Research Experiences for Undergraduates (REU)

Snow depth retrieval over sea ice on the polar oceansSea ice and its overlaying snow layer play a vital role in the Earth’s climate system by acting as a thermal shield for the polar oceans. Because sea ice and snow are highly reflective surfaces, they bounce most of the incoming Sun’s radiation back to space (i.e., high albedo) thereby helping regulate the ocean temperature and contributing to the modulation of global temperatures and the climate. It is therefore important to obtain accurate retrievals of snow accumulation over sea ice in the Arctic Ocean and the Southern Ocean to better understand what controls their loss and formation, and to constrain climate models.

In this project, the student will learn how to estimate snow thickness over sea ice in the polar oceans by analyzing publicly available data from the Global Navigation Satellite System (GNSS) and by developing new software tools in Python.

Mentors: Dhiman Mondal, Pedro Elosegui, Chet Ruszczyk, John Barrett, Dan Hoak

Atmospheric turbulence in high-precision Earth measurementsThe radio-observational technique known as Very Long Baseline Interferometry (VLBI) is widely used by astronomers to study distant cosmic objects, such as black holes and quasars, and by geodesists to determine key Earth’s dynamic properties such as its shape and rotation. VLBI geodesy is fundamentally about measuring times with very high precision (few picoseconds), from which positions, angles, and distances can be accurately derived (e.g., mm-level). These measurements, however, are affected by the presence of water vapor and other constituents in the lower atmosphere (that is, the troposphere), which can cause atmospheric turbulence. Just as turbulence can shake an airplane, it also introduces a delay in the geodetic measurements, which needs to be modeled to achieve pinpoint accuracy.

In this project, the student will research ways to assess the effect of atmospheric turbulence on geodetic VLBI measurements using MATLAB tools and publicly available software. The student will learn about geodetic VLBI data processing, advanced statistical methods, inversion techniques, and geophysical modeling.

Mentors: Dhiman Mondal, Pedro Elosegui, Chet Ruszczyk, John Barrett, Dan Hoak

The technique of very-long-baseline interferometry (VLBI) offers geodesy the potential of estimating distances on the Earth separated by thousands of kilometers with precisions of a few millimeters or less. A primary goal of the developing next-generation VLBI geodetic observing system (VGOS) –whose delay measurements span very broad frequency bands– is to overcome the major source of error that limits this mm-level precision, the delay introduced by the presence of water vapor in the lower troposphere. These so-called atmospheric “wet” delays could be measured if the VGOS telescopes were also operating as water-vapor radiometers (WVR), that is, by tuning some of the VGOS frequency bands to measure the thermal radiation of water vapor near the 22-GHz resonance frequency. The student will explore new instrument designs (that include Dicke-switching, MMIC, and diplexers) and data processing approaches (such as optimal estimation method (OEM) retrieval) that lead to correcting atmospheric wet delays in VGOS observations using WVR techniques.

Mentors: Dhiman Mondal, Pedro Elosegui, Chet Ruszczyk, Scott Paine

It is hard to study fine details even in the most nearby galaxies. To give an example, some of the most exciting research today focuses on the formation of stars in the Milky Way and other galaxies. The star-forming sites in the Milky Way, also known as dark clouds, can be studied at an amazing level of detail. We can actually see how individual stars and planets form in our neighborhood. However, if we turn to galaxies, even the best telescopes available today cannot resolve dark clouds at a meaningful level of detail. Astronomers have therefore developed tricks to study the structure of clouds they cannot resolve. They study radiation from a variety of molecules, e.g. hoping that some molecules provide clues on dense gas while others might indicate that a dark cloud is being stirred up by embedded young stars. These are fascinating methods — but they have never been fully tested in the Milky Way. The LEGO survey therefore images dark clouds in the Milky Way to perform such tests. This teaches us lessons about star formation in the Milky Way and other galaxies.

As part of this program, you will lead a small original research project that uses LEGO data. You will learn how to visualize and analyze the data from several astronomical observatories, and how to draw conclusions from the trends in the data. You will do this as a member in an international collaboration that includes researchers from the US, the EU, Chile, and Japan. Successful projects are expected to produce results that will be published as parts of the LEGO papers.

