Unbiasing the initiator approximation in Full Configuration Interaction Quantum Monte Carlo
Khaldoon Ghanem, Alexander Y. Lozovoi, Ali Alavi

TL;DR
This paper introduces a simple correction to the initiator FCIQMC algorithm that effectively removes bias, enabling highly accurate quantum chemistry calculations with fewer walkers and less dependence on the initiator threshold.
Contribution
The authors propose a novel bias correction method using acceptance probability to unbias the initiator FCIQMC, improving convergence and accuracy in large systems.
Findings
Rapid convergence to FCI limit with fewer walkers.
Significant reduction of initiator bias dependence.
Accurate energies within milli-Hartree of CCSDT(Q) for large molecules.
Abstract
We identify and rectify a crucial source of bias in the initiator FCIQMC algorithm. Non-initiator determinants (i.e. determinants whose population is below the initiator threshold) are subject to a systematic {\em undersampling} bias, which in large systems leads to a bias in the energy when an insufficient number of walkers is used. We show that the acceptance probability (), that a non-initiator determinant has its spawns accepted, can be used to unbias the initiator bias, in a simple and accurate manner, by reducing the applied shift to the non-initiator proportionately to . This modification preserves the property that in the large walker limit, when , the unbiasing procedure disappears, and the initiator approximation becomes exact. We demonstrate that this algorithm shows rapid convergence to the FCI limit with respect to walker number, and…
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