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From qiskit_nature.drivers.second_quantization import gaussianforcesdriver # if you ran gaussian elsewhere and already have the output file driver = gaussianforcesdriver(logfile=./co2_freq_b3lyp_631g.log) Driver = gaussianforcesdriver(logfile=co2_freq_b3lyp_631g.log) # define a harmonic basis with two modals per mode from qiskit_nature.second_q.problems import harmonicbasis Driver = gaussianforcesdriver(logfile=co2_freq_b3lyp_631g.log) step 3 Defining the vibrational basis i defined the harmonic basis functions, specifying the number of energy levels (modals) for each vibrational mode
For co₂, which has four primary vibrational modes, i started with two modals per mode for simplicity. Sparsepauliop(['iiiiiiii', 'iiiiiiiz', 'iiiiiizi', 'iiiiizii', 'iiiixxii', 'iiiiyyii', 'iiiiziii', 'iiiziiii', 'iiziiiii', 'iziiiiii', 'ziiiiiii', 'iiiiiziz. Gaussian calculates the single point energy of each intermediate geometry it generates during optimization as well as at the start of a vibrational frequency analysis We can exploit this fact to save us from having to set up another calculation
These keywords will start a gaussian job which first optimizes the geometry for the initial state and then calculates the frequencies of the optimized geometry By using the option freq=savenm, the frequency information will be saved in the checkpoint file anisole_s0.chk From qiskit_algorithms import vqe from qiskit_algorithms.optimizers import cobyla #from qiskit.primitives import estimator from quantumrings.toolkit.qiskit import qrestimatorv1 as estimator from qiskit_nature.second_q.circuit.library import hartreefock, uccsd ansatz = uccsd( es_problem.num_spatial_orbitals, es_problem.num_particles, mapper, initial_state=hartreefock( es_problem.num_spatial.
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