In recent years, millimeter wavelength observations of protoplanetary disks around young stars have revealed substructures. These structures include asymmetries, gaps, and rings that could be indicative of phenomena creating gas pressure maxima which trap large dust grains, aiding their growth and promoting planet formation. The congregation and growth of large dust grains is thought to be a critical step in the grain growth that allows planets to form in the relatively short time frame before the circumstellar disk dissipates. We present new, high-resolution Sub-Millimeter Array observations (at a wavelength of 1.3 mm) of the HD 34700 system. The multiple Herbig Ae system HD 34700 is comprised of a close central binary and a distant companion, and has a bright disk around its central binary inferred through its strong infrared and millimeter excess. Recent scattered light observations showed that the smaller dust grains form a spiral arm structure with a large central cavity and an azimuthal discontinuity. Our SMA observations show an azimuthal asymmetry in the dust continuum which is indicative of a dust trap: a strong concentration of larger dust grains toward a likely pressure maximum in the gas. The trap is located at approximately 167 au from the central binary and with an azimuthal extent of 24 degrees. This is confirmed by our detection of CO gas centered on the binary location and consistent with a standard Keplerian disk. The large dust asymmetry could be produced by a planet producing a vortex at the cavity’s edge, or by the dynamical interactions of the central binary. Finally, we also detect a previously-unknown small dust disk around the distant companion HD 34700B, with a radius of approximately 43 au.
Gravitational microlensing is a powerful tool to study invisible objects, such as black holes, in the Milky Way. By monitoring highly populated areas like the Galactic bulge region, one can observe a variety of microlensing events due to brown dwarfs, main-sequence stars, white dwarfs, neutron stars, and black holes. We model the microlensing event rates with source stars in the Galactic bulge region using standard spatial and velocity distributions of stars in the Galactic bulge and disk regions. We observe that if black holes have an extended Salpeter-like mass function (as indicated by the recent LIGO binary-black hole gravitational wave events) and a similar velocity and spatial structure to stars, the population leads to a distinct increase in the microlensing event rate with Einstein crossing time on the order of 100 days. By looking toward the Galactic bulge region and observing on the order of 108 stars, we could potentially observe this excess of microlensing events. The Large Synoptic Survey Telescope (LSST) holds the potential to make these observations, though the success of observing microlensing events depends on the cadence of the telescope. We evaluate the efficacy of potential LSST cadences as either a trigger or a measurer of the light curves of black hole microlensing.
The Theory of General Relativity (GR) is very well-tested on local Solar System scales, but tests on the largest cosmological scales have been limited by the volume and precision of existing galaxy surveys. This situation is expected to change in the coming decade with the advent of several new spectroscopic redshifts surveys like DESI and Euclid. In this project, we aim to test the nature of gravity on these scales by using cosmological simulations to construct mock galaxy catalogs that mimic surveys as closely as possible. In particular, we focus on ΛCDM and three variants of the f(R) model of modified gravity: F6, F5, F4, each of which enhance the strength of gravity relative to GR with increasing intensity. Because of the inherent nonlinearity of the f(R) model, we use large-scale numerical simulations which self-consistently evolve dark matter particles according to these modified equations of motion. Previous simulations have predicted a higher abundance of massive halos and stronger clustering in the f(R) model relative to GR; however, it is unclear as to how much these differences persist in the galaxy distribution. We transform each of the halo catalogs using the Halo Occupation Distribution model, which determines the likelihood of a halo having a certain number of galaxies based upon its mass. Automating this process allows us to compare the differences in the redshift-space clustering between f(R) and GR using galaxies as tracers. Finally, we trim these galaxy catalogues even further by applying survey realism, ensuring that the galaxy distribution in the two cosmologies is identical to the observer.
