit cycles
  • chi2rav_thres: Average chi2r variation threshold between cycles
  • max_nfev: Maximum number of function evaluation
  • append: Append systems to existing system list
JSON template 
{
  "cookbook": "cb",
  "recipe": "systs_complete_from_like",
  "params": {
    "series": "'all'",
    "series_ref": "null",
    "z_start": "0",
    "z_end": "6",
    "binz": "0.01",
    "dz": "0.0001",
    "modul": "1",
    "thres": "0.997",
    "distance": "10",
    "logN": "14",
    "b": "10",
    "resol": "null",
    "chi2r_thres": "inf",
    "dlogN_thres": "inf",
    "refit_n": "0",
    "chi2rav_thres": "0.01",
    "max_nfev": "1000",
    "append": "true"
  }
}

TBD

New systems from line list

Method CookbookAbsorbers.systs_new_from_lines
Parameters
  • series: Series of transitions
  • z_start: Start redshift
  • z_end: End redshift
  • dz: Threshold for redshift coincidence
  • logN: Guess (logarithmic) column density
  • b: Guess Doppler broadening
  • resol: Resolution
  • chi2r_thres: Reduced chi2 threshold to accept the fitted model
  • dlogN_thres: Column density error threshold to accept the fitted model
  • refit_n: Number of refit cycles
  • chi2rav_thres: Average chi2r variation threshold between cycles
  • max_nfev: Maximum number of function evaluation
  • append: Append systems to existing system list
JSON template 
{
  "cookbook": "cb",
  "recipe": "systs_new_from_lines",
  "params": {
    "series": "'Ly-a'",
    "z_start": "0",
    "z_end": "6",
    "dz": "0.0001",
    "logN": "14",
    "b": "10",
    "resol": "null",
    "chi2r_thres": "inf",
    "dlogN_thres": "inf",
    "refit_n": "0",
    "chi2rav_thres": "0.01",
    "max_nfev": "1000",
    "append": "true"
  }
}

Add and fit Voigt models to a line list, given a redshift range.

Complete systems

Method CookbookAbsorbers.systs_complete
Parameters
  • series: Series of transitions
  • dz: Threshold for redshift coincidence
  • resol: Resolution
  • avoid_systs: Avoid adding transitions over systems already fitted
JSON template 
{
  "cookbook": "cb",
  "recipe": "systs_complete",
  "params": {
    "series": "'all'",
    "dz": "0.0001",
    "resol": "null",
    "avoid_systs": "true"
  }
}

Add candidate transitions to fitted systems.

Find candidate systems

Method CookbookAbsorbers.cands_find
Parameters
  • series: Series of transitions
  • z_start: Start redshift
  • z_end: End redshift
  • dz: Threshold for redshift coincidence
  • resol: Resolution
  • avoid_systs: Avoid finding candidates over systems already detected
  • append: Append systems to existing system list
JSON template 
{
  "cookbook": "cb",
  "recipe": "cands_find",
  "params": {
    "series": "'all'",
    "z_start": "0",
    "z_end": "6",
    "dz": "0.0001",
    "resol": "null",
    "avoid_systs": "true",
    "append": "true"
  }
}

Cross-match line wavelengths with known transitions to find candidate systems.

Improve systems

Method CookbookAbsorbers.systs_improve
Parameters
  • impr_n: Number of improve cycles
  • refit_n: Number of refit cycles
JSON template 
{
  "cookbook": "cb",
  "recipe": "systs_improve",
  "params": {
    "impr_n": "3",
    "refit_n": "0"
  }
}

Improve systems adding components to reduce residuals

Fit systems

Method CookbookAbsorbers.systs_fit
Parameters
  • refit_n: Number of refit cycles
  • chi2rav_thres: Average chi2r variation threshold between cycles
  • max_nfev: Maximum number of function evaluation
  • sel_fit: Selective fit (only new systems will be fitted)
JSON template 
{
  "cookbook": "cb",
  "recipe": "systs_fit",
  "params": {
    "refit_n": "3",
    "chi2rav_thres": "0.01",
    "max_nfev": "1000",
    "sel_fit": "false"
  }
}

Fit all Voigt model from a list of systems.

Clean system list

Method CookbookAbsorbers.systs_clean
Parameters
  • chi2r_thres: Reduced chi2 threshold to accept the fitted model
  • dlogN_thres: Column density error threshold to accept the fitted model
  • max_nfev: Maximum number of function evaluation
JSON template 
{
  "cookbook": "cb",
  "recipe": "systs_clean",
  "params": {
    "chi2r_thres": "2.0",
    "dlogN_thres": "1.0",
    "max_nfev": "1000"
  }
}

Clean systems from a list by rejecting systems with reduced chi2 and/or error on column density above a given threshold

Recreate the models

Method CookbookAbsorbers.mods_recreate
Parameters –
JSON template 
{
  "cookbook": "cb",
  "recipe": "mods_recreate",
  "params": {
  }
}

Recreate the models from the current system list.

Estimate SNR of systems

Method CookbookAbsorbers.systs_snr
Parameters –
JSON template 
{
  "cookbook": "cb",
  "recipe": "systs_snr",
  "params": {
  }
}

Estimate the signal-to-noise ratio of systems as the median flux/flux error ratio in the group interval.

Select systems

Method CookbookAbsorbers.systs_select
Parameters
  • series: Series
  • z_min: Minimum redshift
  • z_max: Maximum redshift
  • logN_min: Minimum (logarithmic) column density
  • logN_max: Maximum (logarithmic) column density
  • b_min: Minimum Doppler broadening
  • b_max: Maximum Doppler broadening
  • col: Other column
  • col_min: Minimum of other column
  • col_max: Maximum of other column
JSON template 
{
  "cookbook": "cb",
  "recipe": "systs_select",
  "params": {
    "series": "'any'",
    "z_min": "0.0",
    "z_max": "10.0",
    "logN_min": "10.0",
    "logN_max": "22.0",
    "b_min": "1.0",
    "b_max": "100.0",
    "col": "null",
    "col_min": "null",
    "col_max": "null"
  }
}

Select systems based on their Voigt and fit parameters. A logical and is applied to all conditions.

Extract systems based on components

Method CookbookAbsorbers.comp_extract
Parameters
  • num: Number of components
JSON template 
{
  "cookbook": "cb",
  "recipe": "comp_extract",
  "params": {
    "num": "1"
  }
}

Extract systems with less than a given number of components

Merge a system into the current system

Method CookbookAbsorbers.systs_merge
Parameters
  • num1: Row of the current system
  • num2: Row of the system to be merged
JSON template 
{
  "cookbook": "cb",
  "recipe": "systs_merge",
  "params": {
    "to_row": "0",
    "from_rows": "[1]"
  }
}

Merged systems appear as a single entry in the compressed system table.