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+'''
+This file is written by James R. Wootton (@quantumjim).
+
+=== Dependencies ===
+
+To run this file you'll need MicroQiskit. This is a minimal version of the 'Qiskit' framework for quantum computing.
+It just needs you to download the microqiskit.py from the following link
+https://github.com/qiskit-community/MicroQiskit/blob/master/microqiskit.py
+and then put it somewhere importable (such as in the same folder as this file).
+
+=== Inputs ===
+
+Two optional inputs can be supplied when running the file.
+The first is a 1 or 0, to determine whether to implement a quantum interference pattern or just use random bit flips.
+The second is the maxmimum pixel brightness. By default, quantum is on and the max brightness is 128.
+
+==== Summary of the Method ====
+
+Quantum computers output bit strings, so to control the lights with a (simulation of) a quantum computer,
+we need to assign a bit string to each light. For 500 lights we'll use 9 bits (since that allows 512)
+
+Now imagine a graph for which each vertex is labelled by a bit string, and vertices are connected by an
+edge if their bit strings differ on only a single bit. This is a graph on which a random walk can be
+implemented simply by randomly choosing and flipping one of the bits.
+
+Unfortunately, this graph is a 9-dimensional hypercube and not a Christmas tree. Nethertheless, we can
+try to assign bit strings to the lights on the tree such that those for neighbouring lights differ on as
+few bits as possible.
+Once we've done this, we can implement an approximation of a random walk on the tree by implementing a
+random walk on the hypercube, simply by randomly choosing and flipping a bit. That's what this program
+will do if `quantum=False`, but it's not really what this program is about. After all, there are easier
+and better ways a random walk could be run on the tree.
+
+Instead we implement a continuous quantum analogue of a random walk, a simple form of so-called 'quantum walk'.
+There are multiple forms of quantum walk that people have looked at, for multiple different reasons. The one
+we use is the one that requires the least resources to to simulate. I won't go on about it here. See
+https://github.com/qiskit-community/Quantumblur
+if you are interested. The important point is that it naturally runs on a hypercube, which is why we need to do
+hypercube stuff.
+
+The method to project the hypercube onto a Christmas tree is fairly simple, but it seems to work okay.
+First we sort the points by height into32 bins, and then sort the 16 elements in each bin by radius.
+This gives a nice pair of coordinates to convert into binary, which should preserve some degree of locality.
+'''
+
+# First get user supplied parameters
+import  sys
+if len(sys.argv)>1:
+    quantum = sys.argv[1]=='1'
+else:
+    quantum = True
+if len(sys.argv)>2:
+    max_brightness = int(sys.argv[2])
+else:
+    max_brightness = 128
+
+# Now let's import everything we need
+import time
+try:
+    import board
+    import neopixel
+except: # use a simulator when the actual hardware is not present
+    from sim import board
+    from sim import neopixel
+import re
+import math
+from microqiskit import *
+
+# We'll also use a `make_line` function which does the same job as the one from QuantumBlur
+# see https://github.com/qiskit-community/QuantumBlur/blob/master/README.md for more info
+def make_line ( length ):
+    # number of bits required
+    n = int(math.ceil(math.log(length)/math.log(2)))
+    # iteratively build list
+    line = ['0','1']
+    for j in range(n-1):
+        # first append a reverse-ordered version of the current list
+        line = line + line[::-1]
+        # then add a '0' onto the end of all bit strings in the first half
+        for j in range(int(float(len(line))/2)):
+            line[j] += '0'
+        # and a '1' for the second half
+        for j in range(int(float(len(line))/2),int(len(line))):
+            line[j] += '1'     
+    return line
+
+
+# Before we finally get on with actually doing something, we need to take the coordinates for the lights from Matt's file
+coordfilename = "Python/coords.txt"
+fin = open(coordfilename,'r')
+coords_raw = fin.readlines()
+coords_bits = [i.split(",") for i in coords_raw]
+coords = []
+for slab in coords_bits:
+    new_coord = []
+    for i in slab:
+        new_coord.append(int(re.sub(r'[^-\d]','', i)))
+    coords.append(new_coord)
+
+# And also set up the pixels (AKA 'LEDs')
+PIXEL_COUNT = len(coords) # this should be 500
+pixels = neopixel.NeoPixel(board.D18, PIXEL_COUNT, auto_write=False)
+
+
+# Finally we can get on with making a Christmas tree effect with some quantum simulations!
