Using quantum computers to simulate polyatomic reaction dynamics has an exponential advantage in the amount of resources needed over classical computers. Here we demonstrate an exact simulation of the dynamics of the laser-driven isomerization reaction of asymmetric malondialdehydes. We discretize space and time, decompose the Hamiltonian operator according to the number of qubits and use Walsh-series approximation to implement the quantum circuit for diagonal operators. We observe that the reaction evolves by means of a tunneling mechanism through a potential barrier and the final state is in close agreement with theoretical predictions. All quantum circuits are implemented through IBM's QISKit platform in an ideal quantum simulator.
Using quantum computers to simulate polyatomic reaction dynamics has an exponential advantage in the amount of resources needed over classical computers. Here we demonstrate an exact simulation of the dynamics of the laser-driven isomerization reaction of asymmetric malondialdehydes. We discretize space and time, decompose the Hamiltonian operator according to the number of qubits and use Walsh-series approximation to implement the quantum circuit for diagonal operators. We observe that the reaction evolves by means of a tunneling mechanism through a potential barrier and the final state is in close agreement with theoretical predictions. All quantum circuits are implemented through IBM's QISKit platform in an ideal quantum simulator.
Quantum simulation can beat current classical computers with minimally a few tens of qubits. Here we report an experimental demonstration that a small nuclear-magnetic-resonance quantum simulator is already able to simulate the dynamics of a prototype laser-driven isomerization reaction using engineered quantum control pulses. The experimental results agree well with classical simulations. We conclude that the quantum simulation of chemical reaction dynamics not computable on current classical computers is feasible in the near future.
This paper explores the potential of quantum computing for simulating complex chemical reactions. Traditional classical computational methods often struggle with the inherent quantum mechanical nature of chemical systems, particularly when dealing with large molecules and intricate reaction pathways. This work proposes a novel quantum algorithm leveraging superposition and entanglement to directly simulate the time evolution of these systems. The core of the algorithm centers on a time-dependent Schrödinger equation (TDSE) implemented on a quantum computer. We outline the key elements, including the encoding of molecular states, the construction of a suitable Hamiltonian operator, and the execution of the quantum algorithm to obtain the final state of the system. The efficiency gains compared to classical methods, particularly for reactions involving significant quantum effects, are discussed. Furthermore, we highlight the potential impact of this technology on accelerating drug discovery, materials science, and fundamental chemical research. The algorithm's core relies on the ability of a quantum computer to perform a vast number of calculations simultaneously, offering a substantial advantage over classical computers when simulating quantum systems.
The computational cost of exact methods for quantum simulation using classical computers grows exponentially with system size. As a consequence, these techniques can be applied only to small systems. By contrast, we demonstrate that quantum computers could exactly simulate chemical reactions in polynomial time. Our algorithm uses the split-operator approach and explicitly simulates all electron-nuclear and interelectronic interactions in quadratic time. Surprisingly, this treatment is not only more accurate than the Born-Oppenheimer approximation but faster and more efficient as well, for all reactions with more than about four atoms. This is the case even though the entire electronic wave function is propagated on a grid with appropriately short time steps. Although the preparation and measurement of arbitrary states on a quantum computer is inefficient, here we demonstrate how to prepare states of chemical interest efficiently. We also show how to efficiently obtain chemically relevant observables, such as state-to-state transition probabilities and thermal reaction rates. Quantum computers using these techniques could outperform current classical computers with 100 qubits.
Simulations of chemical dynamics are a powerful means for understanding chemistry. However, classical computers struggle to simulate many chemical processes, especially non-adiabatic ones, where the Born-Oppenheimer approximation breaks down. Quantum computers could simulate quantum-chemical dynamics more efficiently than classical computers, but there is currently no complete quantum algorithm for calculating dynamical observables to within a known error. Here, we develop an efficient, end-to-end quantum algorithm for simulating chemical dynamics that avoids all uncontrolled approximations (including the Born-Oppenheimer approximation) and whose error is bounded subject to mild assumptions. To do so, we treat the nuclei and the electrons on an equal footing and simulate the full molecular wavefunction on a momentum-space grid in first quantization, including all algorithmic steps: initial-state preparation, time evolution using qubitization, and measurement of chemical observables such as reaction yields and rates. Our work gives the first algorithm for quantum simulation of chemistry whose end-to-end complexity achieves sublinear scaling in the size of the grid. We achieve this by developing an exponentially faster method for initial-state-preparation. Photochemistry is a likely early application of our algorithm and we estimate resources required for end-to-end simulations of non-adiabatic dynamics of atmospherically important molecules. Classically intractable photochemical computations could be performed using resources comparable to those required for other chemical applications of quantum computing.
The simulation of chemical reactions is an anticipated application of quantum computers. Using a Diels-Alder reaction as a test case, in this study we explore the potential applications of quantum algorithms and hardware in investigating chemical reactions. Our specific goal is to calculate the activation barrier of a reaction between ethylene and cyclopentadiene forming a transition state. To achieve this goal, we use quantum algorithms for near-term quantum hardware (entanglement forging and quantum subspace expansion) and classical post-processing (many-body perturbation theory) in concert. We conduct simulations on IBM quantum hardware using up to 8 qubits, and compute accurate activation barrier in the reaction between cyclopentadiene and ethylene by accounting for both static and dynamic electronic correlation. This work illustrates a hybrid quantum-classical computational workflow to study chemical reactions on near-term quantum devices, showcasing the potential for performing quantum chemistry simulations on quantum hardware to predict activation barriers in agreement with those predicted by CASCI.
Accurately simulating molecular dynamics during chemical reactions remains a central challenge in computational chemistry. These processes are inherently quantum mechanical, involving coupled electronic and nuclear motion and non-adiabatic effects. A fully quantum description is therefore required, yet the associated computational cost grows exponentially with system size. Even with modern supercomputers, storing and evolving a molecular wavefunction rapidly becomes intractable, limiting exact simulations of chemical dynamics. Quantum simulation offers a promising alternative by using controllable quantum systems to directly reproduce molecular dynamics. However, fully digital, qubit-based approaches remain impractical for chemistry due to limited qubit numbers, coherence times, and gate fidelities. This motivates the exploration of more resource-efficient quantum architectures. In this thesis, we demonstrate that mixed-qudit-boson (MQB) quantum simulators provide a practical platform for simulating chemical dynamics in the quantum regime. In MQB devices, multilevel qudits encode electronic states while bosonic modes natively represent vibrational degrees of freedom, avoiding costly qubit encodings of nuclear motion and substantially reducing resource requirements. The thesis makes three main contributions. First, it reports the direct observation of geometric-phase interference in non-adiabatic dynamics using an MQB simulation of the Jahn–Teller model. Second, it extends the MQB framework to open-system chemical dynamics through programmable Lindblad dissipation. Third, it presents a resource analysis showing that MQB simulators can reduce resource costs by several orders of magnitude relative to qubit-only approaches. Together, these results establish MQB quantum simulators as a promising route for studying chemical dynamics beyond the reach of classical computation.