We are developing a novel means of microlensing detection that will enable us to detect the signature associated with intermediate mass black holes, which will in turn enable us to (1) detect and constrain the fraction of dark matter composed of these black holes and (2) measure their mass spectrum in the Milky Way. This method of detecting and discriminating signals can be applied to other sources, such as satellites and space debris.
The visible universe is composed of approximately 70% dark energy, 25% dark matter, and 5% normal matter. However, dark matter has remained a mystery since it was first posited in 1933. The MACHO Survey, led by Lawrence Livermore, sought to test whether dark matter was composed of baryonic massive compact halo objects (MACHOs). The survey concluded that baryonic MACHOs with below 10 solar masses could not account for more than 40% of the total dark matter mass. Recently, the discovery of two merging black holes at the Laser Interferometer Gravitational Wave Observatory (two widely separated interferometers located in Hanford, Washington and in Livingston, Louisiana, that are operated in unison to detect gravitational waves) has renewed interest in MACHO dark matter composed of primordial black holes (formed in the early universe, before the first stars) with approximately 10 to 104 solar masses. The most direct means of exploring this mass range is by searching for the gravitational microlensing signal in existing archival astronomical imaging and carrying out a next-generation microlensing survey with state-of-the-art wide-field optical imagers on telescopes 10 to 25 times more powerful than those used in the original MACHO surveys. Microlensing is an astronomical effect predicted by Einstein’s general theory of relativity. According to Einstein, when the light emanating from a star passes very close to another star on its way to an observer on Earth, the gravity of the intermediary star will slightly bend the light rays from the source star, causing the two stars to appear farther apart than they normally would. We are developing a novel means of microlensing detection, based on Bayesian probability feature-detection methods, that will enable us to detect the parallactic microlensing signature associated with black holes in this mass range. We will detect and constrain the fraction of dark matter composed of intermediate mass black holes and measure their mass spectrum in the Milky Way.
We expect to produce a Bayesian time-domain signal detection and optimal variable-object photometry methodology (photometry is often used to study the brightness of astronomical objects over time, obtaining light curves where these variations of brightness are represented). We will use this technique to confirm or constrain intermediate-mass MACHOs as dark matter by applying our technique to existing data sets, as well as data from our own DOE Dark Energy Camera survey that builds on the existing Dark Energy Camera galactic bulge survey (with tens to thousands of expected events for the various data sets if the dark matter is determined to be intermediate-mass MACHOs). Even if black holes don’t comprise the majority of dark matter, we expect to directly detect a number of black holes and determine the black hole mass spectrum based on what we know from stellar evolution, existing microlensing black hole discoveries, and black hole merger rates determined by the Laser Interferometer Gravitational Wave Observatory. We will use the parallactic microlensing signal to construct the mass spectrum for the sample, which will be a first-of-its-kind measurement and have major implications for our understanding of black hole formation and interpretation of gravitational wave events discovered by the Laser Interferometer Gravitational Wave Observatory. Additionally, when we combine the parallactic microlensing signal with the astrometric microlensing signal, we can precisely measure the mass of individual black holes.
This effort supports the Laboratory’s mission research challenge area in space security, and our methodology of statistical model discrimination of astronomical data sets is applicable to the core competency in high-performance computing, simulation, and data science. This research also is relevant to the DOE goal to transform our understanding of nature and strengthen the connection between advances in fundamental science and technology innovation. The microlensing multiband photometric variability signal and discrimination of the target signal from other variable sources, such as supernovae and variable stars, is analogous to multiband photometric variability characterization of satellites and debris. Both applications require novel statistical methods to detect low signal-to-noise ratio events and extract meaningful information.
For this project, which started late in the fiscal year, we have (1) begun to develop time-series detection as well as image-analysis algorithms, (2) begun applying detection and characterization algorithms to MACHO survey data, and (3) assumed a collaborative role in the galactic plane survey of the Large Synoptic Survey Telescope based in Chile.
Dawson, W. A., et al. 2017. "A DECam and LSST Microlensing Survey of Intermediate Mass Black Hole Dark Matter." LLNL-PRES-727265.
——— 2017. "A Search for Intermediate-Mass Compact Halo Object Dark Matter in Wide-field Astronomical Imaging Surveys." LLNL-PROP-711064.
——— 2017. "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 23–25, 2017. LLNL-CONF-727498.
——— 2017. Testing Primordial Black Hole Dark Matter with WFIRST and LSST. LLNL. LLNL-PRES-733684.
Feng, J., et al. 2017. US Cosmic Visions: New Ideas in Dark Matter 2017: Community Report. LLNL. LLNL-TR-730998.
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