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arXiv:2609.19484

Scalable Simulation of Quantum Dynamics on Topological Quantum Hardware

Kritanjan Polley, Mark E. Tuckerman

quant-phSubmitted Sep 16, 2026• Announced Sep 18, 2026• 0 citations• Revised Sep 29, 2026 (v2)
v1 · Sep 16, 2026v2 · Sep 29, 2026
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Abstract

Quantum computers offer a significant advantage in simulating quantum systems compared to classical computers for certain problems, although most current applications are limited to calculating static molecular properties using hybrid quantum-classical hardware. In this work, we establish a framework for the representation of quantum dynamics in molecular and condensed matter systems, designed for execution on topological quantum hardware. By leveraging the non-Abelian braiding statistics of Fibonacci and Ising anyons, we utilize the Solovay-Kitaev algorithm to approximate unitary propagators for a range of systems. We demonstrate the efficacy of these algorithms across a hierarchy of complexity, from two-level systems and one dimensional double-well potentials to condensed phase spin-boson models, simple molecules, and molecular reaction kinetics. These algorithms provide a scalable and robust pathway for simulating many-body condensed phase chemical physics on fault-tolerant quantum devices.

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22 pages, 8 figures

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Quantum computers offer a significant advantage in simulating quantum systems compared to classical computers for certain problems, although most current applications are limited to calculating static molecular properties using hybrid quantum-classical hardware. In this work, we establish a framework for the representation of quantum dynamics in molecular and condensed matter systems, designed for execution on topological quantum hardware. By leveraging the non-Abelian braiding statistics of Fibonacci and Ising anyons, we utilize the Solovay-Kitaev algorithm to approximate unitary propagators for a range of systems. We demonstrate the efficacy of these algorithms across a hierarchy of complexity, from two-level systems and one dimensional double-well potentials to condensed phase spin-boson models, simple molecules, and molecular reaction kinetics. These algorithms provide a scalable and robust pathway for simulating many-body condensed phase chemical physics on fault-tolerant quantum devices.
Abstract Topological quantum computers promise a fault tolerant means to perform quantum computation. Topological quantum computers use particles with exotic exchange statistics called non-Abelian anyons, and the simplest anyon model which allows for universal quantum computation by particle exchange or braiding alone is the Fibonacci anyon model. One classically hard problem that can be solved efficiently using quantum computation is finding the value of the Jones polynomial of knots at roots of unity. We aim to provide a pedagogical, self-contained, review of topological quantum computation with Fibonacci anyons, from the braiding statistics and matrices to the layout of such a computer and the compiling of braids to perform specific operations. Then we use a simulation of a topological quantum computer to explicitly demonstrate a quantum computation using Fibonacci anyons, evaluating the Jones polynomial of a selection of simple knots. In addition to simulating a modular circuit-style quantum algorithm, we also show how the magnitude of the Jones polynomial at specific points could be obtained exactly using Fibonacci or Ising anyons. Such an exact algorithm seems ideally suited for a proof of concept demonstration of a topological quantum computer.
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Modeling chemical dynamics is essential for understanding, predicting, and optimizing chemical processes. Because realistic chemical systems involve many interacting degrees of freedom, direct propagation of the many-body Schr"{o}dinger equation is intractable for all but the smallest systems. Quantum information platforms offer a fundamentally different representation: a ddd-dimensional state may be encoded using k=log2(d)k=log_2(d)k=log2​(d) qubits rather than storing each amplitude independently. To harness this advantage for chemistry, it is necessary to develop quantum algorithms and hardware architectures capable of simulating the open-system dynamics ubiquitous in condensed-phase and molecular environments. In the first chapter, we develop a theoretical framework for simulating a cavity-modified photoinduced charge-transfer reaction in the carotenoid–porphyrin–C60_{60}60​ (CPC60_{60}60​) molecular triad dissolved in tetrahydrofuran (THF). Nonequilibrium Fermi’s Golden Rule (NE-FGR) rate coefficients are obtained as a product of cavity-free and cavity-modified correlation functions. We further introduce an approximation based on Instantaneous Marcus Theory (IMT) that closely tracks the full NE-FGR result across all relevant time