With the discovery of over 4000 exoplanets, we are now able to conduct detailed studies of planet demographics. Interestingly, a possible dichotomy has developed, where hot Jupiters on longer orbital periods (between 5 and 15 days) tend to be more massive on average compared to shorter period systems. It is not clear whether this trend is produced by a detection bias or whether it results from some aspect of the planet's formation and evolutionary history. NASA's Transiting Exoplanet Survey Satellite (TESS) provides an opportunity to probe this question by increasing the known population of long-period hot Jupiters. In this work, we focus on the confirmation and characterization of TESS Objects of Interest, TOI-558b and 559b, two giant planet candidates within this period range. We globally modeled the photometric data from TESS along with precise radial velocity measurements, and find that both planets are quite massive (3-6 MJ) and have highly eccentric (0.1-0.3), long period orbits (7 and 14.6 days). Finally, we include the two systems in an analysis of all known giant planets with orbital periods less than 15 days, with a particular focus on their mass-period distribution.
The Harvard-Smithsonian Center for Astrophysics manages the comprehensive paper database Astrophysics Data System (ADS), which hosts nearly 15 million records, each with detailed citation and impact metrics. The Astronomy Image Explorer, hosted by AAS, is a database of images and figures published in peer-reviewed astronomy journals. In these records, the use of color in figures began in the mid-1990s and has become generally conventional since then. Using glue, a Python library that explores relationships within and between related datasets, we generated color distribution histograms of figures in AIE for ADS-listed journal articles in color figure-heavy fields of astronomy, such as stellar formation and galactic evolution. We correlated the color distributions with impact metrics from ADS. We predict results that certain RGB distributions improve article comprehensibility up to a certain threshold.
E+A galaxies are post-starburst galaxies that have recently undergone quenching of their star formation and now lie in the “green valley” transition zone, making them a valuable source for studying the evolution of galaxies. Using data from DR15 of the Sloan Digital Sky Survey, we analyzed a sample of 4,435 galaxies from the MaNGA (Mapping of Nearby Galaxies at APO) catalogue. We identified 52 E+A galaxies using their optical spectra, based on their spectral shape, u-r color, lack of Hα emission, and hydrogen Balmer absorption. We manually measured the equivalent widths of the Balmer absorption lines using PyRAF to overcome inconsistencies in the spectral synthesis modeling of these galaxies that underestimated their line strengths. Interestingly, we found that 27 of the 52 E+As are within 3 degrees projected distance from the center of the Coma Cluster and of comparable redshift to the cluster. The large number of E+As in and around the Coma Cluster hints at the influence of a dense galaxy environment on the formation of E+A galaxies, as has been suggested by previous authors, and the potential value of E+A galaxies as a diagnostic tool to study the formation of clusters. This work was supported by grant #AST-1852355 from the National Science Foundation to the CUNY College of Staten Island and the American Museum of Natural History.
The National Science Olympiad is the United States’ largest K-12 science competition, reaching over 250,000 students at nearly 8,00 schools in all 50 states. Competitors participate in a variety of events designed to prepare students for STEM careers by exploring topics ranging from constructing maximally efficient bridges to implementing advanced machine learning algorithms to analyzing real astronomical data using JS9. Since 2004, the Astronomy event has been a staple of the National competition and supervised at hundreds of college campuses annually. This upcoming year, the event will probe an understanding of fundamental stellar evolution principles in the context of galaxy formation and evolution. Competitors will answer questions related to the concepts underlying modern theories of star and galaxy formation and evolution, such as the warm-hot intergalactic medium, Beta Cephei pulsation mechanisms, and the nuances of the Lambda-CDM model; apply quantitative relations to solve theoretical problems or draw insights from real astronomical data; and demonstrate a masterful awareness of recent research surrounding 16 deep space objects, including M87, 3C 273, and JKCS 041. In addition to welcoming feedback from the community, we invite any interested community member to assist in the development of educational resources or Astronomy event materials for students and coaches by contacting Donna Young (firstname.lastname@example.org), Tad Komacek (email@example.com), or Asher Noel (firstname.lastname@example.org). Additionally, we encourage community members to volunteer at one of Science Olympiad’s 450 annual tournaments by contacting tournament directors to inquire about supervising an event. Supervisors benefit the younger generation by cultivating a passion for either Astronomy or the broader universe of STEM.
