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Published in 2022 at "Advanced Science"
DOI: 10.1002/advs.202104742
Abstract: Y6 and its derivatives have greatly improved the power conversion efficiency (PCE) of organic photovoltaics (OPVs). Further developing high‐performance Y6 derivative acceptor materials through the relationship between the chemical structures and properties of these materials…
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Keywords:
quantum chemistry;
chemistry;
machine learning;
learning quantum ... See more keywords
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Published in 2019 at "Physical Review B"
DOI: 10.1103/physrevb.99.121104
Abstract: Machine learning algorithms provide a new perspective on the study of physical phenomena. In this paper, we explore the nature of quantum phase transitions using multi-color convolutional neural-network (CNN) in combination with quantum Monte Carlo…
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Keywords:
quantum phase;
phase transitions;
machine learning;
learning quantum ... See more keywords
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Published in 2020 at "Physical review letters"
DOI: 10.1103/physrevlett.125.225701
Abstract: Experimental quantum simulators have become large and complex enough that discovering new physics from the huge amount of measurement data can be quite challenging, especially when little theoretical understanding of the simulated model is available.…
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Keywords:
phase;
machine learning;
phase transitions;
unsupervised machine ... See more keywords
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Published in 2019 at "Science Advances"
DOI: 10.1126/sciadv.aau1946
Abstract: A photonic system is used to demonstrate that quantum states can be approximately learned using a linear number of measurements. The number of parameters describing a quantum state is well known to grow exponentially with…
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Keywords:
quantum states;
number;
experimental learning;
approximately learned ... See more keywords