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  3. Modeling Stochastic Chemical Kinetics On Quantum Computers.
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  3. Modeling Stochastic Chemical Kinetics On Quantum Computers.

Related Experiment Video

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
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Published on: April 12, 2019

Modeling stochastic chemical kinetics on quantum computers.

Tilas Kabengele1,2, Yash M Lokare3, J B Marston3,4

  • 1Department of Chemistry, Brown University, Providence, Rhode Island 02912, USA.

The Journal of Chemical Physics
|May 20, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Quantum computing offers a powerful approach to modeling complex chemical kinetics using the Chemical Master Equation (CME). This study demonstrates its potential for simulating stochastic reaction networks, like the Schlögl model, on near-term quantum devices.

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Area of Science:

  • Quantum computing
  • Computational chemistry
  • Chemical kinetics

Background:

  • The Chemical Master Equation (CME) accurately models stochastic chemical kinetics but is computationally intensive due to exponential state scaling.
  • Simulating complex reaction networks requires significant computational resources, limiting classical approaches.

Purpose of the Study:

  • To investigate the application of quantum computing for modeling stochastic chemical kinetics described by the CME.
  • To utilize the Schlögl model as an example to analyze quantum computational approaches.

Main Methods:

  • Analysis of mono- and bistable regimes of the Schlögl model, identifying the bistable regime's suitability for quantum computation.
  • Employment of the Variational Quantum Deflation (VQD) algorithm to compute eigenvalues.
  • Utilizing VQD, Quantum Phase Estimation (QPE), and Variational Quantum Singular Value Decomposition (VQSVD) to estimate the non-equilibrium steady state (zeromode).

    • Main Results:

    • Quantum simulations and hardware results for eigenvalues and zeromodes agree within a few percent with classical computations for up to 4-qubit operators.
    • The bistable regime of the Schlögl model is identified as more amenable to quantum computation.
    • A minimum of 5 qubits is shown to be required for an exact solution, achievable with near-term quantum computers.

    Conclusions:

    • Quantum computing, particularly with algorithms like VQD, QPE, and VQSVD, shows promise for simulating stochastic chemical kinetics.
    • Near-term quantum devices are capable of providing accurate estimations for chemical kinetics problems.
    • Further development towards 5-qubit systems will enable exact solutions for such problems.