We generate ∼100,000 model spectra of Type 1a supernovae (SNe Ia) to form a spectral library for the purpose of building an artificial intelligence–assisted inversion (AIAI) algorithm for theoretical models. As a first attempt, we restrict our studies to the time around B -band maximum and compute theoretical spectra with a broad spectral wavelength coverage from 2000 to 10000 Å using the code TARDIS. Based on the library of theoretically calculated spectra, we construct the AIAI algorithm with a multiresidual convolutional neural network to retrieve the contributions of different ionic species to the heavily blended spectral profiles of the theoretical spectra. The AIAI is found to be very powerful in distinguishing spectral patterns due to coupled atomic transitions and has the capacity to quantitatively measure the contributions from different ionic species. By applying the AIAI algorithm to a set of well-observed SN Ia spectra, we demonstrate that the model can yield p...

中文翻译：

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人工合成的Ia类超新星光谱的辅助反演（AIAI）

我们生成了约100,000个1a型超新星（SNe Ia）的模型光谱，以形成光谱库，目的是为理论模型建立人工智能辅助反演（AIAI）算法。作为首次尝试，我们将研究限制在B带最大值附近，并使用代码TARDIS计算具有2000至10000Å宽光谱波长范围的理论光谱。基于理论计算的光谱库，我们使用多残差卷积神经网络构造AIAI算法，以检索不同离子物种对理论光谱的高度混合光谱图的贡献。由于耦合的原子跃迁，发现AIAI在区分光谱图案方面非常强大，并且具有定量测量不同离子物种贡献的能力。通过将AIAI算法应用于一组观测良好的SN Ia光谱，我们证明了该模型可以产生p ...