William Dawson | 17-ERD-120
Project Overview
The make-up of the visible universe is approximately 70 percent dark energy, 25 percent dark matter (DM), and 5 percent normal matter. However, DM has remained a mystery since it was first posited in 1933. With the LIGO Scientific Collaboration's recent discovery of 30-solar-mass black holes and new theoretical arguments, we were motivated to consider a DM candidate consisting of intermediate-mass primordial black holes (PBHs).
During our exploratory study, we led an astronomical survey of the Milky Way bulge and Magellanic Clouds, and we analyzed public archival data to measure the abundance and properties of black holes in the Milky Way using their gravitational microlensing photometric magnification signature. We also developed a simulation tool to predict the abundance of expected microlensing events both with and without PBHs. In addition, we developed a new means of detecting black holes and measuring their properties. Using these methods, we discovered a population of black holes that exceeds our theoretical predictions. While this excess is consistent with our theoretical predictions for PBH DM, we have yet to explore some systematics associated with our theoretical model (e.g., binary black holes or metal rich stars), so we cannot say for certain whether this excess is due to PBH DM. The time series analysis methods that we developed are directly applicable to several mission-relevant challenges. For example, the microlensing multiband photometric variability signal is analogous to the space situational awareness multiband photometric variability characterization of satellites and debris, and both applications require novel statistical methods to extract low signal-to-noise ratio events and design optimal surveys.
Mission Impact
This research supports Lawrence Livermore National Laboratory's space security mission research challenge, efforts to answer major science questions in cosmology (e.g., dark matter and dark energy), and DOE missions in high-energy physics. The project also benefits the Laboratory core competency in high-performance computing, simulation, and data science, including efforts to develop scalable capabilities to manage and recognize patterns in big data.
Publications, Presentations, and Patents
Bechtol, K., et al. 2019. "Dark Matter Science in the Era of LSST." Bulletin of the AAS, 51,3. LLNL-TR-795278
Chapline, G., and J. Barbieri. 2018. "MACHO Messages from the Big Bang." Letters in High Energy Physics, 01, 17. LLNL-JRNL-752094
——— 2019. "Was there a negative vacuum energy in your past?" Journal of Modern Physics, 10, 1166-1176. LLNL-JRNL-784338
Dana, R., and W. Dawson. 2019. "Using Neural Networks to Detect Black Hole Dark Matter." Lawrence Livermore National Laboratory Summer Symposium Poster Session, Livermore, CA. LLNL-POST-783977
Dawson, W., et al. 2017a. "A DECam and LSST Microlensing Survey of Intermediate Mass Black Hole Dark Matter. U.S. Cosmic Visions: New Ideas in Dark Matter Workshop, University of Maryland, College Park, MD, March 2017. LLNL-PRES-727265
——— 2017b. "Determining Whether Dark Matter is Entirely Primordial Black Holes with a DECam Direct Detection Microlensing Survey." US Cosmic Visions: New Ideas in Dark Matter, College Park, MD, March 2017. LLNL-CONF-727498
——— 2017c. "Testing Primordial Black Hole Dark Matter with WFIRST and LSST." Astronomy in the 2020s: Synergies with WFIRST Workshop, Balitimore, MD, June 2017. LLNL-PRES-733684
——— 2018a. "Intermediate Mass Black Hole Microlensing in the 2020s." 22nd International Microlensing Conference, University of Auckland, New Zealand, January 2018. LLNL-PRES-744948
——— 2018b. "Black Holes Hiding in Plain Sight." 9th LSST Project and Community Workshop, Tuscon, AZ, August 2019. LLNL-PRES-785679
——— 2018c. "DECam Microlensing Studies of Intermediate Mass Black Holes." DECam Community Science Workshop 2018: Science Highlights, Coming Opportunities, LSST Synergies Workshop, Tuscon, AZ, May 2018. LLNL-PRES-751791
Dawson, W., and N. Golovich. 2018. "CTIO Dark Energy Camera Capabilities & Surveys Summary." TDA-MMS 2019: Time Domain Astronomy in the Era of Massively Multiplexed Spectroscopy Workshop, Nikko, Japan, February 8-10, 2019. LLNL-PRES-766214
——— 2019. "Strong and Weak Microlensing in the 2020s." 23rd Microlensing Conference at the Center for Computational Astrophysics, New York City, NY, January 2019. LLNL-PRES-767061
Dawson, W., and S. Mao. 2019. "Search for Galactic Black Holes: Microlensing." TDA-MMS 2019: Time Domain Astronomy in the Era of Massively Multiplexed Spectroscopy Workshop, Nikko, Japan, February 2019. LLNL-PRES-767497
Drlica-Wagner, A., et al. 2019. "Probing the Fundamental Nature of Dark Matter with the Large Synoptic Survey Telescope." arXiv:1902.01055. LLNL-JRNL-795298
Feng, J., et al. 2017. "US Cosmic Visions: New Ideas in Dark Matter 2017: Community Report." arXiv:1707.04591. LLNL-TR-730998
Golovich, N., et al. 2018a. "A Macho Re-Analysis." 22nd International Microlensing Conference, Auckland, New Zealand, January 2018. LLNL-PRES-744945
——— 2018b. "Black holes as dark matter: how new discoveries are reinvigorating old theories." Lawrence Livermore National Laboratory, Livermore, CA. LLNL-PRES-760504
——— 2018c. "Searching for Primordial Black Hole Dark Matter in the Milky Way Halo." Best Poster at Lawrence Livermore National Laboratory, Postdoc Poster Session, Livermore, CA. LLNL-POST-752646
——— 2018d. "Reanalyzing MACHO for Long Timescale Parallax Events." LLNL-PRES-766737
Golovich, N., and W. Dawson. 2019. "Reanalyzing MACHO for Long Timescale Parallax Events." 23rd Microlensing Conference at the Center for Computational Astrophysics, New York City, NY, January 2019. LLNL-PRES-766737
Ivezic, Z., et al. 2019. "LSST: From Science Drivers to Reference Design and Anticipated Data Products." The Astrophysical Journal, 873, 44. LLNL-JRNL-795297
Lu, J., et al. 2019. "From Stars to Compact Objects: The Initial-Final Mass Relation." arXiv:1904.01773. LLNL-TR-795260
Medford, M., et al. 2020. "Gravitational Microlensing Event Statistics for the Zwicky Transient Facility." The Astrophysical Journal, 897 144. doi:10.3847/1538-4357/ab9a4f. LLNL-JRNL-806658
Street, R., et al. 2019a. "The Diverse Science Return from a Wide-Area Survey of the Galactic Plane." arXiv:1812.03137. LLNL-TR-795285
——— 2019b. "Unique Science from a Coordinated LSST-WFIRST Survey of the Galactic Bulge." arXiv:1812.04445. LLNL-TR-795284
