Related Experiment Video
Updated: Jan 20, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
Published on: September 8, 2023
Efficient formulation of full configuration interaction quantum Monte Carlo in a spin eigenbasis via the graphical
Werner Dobrautz1, Simon D Smart2, Ali Alavi1
1Max Planck Institute for Solid State Research, Heisenbergstr. 1, 70569 Stuttgart, Germany.
Abstract:
We provide a spin-adapted formulation of the Full Configuration Interaction Quantum Monte Carlo (FCIQMC) algorithm, based on the Graphical Unitary Group Approach (GUGA), which enables the exploitation of SU(2) symmetry within this stochastic framework. Random excitation generation and matrix element calculation on the Shavitt graph of GUGA can be efficiently implemented via a biasing procedure on the branching diagram. The use of a spin-pure basis explicitly resolves the different spin-sectors and ensures that the stochastically sampled wavefunction is an eigenfunction of the total spin operator S^2. The method allows for the calculation of states with low or intermediate spin in systems dominated by Hund's first rule, which are otherwise generally inaccessible. Furthermore, in systems with small spin gaps, the new methodology enables much more rapid convergence with respect to walker number and simulation time. Some illustrative applications of the GUGA-FCIQMC method are provided: computation of the 2F - 4F spin gap of the cobalt atom in large basis sets, achieving chemical accuracy to experiment, and the Σg+1, Σg+3, Σg+5, and Σg+7 spin-gaps of the stretched N2 molecule, an archetypal strongly correlated system.
Related Concept Videos
Quantum Numbers
05:30Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
11:16Correlative Light- and Electron Microscopy Using Quantum Dot Nanoparticles
08:55Testing the In Vitro and In Vivo Efficiency of mRNA-Lipid Nanoparticles Formulated by Microfluidic Mixing
10:00Gradient Echo Quantum Memory in Warm Atomic Vapor
10:16Production and Targeting of Monovalent Quantum Dots
