An Extravaganza of Lasers and Plasma (Pt. 2)

Please read Pt. 1 (Posted July 10, 2015)

Recently Dr. Tim Good, Gordon McCann, and I (Avery German) took a trip to West Virginia University to visit Dr. Earl Scime and work in his Plasma lab. This provided us with more knowledge to better our own LIF techniques, as well as gain some hands on experience in working in a large lab with other plasma researchers.


This is CHEWIE (Compact HElicon for Waves and Instabilities Experiment), one of the smaller plasma devices at WVU currently being used for LIF measurements. This device was used by one of our own Gettysburg College graduates and former plasma researcher in Dr. Good’s lab, Matthew Galante 08′, for his PhD thesis! The black tube contains collection optics for the LIF measurements which are then transported via fiber to the spectrometer for analysis. See the purple glow? That’s argon plasma!


This is the Large Experiment on Instabilities and Anisotropy (LEIA), a very large plasma chamber, large enough for researchers to go entirely inside the chamber to make modifications! Attached to the near side of the chamber is the Hot hELIcon eXperiment (HELIX) plasma source.

LEIA from another angle

LEIA  and HELIX from another angle. The entire apparatus is used to simulate space plasmas.

Hi Gordon!

Hi Gordon! These coils around the chamber carry electric current to induce a magnetic field in the plasma.

Charged with DNA AsSALT

This summer, Abby Bull, Savannah Miller, and I (Sarah Hansen) are doing biophysics research with Dr. Andresen (when we aren’t Gettypeding, that is). Although our individual projects vary, all of our research is related to the electrostatic properties of DNA. Our lab is interdisciplinary because we use the laws of physics to explain biological and chemical systems. Here is an in-depth look at our research:

IMG_20150723_161035 IMG_20150723_161627












I am a rising Senior in the Physics department with a minor in Mathematics and have just returned from a semester abroad in Australia at the University of Melbourne. When I first came to Gettysburg College, I knew I wanted to major in physics but I was also very interested in the combination of the sciences to solve complex problems. After a few semesters, I discovered the field of biophysics by taking a course lead by Professor Andresen along with Professor Frey in the chemistry department. To further my knowledge of biophysics, I worked in Professor Andresen’s lab last summer on work similar to Sarah’s in which I investigated the electrostatics of DNA in ion competition between monovalent and trivalent cations.

If anyone has seen the chick flick Chasing Liberty, where Mandy Moore plays the president’s daughter and runs around Europe for two weeks with a secret secret agent (as in she didn’t know he was a secret agent), then I have the perfect analogy for the work I do in the lab. In one scene, Mandy Moore is with two guys and they want to hug. The secret agent is put off from this because he doesn’t want to be unmanly and hug another guy. The solution was that Mandy Moore would be in the middle of the hug and act as a “chickie buffer (that) negates the potential for man-touching-man discomfort”. The chickie buffer is what we are trying to understand in this lab. It is the conditions that exist around DNA, nucleosomes or any other highly charged macromolecules that allow them to get so close together even though they are so repulsed by one another electrostatically.

This summer I am continuing my work with electrostatics, but now I will hopefully be studying the electrostatics of nucleosomes, the first packing structure of DNA. Because I came to campus late from Australia, I have only just begun my research project. I currently have nucleosomes that are about three-quarters of the way purified that I will then expose to different ions in different concentrations to see how they react. We hope to better understand the electrostatic conditions that nucleosomes are in when they are in solution or aggregated and what causes the condensation or reabsorption of nucleosomes in solution.

Gel electrophoresis of chromatin in solution to determine the length of DNA in the nucleosomes after digestion with micrococcal nuclease. This and other methods were utilized to purify and test the nucleosomes to determine if they were adequate to use in electrostatic experiments.

Gel electrophoresis of chromatin in solution to determine the length of DNA in the nucleosomes after digestion with micrococcal nuclease. This and other methods were utilized to purify and test the nucleosomes to determine if they were adequate to use in electrostatic experiments.


I am a rising Junior majoring in Biochemistry and Molecular Biology and minoring in Physics. My project is a collaboration with Professor Thompson in the chemistry and is focusing on the interaction of ions with polymer coated gold nanoparticles. Gold nanoparticles are exactly what they sound like, gold particles with diameters on the nanoscale (10^-9 m). They have unique properties that make them ideal for many biomedical processes such as imaging, drug delivery, other medical therapies. They are made using a stabilizer, in this case the positively charged organic molecule CTAB, which prevents the gold from aggregating and falling out of solution. The CTAB on the surface is in equilibrium with the surrounding, which makes it impossible to isolate the gold nanoparticles without some amount of free CTAB in the solution. To rectify this, a layer of polymer can be deposited which deprives the CTAB of contact with the surrounding solution and stops the equilibrium. The polymer itself has an equilibrium constant so high that virtually none of it is exchanged. The polymer we used was Polystyrene Sulfonate (PSS) a negatively charged, sulfur containing polymer. I coated a solution of CTAB nanoparticles with the PSS polymer and then characterized them with UV-vis spectroscopy, Dynamic Light Scattering (DLS), and Zeta Potential. From this data, we can find the concentration, polydispersity, hydrodynamic radius, and the surface charge of the nanoparticle.

