Euclid and CSST Surveys Enable Direct Detection of Type II-P Supernova Progenitors

Identifying the stars that ultimately explode as supernovae remains a fundamental challenge in astrophysics. Junjie Wu, Ning-Chen Sun, and Zexi Niu, from the University of Chinese Academy of Sciences, alongside Tianmang Zhang, Chun Chen, and Xiaohan Chen et al. have investigated the potential of forthcoming surveys to overcome this obstacle. Their research focuses on how the Euclid and Chinese Space Station Telescope (CSST) missions will dramatically improve the detection of Type II-P supernova progenitors. By simulating progenitor visibility and analysing the impact of circumstellar dust, the team demonstrate these surveys could increase detection rates by an order of magnitude, finally allowing astronomers to address the long-standing question of red supergiant star evolution prior to core collapse. This work highlights the power of next-generation telescopes to unlock the secrets of stellar death and the origins of heavy elements in the universe.

Euclid and CSST for Progenitor Star Detection

Core-collapse supernovae (CCSNe) are fundamental to galactic evolution, enriching the interstellar medium and seeding the formation of neutron stars and black holes. Identifying and characterizing the progenitor stars of these explosive events is a central goal of supernova research, yet remains exceptionally challenging due to the limited availability of deep, high-resolution archival images and the obscuring effects of circumstellar dust. This work addresses these limitations, demonstrating how upcoming surveys will dramatically improve progenitor detection rates and refine our understanding of massive star evolution. Through Monte-Carlo simulations, they estimated the annual detection rates achievable with these next-generation telescopes. Crucially, the study also explored methods for recovering the intrinsic properties of supernova progenitors, employing radiation transfer calculations to account for the impact of circumstellar dust on observed spectral energy distributions. Experiments show that the optical and near-infrared filters on both Euclid and CSST are particularly effective at identifying RSG progenitors, offering a significant advantage over previous instrumentation.

This breakthrough reveals that the combined archival images from Euclid and CSST are predicted to enable the detection of approximately 13 to 24 progenitor stars per year within a mass range of 8, 16 (or 8, 25) M⊙. The study establishes that, even in the presence of circumstellar dust, the observed spectral energy distribution is primarily influenced by the dust’s optical depth and is largely independent of its temperature within the filters of the two surveys. Mock tests demonstrate the ability to simultaneously derive progenitor mass and dust optical depth by fitting observed data across the 11 filters of Euclid and CSST, while maintaining a fixed dust temperature. This innovative approach allows for more accurate characterization of progenitor stars, even when obscured by circumstellar material. The research establishes that Euclid and CSST will substantially expand the sample of directly detected progenitors with precise mass measurements, which is essential to resolve the long-standing “RSG problem” in massive star evolution and refine our understanding of the final stages of stellar life.

Euclid and CSST Progenitor Detection Capabilities

Supernova research seeks to identify and characterise the stars that explode as supernovae, a task hampered by the need for deep, high-resolution archival imaging and the obscuring effects of circumstellar dust. Researchers compared model magnitudes of red supergiant (RSG) progenitors against the detection limits of both telescopes, factoring in variables such as distance, extinction, and host-galaxy background. To estimate annual detection rates, the team employed Monte-Carlo simulations, generating numerous scenarios to model potential observations.

The work pioneered a method for recovering intrinsic progenitor properties by utilising radiation transfer calculations to account for the impact of circumstellar dust. These calculations demonstrate that the observed spectral energy distribution is primarily influenced by dust optical depth, remaining largely independent of dust temperature within the filters of Euclid and CSST. Scientists then conducted mock tests, fitting observed spectral energy distributions across the 11 filters available on Euclid and CSST. This approach allows for the simultaneous derivation of progenitor mass and dust optical depth, with dust temperature fixed at a typical value.

The study predicts that completed surveys from Euclid and CSST will enable the detection of approximately 13 to 24 progenitors per year in the 8, 16 (or 8, 25) solar mass range. This methodological innovation is poised to significantly expand the sample of directly detected supernova progenitors with accurate mass measurements. Such a larger sample is crucial to resolving the long-standing “RSG problem” in stellar evolution, which concerns the discrepancy between predicted and observed masses of red supergiant progenitors. The research team focused on identifying and characterizing the stars that explode as supernovae, a challenging task due to the need for deep, high-resolution images and the obscuring effects of circumstellar dust. Their work analyzes the potential of Euclid and CSST to detect red supergiant (RSG) progenitors, crucial for understanding the evolution of massive stars. Experiments revealed that the optical and near-infrared filters on both Euclid and CSST are particularly effective at identifying RSG progenitors.

Through Monte-Carlo simulations, the study predicts that the combined archival images from these two surveys will enable the detection of approximately 13 to 24 progenitor stars per year within a mass range of 8, 16 (or 8, 25) M⊙. The breakthrough delivers a pathway to significantly expand the sample size for studying these stellar deaths. Data shows that the presence of circumstellar dust primarily affects the observed spectral energy distribution through its optical depth, with minimal influence from dust temperature within the filters used by Euclid and CSST.

Mock tests demonstrated the ability to simultaneously determine a progenitor’s mass and dust optical depth by fitting observed data across the 11 filters available on the two surveys, while maintaining a fixed, typical dust temperature. Measurements confirm that this approach allows for accurate characterization of progenitor properties even in dusty environments. Results demonstrate that Euclid and CSST will be instrumental in resolving the long-standing “RSG problem” in supernova research. This problem concerns the discrepancy between predicted and observed masses of RSG progenitors, with current observations suggesting a lower mass limit than theoretical models predict. By providing a larger sample of progenitors with accurate mass measurements, the study anticipates a deeper understanding of the final stages of massive star evolution and the physics governing their explosive deaths. Through detailed modelling and Monte Carlo simulations, the study establishes that these forthcoming surveys will greatly increase the rate of red supergiant progenitor detection, predicting approximately 24 detections per year compared to the current rate of one. This improvement promises a much larger sample size for statistical analysis, crucial for addressing the long-standing ‘red supergiant problem’ in massive star evolution. The work further reveals that the optical and near-infrared filters on both Euclid and CSST are particularly effective at identifying these progenitors, even when circumstellar dust is present.

Importantly, the analysis shows that the spectral energy distribution of a progenitor affected by dust is primarily determined by dust optical depth, with temperature having a limited influence within the survey filters. This allows for simultaneous determination of progenitor mass and dust optical depth by fitting observed data, enhancing the accuracy of derived stellar parameters. The authors acknowledge limitations stemming from assumptions regarding dust temperature, and suggest future work should focus on refining these parameters. Further research could also explore the potential for detecting progenitors of different supernova types, expanding beyond the scope of Type II-P events. These advancements will be vital for resolving uncertainties in models of massive star evolution and the physics of core-collapse supernovae.