# 1P_sr.py¶

## Description¶

This example propagates a 1 particle continuous-time quantum walk on the first member of the strongly regular $$(25,12,5,6)$$ family of graphs.

Amongst the features used, it illustrates:
• the use of the Krylov propagation algorithm

• various plotting abilities:
• probability vs node plot
• probability and graph plot

## Source Code¶

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 #!/usr/bin/env python2.7 # initialize PETSc import sys, petsc4py petsc4py.init(sys.argv) from petsc4py import PETSc import numpy as np # import pyCTQW as qw import pyCTQW.MPI as qw # get the MPI rank rank = PETSc.Comm.Get_rank(PETSc.COMM_WORLD) if rank == 0: print '1P Strong Regular\n' # initialise a 25 node graph CTQW, # and create a Hamiltonian from a file. walk = qw.Graph(25) walk.createH('../graphs/strong-regular-25-12-5-6/1.txt','txt',layout='circle') # create the initial state |0,1> init_state = [[0,1]] walk.createInitState(init_state) # Propagate the CTQW using Krylov subspace methods for t=100s walk.propagate(100,method='krylov') # plot the marginal probabilities # after propagation over all nodes walk.plot('out/1p_sr_plot.png') # plot a 3D graph representation with bars # representing the marginal probabilities walk.plotGraph(output='out/1p_sr_graph.png') # destroy the quantum walk walk.destroy()