Exemple #1
0
def _single_eseries_expect(oper, state):
    """
    Private function used by expect to calculate expectation values for
    eseries.
    """

    out = eseries()

    if isoper(state.ampl[0]):
        out.rates = state.rates
        out.ampl = np.array([expect(oper, a) for a in state.ampl])

    else:
        out.rates = np.array([])
        out.ampl = np.array([])

        for m in range(len(state.rates)):
            op_m = state.ampl[m].data.conj().T * oper.data

            for n in range(len(state.rates)):
                a = op_m * state.ampl[n].data

                if isinstance(a, sp.spmatrix):
                    a = a.todense()

                out.rates = np.append(out.rates, state.rates[n] -
                                      state.rates[m])
                out.ampl = np.append(out.ampl, a)

    return out
Exemple #2
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def ode2es(L, rho0):
    """Creates an exponential series that describes the time evolution for the
    initial density matrix (or state vector) `rho0`, given the Liouvillian
    (or Hamiltonian) `L`.

    Parameters
    ----------
    L : qobj
        Liouvillian of the system.

    rho0 : qobj
        Initial state vector or density matrix.

    Returns
    -------
    eseries : :class:`qutip.eseries`
        ``eseries`` represention of the system dynamics.

    """

    if issuper(L):

        # check initial state
        if isket(rho0):
            # Got a wave function as initial state: convert to density matrix.
            rho0 = rho0 * rho0.dag()

        w, v = L.eigenstates()
        v = np.hstack([ket.full() for ket in v])
        # w[i]   = eigenvalue i
        # v[:,i] = eigenvector i

        rlen = np.prod(rho0.shape)
        r0 = mat2vec(rho0.full())
        v0 = la.solve(v, r0)
        vv = v * sp.spdiags(v0.T, 0, rlen, rlen)

        out = None
        for i in range(rlen):
            qo = Qobj(vec2mat(vv[:, i]), dims=rho0.dims, shape=rho0.shape)
            if out:
                out += eseries(qo, w[i])
            else:
                out = eseries(qo, w[i])

    elif isoper(L):

        if not isket(rho0):
            raise TypeError("Second argument must be a ket if first" + "is a Hamiltonian.")

        w, v = L.eigenstates()
        v = np.hstack([ket.full() for ket in v])
        # w[i]   = eigenvalue i
        # v[:,i] = eigenvector i

        rlen = np.prod(rho0.shape)
        r0 = rho0.full()
        v0 = la.solve(v, r0)
        vv = v * sp.spdiags(v0.T, 0, rlen, rlen)

        out = None
        for i in range(rlen):
            qo = Qobj(np.matrix(vv[:, i]).T, dims=rho0.dims, shape=rho0.shape)
            if out:
                out += eseries(qo, -1.0j * w[i])
            else:
                out = eseries(qo, -1.0j * w[i])

    else:
        raise TypeError("First argument must be a Hamiltonian or Liouvillian.")

    return estidy(out)
Exemple #3
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def ode2es(L, rho0):
    """Creates an exponential series that describes the time evolution for the
    initial density matrix (or state vector) `rho0`, given the Liouvillian
    (or Hamiltonian) `L`.

    .. deprecated:: 4.6.0
        :obj:`~ode2es` will be removed in QuTiP 5.  Please use
        :obj:`Qobj.eigenstates` to get the eigenstates and -values, and use
        :obj:`~QobjEvo` for general time-dependence.

    Parameters
    ----------
    L : qobj
        Liouvillian of the system.

    rho0 : qobj
        Initial state vector or density matrix.

    Returns
    -------
    eseries : :class:`qutip.eseries`
        ``eseries`` represention of the system dynamics.

