Symmetry-Match Fraction for Active-Space Selection: A Simple Route to Accurate Reaction Energies in VQE/UCCSD

Simulation of chemical reactions to compute reaction energies using variational algorithms remains challenging in achieving chemical accuracy relative to benchmark computational chemistry methods due to limitations such as qubit number, circuit depth, and noise. To address this issue, we propose the definition of different active spaces for studying chemical reactions, incorporating irreducible representations of both ground and excited states by defining the maximum contribution of excitation terms in the ansatz, implemented here within a second-order Trotterized UCCSD-VQE framework. Our results demonstrate that this approach can achieve chemical accuracy for several representative reactions and yields close agreement with benchmark methods across a broader range of reactions. For all reactions studied, the difference in reaction energies between VQE and CCSD remains within 1 kcal/mol. At the same time, comparison with FCI shows chemical accuracy for several cases and close agreement for the remaining systems. Furthermore, our analysis simplifies the selection of active spaces and electrons for each reaction, reducing it to a single optimal combination that supports chemically accurate or near-chemical-accuracy predictions.

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Publication Details

Journal
The Journal of Physical Chemistry A
Published
2026-06-08
DOI
https://doi.org/10.1021/acs.jpca.6c00363
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
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article

Symmetry-Match Fraction for Active-Space Selection: A Simple Route to Accurate Reaction Energies in VQE/UCCSD

Atul Kumar, Maitreyee Sarkar, Manikandan Paranjothy, Akash Gutal et al.
The Journal of Physical Chemistry A
Machine Learning in Materials Science
article

Symmetry-Match Fraction for Active-Space Selection: A Simple Route to Accurate Reaction Energies in VQE/UCCSD

Atul Kumar, Maitreyee Sarkar, Manikandan Paranjothy, Akash Gutal, Lisa Roy
article en

Abstract

Simulation of chemical reactions to compute reaction energies using variational algorithms remains challenging in achieving chemical accuracy relative to benchmark computational chemistry methods due to limitations such as qubit number, circuit depth, and noise. To address this issue, we propose the definition of different active spaces for studying chemical reactions, incorporating irreducible representations of both ground and excited states by defining the maximum contribution of excitation terms in the ansatz, implemented here within a second-order Trotterized UCCSD-VQE framework. Our results demonstrate that this approach can achieve chemical accuracy for several representative reactions and yields close agreement with benchmark methods across a broader range of reactions. For all reactions studied, the difference in reaction energies between VQE and CCSD remains within 1 kcal/mol. At the same time, comparison with FCI shows chemical accuracy for several cases and close agreement for the remaining systems. Furthermore, our analysis simplifies the selection of active spaces and electrons for each reaction, reducing it to a single optimal combination that supports chemically accurate or near-chemical-accuracy predictions.

The Journal of Physical Chemistry A
Indian Institute of Technology Jodhpur (IN), Centre for Quantum Computation and Communication Technology (AU), IR Dynamics (United States) (US), Chemical Dynamics (United States) (US)
Openalex Percentile: Top 13%
Machine Learning in Materials Science
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Symmetry-Match Fraction for Active-Space Selection: A Simple Route to Accurate Reaction Energies in VQE/UCCSD — Atul Kumar, Maitreyee Sarkar, et al. · The Journal of Physical Chemistry A (2026) | TGRS Research Map | TGRS