diff --git a/docs/index.rst b/docs/index.rst
index be7484958c2..382e09b0027 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -22,8 +22,6 @@ rapid spectral modelling of supernovae. The code is described in this documentat
     atomic/atomic_data
     workflow/development_workflow
     physics/index
-    plasma
-    montecarlo
     changelog
     glossary
     zreferences
diff --git a/docs/physics/index.rst b/docs/physics/index.rst
index 09b1d72084f..456a8ad461b 100644
--- a/docs/physics/index.rst
+++ b/docs/physics/index.rst
@@ -8,5 +8,6 @@ gradually expanded
 .. toctree::
     :maxdepth: 1
 
+    physical_quantities
     montecarlo
-    plasma
\ No newline at end of file
+    plasma
diff --git a/docs/physics/physical_quantities.rst b/docs/physics/physical_quantities.rst
new file mode 100644
index 00000000000..a6a7eeb6506
--- /dev/null
+++ b/docs/physics/physical_quantities.rst
@@ -0,0 +1,138 @@
+.. _physical_quantities:
+
+*********************
+Accessing Physical Quantities
+*********************
+
+In order to compute the synthetic spectrum, Tardis must either be told
+or must calculate many physical properties of the model. To understand and
+test the code it can be important to look at these values. One
+easy way to do this is to run Tardis in an interactive mode and then
+inspect the model properties.
+
+
+Runing in interactive Python session
+------------------------------
+
+With iPython installed launch a session using
+
+.. code-block:: none
+
+    ipython --pylab
+
+and then run your calculation, which is based on your "my_config.yml" file
+
+.. code-block:: python
+
+    from tardis.io import config_reader
+    from tardis import model, simulation
+    import numpy as np
+    import logging
+    import warnings
+
+    tardis_config = config_reader.TARDISConfiguration.from_yaml("my_config.yml")
+    radial1d = model.Radial1DModel(tardis_config)
+    simulation.run_radial1d(radial1d)
+
+If all goes well, the simulation should run as usual. Afterwards, the
+information from the simulation will all exist in "radial1d" and
+can be examined. Some examples for useful/interesting quantities are
+given below (but much more information is available: contact us via 
+`tardis-sn-users <http://groups.google.com/forum/#!forum/tardis-sn-users>`_ if you need
+further help).
+
+Examples of finding physical quantities
+-------------------------------
+
+For example, two of our important quantities are the parameters of the
+radiation field model, :math:`T_{\rm rad}` and :math:`W`. These exist
+as Astropy `Quantities <http://astropy.readthedocs.org/en/v0.2.1/_generated/astropy.units.quantity.Quantity.html>`_. Thus
+
+.. code-block:: python
+
+    radial1d.t_rads.cgs
+
+will give you a list of the :math:`T_{\rm rad}`-values for the model zones
+in cgs units. To obtain an array of the values (without units) use
+
+.. code-block:: python
+
+    radial1d.t_rads.cgs.value
+
+Similarly, the :math:`W`-values can be accessed using
+
+.. code-block:: python
+
+    radial1d.ws.cgs
+
+
+Several important quantities that were setup when the model was defined
+by the configuration file are located in the "tardis_config"
+section. For example, the inner and outer velocity boundaries of the
+zones in the model
+
+.. code-block:: python
+
+    radial1d.tardis_config.structure.v_inner.cgs
+    radial1d.tardis_config.structure.v_outer.cgs
+
+and the average density in the zones
+
+.. code-block:: python
+
+    radial1d.tardis_config.structure.mean_densities.cgs
+
+Many other interesting quantities are stored in the
+"plasma_array". For example the calculated ion populations or level
+populations:
+
+.. code-block:: python
+
+    radial1d.plasma_array.ion_populations
+    radial1d.plasma_array.level_populations   
+
+These are stored as Pandas `DataFrames
+<http://pandas.pydata.org/pandas-docs/version/0.13.1/generated/pandas.DataFrame.html>`_.
+An index can be supplied to obtain the population in a particular
+zone. E.g., for the ion populations of the innermost zone (index = 0)
+
+.. code-block:: python
+
+    radial1d.plasma_array.ion_populations[0]
+
+Ion populations for a particular ionization stage of a particular
+element can be accessed by specifying an appropriate tuple :math:`(Z,C)`, which
+identifies the element (via atomic number :math:`Z` ) and the charge
+(via the ion charge :math:`C` ). Thus, 
+
+.. code-block:: python
+
+    radial1d.plasma_array.ion_populations.ix[(14,1)]
+
+will identify the ion popuations for  Si II (:math:`Z=14, C=1`) in all
+the zones. The above examples can be combined to obtain e.g. the Si II
+population in the innermost zone
+
+.. code-block:: python
+
+    radial1d.plasma_array.ion_populations[0].ix[(14,1)]
+
+The level populations are stored (and can be accessed) in a similar
+way - a third label can be used to pick out a particular atomic
+level. E.g., to pull out the population of the ground state (index 0)
+of Si II
+
+.. code-block:: python
+
+    radial1d.plasma_array.level_populations.ix[(14,1,0)]
+
+.. note::
+
+    If you prefer to work in SI units, all the astropy Quantities may
+    instead by accessed with "xxx.si".
+
+.. note::
+
+    Information that is not stored as astropy Quantities (e.g. the ion
+    an level populations used in the example above) are usually stored
+    in cgs units (i.e. :math:`{\rm cm}^{-3}` for the populations).