Mentors: Jens Kauffmann, Thushara G.S. Pillai

The Experiment to Detect the Global EoR Signature (EDGES) is an exquisitely sensitive all-sky telescope that is searching for the red-shifted 21-cm signal emitted way back when the very first stars were born, roughly 13.8 billion years ago. Due to the vast expanse of space that this signal has had to traverse, the emitted frequency of 1.4 GHz has undergone significant cosmological red-shift, residing in the ∼50 to 100 MHz range upon reaching the Earth. Since these frequencies lie directly in the FM band, EDGES has observed from incredibly remote areas, including Devon Island in the high Arctic, Adak Island on the Bering Sea, and the outback of Western Australia. These data hold a wealth of information aside from the cosmological signal EDGES is searching for, including ionospheric scintillations of strong radio sources, reflections of terrestrial FM radio signals off of satellites and micrometeorites, evidence of exotic ionospheric propagation modes, and continuous observations as the Sun has approached solar maximum. The REU student involved in this project will explore the EDGES data for these secondary science targets, with the strong potential for discovering exciting, novel, and publishable results. Students comfortable with programming (e.g., Python or C) and with a basic understanding of navigating a Linux operating system, combined with a passion for discovery through data analysis, are encouraged to apply.

Mentors: Rigel Cappallo, John Barrett

Radio jet outflows, located near supermassive black holes, are among the universe’s most powerful astrophysical phenomena. Utilizing Very Long Baseline Interferometry (VLBI), this project aims to unveil the complex kinematics and structures of these jets. High-frequency VLBI observations are essential for examining the core regions of radio jets, but they face obstacles from atmospheric turbulence. In this REU project, students will engage in demonstrating new observational techniques to enhance high-frequency VLBI capabilities, leveraging multi-frequency data. 

Mentors: Thushara G.S. Pillai, Jens Kauffmann, Rigel Cappallo

Improving our understanding of our space environment is critical for technological applications and planetary sciences, as it can impact satellite operations, communication systems, navigation, and even ground-based power grids. A key component of understanding and mitigating these effects is monitoring electron density distribution in the ionosphere, which influences the behavior of radio waves and provides insight into Earth’s plasma environment. GPS receivers, commonly used for navigation, also measure the total electron content along their signal paths, offering a valuable tool for estimating electron density distributions. By applying mathematical techniques, we can reconstruct the 3D spatial structure of the ionosphere from these measurements, a process known as ionospheric tomography. Advances in scientific computing, including new algorithms and increased computational power, enable us to explore innovative methods for improving these reconstructions. In this project, we will start by working with simplified 2D models to test reconstruction methods, then progress to using real-world data to reconstruct smaller volumes of ionospheric plasma. This hands-on approach will provide valuable experience in computational modeling and space physics research.

Mentors: Enrique Rojas Villalba, Sam Thé

Incoherent scatter radar (ISR) has proved to be the most powerful and flexible ground-based instrument for probing the dynamics of thermal plasma in Earth’s ionosphere.  While this technique was first developed in the late 1950’s, scientists today are still developing new ways to extract new data from the measurements.  MIT Haystack is fortunate to have two such ISRs on site, a 46m fully steerable antenna, and a 68m fixed zenith-pointing antenna. Incoherent scatter is a technique that requires large antennas and powerful transmitters to work, because the amount of power from the ion line returned is about a factor of 10^-21 compared to what is transmitted. Recent improvements in electronics and signal processing have allowed these antennas to capture the even weaker plasma line. This project will be focused on extracting even more data from the plasma line signal than we presently do. Techniques used may include image processing and inverse analysis, using advanced tools available through the Python programing language.

Mentor: Bill Rideout, Katherine Cariglia, Bob Schaefer, Nestor Aponte

Wave-like disturbances are ubiquitous in ionospheric plasma, the ionized portion of the Earth’s upper atmosphere. Such disturbances are frequently observed in a broad range of latitudes and longitudes. They can be generated by a large variety of natural and anthropogenic sources.  Correct attribution of the observed perturbations to any specific source remains an outstanding challenge. Powerful explosions are known to generate ionospheric disturbances, and recent experiments suggest that detectable ionospheric perturbations can be generated by a relatively modest explosion of ~1 TNT. This project will focus on analyzing disturbances in the upper atmosphere above Ukraine (~20-40oE, ~40-55oN) using a variety of ionospheric data. This project will utilize data that were taken during the ongoing Russian invasion (post February 2022), attempting to identify potential ionospheric effects related to such attacks, and developing methodologies to separate ionospheric disturbances of natural and man-made origins.

