permutations_fork/models.py at master · lukasfreter/permutations_fork · GitHub

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def setup_counterlaser(lamb, gam_c, gam_d, num_threads = None, progress = False, parallel = False):
    """Generate Liouvillian for counter rotating interaction, lamb(a*sigmam + adag*sigmap)"""

    from operators import tensor, qeye, destroy, create, sigmap, sigmam, sigmaz
    from basis import nspins, ldim_s, ldim_p, setup_L
    from numpy import sqrt

    #note terms with just photon operators need to be divided by nspins
    H = lamb * (tensor(create(ldim_p), sigmap()) +  tensor(destroy(ldim_p), sigmam()))

    c_ops=[]
    c_ops.append(sqrt(gam_c/nspins)*tensor(destroy(ldim_p), qeye(ldim_s)))
    c_ops.append(sqrt(gam_d)*tensor(qeye(ldim_p), sigmam()))

    return setup_L(H, c_ops, num_threads, progress, parallel)


def setup_laser(g, Delta, kappa, gam_dn, gam_up, gam_phi, num_threads = None, progress = False, parallel = False):

    """Generate Liouvillian for laser problem
    H = Delta*sigmaz + g(a*sigmap + adag*sigmam)
    c_ops = kappa L[a] + gam_dn L[sigmam] + gam_up L[sigmap] + gam_phi L[sigmaz]"""

    from operators import tensor, qeye, destroy, create, sigmap, sigmam, sigmaz
    from basis import nspins, ldim_s, ldim_p, setup_L
    from numpy import sqrt


    H = g*(tensor(destroy(ldim_p), sigmap())+ tensor(create(ldim_p), sigmam())) + Delta*tensor(qeye(ldim_p), sigmaz())

    c_ops = [sqrt(kappa/nspins)*tensor(destroy(ldim_p), qeye(ldim_s)), sqrt(gam_dn)*tensor(qeye(ldim_p), sigmam()), sqrt(gam_up)*tensor(qeye(ldim_p), sigmap())]
    c_ops.append(sqrt(gam_phi)*tensor(qeye(ldim_p), sigmaz()))

    return setup_L(H, c_ops, num_threads, progress, parallel)


def setup_3ls(nu, g, kappa, pump, num_threads = None, progress = False, parallel = False):

    """Generate Liouvillian for 3-level system
    H = nu*adag*a + g(a*create(3) + h.c.)
    c_ops = kappa L[a] + pump L[create(3)]
    """

    from operators import tensor, qeye, destroy, create, sigmap, sigmam, sigmaz
    from basis import nspins, ldim_s, ldim_p, setup_L
    from numpy import sqrt

    H = nu * tensor(create(ldim_p) * destroy(ldim_p), qeye(ldim_s)) / nspins\
            + g * tensor(create(ldim_p), destroy(ldim_s)) + g * tensor(destroy(ldim_p), create(ldim_s))
    c_ops = [
        sqrt(kappa/nspins)*tensor(destroy(ldim_p), qeye(ldim_s)),
        sqrt(pump)*tensor(qeye(ldim_p), create(ldim_s)),
            ]

    return setup_L(H, c_ops, num_threads, progress, parallel)

def setup_Dicke(omega, omega0, U, g, gp, kappa, gam_phi, gam_dn, num_threads = None, progress = False, parallel = False):
    """Generate Liouvillian for Dicke model
    H = omega*adag*a + omega0*sz  + g*(a*sp + adag*sm) + gp*(a*sm + adag*sp) + U *adag*a*sz
    c_ops = kappa L[a] + gam_phi L[sigmaz] + gam_dn L[sigmam]"""


    from operators import tensor, qeye, destroy, create, sigmap, sigmam, sigmaz
    from basis import nspins, ldim_s, ldim_p, setup_L
    from numpy import sqrt

    num = create(ldim_p)*destroy(ldim_p)

