Neutron stars are the dense and highly magnetic relics of supernova explosions of massive stars. The quest to constrain the equation of state (EOS) of ultradense matter and thereby probe the behaviour of matter inside neutron stars is one of the core goals of modern physics and astrophysics. A promising method involves investigating the long-term cooling of neutron stars, comparing theoretical predictions with various sources at different ages. However, limited observational data, and uncertainties in source ages and distances, have hindered this approach. Here, by re-analysing XMM-Newton and Chandra data from dozens of thermally emitting isolated neutron stars, we have identified three sources with unexpectedly cold surface temperatures for their young ages. To investigate these anomalies, we conducted magneto-thermal simulations across diverse mass and magnetic fields, considering three different EOSs. We found that the ’minimal’ cooling model failed to explain the observations, regardless of the mass and the magnetic field, as validated by a machine learning classification method. The existence of these young cold neutron stars suggests that any dense matter EOS must be compatible with a fast cooling process at least in certain mass ranges, eliminating a significant portion of current EOS options according to recent meta-modelling analysis.

中子星是大质量恒星超新星爆炸的致密且高磁性的遗迹。寻求约束超致密物质的状态方程（EOS）并由此探测中子星内部物质的行为是现代物理学和天体物理学的核心目标之一。一种有前途的方法包括研究中子星的长期冷却，将理论预测与不同年龄的各种来源进行比较。然而，有限的观测数据以及源年龄和距离的不确定性阻碍了这种方法。在这里，通过重新分析来自数十颗热发射孤立中子星的 XMM-Newton 和 Chandra 数据，我们确定了三个在其年轻时表面温度出乎意料低的源。为了研究这些异常现象，我们考虑了三种不同的 EOS，在不同的质量和磁场中进行了磁热模拟。我们发现，无论质量和磁场如何，“最小”冷却模型都无法解释观察结果，正如机器学习分类方法所验证的那样。这些年轻的冷中子星的存在表明，任何致密物质 EOS 都必须至少在某些质量范围内与快速冷却过程兼容，根据最近的元建模分析，消除了当前 EOS 选项的很大一部分。