# Crystal symmetries

## Theory

In this discussion we will only describe the situation for a monoatomic crystal $\mathcal C \subset \mathbb R^3$, the extension being easy. A symmetry of the crystal is an orthogonal matrix $W$ and a real-space vector $w$ such that

\[W \mathcal{C} + w = \mathcal{C}.\]

The symmetries where $W = 1$ and $w$ is a lattice vector are always assumed and ignored in the following.

We can define a corresponding unitary operator $U$ on $L^2(\mathbb R^3)$ with action

\[ (Uu)(x) = u\left( W x + w \right).\]

We assume that the atomic potentials are radial and that any self-consistent potential also respects this symmetry, so that $U$ commutes with the Hamiltonian.

This operator acts on a plane-wave as

\[\begin{aligned} (U e^{iq\cdot x}) (x) &= e^{iq \cdot w} e^{i (W^T q) x}\\ &= e^{- i(S q) \cdot \tau } e^{i (S q) \cdot x} \end{aligned}\]

where we set

\[\begin{aligned} S &= W^{T}\\ \tau &= -W^{-1}w. \end{aligned}\]

It follows that the Fourier transform satisfies

\[\widehat{Uu}(q) = e^{- iq \cdot \tau} \widehat u(S^{-1} q)\]

(all of these equations being also valid in reduced coordinates). In particular, if $e^{ik\cdot x} u_{k}(x)$ is an eigenfunction, then by decomposing $u_k$ over plane-waves $e^{i G \cdot x}$ one can see that $e^{i(S^T k) \cdot x} (U u_k)(x)$ is also an eigenfunction: we can choose

\[u_{Sk} = U u_k.\]

This is used to reduce the computations needed. For a uniform sampling of the Brillouin zone (the *reducible $k$-points*), one can find a reduced set of $k$-points (the *irreducible $k$-points*) such that the eigenvectors at the reducible $k$-points can be deduced from those at the irreducible $k$-points.

## Symmetrization

Quantities that are calculated by summing over the reducible $k$ points can be calculated by first summing over the irreducible $k$ points and then symmetrizing. Let $\mathcal{K}_\text{reducible}$ denote the reducible $k$-points sampling the Brillouin zone, $\mathcal{S}$ be the group of all crystal symmetries that leave this BZ mesh invariant ($\mathcal{S}\mathcal{K}_\text{reducible} = \mathcal{K}_\text{reducible}$) and $\mathcal{K}$ be the irreducible $k$-points obtained from $\mathcal{K}_\text{reducible}$ using the symmetries $\mathcal{S}$. Clearly

\[\mathcal{K}_\text{red} = \{Sk \, | \, S \in \mathcal{S}, k \in \mathcal{K}\}.\]

Let $Q$ be a $k$-dependent quantity to sum (for instance, energies, densities, forces, etc). $Q$ transforms in a particular way under symmetries: $Q(Sk) = S(Q(k))$ where the (linear) action of $S$ on $Q$ depends on the particular $Q$.

\[\begin{aligned} \sum_{k \in \mathcal{K}_\text{red}} Q(k) &= \sum_{k \in \mathcal{K}} \ \sum_{S \text{ with } Sk \in \mathcal{K}_\text{red}} S(Q(k)) \\ &= \sum_{k \in \mathcal{K}} \frac{1}{N_{\mathcal{S},k}} \sum_{S \in \mathcal{S}} S(Q(k))\\ &= \frac{1}{N_{\mathcal{S}}} \sum_{S \in \mathcal{S}} \left(\sum_{k \in \mathcal{K}} \frac{N_\mathcal{S}}{N_{\mathcal{S},k}} Q(k) \right) \end{aligned}\]

Here, $N_\mathcal{S} = |\mathcal{S}|$ is the total number of symmetry operations and $N_{\mathcal{S},k}$ denotes the number of operations such that leave $k$ invariant. The latter operations form a subgroup of the group of all symmetry operations, sometimes called the *small/little group of $k$*. The factor $\frac{N_\mathcal{S}}{N_{S,k}}$, also equal to the ratio of number of reducible points encoded by this particular irreducible $k$ to the total number of reducible points, determines the weight of each irreducible $k$ point.

