def testRabiInteractionFrame(self):
'''
Test Rabi oscillations after moving into an interaction frame that is different to the pulsing frame and with an irrational timestep for good measure.
'''
#Setup the system
self.systemParams.subSystems[0] = SCQubit(2,5e9, 'Q1')
self.systemParams.create_full_Ham()
#Setup the pulseSequences
pulseSeqs = []
for pulseLength in self.pulseLengths:
tmpPulseSeq = PulseSequence()
tmpPulseSeq.add_control_line(freq=-5.0e9, phase=0)
tmpPulseSeq.controlAmps = self.rabiFreq*np.array([[1]], dtype=np.float64)
tmpPulseSeq.timeSteps = np.array([pulseLength])
tmpPulseSeq.maxTimeStep = pi/2*1e-10
tmpPulseSeq.H_int = Hamiltonian(np.array([[0,0], [0, 5.005e9]], dtype = np.complex128))
pulseSeqs.append(tmpPulseSeq)
results = simulate_sequence_stack(pulseSeqs, self.systemParams, self.rhoIn, simType='unitary')[0]
expectedResults = np.cos(2*pi*self.rabiFreq*self.pulseLengths)
if plotResults:
plt.figure()
plt.plot(self.pulseLengths,results)
plt.plot(self.pulseLengths, expectedResults, color='r', linestyle='--', linewidth=2)
plt.title('10MHz Rabi Oscillations in Interaction Frame')
plt.xlabel('Pulse Length')
plt.ylabel(r'$\sigma_z$')
plt.legend(('Simulated Results', '10MHz Cosine'))
plt.show()
np.testing.assert_allclose(results, expectedResults , atol = 1e-4)
def testTwoPhoton(self):
'''
Test spectroscopy and the two photon transition from the ground to the second excited state.
'''
freqSweep = 1e9 * np.linspace(4.9, 5.1, 1000)
rabiFreq = 1e6
#Setup the pulseSequences as a series of 10us low-power pulses
pulseSeqs = []
for freq in freqSweep:
tmpPulseSeq = PulseSequence()
tmpPulseSeq.add_control_line(freq=freq, phase=0)
tmpPulseSeq.controlAmps = np.array([[rabiFreq]], dtype=np.float64)
tmpPulseSeq.timeSteps = np.array([10e-6])
tmpPulseSeq.maxTimeStep = np.Inf
tmpPulseSeq.H_int = Hamiltonian(
np.diag(freq * np.arange(3, dtype=np.complex128)))
pulseSeqs.append(tmpPulseSeq)
results = simulate_sequence_stack(pulseSeqs,
self.systemParams,
self.rhoIn,
simType='lindblad')[0]
if plotResults:
plt.figure()
plt.plot(freqSweep / 1e9, results)
plt.xlabel('Frequency')
plt.ylabel(r'$\sigma_z$')
plt.title('Qutrit Spectroscopy')
plt.show()
def testTwoPhoton(self):
'''
Test spectroscopy and the two photon transition from the ground to the second excited state.
'''
freqSweep = 1e9*np.linspace(4.9, 5.1, 1000)
rabiFreq = 1e6
#Setup the pulseSequences as a series of 10us low-power pulses
pulseSeqs = []
for freq in freqSweep:
tmpPulseSeq = PulseSequence()
tmpPulseSeq.add_control_line(freq=freq, phase=0)
tmpPulseSeq.controlAmps = np.array([[rabiFreq]], dtype=np.float64)
tmpPulseSeq.timeSteps = np.array([10e-6])
tmpPulseSeq.maxTimeStep = np.Inf
tmpPulseSeq.H_int = Hamiltonian(np.diag(freq*np.arange(3, dtype=np.complex128)))
pulseSeqs.append(tmpPulseSeq)
results = simulate_sequence_stack(pulseSeqs, self.systemParams, self.rhoIn, simType='lindblad')[0]
if plotResults:
plt.figure()
plt.plot(freqSweep/1e9,results)
plt.xlabel('Frequency')
plt.ylabel(r'$\sigma_z$')
plt.title('Qutrit Spectroscopy')
plt.show()
def testRabiRotatingFrame(self):
'''
Test Rabi oscillations in the rotating frame, i.e. with zero drift Hamiltonian drive frequency of zero.