After coating the nanoparticles and characterizing them, I dialyzed them against different salt buffers and then against water. I characterized them again and ran both the dialysis flow through and the resultant nanoparticles through Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). ICP-OES has an argon flame that excites the electrons in each element in solution resulting in an optical emission when the electron falls back to its original state. By making calibration solutions, the machine can match the beam intensity with the concentrations of certain elements. I ran dialysis comparing sodium to potassium and found that the ion to sulfur ratio was roughly 1:1 in both cases. I noticed that the hydrodynamic radius in both cases changed based on the solution it was in. In the low salt it was around 60 nm, in the 10 mM salt it was around 50 nm, and in the pure water it was around 70 nm. Since the amount of PSS per NP is relatively unchanging, this indicates that the PSS is changing its configuration. To investigate this further, I am now doing a dialysis with a range of sodium concentrations from 5 mM to 20 mM. I am going abroad in the fall, to Lancaster University in England, but I am looking forward to continuing this research in the spring semester!




I am a rising junior, and am majoring in Physics and minoring in Math and Chemistry. My favorite aspect about biophysical research is being able to combine topics across disciplines in order to explain biological systems.  As many know from biology, the DNA structure is held together by a phosphate backbone. And as many know from chemistry, phosphate (PO43-) is negatively charged. Physics, and more specifically, electrostatics, dictates that like charges repel. Yet in our bodies, DNA is able to densely condense. In order for DNA to condense, the electrostatic repulsion generated by neighboring phosphate molecules must be overcome. In vivo, this is mediated by histone proteins, which are positively charged. Though, the specific mechanisms behind DNA-ion interactions are unknown. Many theories have been postulated to explain DNA-ion interactions, though no concrete theory has been proven to explain the system.

My project focuses on the competitive binding of hexamminecobalt(III) and magnesium to DNA as the concentration of magnesium increases and DNA-DNA spacing decreases. Hexamminecobalt(III) is trivalent, whereas magnesium ions are divalent, and it has been shown experimentally that trivalent ions are necessary to condense DNA. I was able to use Inductively Coupled Plasma – Atomic Emission Spectra to determine the amount of cobalt, magnesium, and phosphorus in my differing concentration and spacing samples, and determine the charge neutralized by cobalt and magnesium in each one. I found that as the magnesium concentration increased, more charge was neutralized by DNA, and as the DNA spacing decreased, more charge was neutralized by hexamminecobalt(III). Both of these results seem probable given the properties of the system. More recently, I have been using Matlab and Delphi to compare the theoretical Poisson-Boltzmann equation to my experimental results. This involves generating a three-dimensional hexagonal array of DNA strands to simulate the experimental conditions, as well as adjusting boundary conditions, ion valences and concentrations, and other factors to match the theoretical and experimental results.

Hexagonal array of 19 DNA helices created with Matlab.

Hexagonal array of 19 DNA helices created with Matlab.

“Eat your veggies!” The importance of nutrition during the natal environment and its effect on adult sexually selected traits in the tortoise beetle Acromis sparsa

My name is Kalli Qutub and I am one of the students working in Professor Trillo’s lab. In Dr Trillo’s lab, we study a wide variety of sexually selected traits. These are traits that are used, generally by males, to attract, defend or fertilize females. We are especially interested in studying the interactions between primary sexual traits (e.g. testes or genitalia) and secondary sexual traits (e.g. long tail feathers in birds of paradise or antlers in ungulates) in a single organism. How do these traits develop? What trait is more useful for reproductive success?

For this summer research, the main question is: What happens if an organism has limited resources when developing? Would they be more likely to channel the resources to primary or secondary sexual traits or both?

To answer this question, I am using data that was previously collected by Dr. Trillo on the neotropical tortoise beetle  (Acromis sparsa) in Panama. These beetles feed, mate and oviposit on a single hostplant, Merremia umbellata (Convolvulaceae). They are also sexually dimorphic, with males having rigid elongated projections on their elytra and pronotum and females not having them at all. There is also a large amount of variation in the sizes of these projections for males, and some males possess really large projections whereas others lack them completely and resemble females. Males use these projections as weapons or claspers, to lift the opponent and toss him off the leaf surface during competitive encounters to access females. Males of this species also have really large genitalia and testes.

