Overview¶
By now you have hopefully installed the code and downloaded a grid file. You’re now ready to start using synthesizer.
In this section we briefly describe the main elements of the code, and the design philosophy.
Grids¶
Grids are one of the fundamental components in synthesizer.
At its simplest, a grid describes the emission as a function of some parameters.
Typically these are the age and metallicity of a stellar population, and the emission is derived from a stellar population synthesis (SPS) model (see Conroy 2013 for a review).
However, these parameters can be arbitrary, of any number of dimensions, and the emission can describe any source. For example, one could have a grid that has been post-processed through a photoionisation code, where the ionisation parameter is changed, or the source could be the emission from the narrow line region of an active galactic nuclei. Different grids can also be swapped in and out to assess the impact of different modelling choices; for example, one might wish to understand the impact of different SPS models on the integrated stellar emission.
We provide a number of pre-computed grids for stellar and AGN emission that will be sufficient for most use cases.
Advanced users can also generate their own grids, using the synthesizer-grids package (see here).
Particle vs Parametric¶
Synthesizer can be used to generate the multi-wavelength emission from a range of astrophysical models with a wide array of complexity and fidelity. At one end, simple toy models can be generated within synthesizer that describe a galaxy through analytic forms; at the other end, data from high resolution isolated galaxy simulations can be ingested into synthesizer, consisting of tens of thousands of discrete elements describing the galaxy properties.
Wherever your data source lies on this spectrum of complexity, it can typically be described as belonging to one of two types: Particle or Parametric data.
Particle data represents an astrophysical object through discrete elements with individual properties. These can describe, for example, the spatial distribution of stellar mass, or the ages of individual star elements. We use the term ‘particle’ here in the most general form to describe a discrete resolution element; whether that’s a particle element in a smoothed particle hydrodynamics simulation, or a grid element in an adaptive mesh refinement code.
Conversely, Parametric data typically represents a galaxy through binned attributes. This binning can be represented along different dimensions representing various properties of the galaxy. An example of this is the star formation history; a parametric galaxy would describe this history by dividing the mass formed into bins of age.
Whilst both of these approaches may appear to be superficially similar, there are some important distinctions under the hood within synthesizer. In most use cases synthesizer will be smart enough to know what kind of data you are providing, and create the appropriate objects as required. However, it is worth understanding this distinction, particularly when debugging any issues. We provide examples for various tasks in synthesizer using both particle and parametric approaches where applicable.
Galaxies & Components¶
The main object within synthesizer is a Galaxy. A Galaxy object describes various discrete properties of a galaxy (e.g. its redshift), and also contains individual components.
These components can include:
A stellar component
A gas component
Black hole components
A component in synthesizer can be initialised and used independently of a Galaxy object, and the emission from that individual component can also be generated.
However, much of the power of synthesizer comes from combining these components; a Galaxy object simplifies how they interact with one another, making the self-consistent generation of complex spectra from various components within a galaxy simpler and faster.
Emission models¶
The generation of spectra in synthesizer is handled through Emission Models.
An emission model is a set of standardised procedures for generating spectra from a Galaxy or a component.
These often take one of four forms: extraction, combinations, generation, and attenuation.
Further details are provided in the
Emission Models section.
Observables¶
Once the emission from a galaxy or component has been generated, typically through an emission model, it can be represented or transformed into a variety of different observables.
The simplest is the full spectral energy distribution (SED), represented through an Sed object.
Sed objects contain a variety of useful methods for accessing the luminosity, flux and wavelength, as well as other more specific properties and derived properties (for example, the strength of the Balmer break).
An Sed can be transformed into broad- or narrow-band photometry through filters, represented by a Filter object, or a FilterCollection if multiple filters are defined.
Images, either monochromatic, RGB, or integral field unit (IFU), can also be created, typically where spatial information on the emitting sources is provided. Parametric morphologies can also be created for parametric galaxies.
Philosophy¶
Synthesizer is intended to be modular, flexible and fast. The framework developed can be used for a number of tasks, not necessarily limited to generating observables from cosmological simulations. It is not intended as a replacement for detailed codes for generating synthetic galaxy emission that leverage radiative transfer techniques (e.g. SKIRT, Powderday). Instead, synthesizer is intended to be much cheaper computationally, allowing an exploration of parameter and model dependencies. We hope it is of value to the community, and welcome contributions.
We hope you enjoy using synthesizer!