We developed a new analytical method to identify potential missed planets in multi-planet systems found via transit surveys such as those conducted by Kepler and TESS. Our method depends on quantifying a system’s dynamical packing in terms of the dynamical spacing Δ, the number of mutual Hill radii between adjacent planets (“planet pair”). The method determines if a planet pair within a multi-planet system is dynamically unpacked and thus capable of hosting an additional intermediate planet. If a planet pair is found to be unpacked, our method constrains the potential planet’s mass and location. Our method was tested using three well-characterized multi-body systems: the Galilean satellites, the solar system, and TRAPPIST-1. The analysis was run with three previously proposed values for minimum Δ required for planet pair orbital stability (Δ = 10, 12.3, and 21.7). The method was then applied to the Kepler primary mission multi-candidate systems, first via direct calculations and then via Monte Carlo (MC) analysis. Direct calculations show that as many as 560 planet pairs in Kepler multi-candidate systems could contain additional planets (Δ = 12.3). The MC analysis shows that 164 of these pairs have a probability ≥ 0.90 of being unpacked. Furthermore, according to calculated median mass efficiencies, 28.2% of these potential planets could be Earths and Sub-Earths. If these planets exist, the masses and semimajor axes predicted here could facilitate detection by characterizing expected detection signals. Ultimately, understanding the dynamical packing of multi-planet systems could help contribute to our understanding of their architectures.
Asteroseismology, the study of stellar pulsations, provides great insight into a star’s physical parameters, and with different computational methods, we are able to estimate the unknown characteristics of stars (like chemistry or age). In this project, we present a web-based interface with the ability to predict the physical properties of solar-like stars from stellar observations with the use of machine learning. With perturbation techniques and a Classification and Regressions Trees Algorithm (CART) on 350,000 theoretical stellar models to learn the matching between unknown and known properties of the star and predict its unknown parameters with a trained regression model. Initially developed with a database, the architecture of the interface consists of two separate frame-works: a back-end model and a dynamic front-end web application. With an additionally implemented, asynchronous front-end execution, email delivery server, and online database for storage of data and results, the interface successfully handles incoming and existing users and data. Finally, the mean predictions of 16 Cygni A, 16 Cygni B, and KIC 12258514 resulted in a 3.11% difference to original predictions, and the average prediction time was 6.27 ±1.06 seconds per star. This novel engineering project is potentially another great tool for stellar research which we plan to deploy simultaneously with the submission of a future publication that extends the back-end algorithm to handle more kinds of stars.
In this work, we examine spectral energy distribution (SED) fitting techniques commonly used to measure the dust temperatures of galaxies. Using toy models, we show that current far infrared (FIR) fitting techniques do not accurately recover the temperature of the dust within a galaxy. Instead, current fitting techniques recover temperatures which are higher than the actual mean of the dust temperature due to fact that hotter blackbodies are brighter than cooler blackbodies at all wavelengths. We demonstrate a method for FIR SED fitting which uses Markov Chain Monte Carlo (MCMC) methods to recover a distribution of dust temperatures given a galaxy's SED. We show that the mean dust temperature of the distribution recovered using MCMC methods on generated data is significantly different from the temperature recovered from conventional curve fitting techniques. We then demonstrate the power of our our fitting method on synthetic SEDs generated using cosmological galaxy formation simulations coupled with 3D dust radiative transfer models. Using this simulated data, we also establish a temperature distribution shape to use for this MCMC method based on the temperature of the CMB at a given redshift. Code to implement MCMC curve fitting will be made publicly available.
