Full docs for Geometry

Chain(L; spacing=1)

Represents a 1D chain of L spins with regular spacing. Spins are at $x_i = spacing*i$

Box(N, dims)

Represents a box with side-lengths given by dims. N spins are randomly positioned within that box.

NoisyChain(L, σ; spacing=1)

Represents a 1D chain of L spins with random noise on top of regular spaced positions. Spins are at $x_i = spacing*i + \delta$ where $\delta \sim \mathcal{U}([-\frac{\sigma}{2},\frac{\sigma}{2}])$

PartiallyFilledChain(numspins, numsites; spacing=1)

Represents a 1D chain of L sites where N spins are placed randomly. Sites are spacing units apart.

Blockaded(geometry; retries=1000, blockade=1.0)

Modifies the underlying geometry to respect the blockade condition namely all spins need to be at least blockade units apart. Positions are resampled at most retries times.

PBC(geometry)

Modify the underlying geometry to respect periodic boundary conditions.

NN(geometry, k=1)

Modify the geometry to only keep the k closest connections from each spin. Please see nearest_neighbor_from_distances! for further information.

nspins(term)
nspins(sum_of_terms)

Return the number of spins in the underlying geometry if that information was already provided.

nspins(geometry)

Return number of spins the geometry.

positions(geometry)
positions(geometry; rng)

Generate the positions of the spin in the geometry. Disordered geometries allow for setting an RNG.

distance_matrix(geometry[, positions]; rng)

Compute the spin-spin distances. Positions are generated by the geometry via positions or provided directly. Disordered geometries allow for setting an RNG.

nearest_neighbor_from_distances(distance_matrix, k=1)

Non-destructive form of nearest_neighbor_from_distances!. See also: nearest_neighbor_from_interactions!

nearest_neighbor_from_distances!(distance_matrix, k=1)

Set all but the k smallest distances from each column to Inf. k only counts different values! Thus k=1 keeps only the closest distance per spin but allows to have the same distance multiple times.