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A Bayesian phase difference estimation (BPDE) algorithm allows us to compute the energy gap of two electronic states of a given Hamiltonian directly by utilizing the quantum superposition of their wave functions. Here we report an extension of the BPDE algorithm to the direct calculation of the energy difference of two molecular geometries. We apply the BPDE algorithm for the calculation of numerical energy gradients based on the two-point finite-difference method, enabling us to execute geometry optimization of one-dimensional molecules at the full-CI level on a quantum computer. Results of numerical quantum circuit simulations of the geometry optimization of the H molecule with the STO-3G and 6-31G basis sets, the LiH and BeH molecules at the full-CI/STO-3G level, and the N molecule at the CASCI(6e,6o)/6-311G* level are given.
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http://dx.doi.org/10.1021/acs.jpclett.2c02737 | DOI Listing |
J Phys Chem Lett
December 2022
Department of Chemistry, Graduate School of Science, Osaka Metropolitan University, 3-3-138 Sugimoto, Sumiyoshi-ku, Osaka558-8585, Japan.
A Bayesian phase difference estimation (BPDE) algorithm allows us to compute the energy gap of two electronic states of a given Hamiltonian directly by utilizing the quantum superposition of their wave functions. Here we report an extension of the BPDE algorithm to the direct calculation of the energy difference of two molecular geometries. We apply the BPDE algorithm for the calculation of numerical energy gradients based on the two-point finite-difference method, enabling us to execute geometry optimization of one-dimensional molecules at the full-CI level on a quantum computer.
View Article and Find Full Text PDFPhys Chem Chem Phys
September 2021
Department of Chemistry and Molecular Materials Science, Graduate School of Science, Osaka City University, 3-3-138 Sugimoto, Sumiyoshi-ku, Osaka 558-8585, Japan.
Quantum computers can perform full configuration interaction (full-CI) calculations by utilising the quantum phase estimation (QPE) algorithms including Bayesian phase estimation (BPE) and iterative quantum phase estimation (IQPE). In these quantum algorithms, the time evolution of wave functions for atoms and molecules is simulated conditionally with an ancillary qubit as the control, which make implementation to real quantum devices difficult. Also, most of the problems in chemistry discuss energy differences between two electronic states rather than total energies themselves, and thus direct calculations of energy gaps are promising for future applications of quantum computers to real chemistry problems.
View Article and Find Full Text PDFSci Rep
November 2016
Department of Environmental Science and Analytical Chemistry, Stockholm University, SE-10691 Stockholm, Sweden.
Carcinogenicity of benzo[a]pyrene {B[a]P, a polycyclic aromatic hydrocarbon (PAH)} involves DNA-modification by B[a]P diol epoxide (BPDE) metabolites. Adducts to serum albumin (SA) are not repaired, unlike DNA adducts, and therefore considered advantageous in assessment of in vivo dose of BPDEs. In the present work, kinetic experiments were performed in relation to the dose (i.
View Article and Find Full Text PDFMicrob Biotechnol
May 2016
Faculty of BioScience and Technology for Food, Agriculture and Environment, University of Teramo, Mosciano Sant'Angelo (TE), 64023, Italy.
Random amplified polymorphic DNA (RAPD) PCR is a feasible method to evaluate genotoxin-induced DNA damage and mutations. In this study, Lactobacillus plantarum ATCC 14917T, Enterococcus faecium DSMZ 20477T, Escherichia coli PQ37 and Saccharomyces cerevisiae S441 were screened for DNA genetic alterations by DNA fingerprinting using M13 and LA1 primers after treatment with three compounds forming covalent adducts with DNA [benzo[a]pyrenediol epoxide (BPDE), methyl methanesulfonate and 1,2,3,4-diepoxybutane (DEB)]. M13 RAPD fingerprinting revealed that the total number of bands decreased in all treated DNA compared to control samples and generally the lost bands were characterized by high molecular weight.
View Article and Find Full Text PDFEnviron Toxicol
February 2011
Department of Epidemiology and Health Statistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, People's Republic of China.
Coke-oven workers are exposed to many kinds of pollutants that can cause health damage even lead to carcinogenesis. Therefore, it is critical to identify biomarkers that predict early health damage in these exposed individuals in molecular epidemiological studies. We applied an artificial neural network (ANN) model to the identification of such predictors in a study of coke-oven workers.
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