Mia Hu: hunting for Earth-like exoplanets

Wednesday, Feb 24, 2021
by Sharon Adarlo

Mia Hu, doctoral student


Mia Hu is a doctoral student in the mechanical and aerospace engineering department. She is in the midst of completing her thesis and expects to receive her PhD this May. In addition, she is completing the Graduate Certificate Program in Statistics and Machine Learning at the Center for Statistics and Machine Learning (CSML). Before coming to Princeton, Hu earned her bachelor’s degree in engineering from the University of Science and Technology of China (USTC), a national research university in the city of Hefei. At USTC, she focused on thermal science and energy engineering.



Hu’s research concerns itself with a simple and yet difficult question: Are humans the only intelligent life form in the universe? Hu’s answering of this question manifests itself in the task of trying to find exoplanets that can possibly harbor life.

“What we are trying to do is to find another Earth,” she said.

Hu said there is an exoplanet finding technique called direct imaging, which directly measures the light of a planet. Direct imaging has been a boon to scientists because the light captured in this process reveals valuable photometric, spectroscopic, and astrometric measurements of the detected planet.

“We can determine whether oxygen and water vapor are present at the planet’s atmosphere via spectroscopy if enough light from the planet is collected,” said Hu. “And the existence of oxygen and water are important factors for the existence of life.”

This evidence of the presence of life helps answer the ultimate question, "Are we alone?” Many research scientists have been finding exoplanets through other methods but these modes use indirect observations in comparison to direct imaging.

The challenges for direct imaging are the large intensity difference between the host star and the planets, and the small separation between them. Hu’s research concerns itself with one solution to this challenge of imaging objects in close proximity to much brighter ones: the starshade.  A starshade is a large flower-shaped mask that would be positioned between the telescope and the star to block out the light of a bright star, allowing observation of the faint planet.

It is impossible to have a full scale, ground-based starshade system test due to the large distance between a starshade and a telescope (tens of thousands of kilometers) and the large size of a starshade (tens of meters). Thus, Hu’s research involves simulating the images that will be obtained from future telescope systems with a starshade. These stimulations are helpful to assess the on-sky performance of these systems and provide a foundation for further investigations such as image processing.

The other component of her research involves the use of machine learning techniques to detect exoplanets in images taken during starshade missions. Detecting planets in a starshade mission would still be difficult because the planets are extremely faint. The images can also be distorted due to equipment properties or are “noisy” due to space particles (also known as exozodiacal dust). Hu developed algorithms to efficiently detect exoplanets in the images and also distinguish them from dust and equipment defects.

“The algorithms can also guide stopping observations early, providing confidence for the existence (or absence) of planets. As a result, the observation time is efficiently used,” said Hu about her research.

Another aspect of her research is that it can also give scientists who will be working on these starshade missions quantitative guidance on image parameters as they take pictures.

With the wrap-up of her research project, Hu is looking to the future. She will join Microsoft as a data scientist, where she interned last summer and engaged in research on natural language processing.


Extracurricular Activities:

Hu was vice president of the Princeton Graduate Society of Women Engineers and the liaison minister of the Association of Chinese Students and Scholars at Princeton University.

For Fun:

Hu enjoys doing martial arts and watching TV.