def create(cls) -> "FullZeroPi":
phi_grid = discretization.Grid1d(-25.0, 25.0, 360)
init_params = cls.default_params()
init_params["grid"] = phi_grid
zeropi = cls(**init_params)
zeropi.widget()
return zeropi
def create(cls) -> 'ZeroPi':
phi_grid = discretization.Grid1d(-19.0, 19.0, 200)
init_params = cls.default_params()
init_params['grid'] = phi_grid
zeropi = cls(**init_params)
zeropi.widget()
return zeropi
def __init__(self,
EJ1: float,
EJ2: float,
EJ3: float,
ECJ1: float,
ECJ2: float,
ECJ3: float,
ECg1: float,
ECg2: float,
ng1: float,
ng2: float,
flux: float,
ncut: int,
truncated_dim: int = 6) -> None:
self.EJ1 = EJ1
self.EJ2 = EJ2
self.EJ3 = EJ3
self.ECJ1 = ECJ1
self.ECJ2 = ECJ2
self.ECJ3 = ECJ3
self.ECg1 = ECg1
self.ECg2 = ECg2
self.ng1 = ng1
self.ng2 = ng2
self.flux = flux
self.ncut = ncut
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.complex_
self._default_grid = discretization.Grid1d(
-np.pi / 2, 3 * np.pi / 2, 100) # for plotting in phi_j basis
self._image_filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)),
'qubit_img/flux-qubit.jpg')
def __init__(self,
EJ1,
EJ2,
EJ3,
ECJ1,
ECJ2,
ECJ3,
ECg1,
ECg2,
ng1,
ng2,
flux,
ncut,
truncated_dim=None):
self.EJ1 = EJ1
self.EJ2 = EJ2
self.EJ3 = EJ3
self.ECJ1 = ECJ1
self.ECJ2 = ECJ2
self.ECJ3 = ECJ3
self.ECg1 = ECg1
self.ECg2 = ECg2
self.ng1 = ng1
self.ng2 = ng2
self.flux = flux
self.ncut = ncut
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.complex_
self._default_grid = discretization.Grid1d(
-np.pi / 2, 3 * np.pi / 2, 100) # for plotting in phi_j basis
self._image_filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)),
'qubit_pngs/fluxqubit.png')
def set_params(self, **kwargs):
phi_grid = discretization.Grid1d(kwargs.pop('grid_min_val'),
kwargs.pop('grid_max_val'),
kwargs.pop('grid_pt_count'))
self.grid = phi_grid
for param_name, param_val in kwargs.items():
setattr(self, param_name, param_val)
def __init__(
self,
EJ: float,
EL: float,
EC: float,
ECL: float,
ng: float,
flux: float,
grid: Grid1d,
ncut: int,
dEJ: float = 0.0,
truncated_dim: int = 6,
) -> None:
self.EJ = EJ
self.EL = EL
self.EC = EC
self.ECL = ECL
self.dEJ = dEJ
self.ng = ng
self.flux = flux
self.grid = grid
self.ncut = ncut
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.complex_
# _default_grid is for *theta*, needed for plotting wavefunction
self._default_grid = discretization.Grid1d(-np.pi / 2, 3 * np.pi / 2,
200)
self._image_filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)),
"qubit_img/bifluxon.jpg")
dispatch.CENTRAL_DISPATCH.register("GRID_UPDATE", self)
def create(cls) -> "Bifluxon":
phi_grid = discretization.Grid1d(-19.0, 19.0, 200)
init_params = cls.default_params()
init_params["grid"] = phi_grid
bifluxon = cls(**init_params)
bifluxon.widget()
return bifluxon
def __init__(self, EJ, EL, ECJ, EC, ng, flux, grid, ncut, dEJ=0, dCJ=0, ECS=None, truncated_dim=None):
self.EJ = EJ
self.EL = EL
self.ECJ = ECJ
if EC is None and ECS is None:
raise ValueError("Argument missing: must either provide EC or ECS")
if EC and ECS:
raise ValueError("Argument error: can only provide either EC or ECS")
if EC:
self.EC = EC
else:
self.EC = 1 / (1 / ECS - 1 / self.ECJ)
self.dEJ = dEJ
self.dCJ = dCJ
self.ng = ng
self.flux = flux
self.grid = grid
self.ncut = ncut
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.complex_
# for theta, needed for plotting wavefunction
self._default_grid = discretization.Grid1d(-np.pi / 2, 3 * np.pi / 2, 100)
self._init_params.remove('ECS') # used in for file Serializable purposes; remove ECS as init parameter
self._image_filename = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'qubit_pngs/zeropi.png')
dispatch.CENTRAL_DISPATCH.register('GRID_UPDATE', self)
def __init__(self,
EJ1,
EJ2,
EJ3,
ECJ1,
ECJ2,
ECJ3,
ECg1,
ECg2,
ng1,
ng2,
flux,
ncut,
truncated_dim=None):
self.EJ1 = EJ1
self.EJ2 = EJ2
self.EJ3 = EJ3
self.ECJ1 = ECJ1
self.ECJ2 = ECJ2
self.ECJ3 = ECJ3
self.ECg1 = ECg1
self.ECg2 = ECg2
self.ng1 = ng1
self.ng2 = ng2
self.flux = flux
self.ncut = ncut
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.complex_
