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Tracers

Classes to handle a biased tracer on top of a density field.

HITracer (TracerModel)

Source code in fastbox/tracers.py 
class HITracer(TracerModel):

    def __init__(self, box, OmegaHI0=0.000486, bHI0=0.677105):
        """
        An object to manage a biased tracer on top of a realisation of a 
        density field in a box.

        Parameters:
            box (CosmoBox):
                Object containing a simulation box.

            OmegaHI0 (float, optional):
                Fractional density of HI at redshift 0.

            bHI0 (float, optional):
                HI bias at redshift 0.
        """
        # Initialise superclass
        super().__init__(box)

        # Set parameters
        self.OmegaHI0 = OmegaHI0
        self.bHI0 = bHI0


    def signal_amplitude(self, redshift=None, formula='powerlaw'):
        """
        Brightness temperature Tb(z), in mK. Several different expressions for the 
        21cm line brightness temperature are available:

        Parameters:
            redshift (float, optional):
                Central redshift to evaluate the signal amplitude at. If not 
                specified, uses `self.box.redshift`.

            formula (str, optional):
                Which fitting formula to use for the brightness temperature. Some 
                of the options are a function of Omega_HI(z)

                - ``powerlaw``: Simple power-law fit to Mario's updated data 
                (powerlaw M_HI function with alpha=0.6) (Default)

                - ``hall``: From Hall, Bonvin, and Challinor.
        """
        if redshift is None:
            redshift = self.box.redshift
        z = redshift

        # Calculate OmegaHI(z)
        omegaHI = self.Omega_HI(redshift=redshift)

        # Select which formula to use
        if formula == 'powerlaw':
            # Mario Santos' fit, used in Bull et al. (2015)
            Tb = 5.5919e-02 + 2.3242e-01*z - 2.4136e-02*z**2.

        elif formula == 'hall':
            # From Hall et al.
            E = ccl.h_over_h0(self.box.cosmo, 1./(1.+z))
            Tb = 188. * self.box.cosmo['h'] * omegaHI * (1.+z)**2. / E

        else:
            raise ValueError("No formula found with name '%s'" % formula)
        return Tb


    def bias_HI(self, redshift=None):
        """
        HI bias as a function of redshift.

        Parameters:
            redshift (float, optional):
                Central redshift to evaluate the signal amplitude at. If not 
                specified, uses `self.box.redshift`.
        """
        if redshift is None:
            redshift = self.box.redshift
        z = redshift

        # Fitting formula, based on Mario Santos' halo model calculation 
        # (see Bull et al. 2015)
        return (self.bHI0/0.677105)*(6.6655e-01 + 1.7765e-01*z + 5.0223e-02*z**2.)


    def Omega_HI(self, redshift=None, formula='powerlaw'):
        """
        Fractional density of HI as a function of redshift, from a fitting 
        function.

        Parameters:
            redshift (float, optional):
                Central redshift to evaluate the signal amplitude at. If not 
                specified, uses `self.box.redshift`.
        """
        if redshift is None:
            redshift = self.box.redshift
        z = redshift

        # Fitting formula; see Bull et al. (2015)
        return (self.OmegaHI0 / 0.000486) \
             * (4.8304e-04 + 3.8856e-04*z - 6.5119e-05*z**2.)

Omega_HI(self, redshift=None, formula='powerlaw')

Fractional density of HI as a function of redshift, from a fitting function.

Parameters:

Name Type Description Default
redshift float

Central redshift to evaluate the signal amplitude at. If not specified, uses self.box.redshift.

 None
Source code in fastbox/tracers.py 
def Omega_HI(self, redshift=None, formula='powerlaw'):
    """
    Fractional density of HI as a function of redshift, from a fitting 
    function.

    Parameters:
        redshift (float, optional):
            Central redshift to evaluate the signal amplitude at. If not 
            specified, uses `self.box.redshift`.
    """
    if redshift is None:
        redshift = self.box.redshift
    z = redshift

    # Fitting formula; see Bull et al. (2015)
    return (self.OmegaHI0 / 0.000486) \
         * (4.8304e-04 + 3.8856e-04*z - 6.5119e-05*z**2.)

__init__(self, box, OmegaHI0=0.000486, bHI0=0.677105) special

An object to manage a biased tracer on top of a realisation of a density field in a box.

Parameters:

Name Type Description Default
box CosmoBox

Object containing a simulation box.

 required
OmegaHI0 float

Fractional density of HI at redshift 0.

 0.000486
bHI0 float

HI bias at redshift 0.

 0.677105
Source code in fastbox/tracers.py 
def __init__(self, box, OmegaHI0=0.000486, bHI0=0.677105):
    """
    An object to manage a biased tracer on top of a realisation of a 
    density field in a box.

    Parameters:
        box (CosmoBox):
            Object containing a simulation box.

        OmegaHI0 (float, optional):
            Fractional density of HI at redshift 0.

        bHI0 (float, optional):
            HI bias at redshift 0.
    """
    # Initialise superclass
    super().__init__(box)

    # Set parameters
    self.OmegaHI0 = OmegaHI0
    self.bHI0 = bHI0

bias_HI(self, redshift=None)

HI bias as a function of redshift.

Parameters:

Name Type Description Default
redshift float

Central redshift to evaluate the signal amplitude at. If not specified, uses self.box.redshift.

 None
Source code in fastbox/tracers.py 
def bias_HI(self, redshift=None):
    """
    HI bias as a function of redshift.