## Example

Let us demonstrate this in practice. We consider silicon, setup appropriately in the `lattice`

, `atoms`

and `positions`

objects as in Tutorial and to reach a fast execution, we take a small `Ecut`

of `5`

and a `[4, 4, 4]`

Monkhorst-Pack grid. First we perform the DFT calculation disabling symmetry handling

```
model_nosym = model_LDA(lattice, atoms, positions; symmetries=false)
basis_nosym = PlaneWaveBasis(model_nosym; Ecut, kgrid)
scfres_nosym = @time self_consistent_field(basis_nosym, tol=1e-6)
```

```
n Energy log10(ΔE) log10(Δρ) Diag Δtime
--- --------------- --------- --------- ---- ------
1 -7.864650761921 -0.72 3.4
2 -7.868973525612 -2.36 -1.54 1.0 225ms
3 -7.869173268932 -3.70 -2.60 1.0 231ms
4 -7.869209142243 -4.45 -2.88 2.5 371ms
5 -7.869209572574 -6.37 -3.10 1.0 308ms
6 -7.869209810651 -6.62 -4.47 1.0 235ms
7 -7.869209817466 -8.17 -5.08 2.1 347ms
8 -7.869209817528 -10.21 -5.85 1.6 281ms
9 -7.869209817530 -11.65 -5.90 1.9 377ms
10 -7.869209817531 -12.22 -6.48 1.0 225ms
3.180431 seconds (1.65 M allocations: 725.164 MiB, 8.16% gc time)
```

and then redo it using symmetry (the default):

```
model_sym = model_LDA(lattice, atoms, positions)
basis_sym = PlaneWaveBasis(model_sym; Ecut, kgrid)
scfres_sym = @time self_consistent_field(basis_sym, tol=1e-6)
```

```
n Energy log10(ΔE) log10(Δρ) Diag Δtime
--- --------------- --------- --------- ---- ------
1 -7.864315998731 -0.72 4.2
2 -7.868934884974 -2.34 -1.54 1.0 39.2ms
3 -7.869164410096 -3.64 -2.62 1.1 40.4ms
4 -7.869209109758 -4.35 -2.84 2.5 56.9ms
5 -7.869209278113 -6.77 -2.86 1.0 40.1ms
6 -7.869209806680 -6.28 -4.00 1.0 39.9ms
7 -7.869209817025 -7.99 -4.89 1.6 47.7ms
8 -7.869209817501 -9.32 -5.06 2.0 52.6ms
9 -7.869209817514 -10.87 -5.14 1.0 40.3ms
10 -7.869209817519 -11.31 -5.22 1.0 39.8ms
11 -7.869209817530 -10.94 -6.32 1.0 95.7ms
0.578678 seconds (263.44 k allocations: 137.606 MiB, 9.13% gc time)
```

Clearly both yield the same energy but the version employing symmetry is faster, since less $k$-points are explicitly treated:

`(length(basis_sym.kpoints), length(basis_nosym.kpoints))`

`(8, 64)`

Both SCFs would even agree in the convergence history if exact diagonalization was used for the eigensolver in each step of both SCFs. But since DFTK adjusts this `diagtol`

value adaptively during the SCF to increase performance, a slightly different history is obtained. Try adding the keyword argument `determine_diagtol=(args...; kwargs...) -> 1e-8`

in each SCF call to fix the diagonalization tolerance to be `1e-8`

for all SCF steps, which will result in an almost identical convergence history.

We can also explicitly verify both methods to yield the same density:

```
(norm(scfres_sym.ρ - scfres_nosym.ρ),
norm(values(scfres_sym.energies) .- values(scfres_nosym.energies)))
```

`(3.653829889250293e-7, 8.152839611532698e-7)`

The symmetries can be used to map reducible to irreducible points:

```
ikpt_red = rand(1:length(basis_nosym.kpoints))
# find a (non-unique) corresponding irreducible point in basis_nosym,
# and the symmetry that relates them
ikpt_irred, symop = DFTK.unfold_mapping(basis_sym, basis_nosym.kpoints[ikpt_red])
[basis_sym.kpoints[ikpt_irred].coordinate symop.S * basis_nosym.kpoints[ikpt_red].coordinate]
```

```
3×2 StaticArraysCore.SMatrix{3, 2, Float64, 6} with indices SOneTo(3)×SOneTo(2):
-0.5 0.0
0.25 -0.5
0.0 0.25
```

The eigenvalues match also:

`[scfres_sym.eigenvalues[ikpt_irred] scfres_nosym.eigenvalues[ikpt_red]]`

```
7×2 Matrix{Float64}:
-0.0678642 -0.0678642
0.0340214 0.0340214
0.131311 0.131311
0.179372 0.179372
0.319769 0.319769
0.42817 0.428169
0.482894 0.476345
```