Parallelized Givens Ansatz for Molecular ground-states: Bridging Accuracy and Efficiency on NISQ Platforms
- URL: http://arxiv.org/abs/2504.18264v1
- Date: Fri, 25 Apr 2025 11:19:21 GMT
- Title: Parallelized Givens Ansatz for Molecular ground-states: Bridging Accuracy and Efficiency on NISQ Platforms
- Authors: M. R. Nirmal, Ankit Khandelwal, Manoj Nambiar, Sharma S. R. K. C. Yamijala,
- Abstract summary: The utility of the Variational Quantum Eigensolver (VQE) is often hindered by the limitations of current quantum hardware.<n>We propose a low-depth ansatz based on parallelized Givens rotations, which can recover substantial correlation energy.<n>Noiseless simulations using the new ansatz yield ground-state energies comparable to those from the UCCSD ansatz.
- Score: 10.562278615096215
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: In recent years, the Variational Quantum Eigensolver (VQE) has emerged as one of the most popular algorithms for solving the electronic structure problem on near-term quantum computers. The utility of VQE is often hindered by the limitations of current quantum hardware, including short qubit coherence times and low gate fidelities. These limitations become particularly pronounced when VQE is used along with deep quantum circuits, such as those required by the "Unitary Coupled Cluster Singles and Doubles" (UCCSD) ansatz, often resulting in significant errors. To address these issues, we propose a low-depth ansatz based on parallelized Givens rotations, which can recover substantial correlation energy while drastically reducing circuit depth and two-qubit gate counts for an arbitrary active space (AS). Also, considering the current hardware architectures with low qubit counts, we introduce a systematic way to select molecular orbitals to define active spaces (ASs) that retain significant electron correlation. We validate our approach by computing bond dissociation profiles of water and strongly correlated systems, such as molecular nitrogen and oxygen, across various ASs. Noiseless simulations using the new ansatz yield ground-state energies comparable to those from the UCCSD ansatz while reducing circuit depth by 50-70%. Moreover, in noisy simulations, our approach achieves energy error rates an order of magnitude lower than that of UCCSD. Considering the efficiency and practical usage of our ansatz, we hope that it becomes a potential choice for performing quantum chemistry calculations on near-term quantum devices.
Related papers
- Parallel Quantum Computing Simulations via Quantum Accelerator Platform Virtualization [44.99833362998488]
We present a model for parallelizing simulation of quantum circuit executions.
The model can take advantage of its backend-agnostic features, enabling parallel quantum circuit execution over any target backend.
arXiv Detail & Related papers (2024-06-05T17:16:07Z) - Characterizing randomness in parameterized quantum circuits through expressibility and average entanglement [39.58317527488534]
Quantum Circuits (PQCs) are still not fully understood outside the scope of their principal application.<n>We analyse the generation of random states in PQCs under restrictions on the qubits connectivities.<n>We place a connection between how steep is the increase on the uniformity of the distribution of the generated states and the generation of entanglement.
arXiv Detail & Related papers (2024-05-03T17:32:55Z) - Towards Efficient Quantum Computing for Quantum Chemistry: Reducing Circuit Complexity with Transcorrelated and Adaptive Ansatz Techniques [0.0]
This work demonstrates how to reduce circuit depth by combining the transcorrelated (TC) approach with adaptive quantum ans"atze.
Our study demonstrates that combining the TC method with adaptive ans"atze yields compact, noise-resilient, and easy-to-optimize quantum circuits.
arXiv Detail & Related papers (2024-02-26T15:31:56Z) - A Quantum-Classical Collaborative Training Architecture Based on Quantum
State Fidelity [50.387179833629254]
We introduce a collaborative classical-quantum architecture called co-TenQu.
Co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting.
It outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.
arXiv Detail & Related papers (2024-02-23T14:09:41Z) - A multiple-circuit approach to quantum resource reduction with application to the quantum lattice Boltzmann method [39.671915199737846]
We introduce a multiple-circuit algorithm for a quantum lattice Boltzmann method (QLBM) solve of the incompressible Navier--Stokes equations.<n>The presented method is validated and demonstrated for 2D lid-driven cavity flow.
arXiv Detail & Related papers (2024-01-20T15:32:01Z) - QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum
Circuits [82.50620782471485]
QuantumSEA is an in-time sparse exploration for noise-adaptive quantum circuits.