scales. Population transfer rates computed from the population-only off-diagonal quantum master equation (p-tcl-OD-QME) are shown to be consistent with the NE-FGR predictions. Our results demonstrate that nonequilibrium charge-transfer dynamics are significantly modified by coupling to an optical cavity. The second chapter addresses the integration of linear nonautonomous ordinary differential equations on digital quantum hardware. Rather than classically constructing a nonunitary propagator at each time step and embedding it into a larger unitary operation for execution on quantum hardware, we eliminate this classical–quantum partitioning. We derive and propagate differential equations for the singular value decomposition (SVD) factors of the propagator directly, enabling time evolution to be implemented within a quantum-compatible framework. This approach shifts the locus of time integration from the classical processor to the quantum device. In the third chapter, we investigate the feasibility of simulating chemical reaction dynamics on a parametrically driven bosonic superconducting Kerr-cat device. This analog platform enables direct control over parameters defining an effective double-well free-energy landscape, as well as over environmental factors such as temperature and system–bath coupling strength. We demonstrate that proton transfer dynamics in prototypical benchmark systems, including hydrogen-bonded dimers of malonaldehyde and DNA base pairs, can be accurately reproduced using experimentally accessible Kerr-cat architectures.
Topological quantum computers promise a fault tolerant means to perform quantum computation. Topological quantum computers use particles with exotic exchange statistics called non-Abelian anyons, and the simplest anyon model which allows for universal quantum computation by particle exchange or braiding alone is the Fibonacci anyon model. One classically hard problem that can be solved efficiently using quantum computation is finding the value of the Jones polynomial of knots at roots of unity. We aim to provide a pedagogical, self-contained, review of topological quantum computation with Fibonacci anyons, from the braiding statistics and matrices to the layout of such a computer and the compiling of braids to perform specific operations. Then we use a simulation of a topological quantum computer to explicitly demonstrate a quantum computation using Fibonacci anyons, evaluating the Jones polynomial of a selection of simple knots.
Hybrid quantum-classical algorithms have begun to leverage quantum devices to efficiently represent many-electron wavefunctions, enabling early demonstrations of molecular simulations on real hardware. A key prerequisite for scalable quantum chemistry, however, is size consistency: the energy of non-interacting subsystems must scale linearly with system size. While many algorithms are theoretically size-consistent, noise on quantum devices may couple nominally independent subsystems and degrade this fundamental property. Here, we systematically evaluate size consistency on quantum hardware by simulating systems composed of increasing numbers of non-interacting H2_{2}2​ molecules using optimally shallow unitary circuits. We find that molecular energies remain size-consistent within chemical accuracy for an estimated 118 and 71 H2_{2}2​ subsystems for one- and two-qubit unitary designs, respectively, demonstrating that current quantum devices preserve size consistency over chemically relevant system sizes and supporting the feasibility of scalable, noise-resilient simulation of strongly correlated molecules and materials.
A central problem in realizing universal quantum computers is dealing with decoherence effects, which can destroy the vulnerable quantum states present in the internal registers. Several schemes have been developed that provide resistance to decoherence, leading to theories of fault-tolerant quantum computation. One such scheme is the theory of topological quantum computation, which encodes qubit states in robust topological properties of certain quantum systems. However, fault-tolerant theories typically only provide a finite set of primitive gates, from which we must then form approximations to arbitrary quantum gates. The Solovay-Kitaev algorithm describes a procedure for accomplishing this, and proves that the number of primitive gates required to approximate an arbitrary gate is only polylogarithmic in the desired degree of accuracy. In this thesis, we first outline the basic theory of quantum computation. Secondly, we describe the general problem of quantum compilation, list several possible strategies for relevant optimizations, and outline a proof of the Solovay-Kitaev theorem. Next, we give an introduction to the theory of topological quantum computation by anyons, with special focus on Fibonacci-anyons. Finally, we list some numerical results of an implementation of the Solovay-Kitaev algorithm when applied to a Fibonacci-anyon model and analyze the performance gains obtained through applications of the proposed optimizations.