Build a science mission portfolio

The Chinese Academy of Sciences included space science in its Strategic Priority Program in 2011. Its first phase supported four different missions: DAMPE, Shijian-10, QUESS and HXMT. This was a portfolio of scientific investigations, not a single spacecraft design. The National Space Science Center’s directory distinguishes that first phase from a later group of missions.

A program can support several questions while sharing expertise in spacecraft, instruments and data handling. A mission needs a more specific chain: what question is being asked, which quantity would discriminate between explanations, and how an instrument can measure it. A proposal that promises to “understand the universe” still needs a testable observation.

Wukong, also known as DAMPE, studies high-energy particles and gamma rays. Huiyan, the HXMT observatory launched in June 2017, measures cosmic X-rays. Shijian-10 provided a recoverable platform for experiments in microgravity and space life science. QUESS investigated quantum experiments across space-to-ground links. These missions share program support without producing interchangeable evidence.

The photograph shows Chang Zheng 4B carrying HXMT from Jiuquan. The telescope is hidden inside the fairing. It records a transportation milestone; the X-ray observations come later. An experimental satellite can therefore succeed at launch while its scientific usefulness still depends on commissioning, calibration and analysis.

Consider an original selection exercise. Proposal A offers an exciting question but no demonstrated way to separate its target signal from background. Proposal B offers a narrower question with a tested measurement chain. A review should examine both scientific value and feasibility rather than reward the most dramatic title. Further instrument development may make A a better future candidate.

Wu Ji’s historical account describes proposals from the research community, mission science leadership and evaluation across a mission’s life. A useful portfolio also asks whether projects duplicate one another, whether their measurements complement existing data and whether people can analyze the results. These are planning questions, not a claim that one simple score decides an actual funding competition.