An equation-of-state-meter of quantum chromodynamics transition from deep learning
The large data generated in heavy-ion collision experiments require careful analysis to understand the physics. Here the authors use the deep-learning method to sort equation of states in QCD transition and analyze the simulated data sets mimicking the heavy-ion collision experiments.
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2018-01-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-017-02726-3 |
| Summary: | The large data generated in heavy-ion collision experiments require careful analysis to understand the physics. Here the authors use the deep-learning method to sort equation of states in QCD transition and analyze the simulated data sets mimicking the heavy-ion collision experiments. |
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| ISSN: | 2041-1723 |