'''
#Setup the pulseSequences
pulseSeqs = []
for pulseLength in self.pulseLengths:
tmpPulseSeq = PulseSequence()
tmpPulseSeq.add_control_line(freq=0e9, phase=0)
tmpPulseSeq.controlAmps = self.rabiFreq*np.array([[1]], dtype=np.float64)
tmpPulseSeq.timeSteps = np.array([pulseLength])
tmpPulseSeq.maxTimeStep = pulseLength
tmpPulseSeq.H_int = None
pulseSeqs.append(tmpPulseSeq)
results = simulate_sequence_stack(pulseSeqs, self.systemParams, self.rhoIn, simType='unitary')[0]
expectedResults = np.cos(2*pi*self.rabiFreq*self.pulseLengths)
if plotResults:
plt.figure()
plt.plot(self.pulseLengths,results)
plt.plot(self.pulseLengths, expectedResults, color='r', linestyle='--', linewidth=2)
plt.title('10MHz Rabi Oscillations in Rotating Frame')
plt.xlabel('Pulse Length')
plt.ylabel(r'$\sigma_z$')
plt.legend(('Simulated Results', '10MHz Cosine'))
plt.show()
np.testing.assert_allclose(results, expectedResults , atol = 1e-4)
def testT1Recovery(self):
'''
Test a simple T1 recovery without any pulses. Start in the first excited state and watch recovery down to ground state.
'''
self.systemParams.dissipators = [Dissipator(self.qubit.T1Dissipator)]
#Just setup a series of delays
delays = np.linspace(0,5e-6,40)
pulseSeqs = []
for tmpDelay in delays:
tmpPulseSeq = PulseSequence()
tmpPulseSeq.add_control_line()
tmpPulseSeq.controlAmps = np.array([[0]])
tmpPulseSeq.timeSteps = np.array([tmpDelay])
tmpPulseSeq.maxTimeStep = tmpDelay
tmpPulseSeq.H_int = None
pulseSeqs.append(tmpPulseSeq)
results = simulate_sequence_stack(pulseSeqs, self.systemParams, np.array([[0,0],[0,1]], dtype=np.complex128), simType='lindblad')[0]
expectedResults = 1-2*np.exp(-delays/self.qubit.T1)
if plotResults:
plt.figure()
plt.plot(1e6*delays,results)
plt.plot(1e6*delays, expectedResults, color='r', linestyle='--', linewidth=2)
plt.xlabel(r'Recovery Time ($\mu$s)')
plt.ylabel(r'Expectation Value of $\sigma_z$')
plt.title(r'$T_1$ Recovery to the Ground State')
plt.legend(('Simulated Results', 'Exponential T1 Recovery'))
plt.show()
np.testing.assert_allclose(results, expectedResults, atol=1e-4)
def sim_setup_cython(Hnat, controlHams, controlFields, controlFreqs):
systemParams = SystemParams()
systemParams.Hnat = Hamiltonian(Hnat)
pulseSeq = PulseSequence()
pulseSeq.controlAmps = controlFields
for ct in range(len(controlHams)):
systemParams.add_control_ham(inphase=Hamiltonian(controlHams[ct]))
pulseSeq.add_control_line(freq = controlFreqs[ct], phase=0, controlType='sinusoidal')
for ct in range(np.int(np.log2(Hnat.shape[0]))):
systemParams.add_sub_system(SCQubit(2,0e9, name='Q1', T1=1e-6))
pulseSeq.timeSteps = 0.01*np.ones(controlFields.shape[1])
pulseSeq.maxTimeStep = 1e6
return systemParams, pulseSeq
def testZZGate(self):
'''Test whether the ZZ interaction performs as expected'''
#Take the bare Hamiltonian as the interaction Hamiltonian
H_int = Hamiltonian(self.systemParams.Hnat.matrix)
#First add a 2MHz ZZ interaction and add it to the system
self.systemParams.add_interaction('Q1', 'Q2', 'ZZ', 2e6)
self.systemParams.create_full_Ham()
#Setup the pulseSequences
delays = np.linspace(0, 4e-6, 100)
pulseSeqs = []
for delay in delays:
tmpPulseSeq = PulseSequence()
tmpPulseSeq.add_control_line(freq=-5.0e9, phase=0)
tmpPulseSeq.add_control_line(freq=-6.0e9, phase=0)
tmpPulseSeq.controlAmps = self.rabiFreq * np.array(
[[1, 0], [0, 0]], dtype=np.float64)
tmpPulseSeq.timeSteps = np.array([25e-9, delay])
tmpPulseSeq.maxTimeStep = np.Inf
tmpPulseSeq.H_int = H_int
pulseSeqs.append(tmpPulseSeq)
self.systemParams.measurement = np.kron(self.Q1.pauliX, self.Q2.pauliZ)
resultsXZ = simulate_sequence_stack(pulseSeqs,
self.systemParams,
self.rhoIn,
simType='unitary')[0]
self.systemParams.measurement = np.kron(self.Q1.pauliY, self.Q2.pauliZ)
resultsYZ = simulate_sequence_stack(pulseSeqs,
self.systemParams,
self.rhoIn,
simType='unitary')[0]
if plotResults:
plt.figure()
plt.plot(delays * 1e6, resultsXZ)
plt.plot(delays * 1e6, resultsYZ, 'g')
plt.legend(('XZ', 'YZ'))
plt.xlabel('Coupling Time')
plt.ylabel('Operator Expectation Value')
plt.title('ZZ Coupling Evolution After a X90 on Q1')
plt.show()
def testRabiInteractionFrame(self):
'''
Test Rabi oscillations after moving into an interaction frame that is different to the pulsing frame and with an irrational timestep for good measure.