Mentors: Larisa Goncharenko, Shunrong Zhang, Sevag Derghazarian

Scientific use of the radio spectrum aids in the study of Earth’s atmosphere, near space environment, and the astronomical universe. To enable fundamental research, scientific instruments span wide radio bandwidths and have high sensitivity. The proliferation of radio frequency (RF) systems – cell phones, radars, wifi, etc. –  has created a growing set of interference challenges for radio science instruments. The signals used for radio science are often extremely weak and can easily be overwhelmed by interference. This has driven new radio science instruments to very remote locations. Most recently, the launch of satellite communications constellations is creating a new generation of globally visible mobile sources that cannot be easily avoided. In this team project we will develop novel capabilities for radio interference monitoring, visualization, and localization. This will include signal processing development using an advanced software radio platforms, experimentation with advanced array antennas for RFI localization, and implementation of beamforming and imaging approaches to enable the localization of radio interference. Linking interference to specific effects in radio astronomy data for existing and future radio telescopes may be explored as well. Data collection may involve field work both at MIT Haystack Observatory and potentially at other relevant radio science facilities.

The student should have familiarity with in Python programming. Some background in radio (including amateur/HAM), software radio, signal processing, or electromagnetism would also be helpful, but is not strictly required. Experience using a Linux environment will also be relevant, but can also be learned on the job.

Mentors: Frank Lind, Mary Knapp, John Swoboda, Ryan Volz, Sam Thé

This project involves reduction of data from a large and comprehensive Very Long Baseline Interferometry (VLBI) experiment, targeting a powerful radio-bright quasar.  The goal is to generate high quality images across a wide range of angular scales, tracing prodigious energy flows from near the central supermassive black hole, all the way out into intergalactic space.  The work will involve the use of sophisticated astronomical software packages and novel algorithms to pursue state-of-the-art imaging precision and fidelity.

Mentors: Colin Lonsdale, Kazu Akiyama

The Event Horizon Telescope (EHT) is a planet-wide array of millimeter-wavelength radio telescopes that uses the technique of very long baseline interferometry (VLBI) to observe supermassive black holes. The goals of the EHT include testing general relativity and furthering our understanding of the astrophysics of accretion and outflow processes around black holes. The EHT has recently provided the first-ever images of a black hole in the giant elliptical galaxy M87, and the second black hole images for the Milky Way supermassive black hole Sgr A*. EHT data are used to constrain the properties of the accretion flow and jets, to measure the black hole space-time described by its mass and spin, and to test Einstein’s theory of general relativity. 

In this REU project, we will enhance the capabilities of the EHT and the Black Hole Explorer (BHEX) through the development of the cutting-edge data processing algorithms, computational imaging techniques and their software implementations. The project will primarily utilize the Julia programming language, and also existing software packages in Python. Although the project doesn’t require prior experience with Julia programming and software development, successful candidates should be comfortable with programming (e.g., Julia or Python) and have a basic understanding of navigating the Linux operating system.

Mentors: Kazu Akiyama, Vincent Fish, Dan Hoak, and John Barrett

VGOS (VLBI Global Observing System) is a current state-of-the-art space geodesy system that observes dozens of supermassive black holes on the radio sky with an approximately weekly cadence, with the goal of regularly monitoring the rotation and orientation of the Earth.  These geodetic observations directly support high-precision studies of the Earth’s geometric shape, gravity field, tectonic drift, and sea level rise. VGOS utilizes the technique of very long baseline interferometry (VLBI) to form a computational planet-size radio camera with an extremely sharp angular resolution from a network of radio telescopes. This project aims to enhance VGOS by incorporating novel data processing and imaging algorithms originally developed for the Event Horizon Telescope (EHT).

The student will collaborate with scientists in the Haystack EHT and Geodesy teams, including Drs. Kazu Akiyama, Dan Hoak, and Dhiman Mondal. The project will primarily use Python, MATLAB, and/or potentially the Julia programming language. Although the project doesn’t require prior experience with Julia programming, candidates should be comfortable with programming (e.g., Python/MATLAB) and have a basic understanding of navigating the Linux operating system.

Mentors: Kazu Akiyama, Dhiman Mondal, Dan Hoak

Q: When can I apply for next summer? What is the time frame for applications?

