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Fanpy is a free, open-source, and cross-platform Python 3 library designed for ab initio electronic structure calculations. The Fanpy implementation is based on the mathematical framework called Flexible Ansatz for N-electron Configuration Interaction (FANCI). The adoption of the FANCI framework gives a highly modular structure to Fanpy resulting in 5 modules - Hamiltonian, Wavefunction, Objective, Solver, and Tools. The modular structure offers two greatest virtues, The first is its 'sandbox-like' ability to handle any combinations of wavefunction ansatz and different methods, and the second is the ease of transition from the formal conception of a method to its working implementation.

The following wavefunctions are already implemented in Fanpy.

Configuration Interaction

• Configuration Interaction with singles and doubles (CISD)
• Doubly-occupied Configuration Interaction (DOCI)
• Full CI
• Selected CI wavefunctions with a user-specified set of Slater determinants

Coupled-Cluster

• Standard Coupled Cluster (CCSD, CCSDT, ...)
• CC with seniority-specific excitations
• Seniority-restricted CC

Geminal wavefunctions

• Antisymmetrized Product of Geminals (APG)
• Antisymmetrized Product of Interacting Geminals (APIG)
• Antisymmetrized Product of rank-two Interacting Geminals (APr2G)
• Matrix Product States (MPS)

Coupled Cluster-Inspired Geminal Wavefunctions

• The following 1-reference orbital geminal wavefunctions are implemented incorporating single-like excitations.
• Antisymmetrized Product of 1-reference Orbital Interacting Geminals (AP1roG)
• Antisymmetrized Product of Set-separated 1-reference Orbital Geminals (APset1roG)
• Antisymmetrized Product of Geminals with 1-reference Orbital (APG1ro)

The following Hamiltonians are implemented:
Electronic Hamiltonian - restricted, unrestricted, and generalized basis

The Objective module combines the wavefunction and Hamiltonian to represent the following forms of Schrodinger Equations.

• Variational (solving for the expectation value of the energy)
• Projected (solving for the system of equations generated)

The Solver module supports the following optimizers to optimize/solve the equations from the Objective module.

• For CI, it supports brute-force eigenvalue decomposition.
• Optimizers from SciPy
• Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm from pycma
• Decision trees and Bayesian optimization algorithms from scikit-optimize

The Tool module provides different utility functions used throughout the Fanpy package—for example, tools for generating and manipulating Slater determinants.

For detailed information about the mathematical formulation, please take a look at the FANCI publication. The official notes of the Fanpy library can be found in this article.