I am a postdoc member at the Institute for Advanced Study at Princeton and a visiting fellow at Perimeter Institute in Canada. I got my Ph.D. in astrophysics in 2021 at Johns Hopkins University. I love physics, math, philosophy, classical music, kendo, and anime, and my better half.
I am interested in using statistical analysis of survey data to reveal beautiful physics and make discoveries. In this data-rich era, we are limited less by the size of data but more by the ideas to explore it. My innovative analyses have led to several discoveries and contribution across cosmic scales, including cosmological applications of a new statistic that borrows ideas from deep learning, a discovery of freezing stars that shine out of gravitational sedimentation, the best measurement of white dwarf merger rate, and a “Jupiter” candidate that opens a unique window to study exoplanets around massive stars. I am also working on a new method to map stellar orbit distribution in milkyway and a search for Planet X, a hypothesized new planet in our solar system.
Despite the success in finding more than 5000 extra-solar planets, traditional methods face challenges in finding planets around stars over 3 Msun. I work on a new method by searching around massive white dwarfs – the remnants of massive stars. In Spitzer archival data, I identified a 4-Jupiter-mass planet candidate, and I am the PI of a JWST Cycle 3 program for its spectroscopic follow-up. This technique opens a unique window to study planets around massive stars. Interestingly, as shown in the figure above, these giant planets (Jupiter-sized) are even larger than the host stars (Earth-sized) because the hosts are white dwarfs!
Extracting information from stochastic fields is a ubiquitous task in science. However, from cosmology to biology, it tends to be done either through a power spectrum analysis, which is often too limited, or the use of convolutional neural networks, which requires large training sets and lack interpretability. I showed that a new powerful tool called the scattering transform stands nicely between the two extremes. I studied in depth how to intuitively understand this new statistic which is unfamiliar to most physicists, and used cosmology as an example where its performance is on a par with neural networks while being well-structured statistics. My paper won an award of astrostatistics and was reported by this astrobites blog.
Recently, we successfully applied this new tool to real weak lensing data with expected improvement, and we argued that photo-z calibration rather than spatial statistic becomes the main limitation.
To advocate the use of the scattering transform, I wrote a publicly available module ST.py
based on pytorch, which can implement 1D and 2D scattering transform in a fast and transparent way.
I also work on white dwarfs, the destiny of most stars in the universe. Using data from the Gaia space mission, I discovered a new population of white dwarfs that cool extremely slowly and some others that are merger products. My work has led to two papers (click the figures below), one of which was highlighted by astrobites and AAS Nova and considered a major discovery in Gaia data. More recently, we explained the astounding physics behind it in a Nature paper, which is covered by Physics Today, elementy and many other media. I am very proud of this discovery!
To make white dwarf research easier, I also built a publically available package WD_models
in python for transformation between white dwarf photometry and physical properties.
In high school, my twin brother (who is studying philosophy now) and I found an efficient way to take spectra of meteors with digital camera. We designed a prism device that can screw in front of a lens. We ordered several from a factory, and sold them to other amateurs of astronomy. Shown below is one spectrum of the Geminid meteor shower, taken in 2010. We have made a new batch of such prism devices with a cost of less than 200 dollars each. If you are interested, please contact us or buy it here!
School of Natural Science, Astrophysics Group
2022-, member
2022-, visiting fellow
The Centre for Sciences of Data
2021-2022, visiting fellow
Advisor: Prof. Brice Ménard, Prof. Stéphane Mallat
Department of Physics and Astronomy
2021-2022, postdoc fellow
2017-2021, M.A., Ph.D. (Thesis)
Advisor: Prof. Brice Ménard
Department of Astronomy
2012-2016, B.S.
