Data for "Tailored and Externally Corrected Coupled Cluster with Quantum Inputs"

This data set accompanies the manuscript "Tailored and Externally Corrected Coupled Cluster with Quantum Inputs", which can be found on arXiv. The environment.yml file contains specifications for a conda environment that (hopefully) sets up all dependencies to run the notebooks contained herein. - matchgate_shadow_statistics contains raw data for the 8-qubit shadow recorded on a 22-layer QNP-VQE circuit of N2/cc-pVDZ. The notebook `shadow_estimation.ipynb` contains the code to produce the plots for Figures C1 and C2. - error_model contains the raw data from noisy TCCSD calculations on 13 molecules with different basis sets as a `pandas.DataFrame` in `error_model_noise_tccsd.h5`. A script `test_diagnostics.py`, including the molecular geometries, computes the CC diagonstics using `pyscf` and can be run with `pytest` using the `pytest-harvest` plugin, and writes them to `diagnostics_data_general.h5`. The notebook `error_model_resources.ipynb` includes the following tasks: 1. Read in the data and create a new `DataFrame` which contains the average TCCSD energy error (over 30 samples) 2. Power law fit of the whole data set to extract the exponents $\beta$ and $\gamma$ (eq 9, Table C3) 3. Bootstrap estimation of the exponents' standard errors 4. The per-molecule power law fit with fixed exponents to obtain the molecule-specific prefactor $a$ 5. Read-in of diagnostics data and creation of diagnostic->prefactor linear fit (Figure 4, eq C7) 6. Shot budget estimation for the N2 dissociation curve (requires `pyscf`)