'''
#Setup the system
self.systemParams.subSystems[0] = SCQubit(2, 5e9, 'Q1')
self.systemParams.create_full_Ham()
#Setup the pulseSequences
pulseSeqs = []
for pulseLength in self.pulseLengths:
tmpPulseSeq = PulseSequence()
tmpPulseSeq.add_control_line(freq=-5.0e9, phase=0)
tmpPulseSeq.controlAmps = self.rabiFreq * np.array(
[[1]], dtype=np.float64)
tmpPulseSeq.timeSteps = np.array([pulseLength])
tmpPulseSeq.maxTimeStep = pi / 2 * 1e-10
tmpPulseSeq.H_int = Hamiltonian(
np.array([[0, 0], [0, 5.005e9]], dtype=np.complex128))
pulseSeqs.append(tmpPulseSeq)
results = simulate_sequence_stack(pulseSeqs,
self.systemParams,
self.rhoIn,
simType='unitary')[0]
expectedResults = np.cos(2 * pi * self.rabiFreq * self.pulseLengths)
if plotResults:
plt.figure()
plt.plot(self.pulseLengths, results)
plt.plot(self.pulseLengths,
expectedResults,
color='r',
linestyle='--',
linewidth=2)
plt.title('10MHz Rabi Oscillations in Interaction Frame')
plt.xlabel('Pulse Length')
plt.ylabel(r'$\sigma_z$')
plt.legend(('Simulated Results', '10MHz Cosine'))
plt.show()
np.testing.assert_allclose(results, expectedResults, atol=1e-4)
def testT1Recovery(self):
'''
Test a simple T1 recovery without any pulses. Start in the first excited state and watch recovery down to ground state.
'''
self.systemParams.dissipators = [Dissipator(self.qubit.T1Dissipator)]
#Just setup a series of delays
delays = np.linspace(0, 5e-6, 40)
pulseSeqs = []
for tmpDelay in delays:
tmpPulseSeq = PulseSequence()
tmpPulseSeq.add_control_line()
tmpPulseSeq.controlAmps = np.array([[0]])
tmpPulseSeq.timeSteps = np.array([tmpDelay])
tmpPulseSeq.maxTimeStep = tmpDelay
tmpPulseSeq.H_int = None
pulseSeqs.append(tmpPulseSeq)
results = simulate_sequence_stack(pulseSeqs,
self.systemParams,
np.array([[0, 0], [0, 1]],
dtype=np.complex128),
simType='lindblad')[0]
expectedResults = 1 - 2 * np.exp(-delays / self.qubit.T1)
if plotResults:
plt.figure()
plt.plot(1e6 * delays, results)
plt.plot(1e6 * delays,
expectedResults,
color='r',
linestyle='--',
linewidth=2)
plt.xlabel(r'Recovery Time ($\mu$s)')
plt.ylabel(r'Expectation Value of $\sigma_z$')
plt.title(r'$T_1$ Recovery to the Ground State')
plt.legend(('Simulated Results', 'Exponential T1 Recovery'))
plt.show()
np.testing.assert_allclose(results, expectedResults, atol=1e-4)
def testRabiRotatingFrame(self):
'''
Test Rabi oscillations in the rotating frame, i.e. with zero drift Hamiltonian drive frequency of zero.
