Available Reaction Networks
A network defines the composition, which is needed by the equation of state and transport coefficient routines. Even if there are no reactions taking place, a network still needs to be defined, so Microphysics knows the properties of the fluid.
Tip
If reactions can be ignored, then the general_null
network can
be used — this simply defines a composition with no reactions.
Note
Many of the networks here are generated using pynucastro using the AmrexAstroCxxNetwork
class.
general_null
general_null
is a bare interface for a nuclear reaction network —
no reactions are enabled. The
data in the network is defined at compile type by specifying an
inputs file. For example,
networks/general_null/triple_alpha_plus_o.net
would describe the
triple-
# name short name aion zion
helium-4 He4 4.0 2.0
carbon-12 C12 12.0 6.0
oxygen-16 O16 16.0 8.0
iron-56 Fe56 56.0 26.0
The four columns give the long name of the species, the short form that will be used
for plotfile variables, and the mass number,
The name of the inputs file by one of two make variables:
NETWORK_INPUTS
: this is simply the name of the “.net” file, without any path. The build system will look for it in the current directory and then in$(MICROPHYSICS_HOME)/networks/general_null/
.For the example above, we would set:
NETWORK_INPUTS := triple_alpha_plus_o.net
GENERAL_NET_INPUTS
: this is the full path to the file. For example we could set:GENERAL_NET_INPUTS := /path/to/file/triple_alpha_plus_o.net
At compile time, the “.net” file is parsed and a network header
network_properties.H
is written using the python script
write_network.py
. The make rule for this is contained in
Microphysics/networks/Make.package
.
iso7
, aprox13
, aprox19
, and aprox21
These are alpha-chains (with some other nuclei) based on the original
Fortran networks from Frank Timmes. These
networks share common rates from Microphysics/rates
and are
implemented using the templated C++ network infrastructure.
These networks approximate a lot of the links, in particular,
combining
The available networks are:
iso7
: contains , , , , , , and is based on [11].aprox13
: adds , , , , ,aprox19
: adds , , , , , . Here, participates only in the photodisintegration rates at high mass number, and is distinct from .aprox21
: adds , . This is designed to reach a lower than the other networks, for use in massive star simulations. Note that the link to is greatly approximated.
These networks store the total binding energy of the nucleus in MeV as
bion(:)
. They then compute the mass of each nucleus in grams as:
where mion(:)
in the network.
The energy release per gram is converted from the rates as:
where
CNO_extras
This network replicates the popular MESA “cno_extras” network which is meant to study hot-CNO burning and the start of the breakout from CNO burning. This network is managed by pynucastro.
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Note
We add
nova networks
The nova
and nova2
networks both are intended for modeling classical novae.
nova
focuses just on CNO/hot-CNO:nova2
expandsnova
by adding the pp-chain nuclei:
He-burning networks
This is a collection of networks meant to model He burning. The are inspired by the “aprox”-family of networks, but contain more nuclei/rates, and are managed by pynucastro.
One feature of these networks is that they include a bypass rate for
at high temperatures (T > 1 GK). We don’t consider this. is the one they consider important, since it produces protons that are then available for .
This leaves
For the
Since the neutron captures on those intermediate nuclei are so fast, we leave those out and take the forward rate to just be the first rate. We do not include reverse rates for these processes.
These networks also combine some of the
The networks are named with a descriptive name, the number of nuclei,
and the letter a
if they approximate n
if they approximate double-neutron capture, and the
letter p
if they split the protons into two groups (one for
photo-disintegration).
he-burn-18a
Note
This network was previously called subch_base
.
This is the simplest network and is similar to aprox13
, but includes
a better description of
It has the following features / simplifications:
, , , , , and are approximated out of the links.The nuclei
, , , and are not included. This means that we do not capture the rate sequence.The reverse rates of
, , are neglected since they’re not present in the original aprox13 networkThe
rate is removedThe
links between , and between and are removed, since they’re not in the original aprox13 network.
The network appears as:

The nuclei in gray are those that have been approximated about, but the links are effectively accounted for in the approximate rates.
There are 2 runtime parameters that can be used to disable rates:
network.disable_p_c12__n13
: if set to1
, then the rate and its inverse are disabled.network.disable_he4_n13__p_o16
: if set to1
, then the rate and its inverse are disabled.
Together, these parameters allow us to turn off the sequence
he-burn-22a
Note
This network was previously called subch_simple
.
This builds on he-burn-18a
by including the
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Warning
Due to inclusion of the rate sequence,
Like he-burn-18a
, there are 2 runtime parameters that can disable
the rates for the
he-burn-31anp
This builds on he-burn-22a
by adding some iron-peak nuclei. It no longer
approximates out
The iron group here resembles aprox21
, but has the addition of stable

he-burn-36a
This has the most complete iron-group, with nuclei up to

CNO_He_burn
This network is meant to study explosive H and He burning. It combines
the CNO_extras
network (with the exception of the inert he-burn-22a
network. This allows it to capture hot-CNO and
He burning.
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ECSN
ECSN
is meant to model electron-capture supernovae in O-Ne white dwarfs.
It includes various weak rates that are important to this process.
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C-ignition networks
There are a number of networks that have been developed for exploring carbon burning in near-Chandrasekhar mass which dwarfs.
ignition_chamulak
This network was introduced in our paper on convection in white dwarfs as a model of Type Ia supernovae [13]. It models carbon burning in a regime appropriate for a simmering white dwarf, and captures the effects of a much larger network by setting the ash state and energetics to the values suggested in [14].
The binding energy,
(this is positive since both
ignition_reaclib
This contains several networks designed to model C burning in WDs. They include:
C-burn-simple
: a version ofignition_simple
built from ReacLib rates. This just includes the C+C rates and doesn’t group the endpoints together.URCA-simple
: a basic network for modeling convective Urca, containing the - Urca pair.URCA-medium
: a more extensive Urca network thanURCA-simple
, containing more extensive C burning rates.
ignition_simple
This is the original network used in our white dwarf convection
studies [15]. It includes a single-step
where
powerlaw
This is a simple single-step reaction rate.
We will consider only two species, fuel,
with
Here,
We define a new rate constant,
where
Finally, for the
energy generation, we take our reaction to release a specific energy,
There are a number of parameters we use to control the constants in
this network. This is one of the few networks that was designed
to work with gamma_law
as the EOS.
rprox
This network contains 10 species, approximating hot CNO,
triple-
triple_alpha_plus_cago
This is a 2 reaction network for helium burning, capturing the