    Parameters:
        redshift (float, optional):
            Central redshift to evaluate the signal amplitude at. If not 
            specified, uses `self.box.redshift`.
    """
    if redshift is None:
        redshift = self.box.redshift
    z = redshift

    # Fitting formula, based on Mario Santos' halo model calculation 
    # (see Bull et al. 2015)
    return (self.bHI0/0.677105)*(6.6655e-01 + 1.7765e-01*z + 5.0223e-02*z**2.)

signal_amplitude(self, redshift=None, formula='powerlaw')

Brightness temperature Tb(z), in mK. Several different expressions for the 21cm line brightness temperature are available:

Parameters:

Name Type Description Default
redshift float

Central redshift to evaluate the signal amplitude at. If not specified, uses self.box.redshift.

 None
formula str

Which fitting formula to use for the brightness temperature. Some of the options are a function of Omega_HI(z)

  • powerlaw: Simple power-law fit to Mario's updated data (powerlaw M_HI function with alpha=0.6) (Default)

  • hall: From Hall, Bonvin, and Challinor.

 'powerlaw'
Source code in fastbox/tracers.py 
def signal_amplitude(self, redshift=None, formula='powerlaw'):
    """
    Brightness temperature Tb(z), in mK. Several different expressions for the 
    21cm line brightness temperature are available:

    Parameters:
        redshift (float, optional):
            Central redshift to evaluate the signal amplitude at. If not 
            specified, uses `self.box.redshift`.

        formula (str, optional):
            Which fitting formula to use for the brightness temperature. Some 
            of the options are a function of Omega_HI(z)

            - ``powerlaw``: Simple power-law fit to Mario's updated data 
            (powerlaw M_HI function with alpha=0.6) (Default)

            - ``hall``: From Hall, Bonvin, and Challinor.
    """
    if redshift is None:
        redshift = self.box.redshift
    z = redshift

    # Calculate OmegaHI(z)
    omegaHI = self.Omega_HI(redshift=redshift)

    # Select which formula to use
    if formula == 'powerlaw':
        # Mario Santos' fit, used in Bull et al. (2015)
        Tb = 5.5919e-02 + 2.3242e-01*z - 2.4136e-02*z**2.

    elif formula == 'hall':
        # From Hall et al.
        E = ccl.h_over_h0(self.box.cosmo, 1./(1.+z))
        Tb = 188. * self.box.cosmo['h'] * omegaHI * (1.+z)**2. / E

    else:
        raise ValueError("No formula found with name '%s'" % formula)
    return Tb

TracerModel

Source code in fastbox/tracers.py 
class TracerModel(object):

    def __init__(self, box):
        """
        An object to manage a biased tracer on top of a realisation of a 
        density field in a box.

        Parameters:
            box (CosmoBox):
                Object containing a simulation box.
        """
        self.box = box


    def signal_amplitude(self, amp, redshift):
        """
        Overall signal amplitude (e.g. mean brightness temperature). This is a 
        simple constant-amplitude model.

        Parameters:
            amp (float):
                Overall amplitude.

            redshift (float):
                Redshift to evaluate the amplitude at.

        Returns:
            bias (float):
                Bias at given redshift.
        """
        return amp + 0.*redshift # same shape as redshift


    def linear_bias(self, b0, redshift):
        """
        Linear bias model, b(z) = b0 sqrt(1 + z)

        Parameters:
            b0 (float):
                Overall bias amplitude.

        redshift (float):
            Redshift to evaluate the bias at.

        Returns:
            bias (float):
                Bias at given redshift.
        """
        return b0 * np.sqrt(1. + redshift)

__init__(self, box) special

An object to manage a biased tracer on top of a realisation of a density field in a box.

Parameters:

Name Type Description Default
box CosmoBox

Object containing a simulation box.

 required
Source code in fastbox/tracers.py 
def __init__(self, box):
    """
    An object to manage a biased tracer on top of a realisation of a 
    density field in a box.

    Parameters:
        box (CosmoBox):
            Object containing a simulation box.
    """
    self.box = box

linear_bias(self, b0, redshift)

Linear bias model, b(z) = b0 sqrt(1 + z)

Parameters:

Name Type Description Default
b0 float

Overall bias amplitude.

 required

redshift (float): Redshift to evaluate the bias at.

Returns:

Type Description
bias (float)

Bias at given redshift.
Source code in fastbox/tracers.py 
def linear_bias(self, b0, redshift):
    """
    Linear bias model, b(z) = b0 sqrt(1 + z)

    Parameters:
        b0 (float):
            Overall bias amplitude.

    redshift (float):
        Redshift to evaluate the bias at.

    Returns:
        bias (float):
            Bias at given redshift.
    """
    return b0 * np.sqrt(1. + redshift)

signal_amplitude(self, amp, redshift)

Overall signal amplitude (e.g. mean brightness temperature). This is a simple constant-amplitude model.

Parameters:

Name Type Description Default
amp float

Overall amplitude.

 required
redshift float

Redshift to evaluate the amplitude at.

 required

Returns:

Type Description
bias (float)

Bias at given redshift.
Source code in fastbox/tracers.py 
def signal_amplitude(self, amp, redshift):
    """
    Overall signal amplitude (e.g. mean brightness temperature). This is a 
    simple constant-amplitude model.

    Parameters:
        amp (float):
            Overall amplitude.

        redshift (float):
            Redshift to evaluate the amplitude at.

    Returns:
        bias (float):
            Bias at given redshift.
    """
    return amp + 0.*redshift # same shape as redshift