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Shor_Sequential_QFT.py
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"""
This is the final implementation of Shor's Algorithm using the circuit presented in section 2.3 of the report about the second
simplification introduced by the base paper used.
The circuit is general, so, in a good computer that can support simulations infinite qubits, it can factorize any number N. The only limitation
is the capacity of the computer when running in local simulator and the limits on the IBM simulator (in the number of qubits and in the number
of QASM instructions the simulations can have when sent to IBM simulator).
The user may try N=21, which is an example that runs perfectly fine even just in local simulator because, as in explained in report, this circuit,
because implements the QFT sequentially, uses less qubits then when using a "normal"n QFT.
"""
""" Imports from qiskit"""
from qiskit import QuantumCircuit, ClassicalRegister, QuantumRegister
from qiskit import execute, IBMQ
from qiskit import BasicAer
import sys
""" Imports to Python functions """
import math
import array
import fractions
import numpy as np
""" Function to check if N is of type q^p"""
def check_if_power(N):
""" Check if N is a perfect power in O(n^3) time, n=ceil(logN) """
b=2
while (2**b) <= N:
a = 1
c = N
while (c-a) >= 2:
m = int( (a+c)/2 )
if (m**b) < (N+1):
p = int( (m**b) )
else:
p = int(N+1)
if int(p) == int(N):
print('N is {0}^{1}'.format(int(m),int(b)) )
return True
if p<N:
a = int(m)
else:
c = int(m)
b=b+1
return False
""" Function to get the value a ( 1<a<N ), such that a and N are coprime. Starts by getting the smallest a possible
This normally can be done fully randomly, we just did it like this for thr user (professor) to have control
over the a value that gets selected """
def get_value_a(N):
""" ok defines if user wants to used the suggested a (if ok!='0') or not (if ok=='0') """
ok='0'
""" Starting with a=2 """
a=2
""" Get the smallest a such that a and N are coprime"""
while math.gcd(a,N)!=1:
a=a+1
""" Store it as the smallest a possible """
smallest_a = a
""" Ask user if the a found is ok, if not, then increment and find the next possibility """
ok = input('Is the number {0} ok for a? Press 0 if not, other number if yes: '.format(a))
if ok=='0':
if(N==3):
print('Number {0} is the only one you can use. Using {1} as value for a\n'.format(a,a))
return a
a=a+1
""" Cycle to find all possibilities for a not counting the smallest one, until user says one of them is ok """
while ok=='0':
""" Get a coprime with N """
while math.gcd(a,N)!=1:
a=a+1
""" Ask user if ok """
ok = input('Is the number {0} ok for a? Press 0 if not, other number if yes: '.format(a))
""" If user says it is ok, then exit cycle, a has been found """
if ok!='0':
break
""" If user says it is not ok, increment a and check if are all possibilites checked. """
a=a+1
""" If all possibilities for a are rejected, put a as the smallest possible value and exit cycle """
if a>(N-1):
print('You rejected all options for value a, selecting the smallest one\n')
a=smallest_a
break
""" Print the value that is used as a """
print('Using {0} as value for a\n'.format(a))
return a
""" Function to apply the continued fractions to find r and the gcd to find the desired factors"""
def get_factors(x_value,t_upper,N,a):
if x_value<=0:
print('x_value is <= 0, there are no continued fractions\n')
return False
print('Running continued fractions for this case\n')
""" Calculate T and x/T """
T = pow(2,t_upper)
x_over_T = x_value/T
""" Cycle in which each iteration corresponds to putting one more term in the
calculation of the Continued Fraction (CF) of x/T """
""" Initialize the first values according to CF rule """
i=0
b = array.array('i')
t = array.array('f')
b.append(math.floor(x_over_T))
t.append(x_over_T - b[i])
while i>=0:
"""From the 2nd iteration onwards, calculate the new terms of the CF based
on the previous terms as the rule suggests"""
if i>0:
b.append( math.floor( 1 / (t[i-1]) ) )
t.append( ( 1 / (t[i-1]) ) - b[i] )
""" Calculate the CF using the known terms """
aux = 0
j=i
while j>0:
aux = 1 / ( b[j] + aux )
j = j-1
aux = aux + b[0]
"""Get the denominator from the value obtained"""
frac = fractions.Fraction(aux).limit_denominator()
den=frac.denominator
print('Approximation number {0} of continued fractions:'.format(i+1))
print("Numerator:{0} \t\t Denominator: {1}\n".format(frac.numerator,frac.denominator))
""" Increment i for next iteration """
i=i+1
if (den%2) == 1:
if i>=15:
print('Returning because have already done too much tries')
return False
print('Odd denominator, will try next iteration of continued fractions\n')
continue
""" If denominator even, try to get factors of N """
""" Get the exponential a^(r/2) """
exponential = 0
if den<1000:
exponential=pow(a , (den/2))
""" Check if the value is too big or not """
if math.isinf(exponential)==1 or exponential>1000000000:
print('Denominator of continued fraction is too big!\n')
aux_out = input('Input number 1 if you want to continue searching, other if you do not: ')
if aux_out != '1':
return False
else:
continue
"""If the value is not to big (infinity), then get the right values and
do the proper gcd()"""
putting_plus = int(exponential + 1)
putting_minus = int(exponential - 1)
one_factor = math.gcd(putting_plus,N)
other_factor = math.gcd(putting_minus,N)
""" Check if the factors found are trivial factors or are the desired
factors """
if one_factor==1 or one_factor==N or other_factor==1 or other_factor==N:
print('Found just trivial factors, not good enough\n')
""" Check if the number has already been found, use i-1 because i was already incremented """
if t[i-1]==0:
print('The continued fractions found exactly x_final/(2^(2n)) , leaving funtion\n')
return False
if i<15:
aux_out = input('Input number 1 if you want to continue searching, other if you do not: ')
if aux_out != '1':
return False
else:
""" Return if already too much tries and numbers are huge """
print('Returning because have already done too many tries\n')
return False
else:
print('The factors of {0} are {1} and {2}\n'.format(N,one_factor,other_factor))
print('Found the desired factors!\n')
return True
"""Functions that calculate the modular inverse using Euclid's algorithm"""
def egcd(a, b):
if a == 0:
return (b, 0, 1)
else:
g, y, x = egcd(b % a, a)
return (g, x - (b // a) * y, y)
def modinv(a, m):
g, x, y = egcd(a, m)
if g != 1:
raise Exception('modular inverse does not exist')
else:
return x % m
""" Function to create the QFT """
def create_QFT(circuit,up_reg,n,with_swaps):
i=n-1
""" Apply the H gates and Cphases"""
""" The Cphases with |angle| < threshold are not created because they do
nothing. The threshold is put as being 0 so all CPhases are created,
but the clause is there so if wanted just need to change the 0 of the
if-clause to the desired value """
while i>=0:
circuit.h(up_reg[i])
j=i-1
while j>=0:
if (np.pi)/(pow(2,(i-j))) > 0:
circuit.cu1( (np.pi)/(pow(2,(i-j))) , up_reg[i] , up_reg[j] )
j=j-1
i=i-1
""" If specified, apply the Swaps at the end """
if with_swaps==1:
i=0
while i < ((n-1)/2):
circuit.swap(up_reg[i], up_reg[n-1-i])
i=i+1
""" Function to create inverse QFT """
def create_inverse_QFT(circuit,up_reg,n,with_swaps):
""" If specified, apply the Swaps at the beggining"""
if with_swaps==1:
i=0
while i < ((n-1)/2):
circuit.swap(up_reg[i], up_reg[n-1-i])
i=i+1
""" Apply the H gates and Cphases"""
""" The Cphases with |angle| < threshold are not created because they do
nothing. The threshold is put as being 0 so all CPhases are created,
but the clause is there so if wanted just need to change the 0 of the
if-clause to the desired value """
i=0
while i<n:
circuit.h(up_reg[i])
if i != n-1:
j=i+1
y=i
while y>=0:
if (np.pi)/(pow(2,(j-y))) > 0:
circuit.cu1( - (np.pi)/(pow(2,(j-y))) , up_reg[j] , up_reg[y] )
y=y-1
i=i+1
"""Function that calculates the angle of a phase shift in the sequential QFT based on the binary digits of a."""
