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A Reproducible Workflow for Extracting Quantum Hamiltonians from Surface-Adsorbate Models

Manisha Malhotra, Neil Ramarapu, F. Rinaldi

Published Apr 10, 2026• 0 citations
Publisher

Abstract

An open-source, reproducible software workflow that optimizes a DFT slab model of a catalyst surface and produces a few-body Hamiltonian suitable for quantum simulation.
DOI
10.5281/zenodo.19491026

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A Reproducible Workflow for Extracting Quantum Hamiltonians from Surface-Adsorbate Models

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Abstract Bridging the gap between realistic surface catalysis models from density functional theory (DFT) and the input requirements of quantum algorithms is a non-trivial task. Surface DFT calculations typically model extended slabs and yield total energies or reaction energetics, whereas quantum algorithms (such as variational quantum eigensolvers) require a many-body Hamiltonian (e.g. a list of fermionic or qubit operators) as input. We present an open-source, reproducible software workflow that takes an optimized DFT slab model of a catalyst surface and produces a few-body Hamiltonian suitable for quantum simulation. Starting from a DFT-optimized slab geometry, the workflow extracts a localized cluster around the active site, identifies an appropriate set of active orbitals, and constructs the corresponding fermionic and qubit Hamiltonians. Orbital selection is guided by manual cross-referencing of semiempirical orbital contributions across neutral and anionic cluster states, using localisation and energetic proximity to the HOMO as selection criteria. This end-to-end pipeline enables researchers to bridge surface science and quantum computing in a transparent and automated manner. We demonstrate the workflow on a representative electrochemical system: a hydrogen-based adsorbate (H* or OH*) on an IrO$_2$ catalyst surface. For this system, our software produces a 14-qubit Hamiltonian (derived from a 7-orbital active space) that can be directly used in quantum algorithms such as the Variational Quantum Eigensolver (VQE \cite{VQE}). This work provides a reproducible, end-to-end pipeline bridging periodic surface DFT models and quantum-ready Hamiltonians for heterogeneous catalytic systems, enabling direct integration of realistic surface chemistry with near-term quantum algorithms.

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A Reproducible Workflow for Extracting Quantum Hamiltonians from Surface-Adsorbate Models

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Abstract Bridging realistic surface-catalysis models from density functional theory (DFT) and the many-body Hamiltonian inputs required by quantum algorithms remains a practical obstacle: surface DFT yields total energies and densities, whereas algorithms such as the variational quantum eigensolver require an explicit fermionic or qubit operator. We present an open-source, reproducible workflow that takes a DFT-optimised slab, extracts a hydrogen-capped cluster around the active site, selects a frontier active space automatically, and constructs the corresponding fermionic and qubit Hamiltonians. Heavy-element cores are treated with an effective core potential (ECP) at the Hartree–Fock stage, an established molecular-cluster strategy for quantum-computing catalysis workflows. WedemonstratethepipelineonH*/OH* adsorption on rutile IrO2(110) at two adsorption sites, producing 14-qubit Hamiltonians from (8e, 7o) active spaces. The pipeline is validated end to end: the Hartree–Fock reference reconstructed from the qubit Hamiltonian reproduces the self-consistent-field energy to better than 10 −6 Hartree, and exact diagonalisation yields physically sensible static correlation energies at the milli-Hartree scale. The entire active-space pipeline runs on commodity hardware without high-performance computing. We additionally document a methodological caution: the def2-SVP basis is defined for Iridium only together with its ECP, so an all-electron treatment in this basis is ill-defined rather than merely approximate.

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Abstract Bridging the gap between realistic surface catalysis models from density functional theory (DFT) and the input requirements of quantum algorithms is a non-trivial task. Surface DFT calculations typically model extended slabs and yield total energies or reaction energetics, whereas quantum algorithms (such as variational quantum eigensolvers) require a many-body Hamiltonian (e.g. a list of fermionic or qubit operators) as input. We present an open-source, reproducible software workflow that takes an optimized DFT slab model of a catalyst surface and produces a few-body Hamiltonian suitable for quantum simulation. Starting from a DFT-optimized slab geometry, the workflow extracts a localized cluster around the active site, identifies an appropriate set of active orbitals, and constructs the corresponding fermionic and qubit Hamiltonians. Orbital selection is guided by manual cross-referencing of semiempirical orbital contributions across neutral and anionic cluster states, using localisation and energetic proximity to the HOMO as selection criteria. This end-to-end pipeline enables researchers to bridge surface science and quantum computing in a transparent and automated manner. We demonstrate the workflow on a representative electrochemical system: a hydrogen-based adsorbate (H* or OH*) on an IrO2_22​ catalyst surface. For this system, our software produces a 14-qubit Hamiltonian (derived from a 7-orbital active space) that can be directly used in quantum algorithms such as the Variational Quantum Eigensolver (VQE \cite{VQE}). This work provides a reproducible, end-to-end pipeline bridging periodic surface DFT models and quantum-ready Hamiltonians for heterogeneous catalytic systems, enabling direct integration of realistic surface chemistry with near-term quantum algorithms.
Abstract Bridging realistic surface-catalysis models from density functional theory (DFT) and the many-body Hamiltonian inputs required by quantum algorithms remains a practical obstacle: surface DFT yields total energies and densities, whereas algorithms such as the variational quantum eigensolver require an explicit fermionic or qubit operator. We present an open-source, reproducible workflow that takes a DFT-optimised slab, extracts a hydrogen-capped cluster around the active site, selects a frontier active space automatically, and constructs the corresponding fermionic and qubit Hamiltonians. Heavy-element cores are treated with an effective core potential (ECP) at the Hartree–Fock stage, an established molecular-cluster strategy for quantum-computing catalysis workflows. WedemonstratethepipelineonH*/OH* adsorption on rutile IrO2(110) at two adsorption sites, producing 14-qubit Hamiltonians from (8e, 7o) active spaces. The pipeline is validated end to end: the Hartree–Fock reference reconstructed from the qubit Hamiltonian reproduces the self-consistent-field energy to better than 10 −6 Hartree, and exact diagonalisation yields physically sensible static correlation energies at the milli-Hartree scale. The entire active-space pipeline runs on commodity hardware without high-performance computing. We additionally document a methodological caution: the def2-SVP basis is defined for Iridium only together with its ECP, so an all-electron treatment in this basis is ill-defined rather than merely approximate.
This software-framework note archives scpn-quantum-control, a reproducible Kuramoto--XY quantum-control workflow combining Python/Qiskit orchestration, Rust acceleration, hardware artefact packaging, and publication-grade analysis surfaces. The software supports construction of heterogeneous oscillator networks, XY-Hamiltonian mapping, topology-informed ansatz generation, simulator and hardware execution, and reproducible post-processing of IBM artefacts. The record documents the framework as a research software artefact rather than a standalone physics claim. It highlights the repository structure, reproducibility workflow, accelerated kernels, benchmark and parity checks, and the relationship between source code, generated artefacts, and paper records. The archive includes the JOSS-style manuscript source, bibliography, preview TeX, and rebuilt PDF. Repository field and DOI metadata link the software note back to https://github.com/anulum/scpn-quantum-control.