首页|Unmasking the physical information inherent to interstellar spectral line profiles with Machine Learning. I. Application of LTE to HCN and HNC transitions

Unmasking the physical information inherent to interstellar spectral line profiles with Machine Learning. I. Application of LTE to HCN and HNC transitions

Edgar Mendoza Pietro Dall'Olio Luciene S. Coelho Antonio PeregrÃn Samuel LÃ³pez-DomÃnguez Floris F. S. van der Tak Miguel Carvajal

DOI：10.1051/0004-6361/202452397

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Arxiv

Unmasking the physical information inherent to interstellar spectral line profiles with Machine Learning. I. Application of LTE to HCN and HNC transitions

Edgar Mendoza Pietro Dall'Olio Luciene S. Coelho Antonio PeregrÃn Samuel LÃ³pez-DomÃnguez Floris F. S. van der Tak Miguel Carvajal

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Edgar Mendoza,Pietro Dall'Olio,Luciene S. Coelho,Antonio PeregrÃn,Samuel LÃ³pez-DomÃnguez,Floris F. S. van der Tak,Miguel Carvajal.Unmasking the physical information inherent to interstellar spectral line profiles with Machine Learning. I. Application of LTE to HCN and HNC transitions[EB/OL].(2025-05-07)[2025-12-14].https://arxiv.org/abs/2504.18760.

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首发时间： 2025-05-07

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Unmasking the physical information inherent to interstellar spectral line profiles with Machine Learning. I. Application of LTE to HCN and HNC transitions

Unmasking the physical information inherent to interstellar spectral line profiles with Machine Learning. I. Application of LTE to HCN and HNC transitions

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