On August 21, 2017, millions of people across North America turned their (protected) eyes to the Sun to witness a total solar eclipse. At the same time in Jackson Hole, Wyoming, LightSound, an Arduino device developed at Harvard University, streamed the event online for the blind and visually impaired around the world. In a process called "sonification," the device uses a light sensor that takes the measured intensity of light (in the IR band, visual band, or both) and converts it to a pitch so that the listener can experience the real-time darkening during an eclipse. In preparation for the 2019 and 2020 eclipses in Chile and Argentina, LightSound has been redesigned with a MIDI synthesizer to allow the user to choose a variety of sound outputs and to offer a more rugged and telescope-adaptable interface. The documentation and code for LightSound, which costs about $70 to build, will be freely available online so that others may build their own (and modify the code, if they wish).
Dark energy, a force that counteracts gravity and accelerates the expansion of the universe on the grandest of scales, continues to confound the astrophysicists. In order to constrain its behavior in the universe, cosmologists are undertaking large surveys to understand its effects. The Dark Energy Survey (DES) is surveying an eighth of the sky for galaxies with redshift 0.2 to 1.5 to observe weak lensing effects and analyze cosmic shear. DES measures galaxy photometry in the four distinct g r i z bands, and hope to constrain their redshift from these photometric measurements. The error associated with these photo-z's contribute significantly to the DES cosmological parameters' error from weak lensing. Invoking Self Organized Maps (SOM), we establish a novel method of estimating the N(z) associated with the tomographic bins created to organize the SOM cells which capture galaxies with discreet color properties, based on the photometric measurements. By using a better constrained photometric survey for a smaller subset of the sky, we can leverage the few known redshifts to inform our color measurements across the SOM, and estimate N(z) for the full survey sample. This method has proven to constrain the mean difference between estimated and true N(z) for a simulated survey within 4%.
In this project, we analyze the spatial structure of HII regions in the interstellar medium of galaxy formation simulations from the FIRE (Feedback in Realistic Environments) project. We focus on a simulation of a Milky Way-like galaxy at high resolution evolved with the time-dependent chemistry solver CHIMES. We compare the properties of HII regions around young, luminous stars to the spherical HII regions predicted by the Strömgren model. To do this, we used Firefly, an interactive web-based visualization application we developed for exploring particle-based data. In addition to zooming in, rotating around, and visually manipulating the particles, we have also implemented in Firefly the ability to apply a unique colormap to each particle type based on a certain attribute. Using this new feature reveals sharp boundaries between ionized and neutral hydrogen regions, similar to what is predicted by the Strömgren approximation. A more quantitative analysis, however, reveals that the Strömgren radius is systematically smaller than the true "ionized radius" measured from the simulation data. We find that this is because the Strömgren model assumes isolated stars, while in the more realistic simulations, young stars are clustered. The assumption of isolated stars underestimates the true ionizing luminosity of an HII region, causing the Strömgren radius to be generally smaller than the true ionized radius. In the future, we plan to use Firefly to further analyze how molecular clouds (traced by H2, CO, etc.) relate to HII regions in the simulations.
The Giant Magellan Telescope (GMT) will be the world\rsquos largest telescope upon completion. The GMT employs seven 8 m primary mirror segments and seven 1 m secondary mirror segments. One challenge of the GMT is keeping the seven pairs of mirror segments on the GMT in phase. In this project, we developed and began assembly on a design for a dispersed fringe sensor prototype consisting of an optical and basic mechanical layout. The prototype design will be tested on the Magellan Clay Telescope as an experiment for future phasing methods to be used on the GMT.
Multiple groups have been working on modeling the mass distributions of the six lensing galaxy clusters in the Hubble Space Telescope Frontier Fields data set. The magnification maps produced from these mass models will be important for the future study of the lensed background galaxies, but there exists significant variation in the different groups\rsquo models and magnification maps. We explore the use of two-dimensional histograms as a tool for visualizing these magnification map variations. Using a number of simple, one- or two-halo singular isothermal sphere models, we explore the features that are produced in 2D histogram model comparisons when parameters such as halo mass, ellipticity, and location are allowed to vary. Our analysis demonstrates the potential of 2D histograms as a means of observing the full range of differences between the Frontier Fields groups\rsquo models.This work has been supported by funding from National Science Foundation grants PHY-1560077 and AST-1211385, and from the Space Telescope Science Institute.