+
+# the following magic numbers define the quadrant boundaries
+# they were found semi manually, and split the points evenly
+theta0 = [-math.pi/2+0.39,0+0.07,math.pi/2+0.025]
+x0,y0 = -21,-26
+# with this, we create four lists of points, one for each quadrant
+quadrants = [[] for _ in range(4)]
+for x,y,z in coords:
+    theta = math.atan2(y-y0,x-x0)
+    q = (theta>theta0[0]) + (theta>theta0[1]) + (theta>theta0[2])
+    quadrants[q].append((x,y,z))
+    
+# we'll sort the 125 coords of each quadrant into 16 bins with a max of 8 items each
+bin_size = 8
+bin_num = 16
+bins = [[[] for _ in range(bin_num)] for _ in range(4)]
+
+for q,quadrant in enumerate(quadrants):
+    
+    # for each coordinate, get the height and radius
+    radii = {}
+    heights = {}
+    for x,y,z in quadrant:
+        radii[x,y,z] = math.sqrt(x**2+y**2)
+        heights[x,y,z] = z
+    
+    # first we sort by height
+    for j,coord in enumerate(sorted(heights, key=heights.get)):
+        bins[q][int(j/bin_size)].append(coord)
+
+    # then the bins are sorted by radius
+    for b in range(bin_num):
+
+        bin_radii = {}
+        for coord in bins[q][b]:
+            bin_radii[coord] = radii[coord]
+
+        new_bin = []
+        for coord in sorted(bin_radii, key=bin_radii.get):
+            new_bin.append(coord)
+
+        bins[q][b] = new_bin
+        
+# now we make lists of bit strings in which neighbouring strings have a Hamming distance of 1
+
+# for the four quadrants we need the four strings of 2 bits
+# quadrant 1 neighbours 0 and 2, so its string should differ from theirs by one bit
+# we do that by assigning 01 to quarant 1, 00 to quadrant 0 and 11 to quadrant 1
+# this also works for all the other sets of neighbours
+quadrants_line = ['00','01','11','10']
+
+# a similar list of bit strings will be used to assign bit strings to bins, and other for entries in bins
+# we'll use `make_line` to generate these for us
+bins_line = make_line(bin_num)
+bin_line = make_line(bin_size)
+
+# with these we assign a bit string to each coord
+bit_strings = {}
+for q in range(4):
+    for b in range(bin_num):
+         for j,coord in enumerate(bins[q][b]):
+                bit_strings[quadrants_line[q] + bins_line[b] + bin_line[j]] = coord
+           
+        
+# Now we are all set up, we can twinkle some Christmas lights!
+def xmaslight():
+
+    # Here's where we do the quantum stuff!
+    # We'll create an entangled GHZ state on 9 qubits and then loop continually add single qubit rotations to the circuit.
+    # After each set of rotations, the quantum circuit is run and probabilities for each output string are extracted.
+    # These probabilities are used to set the brightness the corresponding lights.
+
+    # initialize 9 qubits in a GHZ state
+    n = 9
+    qc = QuantumCircuit(n)
+    qc.h(0)
+    for j in range(n-1):
+        qc.cx(j,j+1)
+
+    # pick random rotation angles for each run
+    theta = [random.random()*math.pi/32 for _ in range(n)] 
+
+    # iterate through the process of addin rotations
+    run = 1
+    while run == 1:
+
+        # get current state vector
+        ket = simulate(qc,get='statevector')
+        # reinitialize circuit with that (to prevent circuits getting long)
+        ket = simulate(qc,get='statevector')
+        qc = QuantumCircuit(n)
+        qc.initialize(ket)
+        
+        if quantum:
+            # add rotations for each qubit (with the random angles)
+            for j in range(n):
+                qc.ry(theta[j],j)
+        else:
+            # just do a random bit flip
+            j = random.choice(range(n))
+            qc.x(j)
+
+        # get probs for each output bit string
+        probs = simulate(qc,get='probabilities_dict')
+
+        # use probs to assign a brightness to each light
+        max_prob = max(probs.values())
+        colour = {}
+        for bit_string,coord in bit_strings.items():
+            c = int(probs[bit_string]*max_brightness/max_prob)
+            colour[coord] = (0,c,c)
+
+        # update all the pixels
+        for j,coord in enumerate(coords):
+            pixels[j] = colour[tuple(coord)]
+        pixels.show()
+        
+        
+xmaslight()
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