Recent quantum algorithms pertaining to electronic structure theory primarily focus on the threshold-based dynamic construction of ansatz by selectively including important many-body operators. These methods can be made systematically more accurate by tuning the threshold to include a greater number of operators into the ansatz. However, such improvements come at the cost of rapid proliferation of the circuit depth, especially for highly correlated molecular systems. In this work, we address this issue by the development of a novel theoretical framework that relies on the segregation of an ansatz into a dynamically selected core "principal" component, which is, by construction, adiabatically decoupled from the remaining operators. This enables us to perform computations involving the principal component using extremely shallow-depth circuits, whereas the effect of the remaining "auxiliary" component is folded into the energy function via a cost-efficient non-iterative correction, ensuring the requisite accuracy. We propose a formalism that analytically predicts the auxiliary parameters from the principal ones, followed by a suite of non-iterative auxiliary subspace correction techniques with different levels of sophistication. The auxiliary subspace corrections incur no additional quantum resources yet complement an inadequately expressive core of the ansatz to recover a significant amount of electronic correlations. We have numerically validated the resource efficiency and accuracy of our formalism with a number of strongly correlated molecular systems.

Download full-text PDF

Source
http://dx.doi.org/10.1063/5.0229137DOI Listing

Publication Analysis

Top Keywords

auxiliary subspace
12
non-iterative auxiliary
8
subspace corrections
8
correlated molecular
8
molecular systems
8
resource-optimized dynamic
4
dynamic quantum
4
quantum algorithm
4
algorithm non-iterative
4
auxiliary
4

Similar Publications

In this paper, a direction of arrival (DOA) estimation algorithm for non-circular signal by a large-spacing uniform array with an auxiliary element has been presented. The auxiliary element is placed away from the last element of the large-spacing uniform array. The spacing between arbitrary two elements of the whole array is not limited by the half-wavelength of the signal.

View Article and Find Full Text PDF

Robust and flexible learning of a high-dimensional classification rule using auxiliary outcomes.

Biometrics

October 2024

Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL 32611, United States.

Correlated outcomes are common in many practical problems. In some settings, one outcome is of particular interest, and others are auxiliary. To leverage information shared by all the outcomes, traditional multi-task learning (MTL) minimizes an averaged loss function over all the outcomes, which may lead to biased estimation for the target outcome, especially when the MTL model is misspecified.

View Article and Find Full Text PDF

Biobased substitutes for plastics are a future necessity. However, the design of substitute materials with similar or improved properties is a known challenge. Here we show an example case of optimizing the mechanical properties of a fully biobased methylcellulose-fiber composite material.

View Article and Find Full Text PDF

Recent quantum algorithms pertaining to electronic structure theory primarily focus on the threshold-based dynamic construction of ansatz by selectively including important many-body operators. These methods can be made systematically more accurate by tuning the threshold to include a greater number of operators into the ansatz. However, such improvements come at the cost of rapid proliferation of the circuit depth, especially for highly correlated molecular systems.

View Article and Find Full Text PDF

Structure of Multi-State Correlation in Electronic Systems.

J Chem Theory Comput

October 2024

Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China.

Beyond the Hohenberg-Kohn density functional theory for the ground state, it has been established that the Hamiltonian matrix for a finite number () of lowest eigenstates is a matrix density functional. Its fundamental variable─the matrix density ()─can be represented by, or mapped to, a set of auxiliary, multiconfigurational wave functions expressed as a linear combination of no more than determinant configurations. The latter defines a minimal active space (MAS), which naturally leads to the introduction of the correlation matrix functional, responsible for the electronic correlation effects outside the MAS.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!