self._default_grid = discretization.Grid1d(
-np.pi / 2, 3 * np.pi / 2, 100) # for plotting in phi_j basis
def plot_wavefunction(self,
esys=None,
which=0,
phi_grid=None,
theta_grid=None,
mode="abs",
zero_calibrate=True,
**kwargs) -> Tuple[Figure, Axes]:
"""
Plots a 2D wave function in :math:`\\theta, \\phi` basis, at :math:`\\zeta = 0`
Parameters
----------
esys: ndarray, ndarray
eigenvalues, eigenvectors as obtained from `.eigensystem()`
which: int, optional
index of wave function to be plotted (default value = (0)
phi_grid: Grid1d, option
used for setting a custom grid for phi; if None use self._default_phi_grid
theta_grid: Grid1d, option
used for setting a custom grid for theta; if None use
self._default_theta_grid
mode: str, optional
choices as specified in `constants.MODE_FUNC_DICT` (default value = 'abs_sqr')
zero_calibrate: bool, optional
if True, colors are adjusted to use zero wavefunction amplitude as the neutral color in the palette
**kwargs:
plot options
"""
phi_grid = phi_grid or self._default_phi_grid
zeta_grid = discretization.Grid1d(0, 0, 1)
theta_grid = theta_grid or self._default_theta_grid
amplitude_modifier = constants.MODE_FUNC_DICT[mode]
wavefunc = self.wavefunction(
esys,
phi_grid=phi_grid,
zeta_grid=zeta_grid,
theta_grid=theta_grid,
which=which,
)
wavefunc.gridspec = discretization.GridSpec(
np.asarray([
[phi_grid.min_val, phi_grid.max_val, phi_grid.pt_count],
[theta_grid.min_val, theta_grid.max_val, theta_grid.pt_count],
]))
wavefunc.amplitudes = np.transpose(
amplitude_modifier(
spec_utils.standardize_phases(
wavefunc.amplitudes.reshape(phi_grid.pt_count,
theta_grid.pt_count))))
return plot.wavefunction2d(wavefunc,
zero_calibrate=zero_calibrate,
ylabel=r"$\theta$",
xlabel=r"$\phi$",
**kwargs)
def __init__(self, EJ, EC, ng, ncut, truncated_dim=None):
self.EJ = EJ
self.EC = EC
self.ng = ng
self.ncut = ncut
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.float_
self._default_grid = discretization.Grid1d(-np.pi, np.pi, 151)
self._default_n_range = (-5, 6)
def __init__(self, EJ, EC, EL, flux, cutoff, truncated_dim=None):
self.EJ = EJ
self.EC = EC
self.EL = EL
self.flux = flux
self.cutoff = cutoff
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.float_
self._default_grid = discretization.Grid1d(-4.5 * np.pi, 4.5 * np.pi,
151)
def __init__(
self,
EJ: float,
ECJ: float,
EL: float,
EC: float,
dL: float,
dCJ: float,
dEJ: float,
flux: float,
ng: float,
ncut: int,
zeta_cut: int,
phi_cut: int,
truncated_dim: int = 6,
) -> None:
self.EJ = EJ
self.ECJ = ECJ
self.EL = EL
self.EC = EC
self.dL = dL
self.dCJ = dCJ
self.dEJ = dEJ
self.flux = flux
self.ng = ng
self.ncut = ncut
self.zeta_cut = zeta_cut
self.phi_cut = phi_cut
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.float_
self._default_phi_grid = discretization.Grid1d(-4 * np.pi, 4 * np.pi,
100)
self._default_zeta_grid = discretization.Grid1d(
-4 * np.pi, 4 * np.pi, 100)
self._default_theta_grid = discretization.Grid1d(
-0.5 * np.pi, 1.5 * np.pi, 100)
self._image_filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)),
"qubit_img/cos2phi-qubit.jpg",
)
def __init__(self, EJ, EC, ng, ncut, truncated_dim=None):
self.EJ = EJ
self.EC = EC
self.ng = ng
self.ncut = ncut
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.float_
self._default_grid = discretization.Grid1d(-np.pi, np.pi, 151)
self._default_n_range = (-5, 6)
self._image_filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)),
'qubit_img/fixed-transmon.jpg')
def __init__(self, EJ, EC, EL, flux, cutoff, truncated_dim=None):
self.EJ = EJ
self.EC = EC
self.EL = EL
self.flux = flux
self.cutoff = cutoff
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.float_
self._default_grid = discretization.Grid1d(-4.5 * np.pi, 4.5 * np.pi,
151)
self._image_filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)),
'qubit_pngs/fluxonium.png')
def __init__(self, EJmax, EC, d, flux, ng, ncut, truncated_dim=None):
self.EJmax = EJmax
self.EC = EC
self.d = d
self.flux = flux
self.ng = ng
self.ncut = ncut
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.float_
