Measurements as a roadblock to near-term practical quantum advantage in
chemistry: resource analysis
- URL: http://arxiv.org/abs/2012.04001v2
- Date: Fri, 26 Aug 2022 19:34:56 GMT
- Title: Measurements as a roadblock to near-term practical quantum advantage in
chemistry: resource analysis
- Authors: J\'er\^ome F. Gonthier, Maxwell D. Radin, Corneliu Buda, Eric J.
Doskocil, Clena M. Abuan, Jhonathan Romero
- Abstract summary: We estimate the number of qubits and number of measurements required to compute the combustion energies of small organic molecules.
We consider several key modern improvements to VQE, including low-rank factorizations of the Hamiltonian.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Recent advances in quantum computing devices have brought attention to hybrid
quantum-classical algorithms like the Variational Quantum Eigensolver (VQE) as
a potential route to practical quantum advantage in chemistry. However, it is
not yet clear whether such algorithms, even in the absence of device error,
could actually achieve quantum advantage for systems of practical interest. We
have performed an exhaustive analysis to estimate the number of qubits and
number of measurements required to compute the combustion energies of small
organic molecules and related systems to within chemical accuracy of
experimental values using VQE. We consider several key modern improvements to
VQE, including low-rank factorizations of the Hamiltonian. Our results indicate
that although these techniques are useful, they will not be sufficient to
achieve practical quantum computational advantage for our molecular set, or for
similar molecules. This suggests that novel approaches to operator estimation
leveraging quantum coherence, such as Enhanced Likelihood Functions
[arxiv:2006.09350, arxiv:2006.09349], may be required.
Related papers
- Benchmarking Variational Quantum Eigensolvers for Entanglement Detection in Many-Body Hamiltonian Ground States [37.69303106863453]
Variational quantum algorithms (VQAs) have emerged in recent years as a promise to obtain quantum advantage.
We use a specific class of VQA named variational quantum eigensolvers (VQEs) to benchmark them at entanglement witnessing and entangled ground state detection.
Quantum circuits whose structure is inspired by the Hamiltonian interactions presented better results on cost function estimation than problem-agnostic circuits.
arXiv Detail & Related papers (2024-07-05T12:06:40Z) - Non-unitary Coupled Cluster Enabled by Mid-circuit Measurements on Quantum Computers [37.69303106863453]
We propose a state preparation method based on coupled cluster (CC) theory, which is a pillar of quantum chemistry on classical computers.
Our approach leads to a reduction of the classical computation overhead, and the number of CNOT and T gates by 28% and 57% on average.
arXiv Detail & Related papers (2024-06-17T14:10:10Z) - 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) - Quantum Embedding Method for the Simulation of Strongly Correlated
Systems on Quantum Computers [0.0]
We introduce the projection-based embedding method for combining the variational quantum eigensolver (VQE) algorithm with density functional theory (DFT)
The developed VQE-in-DFT method is then implemented efficiently on a real quantum device and employed for simulating the triple bond breaking process in butyronitrile.
The developments will benefit many different chemical areas including the computer aided drug design as well as the study of metalloenzymes with a strongly correlated fragment.
arXiv Detail & Related papers (2023-02-06T19:00:03Z) - Potential energy surfaces inference of both ground and excited state
using hybrid quantum-classical neural network [0.0]
A hybrid quantum-classical neural network has been proposed for surrogate modeling of the variational quantum eigensolver.
We extend the model by using the subspace-search variational quantum eigensolver procedure so that the PESs of the both ground and excited state can be inferred with chemical accuracy.
arXiv Detail & Related papers (2022-12-06T14:28:44Z) - A perspective on the current state-of-the-art of quantum computing for
drug discovery applications [43.55994393060723]
Quantum computing promises to shift the computational capabilities in many areas of chemical research by bringing into reach currently impossible calculations.
We briefly summarize and compare the scaling properties of state-of-the-art quantum algorithms.
We provide novel estimates of the quantum computational cost of simulating progressively larger embedding regions of a pharmaceutically relevant covalent protein-drug complex.
arXiv Detail & Related papers (2022-06-01T15:05:04Z) - Toward Practical Quantum Embedding Simulation of Realistic Chemical
Systems on Near-term Quantum Computers [10.26362298019201]
We numerically test the method for the hydrogenation reaction of C6H8 and the equilibrium geometry of the C18 molecule, with basis sets up to cc-pVDZ.
Our work implies the possibility of solving industrial chemical problems on near-term quantum devices.
arXiv Detail & Related papers (2021-09-16T15:44:38Z) - Efficient criteria of quantumness for a large system of qubits [58.720142291102135]
We discuss the dimensionless combinations of basic parameters of large, partially quantum coherent systems.
Based on analytical and numerical calculations, we suggest one such number for a system of qubits undergoing adiabatic evolution.
arXiv Detail & Related papers (2021-08-30T23:50:05Z) - On exploring practical potentials of quantum auto-encoder with
advantages [92.19792304214303]
Quantum auto-encoder (QAE) is a powerful tool to relieve the curse of dimensionality encountered in quantum physics.
We prove that QAE can be used to efficiently calculate the eigenvalues and prepare the corresponding eigenvectors of a high-dimensional quantum state.
We devise three effective QAE-based learning protocols to solve the low-rank state fidelity estimation, the quantum Gibbs state preparation, and the quantum metrology tasks.
arXiv Detail & Related papers (2021-06-29T14:01:40Z) - Simulating quantum chemistry in the seniority-zero space on qubit-based
quantum computers [0.0]
We combine the so-called seniority-zero, or paired-electron, approximation of computational quantum chemistry with techniques for simulating molecular chemistry on gate-based quantum computers.
We show that using the freed-up quantum resources for increasing the basis set can lead to more accurate results and reductions in the necessary number of quantum computing runs.
arXiv Detail & Related papers (2020-01-31T19:44:37Z)
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.