标题： 变分扩散变换器在超新星光谱条件采样的应用 显示英文标题

标题： Variational diffusion transformers for conditional sampling of supernovae spectra

摘要： Ia型超新星（SNe Ia）由于其惊人的观测一致性，已成为天体物理学中最精确的距离指示器。然而，不断增加的发现率揭示了多个具有光谱性质多样且难以用现有物理模型解释的子群体。这些奇特事件很难从稀疏采样的观测中识别，并且如果不及时标记，可能会在宇宙学分析中引入系统误差；它们对于建立热核爆炸的统一理解也具有更广泛的重要性。 在这项工作中，我们介绍了DiTSNe-Ia，这是一种基于变分扩散的生成模型，以光曲线观测为条件，并训练以再现SNe Ia的观测光谱多样性。 在使用来自辐射传输模拟的真实光曲线和光谱的实验中，DiTSNe-Ia在广泛的观测阶段（从峰值光前10天到峰值光后30天）实现了比广泛应用的SALT3模板显著更准确的重建。 DiTSNe-Ia在所有阶段的均方误差为0.108——比SALT3的0.508低五倍——并且峰值后的误差仅为0.0191，比SALT3的0.305小一个数量级。 此外，我们的模型产生了校准良好的可信区间，尤其是在峰值后的阶段，覆盖率接近名义值。 DiTSNe-Ia是快速推断SNe Ia及其他物理描述尚不存在的瞬态天体物理现象的光谱特性的强大工具。 显示英文摘要

摘要： Type Ia Supernovae (SNe Ia) have become the most precise distance indicators in astrophysics due to their incredible observational homogeneity. Increasing discovery rates, however, have revealed multiple sub-populations with spectroscopic properties that are both diverse and difficult to interpret using existing physical models. These peculiar events are hard to identify from sparsely sampled observations and can introduce systematics in cosmological analyses if not flagged early; they are also of broader importance for building a cohesive understanding of thermonuclear explosions. In this work, we introduce DiTSNe-Ia, a variational diffusion-based generative model conditioned on light curve observations and trained to reproduce the observed spectral diversity of SNe Ia. In experiments with realistic light curves and spectra from radiative transfer simulations, DiTSNe-Ia achieves significantly more accurate reconstructions than the widely used SALT3 templates across a broad range of observation phases (from 10 days before peak light to 30 days after it). DiTSNe-Ia yields a mean squared error of 0.108 across all phases-five times lower than SALT3's 0.508-and an after-peak error of just 0.0191, an order of magnitude smaller than SALT3's 0.305. Additionally, our model produces well-calibrated credible intervals with near-nominal coverage, particularly at post-peak phases. DiTSNe-Ia is a powerful tool for rapidly inferring the spectral properties of SNe Ia and other transient astrophysical phenomena for which a physical description does not yet exist.