    #note terms with just photon operators need to be divided by nspins
    H = omega*tensor(num, qeye(ldim_s))/nspins + omega0*tensor(qeye(ldim_p), sigmaz()) + U*tensor(num, sigmaz())
    H = H + g*(tensor(create(ldim_p), sigmam()) +  tensor(destroy(ldim_p), sigmap()))
    H = H + gp*(tensor(create(ldim_p), sigmap()) +  tensor(destroy(ldim_p), sigmam()))

    c_ops=[]
    c_ops.append(sqrt(kappa/nspins)*tensor(destroy(ldim_p), qeye(ldim_s)))
    c_ops.append(sqrt(gam_phi)*tensor(qeye(ldim_p), sigmaz()))
    c_ops.append(sqrt(gam_dn)*tensor(qeye(ldim_p), sigmam()))

    return setup_L(H, c_ops, num_threads, progress, parallel)


def setup_Dicke_kappaup(omega, omega0, U, g, gp, kappa,kappa_up, gam_phi, gam_dn, num_threads = None, progress = False, parallel = False):
    """Generate Liouvillian for Dicke model
    H = omega*adag*a + omega0*sz  + g*(a*sp + adag*sm) + gp*(a*sm + adag*sp) + U *adag*a*sz
    c_ops = kappa L[a] + kappa_up L[adag] + gam_phi L[sigmaz] + gam_dn L[sigmam]"""


    from operators import tensor, qeye, destroy, create, sigmap, sigmam, sigmaz
    from basis import nspins, ldim_s, ldim_p, setup_L
    from numpy import sqrt

    num = create(ldim_p)*destroy(ldim_p)

    #note terms with just photon operators need to be divided by nspins
    H = omega*tensor(num, qeye(ldim_s))/nspins + omega0*tensor(qeye(ldim_p), sigmaz()) + U*tensor(num, sigmaz())
    H = H + g*(tensor(create(ldim_p), sigmam()) +  tensor(destroy(ldim_p), sigmap()))
    H = H + gp*(tensor(create(ldim_p), sigmap()) +  tensor(destroy(ldim_p), sigmam()))

    c_ops=[]
    c_ops.append(sqrt(kappa/nspins)*tensor(destroy(ldim_p), qeye(ldim_s)))
    c_ops.append(sqrt(kappa_up/nspins) * tensor(create(ldim_p), qeye(ldim_s)))
    c_ops.append(sqrt(gam_phi)*tensor(qeye(ldim_p), sigmaz()))
    c_ops.append(sqrt(gam_dn)*tensor(qeye(ldim_p), sigmam()))

    return setup_L(H, c_ops, num_threads, progress, parallel)


def setup_Dicke_block(omega,omega0, U, g, gp, kappa, gam_phi, gam_dn,num_threads = None, progress = False, parallel = False):
    """ Generate Liouvillian for Dicke model (same as in setup_Dicke) but in
        Block structure

    """
    from operators import tensor, qeye, destroy, create, sigmap, sigmam, sigmaz
    from basis import nspins, ldim_s, ldim_p, setup_L_block, setup_L_block1
    from numpy import sqrt

    from scipy.sparse import csr_matrix

    num = create(ldim_p)*destroy(ldim_p)

    #note terms with just photon operators need to be divided by nspins
    H = omega*tensor(num, qeye(ldim_s))/nspins + omega0*tensor(qeye(ldim_p), sigmaz()) + U*tensor(num, sigmaz())
    H = H + g*(tensor(create(ldim_p), sigmam()) +  tensor(destroy(ldim_p), sigmap()))
    H = H + gp*(tensor(create(ldim_p), sigmap()) +  tensor(destroy(ldim_p), sigmam()))
   # print(H.todense())

    c_ops=[]
    c_ops.append(sqrt(kappa/nspins)*tensor(destroy(ldim_p), qeye(ldim_s)))
    c_ops.append(sqrt(gam_phi)*tensor(qeye(ldim_p), sigmaz()))
    c_ops.append(sqrt(gam_dn)*tensor(qeye(ldim_p), sigmam()))

    # L0_old, L1_old= setup_L_block(H,c_ops,num_threads, progress,parallel)
    # for c in range(len(c_ops)):
        # c_ops[c] = csr_matrix(c_ops[c])
    # L0_new, L1_new = setup_L_block1(H,c_ops,num_threads,progress,parallel)
    # for c in range(len(c_ops)):
        # c_ops[c] = csr_matrix(c_ops[c])

    # x1 = L0_old[1].todense()
    # x2 = L0_new[1].todense()
    # y1 = L0_old[2].todense()
    # y2 = L0_new[2].todense()
    # z1 = L0_old[3].todense()
    # z2 = L0_new[3].todense()

    # import numpy as np
    # for bi in range(len(L0_old)):
    #     assert np.allclose(L0_old[bi].todense(), L0_new[bi].todense())


    return setup_L_block(H, c_ops, num_threads, progress, parallel)


def setup_Dicke_block1(omega,omega0, U, g, gp, kappa, gam_phi, gam_dn,num_threads = None, progress = False, parallel = False):
    """ Generate Liouvillian for Dicke model (same as in setup_Dicke) but in
        Block structure

