Physics Models#

UCLCHEM includes several physics modules that model different astrophysical environments. Each module implements specific physical processes — density evolution, temperature profiles, shock physics — alongside the chemical network. This guide introduces the available models and helps you choose the right one for your research.

Available Models#

UCLCHEM provides six physics modules:

Cloud

Static or collapsing spherical clouds with depth-dependent chemistry

uclchem.model.cloud()

Cloud Model
Collapse

Power-law density evolution for gravitational collapse

uclchem.model.collapse()

Collapse Models
Hot Core

Warm-up from cold core to hot protostellar environment

uclchem.model.hot_core()

Hot Core
C-Shock

C-type magnetohydrodynamic shocks with ion-neutral drift

uclchem.model.cshock()

Shock Models
J-Shock

J-type jump shocks with discontinuous fronts

uclchem.model.jshock()

Shock Models
Hydro

Post-process hydrodynamical simulation outputs

Python postprocess module

Hydro Post Processing

Quick Guide: Choosing a Model#

For static molecular clouds: Use Cloud with freefall=0. Good for UV-shielded regions with constant density and temperature.

For collapsing clouds: Use Cloud with freefall=1 for simple freefall, or Collapse for specific density profiles.

For prestellar cores: Use Prestellar Core to model warm-up from a cold initial state to protostellar temperatures with ice sublimation.

For shock chemistry: Use C-Shock for magnetized shocks or J-Shock for fast, discontinuous shocks.

For hydrodynamical simulations: Use the Hydro postprocessing module to integrate UCLCHEM chemistry along particle trajectories.

Common Features#

All physics modules share core capabilities:

  • 1D spatial structure: Most models support multi-point calculations with depth-dependent UV shielding. See Tram et al 2026 for a detailed treatment.

  • Time integration: ODE solver advances chemistry and physics together

  • Output control: Flexible frequency and format options

  • Multi-stage workflows: Link models in sequence (e.g., cloud → prestellar core → shock model)

Getting Started#

The best way to learn is through examples:

Tutorials:

  • First Model — Run a basic cloud model

  • Multi-stage Modelling — Chain physics modules

  • Advanced Settings — Custom physics

Detailed Documentation: Each model has comprehensive documentation covering physics equations, parameters, and best practices. See the linked pages above or the User Guide index.

API Reference: All physics functions are documented in the API section with complete parameter lists and return values.

See also