A: Applications are made available on Thanksgiving each year for the following summer. The deadline is February 1; we notify successful applicants on March 1, followed by a series of notifications for acceptances if any are open after the first round of notifications. Please do not contact us about the status of your application. We will notify you if you are missing any pieces of the application. If you are not accepted, you will receive notification of this in March after all positions have been filled.

Q: My institution is on a quarterly system (or another schedule). This means that I won’t be available on the exact start date. Can I still apply?

A: Yes, please apply to the program. Make a note of your possible start date in your statement letter. The mentors will determine whether your earliest possible start date is acceptable within the requirements for their project. We prefer that people be available for the actual start date but realize that some institutions’ schedules make this difficult.

Q: Do you accept international students?

A: Unfortunately our sponsor, the NSF, requires applicants to be a U.S. citizen or permanent resident to qualify. We won’t be able to respond to inquiries regarding this.

Q: How is “undergraduate student” defined for this application?

A: An undergraduate student is a student who is enrolled in a degree program (part-time or full-time) leading to a baccalaureate or associate degree. Students who are transferring from one college or university to another and are enrolled at neither institution during the intervening summer may participate. High school graduates who have been accepted at an undergraduate institution but who have not yet started their undergraduate study are also eligible to participate. Students who have received their bachelor’s degrees and are no longer enrolled as undergraduates are not eligible to participate. Undergraduate students eligible for this program must not have graduated prior to the start of the summer internship in June.

Q: Will the REU program be held in person or online this year?

A: We expect that the Haystack internship program will be held in person this year. However, this decision is affected by local and MIT safety and health regulations. (In 2020 and 2021, our research internship program was successfully held completely remote due to the COVID pandemic.)

Q: Do you send notification letters when my application is submitted?

A: We will notify everyone of their application status after the final deadline for submission (February 1) has passed. If you are missing a piece of your application, we’ll let you know then.

Q: I applied but did not hear from you on March 1. How will I find out about my application’s status?

A: The first round of acceptances is sent out every year on March 1; if any of these positions is not accepted, it will be offered to the next round of candidates on March 8, and so on until all of the positions are filled. This means there is a series of acceptance letters, starting on March 1 and possibly continuing into March. We do not inform applicants of their status until all the positions have been accepted; if you are offered another position in the meantime, we suggest that you accept it, as we have only a very limited number of internships available.

Q: To whom should the cover letter be addressed?

A: Please address your cover letter to the MIT Haystack Observatory REU Selection Committee. (If you have already submitted a cover letter addressed otherwise, it’s okay.)

The Haystack REU program starts in early June and ends mid-August. The 2025 REU program at Haystack will run from June 2, 2025, through August 9, 2024.

A uniform start date is preferred in order to conduct orientation activities for the group. For students on an academic quarter system or those interested in extending their stay, such requests can be considered on a case-by-case basis.

The Haystack summer undergraduate internship includes participation in the following:

• Science discussions: Haystack staff members lead discussions on numerous current research subjects, which include introductory information for all students, as well as a chance for active conversation with scientists, engineers, and other staff.
• Tours: Students will attend tours of the various Observatory facilities to learn about the extensive state-of-the-art instrumentation at Haystack. 
• Group meetings: In addition to the frequent meetings between the sponsoring staff member and the student, several meetings with all students are held to review project status and encourage interactions among the students.
• Final reports and seminar: Students prepare brief final reports and create presentations on their projects to teach the Haystack community about their summer work.
• Attendance at conferences: Depending on available funds and meeting schedules, there are opportunities for students to participate in national conferences.
• Follow-up academic year program: Depending on available funds, interest, and project status, a student may continue the summer project during the following academic year.
• Travel support: Limited travel support is available for those students whose homes and colleges are more than 100 miles away from Haystack.

Students are assigned a mentor from the Haystack research staff for their summer work.

At the end of the summer, students present their research to a general audience at the Observatory. Their presentations are available in the REU presentation archives.

Compensation is provided as a weekly stipend of $620, paid biweekly. You will receive an advance before traveling to the Observatory.

The Observatory makes arrangements for student dormitory housing and pays the cost of housing for all students. Kitchen facilities are available in the dormitories. Daily transportation to and from Haystack is also provided.

(Students can arrange alternative housing on their own if they wish.) 

The Observatory provides free daily transportation for all students from REU housing to our offices.

Accepted students must have a current medical insurance plan in place which will cover their health needs during the period of the REU program. Evidence of such insurance must be submitted upon acceptance, before the start of the program.