Minor typo fixes

data/astro.md

@@ -7,13 +7,13 @@ directly be read by SWIFT. The only difference is the parameter file
 that will need to be adapted for SWIFT. 
 
 SWIFT combines multiple numerical methods that are briefly outlined
-here. The whole art is to efficiently couple them to efficiently
+here. The whole art is to efficiently couple them to
 exploit modern computer architectures.
  
 ## Gravity
 
 SWIFT uses the Fast Multipole Method (FMM) to calculate gravitational
-forces between near-by particles. These forces are combined with
+forces between nearby particles. These forces are combined with
 long-range forces provided by a mesh that captures both the periodic
 nature of the calculation and the expansion of the simulated universe.
 SWIFT currently uses a single fixed but time-variable softening length
@@ -32,7 +32,7 @@ frequency of the update.
 
 SWIFT implements a standard LCDM cosmology background expansion and
 solves the equations in a comoving frame. We allow for equations of
-state of dark-energy that evolves with scale-factor. The structure of
+state of dark-energy that evolve with scale-factor. The structure of
 the code can easily allow for modified-gravity solvers or
 self-interacting dark matter schemes to be implemented. These will be
 part of future releases of the code.
@@ -64,12 +64,12 @@ can be written with no viscosity switches nor thermal diffusion
 terms. It follows exactly the description in the review of the topic
 by [Price 2012](http://adsabs.harvard.edu/abs/2012JCoPh.231..759P) and
 is not optimised. This mode is used for education purposes or can
-serve as the basis to help developers create other hydrodynamics
+serve as a basis to help developers create other hydrodynamics
 schemes. 
 
 ### GADGET-2 SPH
 
-SWIFT makes a 'backwards-compatible' [GADGET-2
+SWIFT contains a 'backwards-compatible' [GADGET-2
 SPH](http://adsabs.harvard.edu/abs/2002MNRAS.333..649S) mode, which
 uses a standard [Monaghan
 1977](http://adsabs.harvard.edu/abs/1977MNRAS.181..375G) artificial
@@ -87,11 +87,10 @@ schemes from [Hopkins
 available for use. These schemes use a weighting factor of either
 entropy or energy in the calculation of density, which has the effect
 of promoting mixing and reducing spurious surface tensions that are
-present in a traditional "Density-Entropy" scheme (such as the
-GADGET-2 one presented above). This scheme avoids artificial surface
-tension at contact discontinuities and allows for better mixing
-between phases. This leads to a much better behaviour of the SPH
-method in cases such at the Kelvin-Helmholtz instabilities or the
+present in a traditional "Density-Entropy" scheme (such as the GADGET-2 one
+presented above). This scheme avoids artificial surface tension at contact
+discontinuities and allows for better mixing between phases. This leads to much
+better behaviour in cases such at the Kelvin-Helmholtz instabilities or the
 infamous ['blob'
 test](http://adsabs.harvard.edu/abs/2007MNRAS.380..963A).
 
@@ -99,9 +98,9 @@ test](http://adsabs.harvard.edu/abs/2007MNRAS.380..963A).
 
 SWIFT can also use the GIZMO scheme ([Hopkins
 2015](http://adsabs.harvard.edu/cgi-bin/bib_query?arXiv:1409.7395)),
-also know as 'SPH-ALE' outside of astrophysics. This schemes is a
+also know as 'SPH-ALE' outside of astrophysics. This scheme is a
 hybrid between a particle method and a finite volume method. Whilst
-particles are being used to represent the fluid, fluxes between them
+particles are used to represent the fluid, fluxes between them
 are computed and exchanged using Riemann solvers and proper gradient
 reconstruction. This allows for a much more accurate representation of
 the physics without any ad-hoc switches for viscosity or thermal
@@ -150,7 +149,7 @@ project](http://adsabs.harvard.edu/abs/2014ApJS..210...14K).
 SWIFT can be linked to the VELOCIraptor phase-space structure finder
 to return haloes and sub-haloes while the simulation is running. This
 on-the-fly processing allows for a much faster time-to-science than in
-the classic way of post-processing simulations after they are run.
+the classic method of post-processing simulations after they are run.
 
 ## Documentation and tests
 

data/cs.md

@@ -6,11 +6,11 @@ SWIFT uses a hybrid MPI + threads parallelisation scheme with a
 modified version of the publicly available lightweight tasking library
 [QuickShed](https://gitlab.cosma.dur.ac.uk/swift/quicksched) as its
 backbone. Communications between compute nodes are scheduled by the
-library itself and use asynchronous call to MPI to maximise the
+library itself and use asynchronous calls to MPI to maximise the
 overlap between communication and computation. The domain
 decomposition itself is performed by splitting the graph of all the
-compute tasks, using the METIS library, such as to minimise the number
-of required MPI communications. The core calculations in SWIFT used
+compute tasks, using the METIS library, to minimise the number
+of required MPI communications. The core calculations in SWIFT use
 hand-written SIMD intrinsics to process multiple particles in parallel
 and achieve maximal performance.
 
@@ -40,6 +40,6 @@ and where most other codes struggle to harvest any scaling or performance.
 ## I/O performance
 
 SWIFT uses the parallel-hdf5 library to read and write snapshots
-efficiently on distributed file systems. By careful tuning of the
+efficiently on distributed file systems. Through careful tuning of
 Lustre parameters, SWIFT can write snapshots at the maximal disk
 writing speed of a given system. 

data/public.md

@@ -73,10 +73,10 @@ solve the same equations as other software in significantly less time!
 
 ## What is SPH?
 
-Smoothed Particle Hydrodynamics (SPH) is a numericla method of
+Smoothed Particle Hydrodynamics (SPH) is a numerical method for
 approximating the forces between fluid elements (gas or
 liquids). Let's say that we want to simulate some water and a wave
-within it. Even a singlle liter of water has 
+within it. Even a single liter of water has 
 100000000000000000000000000 particles in it.  To store that much data
 we would require a computer that as 100 trillion times as much storage
 space as *all of the data on the internet*. It's clear that we need a