    """
    from operators import tensor, qeye, destroy, create, sigmap, sigmam, sigmaz
    from basis import nspins, ldim_s, ldim_p, setup_L_block, setup_L_block1
    from numpy import sqrt

    from scipy.sparse import csr_matrix

    num = create(ldim_p)*destroy(ldim_p)

    #note terms with just photon operators need to be divided by nspins
    H = omega*tensor(num, qeye(ldim_s))/nspins + omega0*tensor(qeye(ldim_p), sigmaz()) + U*tensor(num, sigmaz())
    H = H + g*(tensor(create(ldim_p), sigmam()) +  tensor(destroy(ldim_p), sigmap()))
    H = H + gp*(tensor(create(ldim_p), sigmap()) +  tensor(destroy(ldim_p), sigmam()))
   # print(H.todense())

    c_ops=[]
    c_ops.append(sqrt(gam_phi)*tensor(qeye(ldim_p), sigmaz()))
    c_ops.append(sqrt(gam_dn)*tensor(qeye(ldim_p), sigmam()))
    c_ops.append(sqrt(kappa/nspins)*tensor(destroy(ldim_p), qeye(ldim_s)))

    # L0_old, L1_old= setup_L_block(H,c_ops,num_threads, progress,parallel)
    # for c in range(len(c_ops)):
    #     c_ops[c] = csr_matrix(c_ops[c])
    # L0_new, L1_new = setup_L_block1(H,c_ops,num_threads,progress,parallel)
    # for c in range(len(c_ops)):
    #     c_ops[c] = csr_matrix(c_ops[c])

    # x1 = L0_old[1].todense()
    # x2 = L0_new[1].todense()
    # y1 = L0_old[2].todense()
    # y2 = L0_new[2].todense()
    # z1 = L0_old[3].todense()
    # z2 = L0_new[3].todense()

    # X1 = L1_old[0].todense()
    # print(X1)
    # X2 = L1_new[0].todense()
    # Y1 = L1_old[1].todense()
    # Y2 = L1_new[1].todense()
    # Z1 = L1_old[2].todense()
    # Z2 = L1_new[2].todense()

    # import numpy as np
    # for bi in range(len(L0_old)):
    #     print('L0 block',bi)
    #     assert np.allclose(L0_old[bi].todense(), L0_new[bi].todense())


    # for bi in range(len(L1_old)):
    #     print('L1 block',bi)
    #     assert np.allclose(L1_old[bi].todense(), L1_new[bi].todense())


    return setup_L_block1(H, c_ops, num_threads, progress, parallel)


def setup_pumped_Dicke(omega, omega0, U, g, gp, kappa, gam_phi, gam_dn, gam_up, num_threads = None,
                       progress = False, parallel = False):
    """Generate Liouvillian for Dicke model wih pumping
    H = omega*adag*a + omega0*sz  + g*(a*sp + adag*sm) + gp*(a*sm + adag*sp) + U *adag*a*sz
    c_ops = kappa L[a] + gam_phi L[sigmaz] + gam_dn L[sigmam] + gam_up L[sigmap]"""


    from operators import tensor, qeye, destroy, create, sigmap, sigmam, sigmaz
    from basis import nspins, ldim_s, ldim_p, setup_L
    from numpy import sqrt

    num = create(ldim_p)*destroy(ldim_p)

    #note terms with just photon operators need to be divided by nspins
    H = omega*tensor(num, qeye(ldim_s))/nspins + omega0*tensor(qeye(ldim_p), sigmaz()) + U*tensor(num, sigmaz())
    H = H + g*(tensor(create(ldim_p), sigmam()) +  tensor(destroy(ldim_p), sigmap()))
    H = H + gp*(tensor(create(ldim_p), sigmap()) +  tensor(destroy(ldim_p), sigmam()))

    c_ops=[]
    c_ops.append(sqrt(kappa/nspins)*tensor(destroy(ldim_p), qeye(ldim_s)))
    c_ops.append(sqrt(gam_phi)*tensor(qeye(ldim_p), sigmaz()))
    c_ops.append(sqrt(gam_dn)*tensor(qeye(ldim_p), sigmam()))
    c_ops.append(sqrt(gam_up)*tensor(qeye(ldim_p), sigmap()))

    return setup_L(H, c_ops, num_threads, progress, parallel)