"""a represents a possile value of the classical register"""
def getAngle(a, N):
"""convert the number a to a binary string with length N"""
s=bin(int(a))[2:].zfill(N)
angle = 0
for i in range(0, N):
"""if the digit is 1, add the corresponding value to the angle"""
if s[N-1-i] == '1':
angle += math.pow(2, -(N-i))
angle *= np.pi
return angle
"""Function that calculates the array of angles to be used in the addition in Fourier Space"""
def getAngles(a,N):
s=bin(int(a))[2:].zfill(N)
angles=np.zeros([N])
for i in range(0, N):
for j in range(i,N):
if s[j]=='1':
angles[N-i-1]+=math.pow(2, -(j-i))
angles[N-i-1]*=np.pi
return angles
"""Creation of a doubly controlled phase gate"""
def ccphase(circuit, angle, ctl1, ctl2, tgt):
circuit.cu1(angle/2,ctl1,tgt)
circuit.cx(ctl2,ctl1)
circuit.cu1(-angle/2,ctl1,tgt)
circuit.cx(ctl2,ctl1)
circuit.cu1(angle/2,ctl2,tgt)
"""Creation of the circuit that performs addition by a in Fourier Space"""
"""Can also be used for subtraction by setting the parameter inv to a value different from 0"""
def phiADD(circuit, q, a, N, inv):
angle=getAngles(a,N)
for i in range(0,N):
if inv==0:
circuit.u1(angle[i],q[i])
"""addition"""
else:
circuit.u1(-angle[i],q[i])
"""subtraction"""
"""Single controlled version of the phiADD circuit"""
def cphiADD(circuit, q, ctl, a, n, inv):
angle=getAngles(a,n)
for i in range(0,n):
if inv==0:
circuit.cu1(angle[i],ctl,q[i])
else:
circuit.cu1(-angle[i],ctl,q[i])
"""Doubly controlled version of the phiADD circuit"""
def ccphiADD(circuit,q,ctl1,ctl2,a,n,inv):
angle=getAngles(a,n)
for i in range(0,n):
if inv==0:
ccphase(circuit,angle[i],ctl1,ctl2,q[i])
else:
ccphase(circuit,-angle[i],ctl1,ctl2,q[i])
"""Circuit that implements doubly controlled modular addition by a"""
def ccphiADDmodN(circuit, q, ctl1, ctl2, aux, a, N, n):
ccphiADD(circuit, q, ctl1, ctl2, a, n, 0)
phiADD(circuit, q, N, n, 1)
create_inverse_QFT(circuit, q, n, 0)
circuit.cx(q[n-1],aux)
create_QFT(circuit,q,n,0)
cphiADD(circuit, q, aux, N, n, 0)
ccphiADD(circuit, q, ctl1, ctl2, a, n, 1)
create_inverse_QFT(circuit, q, n, 0)
circuit.x(q[n-1])
circuit.cx(q[n-1], aux)
circuit.x(q[n-1])
create_QFT(circuit,q,n,0)
ccphiADD(circuit, q, ctl1, ctl2, a, n, 0)
"""Circuit that implements the inverse of doubly controlled modular addition by a"""
def ccphiADDmodN_inv(circuit, q, ctl1, ctl2, aux, a, N, n):
ccphiADD(circuit, q, ctl1, ctl2, a, n, 1)
create_inverse_QFT(circuit, q, n, 0)
circuit.x(q[n-1])
circuit.cx(q[n-1],aux)
circuit.x(q[n-1])
create_QFT(circuit, q, n, 0)
ccphiADD(circuit, q, ctl1, ctl2, a, n, 0)
cphiADD(circuit, q, aux, N, n, 1)
create_inverse_QFT(circuit, q, n, 0)
circuit.cx(q[n-1], aux)
create_QFT(circuit, q, n, 0)
phiADD(circuit, q, N, n, 0)
ccphiADD(circuit, q, ctl1, ctl2, a, n, 1)
"""Circuit that implements single controlled modular multiplication by a"""
def cMULTmodN(circuit, ctl, q, aux, a, N, n):
create_QFT(circuit,aux,n+1,0)
for i in range(0, n):
ccphiADDmodN(circuit, aux, q[i], ctl, aux[n+1], (2**i)*a % N, N, n+1)
create_inverse_QFT(circuit, aux, n+1, 0)
for i in range(0, n):
circuit.cswap(ctl,q[i],aux[i])
a_inv = modinv(a, N)
create_QFT(circuit, aux, n+1, 0)
i = n-1
while i >= 0:
ccphiADDmodN_inv(circuit, aux, q[i], ctl, aux[n+1], math.pow(2,i)*a_inv % N, N, n+1)
i -= 1
create_inverse_QFT(circuit, aux, n+1, 0)
""" Main program """
if __name__ == '__main__':
""" Ask for analysis number N """
N = int(input('Please insert integer number N: '))
print('input number was: {0}\n'.format(N))
""" Check if N==1 or N==0"""
if N==1 or N==0:
print('Please put an N different from 0 and from 1')
exit()
""" Check if N is even """
if (N%2)==0:
print('N is even, so does not make sense!')