It aims to achieve two key objectives: (1) implicit circuits capacity during training and (2) noise robustness.
Our method establishes state-of-the-art results with only half the number of quantum gates and 2x time saving of circuit executions.
arXiv Detail & Related papers (2024-01-10T22:33:00Z) - Resource-Efficient Quantum Circuits for Molecular Simulations: A Case
Study of Umbrella Inversion in Ammonia [1.439738350540859]
We develop a novel quantum circuit that reduces the required circuit depth and number of two-qubit entangling gates by about 60%.
Even in the presence of device noise, these novel shallower circuits yielded substantially low error rates.
arXiv Detail & Related papers (2023-12-07T11:30:09Z) - Orbital-optimized pair-correlated electron simulations on trapped-ion
quantum computers [0.471876092032107]
Variational quantum eigensolvers (VQE) are among the most promising approaches for solving electronic structure problems on quantum computers.
A critical challenge for VQE in practice is that one needs to strike a balance between the expressivity of the VQE ansatz versus the number of quantum gates required to implement the ansatz.
We run end-to-end VQE algorithms with up to 12 qubits and 72 variational parameters - the largest full VQE simulation with a correlated wave function on quantum hardware.
arXiv Detail & Related papers (2022-12-05T18:40:54Z) - Exploring the scaling limitations of the variational quantum eigensolver
with the bond dissociation of hydride diatomic molecules [0.0]
Materials simulations involving strongly correlated electrons pose fundamental challenges to state-of-the-art electronic structure methods.
No quantum computer has simulated a molecule of a size and complexity relevant to real-world applications, despite the fact that the variational quantum eigensolver algorithm can predict chemically accurate total energies.
We show that the inclusion of d-orbitals and the use of the UCCSD ansatz, which are both necessary to capture the correct TiH physics, dramatically increase the cost of this problem.
arXiv Detail & Related papers (2022-08-15T19:21:17Z) - Adiabatic Quantum Computing for Multi Object Tracking [170.8716555363907]
Multi-Object Tracking (MOT) is most often approached in the tracking-by-detection paradigm, where object detections are associated through time.
As these optimization problems are often NP-hard, they can only be solved exactly for small instances on current hardware.
We show that our approach is competitive compared with state-of-the-art optimization-based approaches, even when using of-the-shelf integer programming solvers.
arXiv Detail & Related papers (2022-02-17T18:59:20Z) - Simulating the Mott transition on a noisy digital quantum computer via
Cartan-based fast-forwarding circuits [62.73367618671969]
Dynamical mean-field theory (DMFT) maps the local Green's function of the Hubbard model to that of the Anderson impurity model.
Quantum and hybrid quantum-classical algorithms have been proposed to efficiently solve impurity models.
This work presents the first computation of the Mott phase transition using noisy digital quantum hardware.
arXiv Detail & Related papers (2021-12-10T17:32:15Z) - Variational Quantum Eigensolver with Reduced Circuit Complexity [3.1158760235626946]
We present a novel approach to reduce quantum circuit complexity in VQE for electronic structure calculations.
Our algorithm, called ClusterVQE, splits the initial qubit space into subspaces (qubit clusters) which are further distributed on individual quantum circuits.
The new algorithm simultaneously reduces the number of qubits and circuit depth, making it a potential leader for quantum chemistry simulations on NISQ devices.
arXiv Detail & Related papers (2021-06-14T17:23:46Z) - 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) - Improving the Performance of Deep Quantum Optimization Algorithms with
Continuous Gate Sets [47.00474212574662]
Variational quantum algorithms are believed to be promising for solving computationally hard problems.
In this paper, we experimentally investigate the circuit-depth-dependent performance of QAOA applied to exact-cover problem instances.
Our results demonstrate that the use of continuous gate sets may be a key component in extending the impact of near-term quantum computers.
arXiv Detail & Related papers (2020-05-11T17:20:51Z)
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.