Patterns in the Darkness: Mapping Dark Matter
Patterns in the Darkness: Mapping Dark Matter
Jeff Gerber
Thomas Jefferson High School for Science and Technology
This article was included in the 2019-2020 Teknos Science Journal
Astronomers are currently facing a monumental and unprecedented challenge. Ever since the 1930s, we have been aware of dark matter— and yet to this day, the nature and structure of dark matter continues to confound scientists. This problem, and the groundbreaking discoveries that are sure to come with its solutions, inspired me to enter the Astronomy and Astrophysics lab. Over the past six months, I have conducted research to develop a general model for the structure, density, and shape of dark matter within galaxies.
The existence of dark matter was originally suggested by Fritz Zwicky in 1937, after noticing that the galaxy clusters he was studying did not seem to have enough matter to keep their stars rotating stably. However, the idea of dark matter was not taken seriously for nearly half a century [1]. That changed in the 1970s, when Vera Rubin noticed that the Andromeda galaxy had the same phenomenon Zwicky had found in his clusters: that its rotation seemed to indicate the presence of more matter. This sent ripples through the scientific community, forcing astronomers to accept the possibility of dark matter’s existence. Since Rubin’s discovery, scientists have developed several different methods of indirectly observing dark matter, such as studying its gamma radiation and gravitational effects. Although these methods provide insight into the distribution of dark matter, they have fundamental flaws that limit their capabilities.
For the past 50 years, scientists have primarily measured dark matter through its gravitational effects on movement. This mechanism is simple for a few bodies, such as in a stellar system, but this simplicity quickly breaks down when expanding to galaxies. Galaxies are composed of billions of stars, which are of similar mass on the galactic scale. While the mass of stars in a typical stellar system is concentrated in the center, a galaxy doesn’t have an area that dominates mass distribution. The masses in galaxies are more spread out, and the sheer number of different masses makes a model that attributes mass to individual objects computationally infeasible [3]. Rather, astronomers are constrained to oversimplification. Instead of looking at each individual object, astronomers calculate the mass inside a certain radius about the center of a galaxy. I was able to accomplish this by compiling and analyzing several rotational curves for each galaxy. This method allows for the construction of concentric “shells” between each set of radii, each attributing a different mass. This results in a distribution of total mass and density of the different shells, and by subtracting the mass caused by luminous matter, the dark matter distribution can be calculated [3].
Although this is an effective method for quantifying how much dark matter is in a whole galaxy, this method has major limitations in its applications. Unfortunately, models produced with this method lack any sort of shape and structure that might be present within the distribution. The oversimplification that allows for this method’s computational feasibility leads to its ultimate downfall. By restricting dark matter to spheres, this method produces models that show the distribution of dark matter as uniform throughout the galaxy, including outside the galactic plane. This is almost certainly false. Observations of the stars in our galaxy show that mass distribution can be anything but uniform [5]. The distribution of normal matter is rather uneven, including major fluctuations caused by black holes, nebulae, dwarf galaxies, and star clusters. Dark matter follows a similar distribution, being tightly compact in some areas, called “DM Planets”, and more spread out in others. These objects could be free floating or confined to a stellar system. It is even hypothesized that “Planet 9” of our solar system could be made of dark matter (K. Arun, personal correspondence, Jan. 21, 2020). This means that even on a smaller scale, we expect dark matter to have an irregular distribution. Because dark matter interacts gravitationally with normal matter, it is more likely to display a distribution that would compress to mimic that of normal matter. As a result, this method prohibits astronomers from seeing large-scale dark matter structures. Because of these flaws, studying dark matter through its gravitational effects provides a good estimate for quantifying dark matter, but it lacks the ability to approximate the more intricate structures that dark matter likely occupies.
The other major method astronomers use to indirectly measure dark matter is through observation of gamma radiation. Given the particle nature of dark matter, collisions between these dark matter particles could result in extremely high energy reactions and the emission of gamma rays [2]. Scientists have recently created a simple yet detailed model of gamma emissions within a few galaxies, outlining where dark matter might exist. Their research showed that dark matter roughly outlines the disks of spiral galaxies, concentrates near the center, and forms a minor halo [4]. In my lab, I used gamma ray images of different galaxies to not only discern a shape for the dark matter, but to give a rough estimate of its prevalence in each area as well. To accomplish this, I used pixel measurements from these diagrams to give the dark matter a relative weight of 0 to 255 in each area. Although this method does not give exact measurements of mass, the relative measurements allow me to create generalizations about the concentration and density of dark matter. Therefore, I am able to predict an approximate structure of dark matter within various types of galaxies.
Despite this model’s accuracy in finding the structure of dark matter, it carries two major flaws. Firstly, dark matter collisions are not the sole producer of gamma rays. Objects like supernovas, neutron stars, pulsars, and black holes also emit large amounts of gamma radiation, making it difficult to pinpoint the source of the radiation. For example, scientists studying the Galactic Center Excess, which is an excess in gamma ray emissions near the center of our galaxy, initially ruled out dark matter as the source of this discrepancy, instead choosing a large supply of pulsars as a scapegoat. Thus, these other sources of gamma emissions could skew the model [4]. The other flaw in this method is that the frequency of dark matter collisions is unknown. They could happen once per thousand particles per century, or they could happen once per particle per second. Changes in the collision rate would drastically change how much dark matter the model predicts. Since we are currently unable to produce dark matter in a laboratory setting, scientists are unable to study this rate in the detail required to quantify the mass of dark matter. Thus, while this method is effective in producing the shape and structure of dark matter, it still lacks the ability to create an accurate model.
Despite the shortcomings of both methods, scientists anticipate that as time progresses, our understanding and ability to measure dark matter will greatly improve, limiting the defects in these models and increasing their accuracy. One possible improvement is to combine these two approaches by taking the density calculated from gravitational effects and mapping it onto the shape provided by gamma ray observations. I am looking for ways to implement this combination, allowing me to create better models in the hope that one day, we won’t be so in the dark about dark matter.
References
[1] Arun, K., Gudennavar, S.B., & Sivaram, C. (2017). Dark matter, dark energy, and alternate
models: A review. Advances in Space Research, 60(1), 166-186.
https://doi.org/10.1016/j.asr.2017.03.043
[2] Buckley, M. R., & Peter, A. H.G. (2018). Gravitational probes of dark matter physics. Physics Reports, 761, 1-60. https://doi.org/10.1016/j.physrep.2018.07.003
[3] Chan, M. H., & Lee, C. M. (2019). Fitting dark matter mass with the radio continuum spectral data of the Ophiuchus cluster. Physics of the Dark Matter, 26. https://doi.org/10.1016/j.dark.2019.100355
[4] Morselli, A. (2017). Indirect dark-matter searches with gamma-rays: experiments status and
future plans from KeV to TeV. Nuclear and Particle Physics Proceedings, 291-293,
20-24. https://doi.org/10.1016/j.nuclphysbps.2017.06.005
[5] Vancea, I. V. (2018). Gravity-mediated Dark Matter models in the de Sitter space. Physics of the Dark Universe, 22. https://doi.org/10.1016/j.dark.2018.09.002