exit()
""" Check if N can be put in N=p^q, p>1, q>=2 """
""" Try all numbers for p: from 2 to sqrt(N) """
if check_if_power(N)==True:
exit()
print('Not an easy case, using the quantum circuit is necessary\n')
""" To login to IBM Q experience the following functions should be called """
"""
IBMQ.delete_accounts()
IBMQ.save_account('insert token here')
IBMQ.load_accounts()"""
""" Get an integer a that is coprime with N """
a = get_value_a(N)
""" If user wants to force some values, can do that here, please make sure to update print and that N and a are coprime"""
"""print('Forcing N=15 and a=4 because its the fastest case, please read top of source file for more info')
N=15
a=2"""
""" Get n value used in Shor's algorithm, to know how many qubits are used """
n = math.ceil(math.log(N,2))
print('Total number of qubits used: {0}\n'.format(2*n+3))
""" Create quantum and classical registers """
"""auxilliary quantum register used in addition and multiplication"""
aux = QuantumRegister(n+2)
"""single qubit where the sequential QFT is performed"""
up_reg = QuantumRegister(1)
"""quantum register where the multiplications are made"""
down_reg = QuantumRegister(n)
"""classical register where the measured values of the sequential QFT are stored"""
up_classic = ClassicalRegister(2*n)
"""classical bit used to reset the state of the top qubit to 0 if the previous measurement was 1"""
c_aux = ClassicalRegister(1)
""" Create Quantum Circuit """
circuit = QuantumCircuit(down_reg , up_reg , aux, up_classic, c_aux)
""" Initialize down register to 1"""
circuit.x(down_reg[0])
""" Cycle to create the Sequential QFT, measuring qubits and applying the right gates according to measurements """
for i in range(0, 2*n):
"""reset the top qubit to 0 if the previous measurement was 1"""
circuit.x(up_reg).c_if(c_aux, 1)
circuit.h(up_reg)
cMULTmodN(circuit, up_reg[0], down_reg, aux, a**(2**(2*n-1-i)), N, n)
"""cycle through all possible values of the classical register and apply the corresponding conditional phase shift"""
for j in range(0, 2**i):
"""the phase shift is applied if the value of the classical register matches j exactly"""
circuit.u1(getAngle(j, i), up_reg[0]).c_if(up_classic, j)
circuit.h(up_reg)
circuit.measure(up_reg[0], up_classic[i])
circuit.measure(up_reg[0], c_aux[0])
""" Select how many times the circuit runs"""
number_shots=int(input('Number of times to run the circuit: '))
if number_shots < 1:
print('Please run the circuit at least one time...')
exit()
""" Print info to user """
print('Executing the circuit {0} times for N={1} and a={2}\n'.format(number_shots,N,a))
""" Simulate the created Quantum Circuit """
simulation = execute(circuit, backend=BasicAer.get_backend('qasm_simulator'),shots=number_shots)
""" to run on IBM, use backend=IBMQ.get_backend('ibmq_qasm_simulator') in execute() function """
""" to run locally, use backend=BasicAer.get_backend('qasm_simulator') in execute() function """
""" Get the results of the simulation in proper structure """
sim_result=simulation.result()
counts_result = sim_result.get_counts(circuit)
""" Print info to user from the simulation results """
print('Printing the various results followed by how many times they happened (out of the {} cases):\n'.format(number_shots))
i=0
while i < len(counts_result):
print('Result \"{0}\" happened {1} times out of {2}'.format(list(sim_result.get_counts().keys())[i],list(sim_result.get_counts().values())[i],number_shots))
i=i+1
""" An empty print just to have a good display in terminal """
print(' ')
""" Initialize this variable """
prob_success=0
""" For each simulation result, print proper info to user and try to calculate the factors of N"""
i=0
while i < len(counts_result):
""" Get the x_value from the final state qubits """
all_registers_output = list(sim_result.get_counts().keys())[i]
output_desired = all_registers_output.split(" ")[1]
x_value = int(output_desired, 2)
prob_this_result = 100 * ( int( list(sim_result.get_counts().values())[i] ) ) / (number_shots)
print("------> Analysing result {0}. This result happened in {1:.4f} % of all cases\n".format(output_desired,prob_this_result))
""" Print the final x_value to user """
print('In decimal, x_final value for this result is: {0}\n'.format(x_value))
""" Get the factors using the x value obtained """
success = get_factors(int(x_value),int(2*n),int(N),int(a))
if success==True:
prob_success = prob_success + prob_this_result
i=i+1
print("\nUsing a={0}, found the factors of N={1} in {2:.4f} % of the cases\n".format(a,N,prob_success))