'''
#Setup the pulseSequences
pulseSeqs = []
for pulseLength in self.pulseLengths:
tmpPulseSeq = PulseSequence()
tmpPulseSeq.add_control_line(freq=0e9, phase=0)
tmpPulseSeq.controlAmps = self.rabiFreq * np.array(
[[1]], dtype=np.float64)
tmpPulseSeq.timeSteps = np.array([pulseLength])
tmpPulseSeq.maxTimeStep = pulseLength
tmpPulseSeq.H_int = None
pulseSeqs.append(tmpPulseSeq)
results = simulate_sequence_stack(pulseSeqs,
self.systemParams,
self.rhoIn,
simType='unitary')[0]
expectedResults = np.cos(2 * pi * self.rabiFreq * self.pulseLengths)
if plotResults:
plt.figure()
plt.plot(self.pulseLengths, results)
plt.plot(self.pulseLengths,
expectedResults,
color='r',
linestyle='--',
linewidth=2)
plt.title('10MHz Rabi Oscillations in Rotating Frame')
plt.xlabel('Pulse Length')
plt.ylabel(r'$\sigma_z$')
plt.legend(('Simulated Results', '10MHz Cosine'))
plt.show()
np.testing.assert_allclose(results, expectedResults, atol=1e-4)
def testZZGate(self):
'''Test whether the ZZ interaction performs as expected'''
#Take the bare Hamiltonian as the interaction Hamiltonian
H_int = Hamiltonian(self.systemParams.Hnat.matrix)
#First add a 2MHz ZZ interaction and add it to the system
self.systemParams.add_interaction('Q1', 'Q2', 'ZZ', 2e6)
self.systemParams.create_full_Ham()
#Setup the pulseSequences
delays = np.linspace(0,4e-6,100)
pulseSeqs = []
for delay in delays:
tmpPulseSeq = PulseSequence()
tmpPulseSeq.add_control_line(freq=-5.0e9, phase=0)
tmpPulseSeq.add_control_line(freq=-6.0e9, phase=0)
tmpPulseSeq.controlAmps = self.rabiFreq*np.array([[1, 0], [0,0]], dtype=np.float64)
tmpPulseSeq.timeSteps = np.array([25e-9, delay])
tmpPulseSeq.maxTimeStep = np.Inf
tmpPulseSeq.H_int = H_int
pulseSeqs.append(tmpPulseSeq)
self.systemParams.measurement = np.kron(self.Q1.pauliX, self.Q2.pauliZ)
resultsXZ = simulate_sequence_stack(pulseSeqs, self.systemParams, self.rhoIn, simType='unitary')[0]
self.systemParams.measurement = np.kron(self.Q1.pauliY, self.Q2.pauliZ)
resultsYZ = simulate_sequence_stack(pulseSeqs, self.systemParams, self.rhoIn, simType='unitary')[0]
if plotResults:
plt.figure()
plt.plot(delays*1e6, resultsXZ)
plt.plot(delays*1e6, resultsYZ, 'g')
plt.legend(('XZ','YZ'))
plt.xlabel('Coupling Time')
plt.ylabel('Operator Expectation Value')
plt.title('ZZ Coupling Evolution After a X90 on Q1')
plt.show()
CRGaussOnBlock[4] = halfGauss[-1::-1]
CRGaussOffBlock = np.zeros((2*numChannels,numPoints));
CRGaussOffBlock[4] = halfGauss
CRBlock = np.array([0,0,0,0,1,0]).reshape(2*numChannels,1)
CRBlock *= CRAmp;
baseSeq = PulseSequence()
baseSeq.add_control_line(freq=-drive1Freq, phase=0)
baseSeq.add_control_line(freq=-drive1Freq, phase=-pi/2)
baseSeq.add_control_line(freq=-drive2Freq, phase=0)
baseSeq.add_control_line(freq=-drive2Freq, phase=-pi/2)
baseSeq.add_control_line(freq=-drive1Freq, phase=0)
baseSeq.add_control_line(freq=-drive1Freq, phase=-pi/2)
baseSeq.maxTimeStep = timeStep/4