self._default_grid = discretization.Grid1d(-np.pi, np.pi, 151)
self._default_n_range = (-5, 6)
self._image_filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)),
'qubit_pngs/tunable_transmon.png')
def __init__(
self,
EJ: float,
EL: float,
ECJ: float,
EC: Optional[float],
ng: float,
flux: float,
grid: Grid1d,
ncut: int,
dEJ: float = 0.0,
dCJ: float = 0.0,
ECS: float = None,
truncated_dim: int = 6,
) -> None:
self.EJ = EJ
self.EL = EL
self.ECJ = ECJ
if EC is None and ECS is None:
raise ValueError("Argument missing: must either provide EC or ECS")
if EC and ECS:
raise ValueError(
"Argument error: can only provide either EC or ECS")
if EC:
self.EC = EC
elif ECS:
self.EC = 1 / (1 / ECS - 1 / self.ECJ)
self.dEJ = dEJ
self.dCJ = dCJ
self.ng = ng
self.flux = flux
self.grid = grid
self.ncut = ncut
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.complex_
# _default_grid is for *theta*, needed for plotting wavefunction
self._default_grid = discretization.Grid1d(-np.pi / 2, 3 * np.pi / 2,
200)
self._init_params.remove(
"ECS"
) # used in for file Serializable purposes; remove ECS as init parameter
self._image_filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)), "qubit_img/zeropi.jpg")
dispatch.CENTRAL_DISPATCH.register("GRID_UPDATE", self)
def __init__(self,
EJ: float,
EC: float,
EL: float,
flux: float,
cutoff: int,
truncated_dim: int = 6) -> None:
self.EJ = EJ
self.EC = EC
self.EL = EL
self.flux = flux
self.cutoff = cutoff
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.float_
self._default_grid = discretization.Grid1d(-4.5 * np.pi, 4.5 * np.pi,
151)
self._image_filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)),
'qubit_img/fluxonium.jpg')
def __init__(self,
EJmax: float,
EC: float,
d: float,
flux: float,
ng: float,
ncut: int,
truncated_dim: int = 6) -> None:
self.EJmax = EJmax
self.EC = EC
self.d = d
self.flux = flux
self.ng = ng
self.ncut = ncut
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.float_
self._default_grid = discretization.Grid1d(-np.pi, np.pi, 151)
self._default_n_range = (-5, 6)
self._image_filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)),
'qubit_img/tunable-transmon.jpg')
def __init__(self,
EJ1,
EJ2,
EJ3,
ECJ1,
ECJ2,
ECJ3,
ECg1,
ECg2,
ng1,
ng2,
flux,
ncut,
truncated_dim=None):
self.EJ1 = EJ1
self.EJ2 = EJ2
self.EJ3 = EJ3
self.ECJ1 = ECJ1
self.ECJ2 = ECJ2
self.ECJ3 = ECJ3
self.ECg1 = ECg1
self.ECg2 = ECg2
self.ng1 = ng1
self.ng2 = ng2
self.flux = flux
self.ncut = ncut
self.truncated_dim = truncated_dim
self._sys_type = type(self).__name__
self._evec_dtype = np.complex_
self._default_grid = discretization.Grid1d(
-np.pi / 2, 3 * np.pi / 2, 100) # for plotting in phi_j basis
self._image_filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)),
'qubit_pngs/fluxqubit.png')
super().__init__()
self.add_element(circuit.Capacitance('Cg1'), ['g1', '1'])
self.add_element(circuit.Capacitance('Cg2'), ['g2', '2'])
self.add_element(circuit.Capacitance('CJ1'), ['GND', '1'])
self.add_element(circuit.Capacitance('CJ2'), ['GND', '2'])
self.add_element(circuit.Capacitance('CJ3'), ['1', '3'])
self.add_element(circuit.JosephsonJunction('J1', use_offset=False),
['GND', '1'])
self.add_element(circuit.JosephsonJunction('J2', use_offset=False),
['GND', '2'])
self.add_element(circuit.JosephsonJunction('J3', use_offset=False),
['1', '3'])
self.phi1 = circuit.Variable('\\phi_1')
self.phi2 = circuit.Variable('\\phi_2')
self.f = circuit.Variable('f')
self.g1 = circuit.Variable('g_1')
self.g2 = circuit.Variable('g_2')
self.add_variable(self.phi1)
self.add_variable(self.phi2)
self.add_variable(self.f)
self.add_variable(self.g1)
self.add_variable(self.g2)
self.map_nodes_linear(['GND', '1', '2', '3', 'g1', 'g2'],
['\\phi_1', '\\phi_2', 'f', 'g_1', 'g_2'],
np.asarray([[0, 0, 0, 0, 0], [1, 0, 0, 0, 0],
[0, 1, 0, 0, 0], [0, 1, -1, 0, 0],
[0, 0, 0, 1, 0], [0, 0, 0, 0, 1]]))
self.set_parameters()
def create(cls):
phi_grid = discretization.Grid1d(-19.0, 19.0, 200)
init_params = cls.default_params()
zeropi = cls(**init_params, grid=phi_grid)
zeropi.widget()
return zeropi