Quantinuum And Co-Researchers Develop Advanced Quantum Computing Simulations

Researchers have made advancements in computational chemistry using quantum computing techniques. The team used projector-augmented wave pseudo-potentials and periodic Hartree-Fock calculations to study surface reactions on platinum. Companies like Quantinuum and their platform InQuanto were involved in the work, along with technologies from PySCF and TKET.

The researchers applied their methods to systems like platinum and oxygen molecules, achieving convergence stability with specific basis sets and pseudopotentials. The findings have implications for understanding chemical reactions at the molecular level, potentially leading to breakthroughs in fields like materials science and catalysis.

Density Functional Theory (DFT) calculations

  • The authors used the Quantum Espresso (QE) package to perform DFT calculations with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional and projector-augmented wave (PAW) pseudopotentials.
  • They employed spin-polarized simulations with van der Waals dispersion correction (DFT-D3) for geometry optimization of structures of interest.
  • Different cutoffs and k-point meshes were used for bulk and surface calculations.

Periodic Hartree-Fock calculations

  • The authors performed periodic Hartree-Fock mean-field calculations using the Los Alamos National Laboratory (LANL2DZ) basis/pseudopotentials.
  • They used a Fermi-Dirac smearing with a tuning parameter σ = 0.005 Ha and a k-point mesh of (6 × 6 × 6) to ensure total energy convergence.

Atomic Valence Active Space (AVAS) and Regional Embedding

  • The authors used their own implementation of Regional Embedding (RE), a variant of the AVAS method, to embed quantum computations on a smaller system into the full ab-initio system.
  • They constructed an active space by selecting atomic orbitals (projectors) and computing an overlap matrix of occupied orbitals projected into this space.

Multireference VQE calculations

  • The authors used their proprietary method QRDM_NEVPT2 to account for dynamic correlation effects, which calculates a perturbative correction arising from excitations within the whole RE active space.
  • They employed the VQE-ADAPT ansatz building approach and performed classical and quantum computing simulations using various tools, including InQuanto, TKET, Qulacs, and Quantinuum‘s noisy emulator H1-2E.

Overall, this text describes a range of computational methods used to study the properties of materials, including DFT, periodic Hartree-Fock, AVAS, and multireference VQE calculations. The authors employed various tools and techniques to optimize their calculations and account for different types of correlations and interactions.

 

a An atomistic model of the whole system is generated, firstly geometrically relaxed using a DFT approach and, then, treated at the HF level of theory with a localized basis. b An atomistic representation of the (electron correlated) embedded fragment is carefully chosen and an AVAS/RE procedure is performed to find the best embedded orbital set for the active space. c Energy calculation for the embedded active space including static correlation via a hybrid quantum-classical ADPT-VQE procedure is performed by optimizing the variational parameters for the chosen ansatz and active space (CPU: Intel Xeon; quantum device QPU: Quantinuum H1-series hardware/noisy emulator). d To estimate the contribution of the dynamical correlation to the total energy, a classical post-processing NEVPT2 calculation is made using the set of RDMS, up to the 4th particle order, measured after the optimization cycle in step c is completed.
a An atomistic model of the whole system is generated, firstly geometrically relaxed using a DFT approach and, then, treated at the HF level of theory with a localized basis. b An atomistic representation of the (electron correlated) embedded fragment is carefully chosen and an AVAS/RE procedure is performed to find the best embedded orbital set for the active space. c Energy calculation for the embedded active space including static correlation via a hybrid quantum-classical ADPT-VQE procedure is performed by optimizing the variational parameters for the chosen ansatz and active space (CPU: Intel Xeon; quantum device QPU: Quantinuum H1-series hardware/noisy emulator). d To estimate the contribution of the dynamical correlation to the total energy, a classical post-processing NEVPT2 calculation is made using the set of RDMS, up to the 4th particle order, measured after the optimization cycle in step c is completed.
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