baseSeq.H_int = Hamiltonian(systemParams.expand_operator('Q1', drive1Freq*Q1.numberOp) + systemParams.expand_operator('Q2', drive2Freq*Q2.numberOp))
'''
#Look at the all XY set of experiments
pulseSeqs = []
#Nothing
tmpPulseSeq = deepcopy(baseSeq)
tmpPulseSeq.controlAmps = np.zeros((4,1))
tmpPulseSeq.timeSteps = timeStep*np.ones(tmpPulseSeq.controlAmps.shape[1])
pulseSeqs.append(tmpPulseSeq)
#Setup the pulseSequences to calibrate the optimal control pulse
pulseSeqs = []
nutFreqs = np.linspace(0, 100e6, 50)
for nutFreq in nutFreqs:
tmpPulseSeq = PulseSequence()
tmpPulseSeq.add_control_line(freq=-drive1Freq, initialPhase=0)
tmpPulseSeq.add_control_line(freq=-drive1Freq, initialPhase=-pi / 2)
tmpPulseSeq.add_control_line(freq=-drive2Freq, initialPhase=0)
tmpPulseSeq.add_control_line(freq=-drive2Freq, initialPhase=-pi / 2)
# tmpPulseSeq.controlAmps = np.hstack((Q2PiBlock, nutFreq*jayPulseBlock, Q2PiBlock))
tmpPulseSeq.controlAmps = nutFreq * jayPulseBlock
tmpPulseSeq.timeSteps = timeStep * np.ones(
tmpPulseSeq.controlAmps.shape[1])
tmpPulseSeq.maxTimeStep = timeStep / 4
tmpPulseSeq.H_int = Hamiltonian(
systemParams.expand_operator('Q1', drive1Freq * Q1.numberOp) +
systemParams.expand_operator('Q2', drive2Freq * Q2.numberOp))
pulseSeqs.append(tmpPulseSeq)
results = simulate_sequence_stack(pulseSeqs,
systemParams,
rhoIn,
simType='unitary')
#Calibrates to 9.51MHz as expected
Q1Cal = 0.5 / (np.sum(gaussPulse) * timeStep)
bufferPts = 2
Q1PiPulse = np.zeros((systemParams.numControlHams, numPoints))
Q1PiPulse[0] = Q1Cal * gaussPulse
#Setup the pulseSequences to calibrate the optimal control pulse
pulseSeqs = []
nutFreqs = np.linspace(0,100e6,50)
for nutFreq in nutFreqs:
tmpPulseSeq = PulseSequence()
tmpPulseSeq.add_control_line(freq=-drive1Freq, initialPhase=0)
tmpPulseSeq.add_control_line(freq=-drive1Freq, initialPhase=-pi/2)
tmpPulseSeq.add_control_line(freq=-drive2Freq, initialPhase=0)
tmpPulseSeq.add_control_line(freq=-drive2Freq, initialPhase=-pi/2)
# tmpPulseSeq.controlAmps = np.hstack((Q2PiBlock, nutFreq*jayPulseBlock, Q2PiBlock))
tmpPulseSeq.controlAmps = nutFreq*jayPulseBlock
tmpPulseSeq.timeSteps = timeStep*np.ones(tmpPulseSeq.controlAmps.shape[1])
tmpPulseSeq.maxTimeStep = timeStep/4
tmpPulseSeq.H_int = Hamiltonian(systemParams.expand_operator('Q1', drive1Freq*Q1.numberOp) + systemParams.expand_operator('Q2', drive2Freq*Q2.numberOp))
pulseSeqs.append(tmpPulseSeq)
results = simulate_sequence_stack(pulseSeqs, systemParams, rhoIn, simType='unitary')
#Calibrates to 9.51MHz as expected
Q1Cal = 0.5/(np.sum(gaussPulse)*timeStep)
bufferPts = 2
Q1PiPulse = np.zeros((systemParams.numControlHams,numPoints))
Q1PiPulse[0] = Q1Cal*gaussPulse
Q1PiBlock = np.hstack((np.zeros((systemParams.numControlHams,bufferPts)), Q1PiPulse, np.zeros((systemParams.numControlHams,bufferPts))))
Q1Pi2Block = np.hstack((np.zeros((systemParams.numControlHams,bufferPts)), 0.5*Q1PiPulse, np.zeros((systemParams.numControlHams,bufferPts))))
Q1TimePts = timeStep*np.ones(Q1PiBlock.shape[1])