    """
    if issuper(L):
        # check initial state
        if isket(rho0):
            # Got a wave function as initial state: convert to density matrix.
            rho0 = rho0 * rho0.dag()
        # check if state is below error threshold
        if abs(rho0.full()).sum() < 1e-10 + 1e-24:
            # enforce zero operator
            return eseries(qzero(rho0.dims[0]))
        w, v = L.eigenstates()
        v = np.hstack([ket.full() for ket in v])
        # w[i]   = eigenvalue i
        # v[:,i] = eigenvector i

        rlen = np.prod(rho0.shape)
        r0 = mat2vec(rho0.full())
        v0 = la.solve(v, r0)
        vv = v * sp.spdiags(v0.T, 0, rlen, rlen)

        out = None
        for i in range(rlen):
            qo = Qobj(vec2mat(vv[:, i]), dims=rho0.dims, shape=rho0.shape)
            if out:
                out += eseries(qo, w[i])
            else:
                out = eseries(qo, w[i])

    elif isoper(L):

        if not isket(rho0):
            raise TypeError('Second argument must be a ket if first' +
                            'is a Hamiltonian.')

        # check if state is below error threshold
        if abs(rho0.full()).sum() < 1e-5 + 1e-20:
            # enforce zero operator
            dims = rho0.dims
            return eseries(
                Qobj(sp.csr_matrix((dims[0][0], dims[1][0]), dtype=complex)))

        w, v = L.eigenstates()
        v = np.hstack([ket.full() for ket in v])
        # w[i]   = eigenvalue i
        # v[:,i] = eigenvector i

        rlen = np.prod(rho0.shape)
        r0 = rho0.full()
        v0 = la.solve(v, r0)
        vv = v * sp.spdiags(v0.T, 0, rlen, rlen)

        out = None
        for i in range(rlen):
            qo = Qobj(np.array(vv[:, i]).T, dims=rho0.dims, shape=rho0.shape)
            if out:
                out += eseries(qo, -1.0j * w[i])
            else:
                out = eseries(qo, -1.0j * w[i])

    else:
        raise TypeError('First argument must be a Hamiltonian or Liouvillian.')

    return estidy(out)
Exemple #4
0
def ode2es(L, rho0):
    """Creates an exponential series that describes the time evolution for the
    initial density matrix (or state vector) `rho0`, given the Liouvillian
    (or Hamiltonian) `L`.

    Parameters
    ----------
    L : qobj
        Liouvillian of the system.

    rho0 : qobj
        Initial state vector or density matrix.

    Returns
    -------
    eseries : :class:`qutip.eseries`
        ``eseries`` represention of the system dynamics.

    """

    if issuper(L):

        # check initial state
        if isket(rho0):
            # Got a wave function as initial state: convert to density matrix.
            rho0 = rho0 * rho0.dag()

        w, v = L.eigenstates()
        v = np.hstack([ket.full() for ket in v])
        # w[i]   = eigenvalue i
        # v[:,i] = eigenvector i

        rlen = prod(rho0.shape)
        r0 = mat2vec(rho0.full())
        v0 = la.solve(v, r0)
        vv = v * sp.spdiags(v0.T, 0, rlen, rlen)

        out = None
        for i in range(rlen):
            qo = Qobj(vec2mat(vv[:, i]), dims=rho0.dims, shape=rho0.shape)
            if out:
                out += eseries(qo, w[i])
            else:
                out = eseries(qo, w[i])

    elif isoper(L):

        if not isket(rho0):
            raise TypeError('Second argument must be a ket if first' +
                            'is a Hamiltonian.')

        w, v = L.eigenstates()
        v = np.hstack([ket.full() for ket in v])
        # w[i]   = eigenvalue i
        # v[:,i] = eigenvector i

        rlen = prod(rho0.shape)
        r0 = rho0.full()
        v0 = la.solve(v, r0)
        vv = v * sp.spdiags(v0.T, 0, rlen, rlen)

        out = None
        for i in range(rlen):
            qo = Qobj(np.matrix(vv[:, i]).T, dims=rho0.dims, shape=rho0.shape)
            if out:
                out += eseries(qo, -1.0j * w[i])
            else:
                out = eseries(qo, -1.0j * w[i])

    else:
        raise TypeError('First argument must be a Hamiltonian or Liouvillian.')

    return estidy(out)