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updating project.toml for registration
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bblankrot committed Jun 20, 2019
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1 change: 1 addition & 0 deletions Project.toml
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@@ -1,5 +1,6 @@
name = "ParticleScattering"
uuid = "3532a73c-0c3e-5edc-89e3-d771336b0a2d"
version = "0.1.0"

[deps]
CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
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4 changes: 2 additions & 2 deletions docs/src/tutorial1.md
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Expand Up @@ -15,7 +15,7 @@ R = 0.1\lambda_0, d = 0.05\lambda_0,
```

which is supplied by `rounded_star`. For now, we discretize the shape with `N=260`
nodes and `P=10` cylindrical harmonics – for more information on the
nodes and `P=10` cylindrical harmonics for more information on the
relationship between these parameters and the various resulting errors, see
[Choosing Minimal N and P](@ref minimalNP).

Expand Down Expand Up @@ -99,7 +99,7 @@ sp = ScatteringProblem(shapes, ids, centers, φs)
Looking at the ``4 \times 2`` array `centers`, the coordinates of the `m`-th
shape are given by `centers[m,:]`, and its rotation angle is stored in `φs[m]`.
Likewise, `ids[m]` tells us if the shape has parametrization `shapes[1]`
– in this case a rounded star – or `shapes[2]`, a squircle. It is
in this case a rounded star or `shapes[2]`, a squircle. It is
imperative that the order of these arrays remain consistent for the solver
to correctly precompute the scattering matrix transformation for each particle.
Furthermore, `shapes` should not contain copies of the same shape, as that will
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4 changes: 2 additions & 2 deletions docs/src/tutorial2.md
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Expand Up @@ -139,12 +139,12 @@ ylabel("\$ \\Delta \$" * " Potential Density")

In both subplots, we see that increasing `P` actually leads to a decrease in
accuracy (plotting the results separately also shows that the FMM results stay
virtually constant, while the direct results blow up). This is due to two main reasons –
virtually constant, while the direct results blow up). This is due to two main reasons
conditioning of the system matrix, and the fact that high-order cylindrical
harmonics are responsible for substantially greater potential densities than
lower-order ones. Both of these are impacted by the number of particles as well
as the wavelength, but mitigated by the iterative solver used by the FMM solver.

This ties in with [Choosing Minimal N and P](@ref minimalNP) – not only does
This ties in with [Choosing Minimal N and P](@ref minimalNP) not only does
increasing `P` far beyond that required for a certain error impact runtime, but
can also increase the error in the solution.

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