Truncated Variational Hamiltonian Ansatz: efficient quantum circuit design for quantum chemistry and material science
- URL: http://arxiv.org/abs/2505.19772v1
- Date: Mon, 26 May 2025 09:54:46 GMT
- Title: Truncated Variational Hamiltonian Ansatz: efficient quantum circuit design for quantum chemistry and material science
- Authors: Clemens Possel, Walter Hahn, Reza Shirazi, Marina Walt, Peter Pinski, Frank K. Wilhelm, Dmitry Bagrets,
- Abstract summary: This paper introduces the truncated Variational Hamiltonian Ansatz (tVHA), a novel circuit design for conducting quantum calculations on Noisy Intermediate-Scale Quantum (NISQ) devices.<n>Our proposed ansatz significantly reduces the parameter count and can decrease circuit size substantially, with a trade-off in accuracy.<n>While this paper concentrates on the practical applications of tVHA in quantum chemistry, its underlying principles suggest a wider applicability extending to the broader field of material science computations on quantum computing platforms.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Quantum computing has the potential to revolutionize quantum chemistry and material science by offering solutions to complex problems unattainable with classical computers. However, the development of efficient quantum algorithms that are efficient under noisy conditions remains a major challenge. This paper introduces the truncated Variational Hamiltonian Ansatz (tVHA), a novel circuit design for conducting quantum calculations on Noisy Intermediate-Scale Quantum (NISQ) devices. tVHA provides a promising approach for a broad range of applications by utilizing principles from the adiabatic theorem in solid state physics. Our proposed ansatz significantly reduces the parameter count and can decrease circuit size substantially, with a trade-off in accuracy. Thus, tVHA facilitates easier convergence within the variational quantum eigensolver framework compared to state-of-the-art ans\"atze such as Unitary Coupled Cluster (UCC) and Hardware-Efficient Ansatz (HEA). While this paper concentrates on the practical applications of tVHA in quantum chemistry, demonstrating its suitability for both weakly and strongly correlated systems and its compatibility with active space calculations, its underlying principles suggest a wider applicability extending to the broader field of material science computations on quantum computing platforms.
Related papers
- Coupled Cluster Downfolding Theory in Simulations of Chemical Systems on Quantum Hardware [9.389379035303165]
We show how classical resources are used to construct effective Hamiltonians characterized by dimensions that conform to the constraints of current quantum devices.<n>We argue that such flexible hybrid algorithms, where problem size can be tailored to available quantum resources, can serve as a bridge between noisy intermediate-scale quantum (QNIS) devices and future fault-tolerant quantum computers.
arXiv Detail & Related papers (2025-07-01T21:34:29Z) - VQC-MLPNet: An Unconventional Hybrid Quantum-Classical Architecture for Scalable and Robust Quantum Machine Learning [60.996803677584424]
Variational Quantum Circuits (VQCs) offer a novel pathway for quantum machine learning.<n>Their practical application is hindered by inherent limitations such as constrained linear expressivity, optimization challenges, and acute sensitivity to quantum hardware noise.<n>This work introduces VQC-MLPNet, a scalable and robust hybrid quantum-classical architecture designed to overcome these obstacles.
arXiv Detail & Related papers (2025-06-12T01:38:15Z) - Provably Robust Training of Quantum Circuit Classifiers Against Parameter Noise [49.97673761305336]
Noise remains a major obstacle to achieving reliable quantum algorithms.<n>We present a provably noise-resilient training theory and algorithm to enhance the robustness of parameterized quantum circuit classifiers.
arXiv Detail & Related papers (2025-05-24T02:51:34Z) - An Introduction to Variational Quantum Eigensolver Applied to Chemistry [0.0]
Variational Quantum Algorithms (VQAs) stand out as a feasible approach to demonstrating advantages over classical methods in the near term.<n>We present the application of quantum mechanics to the study of molecules, provide an introduction to the fundamentals of quantum computing, and explore the integration of these fields by employing the VQE in molecular simulations.
arXiv Detail & Related papers (2025-05-07T19:46:15Z) - HIVQE: Handover Iterative Variational Quantum Eigensolver for Efficient Quantum Chemistry Calculations [0.18574358541506214]
The Handover Iterative Variational Quantum Eigensolver (HiVQE) is designed to accurately estimate ground-state wavefunctions.<n>By generating compact yet chemically accurate wavefunctions, HiVQE advances quantum chemistry simulations and facilitates the discovery of novel materials.
arXiv Detail & Related papers (2025-03-08T17:50:56Z) - State-Averaged Orbital-Optimized VQE: A quantum algorithm for the
democratic description of ground and excited electronic states [0.0]
The SA-OO-VQE package aims to answer both problems with its hybrid quantum-classical conception based on a typical Variational Quantum Eigensolver approach.
The SA-OO-VQE has the ability to treat degenerate (or quasi-degenerate) states on the same footing, thus avoiding known numerical optimization problems around avoided crossings or conical intersections.
arXiv Detail & Related papers (2024-01-22T12:16:37Z) - Quantum Annealing for Single Image Super-Resolution [86.69338893753886]
We propose a quantum computing-based algorithm to solve the single image super-resolution (SISR) problem.
The proposed AQC-based algorithm is demonstrated to achieve improved speed-up over a classical analog while maintaining comparable SISR accuracy.
arXiv Detail & Related papers (2023-04-18T11:57:15Z) - Synergy Between Quantum Circuits and Tensor Networks: Short-cutting the
Race to Practical Quantum Advantage [43.3054117987806]
We introduce a scalable procedure for harnessing classical computing resources to provide pre-optimized initializations for quantum circuits.
We show this method significantly improves the trainability and performance of PQCs on a variety of problems.
By demonstrating a means of boosting limited quantum resources using classical computers, our approach illustrates the promise of this synergy between quantum and quantum-inspired models in quantum computing.
arXiv Detail & Related papers (2022-08-29T15:24:03Z) - 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) - On exploring the potential of quantum auto-encoder for learning quantum systems [60.909817434753315]
We devise three effective QAE-based learning protocols to address three classically computational hard learning problems.
Our work sheds new light on developing advanced quantum learning algorithms to accomplish hard quantum physics and quantum information processing tasks.
arXiv Detail & Related papers (2021-06-29T14:01:40Z) - Quantum circuit architecture search for variational quantum algorithms [88.71725630554758]
We propose a resource and runtime efficient scheme termed quantum architecture search (QAS)
QAS automatically seeks a near-optimal ansatz to balance benefits and side-effects brought by adding more noisy quantum gates.
We implement QAS on both the numerical simulator and real quantum hardware, via the IBM cloud, to accomplish data classification and quantum chemistry tasks.
arXiv Detail & Related papers (2020-10-20T12:06:27Z) - Electronic structure with direct diagonalization on a D-Wave quantum
annealer [62.997667081978825]
This work implements the general Quantum Annealer Eigensolver (QAE) algorithm to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer.
We demonstrate the use of D-Wave hardware for obtaining ground and electronically excited states across a variety of small molecular systems.
arXiv Detail & Related papers (2020-09-02T22:46:47Z)
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.