Advisor: Prof. Eric Peng (彭逸西)
Cheng, S., Schlaufman, K. C., & Caiazzo, I., A Candidate Giant Planet Companion to the Massive, Young White Dwarf GALEX J071816.4+373139 Informs the Occurrence of Giant Planets Orbiting B Stars, 2024, arxiv:2408.03985
Cheng, S., et al., Cosmological constraints from weak lensing scattering transform using HSC Y1 data, 2024, arxiv:2404.16085, Accepted to JCAP
Cheng, S., Morel, R., Allys, E., Ménard, B. & Mallat, S., Scattering Spectra for Physics, 2024, PNAS Nexus
Cheng, S. & Ménard, B., How to quantify fields and textures? A guide to the scattering transoform, 2021, arXiv:2112.01288
Cheng, S. & Ménard, B., Weak lensing scattering transform: dark energy and neutrino mass sensitivity, 2021, MNRAS, 507, 1012
Cheng, S., Ting, Y.-S., Ménard, B., & Bruna, J., A new approach to observational cosmology using the scattering transform, 2020, MNRAS, 499, 5902
Cheng, S., Cummings, J. D., Ménard, B., & Toonen, S., Double White Dwarf Merger Products among High-mass White Dwarfs, 2020, ApJ, 891, 160
Cheng, S., Two delays in white dwarf evolution revealed by Gaia, 2019, Proceedings of IAU, 15(S357), 175
Cheng, S., Cummings, J. D., Ménard, B., A Cooling Anomaly of High-mass White Dwarfs, 2019, ApJ, 886, 100
Cheng, S., Cheng, S., Meteor spectral observation with DSLR, normal lens and prism, 2011, JIMO, 39, 39
Bédard, A., Blouin, S., Cheng, S., Buoyant crystals halt the cooling of white dwarf stars, 2024, Nature, (free access link)
Chandra, V., Hwang, H.-C., Zakamska, N. L., Cheng, S., A Gravitational Redshift Measurement of the White Dwarf Mass–Radius Relation, 2020, ApJ, 899, 146
Lu, C. X., Schlaufman, K. C., Cheng, S., An Increase in Small-planet Occurrence with Metallicity for Late-type Dwarf Stars in the Kepler Field and Its Implications for Planet Formation, 2020, AJ, 160, 253
Liu, G., et al., A new code for low-resolution spectral identification of white dwarf binary candidates, 2024, A&A, 690, A29
Grandón, D. et al., Impact of baryonic feedback on HSC Y1 weak lensing non-Gaussian statistics, 2024, PRD, 110, 103539
Hwang, H.-C., Ting, Y.-S., Cheng, S., Speagle, J, Dynamical masses across the Hertzsprung-Russell diagram, 2024, MNRAS, 528, 4272
Marques, G. A. et al., Cosmology from weak lensing peaks and minima with Subaru Hyper Suprime-Cam survey first-year data, 2023, MNRAS, 528, 4513
Ren, L., et al., A Systematic Search for Short-period Close White Dwarf Binary Candidates Based on Gaia EDR3 Catalog and Zwicky Transient Facility Data, 2023, ApJS, 264, 39
Euclid Collaboration, et al., Euclid preparation-XXVIII. Forecasts for ten different higher-order weak lensing statistics, 2023, A&A, 675, A120
Liu, D. Z., et al., Potential scientific synergies in weak lensing studies between the CSST and Euclid space probes, 2023, A&A, 669, A128
Camisassa, M., et al., Forever young white dwarfs: when stellar ageing stops, 2021, A&A Letters, 649, 7
Bauer, E. B., Schwab, J., Bildsten, L., and Cheng, S., Multi-Gigayear White Dwarf Cooling Delays from Clustering-Enhanced Gravitational Sedimentation, 2020, ApJ, 902, 93
Marigo, P., Cummings, J. D., et al., Carbon star formation as seen through the non-monotonic initial–final mass relation, 2020, Nature Astronomy, full text here
scheng@ias.edu
+1 443 207 1532
Bloomberg Hall 150
1 Einstein Dr, Institute for Advanced Study
Princeton, NJ08540, USA