MolKet offers consulting and AI services for modeling solutions for quantum molecular dynamics and cryptography with cloud-based software on hybrid HPC and quantum computing platforms.
You can choose a jupyterhub like environment Or MolKet studio
You can use MolKet’s engine on your computer in visual studio or program it online on the web.
import molket_engine as me
import molket_visual as mv
import molket_data as md
# define the molecular structure
# insert H2 molecule
molecule = me.Molecule('H_2')
# define the geometry of the molecule: example H2
molecule.geometry = [('H', (0, 0, 0)), ('H', (0, 0, 0.74))]
# you can also define a grid of points to sample the wavefunction
r = [0.5,0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2,1.3,1.4,1.5,1.6,
1.7,1.8,1.9,2] # in Angstrom
molecule.geometry = [('H', (0, 0, -r/2)), ('H', (0, 0, r/2))]
Type your code in natural language, or choose from our library. Our AI-assistant will help you filling the code writing and suggest modules that you can use.
Alternatively, you can design the simulation in a flow chart format and our AI-assistant will convert it into code. Then, it will choose the proper modules and print the code sequence for to confirm.
# create the Hamiltonian operator with the molecule and data structure
H_op = me.Operator('H_2')
H_op.molecule = molecule
# define the electronic basis set
H_op.elec_basis = 'sto-3g'
# define the nuclear motion basis set, the vibrational basis set
H_op.nuc_basis = ('harmonic','Gaussian')
Depending on the computational complexity and the type of each step in the simulation, MolKet’s AI engine will choose the proper quantum/HPC architecture for you.
It will also optimize the execution on each type of hardware by training the general Hamiltonians and map them onto quantum
# define the rotational basis set (wavefunctions), ...
# Default: spherical harmonics for linear molecules, and Wigner D-matrices for non-linear molecules.
H_op.rot_basis = ('Ylm')
# you can also define phase or choose real harmonics depending on the symmetry of the molecule
# Define the chips for the computing part: the choice of the hardware and the backend
H_op.Qchip = 'Qqx2' ## variations of Qqx4: Qqx2, Qqx3, Qqx4, Qqx5, Qqx20, Qqx_qasm_simulator
## accelerated computing with GPU
H_op.HPCchip = 'GPU'
Depending on the computational complexity and the type of each step in the simulation, MolKet’s AI engine will choose the proper quantum/HPC architecture for you.
# choose the simulators for the quantum and HPC backends, to be used in analysis as well
H_op.Qbackend = 'statevector_simulator'
H_op.HPCbackend = 'local_qasm_simulator'
vib_groundstate_energy= H_op.vib_eigE('0','groundstate')
vib_WF0 = H_op.vib_eigW('0','groundstate')
#H = H_vib + H_rot + H_elec + H_nuc