A Digital Quantum Algorithm for Non-Markovian Electron Transfer Dynamics Using Repeated Interactions
- URL: http://arxiv.org/abs/2502.18426v1
- Date: Tue, 25 Feb 2025 18:21:03 GMT
- Title: A Digital Quantum Algorithm for Non-Markovian Electron Transfer Dynamics Using Repeated Interactions
- Authors: Lea K. Northcote, Matthew S. Teynor, Gemma C. Solomon,
- Abstract summary: Quantum algorithms have the potential to revolutionize our understanding of open quantum systems in chemistry.<n>We demonstrate that quantum algorithms leveraging a repeated interaction model can effectively reproduce non-Markovian electron transfer processes.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Quantum algorithms have the potential to revolutionize our understanding of open quantum systems in chemistry. In this work, we demonstrate that quantum algorithms leveraging a repeated interaction model can effectively reproduce non-Markovian electron transfer processes under four different donor-acceptor parameter regimes and for a donor-bridge-acceptor system. We systematically explore how the algorithm scales for the regimes. Notably, our approach exhibits favorable scaling in the required repeated interaction length as the electronic coupling, temperature, damping rate, and system size increase. Furthermore, a single Trotter step per repeated interaction leads to an acceptably small error, and high-fidelity initial states can be prepared with a short time evolution. This efficiency highlights the potential of the algorithm for tackling increasingly complex systems. When fault-tolerant quantum hardware becomes available, the method could be extended to incorporate structured baths, additional energy levels, or more intricate coupling schemes, enabling the simulation of real-world open quantum systems that remain beyond the reach of classical computation.
Related papers
- Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [63.733312560668274]
Given a quantum circuit containing d tunable RZ gates and G-d Clifford gates, can a learner perform purely classical inference to efficiently predict its linear properties?
We prove that the sample complexity scaling linearly in d is necessary and sufficient to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d.
We devise a kernel-based learning model capable of trading off prediction error and computational complexity, transitioning from exponential to scaling in many practical settings.
arXiv Detail & Related papers (2024-08-22T08:21:28Z) - Solving reaction dynamics with quantum computing algorithms [42.408991654684876]
We study quantum algorithms for response functions, relevant for describing different reactions governed by linear response.<n>We focus on nuclear-physics applications and consider a qubit-efficient mapping on the lattice, which can efficiently represent the large volumes required for realistic scattering simulations.
arXiv Detail & Related papers (2024-03-30T00:21:46Z) - Overhead-constrained circuit knitting for variational quantum dynamics [0.0]
We use circuit knitting to partition a large quantum system into smaller subsystems that can each be simulated on a separate device.
We show that the same method can be used to reduce the circuit depth by cutting long-ranged gates.
arXiv Detail & Related papers (2023-09-14T17:01:06Z) - On-the-fly Tailoring towards a Rational Ansatz Design for Digital
Quantum Simulations [0.0]
It is imperative to develop low depth quantum circuits that are physically realizable in quantum devices.
We develop a disentangled ansatz construction protocol that can dynamically tailor an optimal ansatz.
The construction of the ansatz may potentially be performed in parallel quantum architecture through energy sorting and operator commutativity prescreening.
arXiv Detail & Related papers (2023-02-07T11:22:01Z) - Optimal quantum control via genetic algorithms for quantum state
engineering in driven-resonator mediated networks [68.8204255655161]
We employ a machine learning-enabled approach to quantum state engineering based on evolutionary algorithms.
We consider a network of qubits -- encoded in the states of artificial atoms with no direct coupling -- interacting via a common single-mode driven microwave resonator.
We observe high quantum fidelities and resilience to noise, despite the algorithm being trained in the ideal noise-free setting.
arXiv Detail & Related papers (2022-06-29T14:34:00Z) - Digital quantum simulation of non-perturbative dynamics of open systems
with orthogonal polynomials [0.0]
We propose the use of the Time Evolving Density operator with Orthogonal Polynomials Algorithm (TEDOPA) on a quantum computer.
We show that exponential scalings of computational resources can potentially be avoided for time-evolution simulations of the systems considered in this work.
arXiv Detail & Related papers (2022-03-28T11:16:33Z) - Quantum algorithms for quantum dynamics: A performance study on the
spin-boson model [68.8204255655161]
Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotter-approximation of the time-evolution operator.
variational quantum algorithms have become an indispensable alternative, enabling small-scale simulations on present-day hardware.
We show that, despite providing a clear reduction of quantum gate cost, the variational method in its current implementation is unlikely to lead to a quantum advantage.
arXiv Detail & Related papers (2021-08-09T18:00:05Z) - Efficient Quantum Simulation of Open Quantum System Dynamics on Noisy
Quantum Computers [0.0]
We show that quantum dissipative dynamics can be simulated efficiently across coherent-to-incoherent regimes.
This work provides a new direction for quantum advantage in the NISQ era.
arXiv Detail & Related papers (2021-06-24T10:37:37Z) - Quantum Markov Chain Monte Carlo with Digital Dissipative Dynamics on
Quantum Computers [52.77024349608834]
We develop a digital quantum algorithm that simulates interaction with an environment using a small number of ancilla qubits.
We evaluate the algorithm by simulating thermal states of the transverse Ising model.
arXiv Detail & Related papers (2021-03-04T18:21:00Z) - Information Scrambling in Computationally Complex Quantum Circuits [56.22772134614514]
We experimentally investigate the dynamics of quantum scrambling on a 53-qubit quantum processor.
We show that while operator spreading is captured by an efficient classical model, operator entanglement requires exponentially scaled computational resources to simulate.
arXiv Detail & Related papers (2021-01-21T22:18:49Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.