SYMMETRY-INVARIANT QUANTUM MACHINE LEARNING FORCE FIELDS

Symmetry-invariant quantum machine learning force fields

Machine learning techniques are essential tools to compute efficient, yet accurate, force fields for atomistic simulations.This approach has recently been extended to incorporate quantum computational methods, making use of variational quantum learning models to predict potential energy surfaces and atomic forces from ab initio training data.Howeve

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Genome‐wide association studies of fruit quality traits in jujube germplasm collections using genotyping‐by‐sequencing

Abstract Chinese jujube (Ziziphus jujuba Mill.) is an important fruit crop and harbors many highly diverse traits of potential economic importance.Fruit size, stone size, and fruit cracking have an important influence on the commercial value of jujube.This study is the first to conduct a genome‐wide association study (GWAS) on 180 accessions of j

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A Survey of Enhanced Cold Tolerance and Low-Temperature-Induced Anthocyanin Accumulation in a Novel Zoysia japonica Biotype

Zoysia japonica is a warm-season turfgrass that is extensively used in landscaping, sports fields, and golf courses worldwide.Uncovering the low-temperature response mechanism of Z.japonica can help to accelerate the development of new cold-tolerant cultivars, which could be used to prolong the ornamental and usage duration of turf.A novel Z.japoni

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