main.html 5.08 KB
 Davison committed Jul 10, 2019 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 `````` Python: module main

main
index
c:\users\davison\research\im-srg_tensorflow\oop_imsrg\main.py

# Main program for IM-SRG.

Modules

tensornetwork.backends
tensornetwork.config
tensornetwork.contractors
tensornetwork.ncon_interface
tensornetwork.network
tensornetwork.network_components
numpy
time
tensornetwork.version
tensornetwork.visualization

Functions

derivative(t, y, hamiltonian, occ_tensors, generator, flow)
Defines the derivative to pass into ode object.

Arguments:
(required by scipy.integrate.ode)
t -- points at which to solve for y
y -- in this case, 1D array that contains E, f, G

hamiltonian -- Hamiltonian object
occ_tensors -- OccupationTensors object
generator -- Generator object
flow -- Flow object

Returns:

dy -- next step in flow
main()
Main method uses scipy.integrate.ode to solve the IMSRG flow
equations.
ravel(y, bas_len)
Transforms 1D array into E, f, and G. Facilitates
compatability with scipy.integrate.ode.

Arugments:

y -- 1D data array (output from unravel)
bas_len -- length of single particle basis

Returns:

E, f, G -- normal-ordered pieces of Hamiltonian
unravel(E, f, G)
Transforms E, f, and G into a 1D array. Facilitates
compatability with scipy.integrate.ode.

Arguments:

E, f, G -- normal-ordered pieces of Hamiltonian

Returns:

concatenation of tensors peeled into 1D arrays

Data
absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0), 16384)
fl = <flow.Flow_IMSRG2 object>
ha = <hamiltonian.PairingHamiltonian2B object>
ot = <occupation_tensors.OccupationTensors object>
wg = <generator.WegnerGenerator object>
``````