The Event Horizon Telescope (EHT) aims to resolve the general relativistic shadow of Sgr A*, the supermassive black hole at the center of our galaxy, via Very Long Baseline Interferometry (VLBI) measurements with a multinational array of radio observatories. In order to optimize the scheduling of future observations, we have developed tools to model the atmospheric opacity at each EHT site using the past 10 years of Global Forecast System (GFS) data describing the atmospheric state. These tools allow us to determine the ideal observing windows for EHT observations and to assess the suitability and impact of new EHT sites. We describe our modeling framework, compare our models to in-situ measurements at EHT sites, and discuss the implications of weather limitations for planned extensions of the EHT to higher frequencies, as well as additional sites and observation windows.
We present results from an analysis comparing simulations of isolated spiral galaxies with recent observations of the circumgalactic medium (CGM). As the interface containing inflows and outflows between the interstellar and intergalactic media, the CGM plays an important role in the composition and evolution of galaxies. Using a set of isolated galaxy simulations over different initial conditions and star formation and feedback parameters, we investigate the evolution of CGM gas. Specifically, in light of recent observational studies, we compute the radial column density profiles and covering fractions of various observable ion species (H I, C IV, O VI, Mg II, Si III) for each simulated galaxy. Taking uniformly random sightlines through the CGM of each simulated galaxy, we find the abundance of gas absorbers and analyze their contribution to the overall column density along each sightline. By identifying the prevalence of high column density absorbers, we seek to characterize the distribution and evolution of observable ion species in the CGM. We also highlight a subset of our isolated galaxy simulations that produce and maintain a stable precipitating CGM that fuels high rates of sustained star formation. This project was supported in part by the NSF REU grant AST-1358980 and by the Nantucket Maria Mitchell Association.
Cataloging astrophysical sources is a fundamental operation in astronomy. While simple in principle, cataloging becomes more complicated for images with low signal to noise and degeneracies across different emission components. We analyze Chandra Deep Field - South (CDF-S) data using a novel method called probabilistic cataloging, which extracts information by sampling from the catalog space, i.e. the space of different point source configurations consistent with a given image. By employing a reversible-jump Markov Chain Monte Carlo (RJMCMC) sampling method, we are able to infer the flux and color distribution for Active Galactic Nuclei (AGN) in the region. We are also able to infer the number of AGN by marginalizing over faint members below the detection threshold. To validate our method, we use simulated deep Chandra exposures and show that the isotropic background emission can be constrained at the 10% level. This result takes into account its covariance with unresolved AGN and the particle background of Chandra. We then present results of probabilistic cataloging applied to the CDF-S 2Ms, 4Ms, and 7Ms datasets in order to evaluate the fidelity of our method. Furthermore, by incorporating auxiliary redshift information from the COMBO Survey within our framework, we present the first three-dimensional probabilistic catalog of AGN and discuss possible implications for AGN synthesis models.
The splashback radius (also known as the last density caustic or the second turnaround radius) is a sharp dark matter halo edge that corresponds to the location of the first orbital apocenter of satellite galaxies after their infall. This definition of a halo boundary is more physical compared to the traditional definitions of halo boundaries which tend to be quite arbitrary. The splashback radius responds to the mass assembly history of clusters. For dark matter halos of the same mass, a large mass accretion rate results in a smaller splashback radius, since its deeper halo potential well has a closer apocenter. Using two cluster samples which had the same mass, but different splashback radii, we set out to check if the incidences of active galactic nuclei (AGN) in the member galaxies of these clusters are affected by their mass assembly history. Using SDSS spectroscopic data, we determined metallicity of galaxies and constructed a BPT diagram to classify each galaxy member in each cluster (Seyfert, Liner, Composite, etc.) and determined if an AGN was likely to be present. We compared the samples and determined that the rapidly assembling sample did have a larger AGN presence.