In an experiment, Dr. Trillo mated virgin A. sparsa females with males and split the broods in two. The first half of the brood was given as much food as they wanted (ad libitum), while the second half was given half of the amount of food. They were then allowed to grow and pupate into adulthood. Once they emerged, various parts of their morphology were photographed. My focus is to use these photographs to measure sexual traits, including their genitalia size, and elytral and pronotal weapon size. I make these measurements blind (meaning I do not know in advance which treatment they belong to), and once I finish, I will look at the effects on nutrient availability on the size of these sexual traits as well whether the amount of nutrition dictates the sexual trait that the energy gets put into. My hypothesis is that if nutrition is limited, the individual would choose to channel most of its energy either to primary sexual traits (testes or genitalia) or to the secondary sexual traits (elytral or pronotal weapons) rather than trying to split the energy evenly.

Most sexual traits are highly costly and understanding how organisms invest energy developing them when resources are not readily available is important because organisms are often faced with substandard natal environments. It would be interesting to see if the effects of nutrition on sexual traits we find in this species translate to other species or insects and maybe eventually look at larger animals to see whether the effects are similar. I believe that this experiment reveals an interesting perspective about sexual selection and the way individuals use the energy they gather during their natal environment.

A typical day in the lab for me involves me using a program called ImageJ, to take several measurements of the photographed morphologies of these beetles. Below are a couple examples of the measurements I need to take. I have mastered the use of Image J for just about any morphological measurement you could throw at me! It is also a relaxing process where I get to listen to my favorite music while I work. I plan to sit down with Dr. Trillo at the end of the summer to go through the statistical analysis of these measurements. I am very curious to see what happens in these beetles! Another interesting question I have been thinking about while measuring these beetles is: What about the females? Females do not usually have to have ornaments to attract males but use their elytra to defend larvae from predators, so it would be interesting to see what morphologies they choose to channel their energy towards.

445A3008 445A3138 445A2589

These three pictures show the tortoise beetle (Acromis sparsa) on its host plant (Merremia umbellata). In these pictures taken by Christian Ziegler, it is possible to see the beetles weapons on the male elytra and pronotum.


This is a picture of an elytra that I have already measured. The white lines on the picture are both my guide lines (mainly on the outside of the elytra) and also my measurements (on top of the elytra). These measurements include the length, width and area of the projection and elytra itself. These are the measurements that I will be using in my statistical analysis.

Earthquakes and collective animal behavior

Our lab studies collective animal behavior and granular materials. While these topics may seem very different, each are collections of many particles.  The ‘particles’ in our lab are athermal, don’t conserve energy, which means that these systems are out-of-equilibrium. Its not so straightforward to connect how individual particles behave back to whats going on in the system as a whole.


My (Sam) research focuses on granular materials, and how can physics help us understand and ultimately predict earthquakes and avalanches.  Some everyday examples of these materials are sand and salt. What makes granular materials so complex is how they can transition from a solid to a liquid (think salt pouring from the shaker). My research consists of analyzing how granular materials act under shear strain and building an apparatus to conduct this analysis in a controlled environment. I will be focusing on what happens at the particle scale and relating that back to behavior of the system. The granular materials in this experiment were PSM-4 (photo-stress materials), which are made specifically so that all contact forces made on each particle can be seen under polarized light. Linear actuators apply shear to a collection of approximately 1,000 particles. The particles are illuminated by a large LED light panel from below. An overhead camera snaps images of the particles. A stepper motor is mounted beneath the camera, which moves a polarizing filter in front of and away from the lens of the camera, so that we could obtain pictures of the particles with and without the force chains.

I’ve written code to automate the motion of linear actuators and a stepper motor, and remotely trigger and download images from a camera.  Now, I’m learning to analyze the images, and track particles using hough transformations and other cool algorithms.

part1   part2

m8ZAPhk03LoQdsK4NNApaBq0r2p8i0BDHjQEL-VTDyE    DSC_0004 exp      out

Collective Animal Behavior

I’m (Julia) researching collective animal behavior.   Many different groups of organisms exhibit collective behavior, from the cells in your body, flocks of birds, to people living in cities, we can ask many of the same questions about their organization and behavior. How and why do motion patterns in collective systems arise? How do individuals in a group communicate? Can we mathematically model systems based on the individual parts or the global properties? Would such models be applicable to a wide range of systems (or species)? Could we then use those models to predict the behavior of groups of animals? In order to start to investigate some of these questions, we are studying cohesion in swarms of young Artemia. Using high-speed cameras and stereo-imaging techniques, we can obtain quantitative spacial data for each individual in a swarm.

After making necessary adjustments to the apparatus that ensure good video quality and high contrast between the brine shrimp and the background, we have been able to start processing videos using (primarily) computer code written in Matlab. First, the cameras must be calibrated in order to obtain accurate 3D data from the videos with different 2D perspectives. To do this, images of the following calibration mask are analyzed.



20150720_155634    DSC_0015

We chose brine shrimp as a test organism because they are relatively inexpensive to raise and they form swarms in response to light. In particular, brine shrimp have a strong phototactic response to blue-green wavelengths of visible light, so we are using green LED light sources to manipulate their swarming behavior. As mentioned, data collection involves utilizing high-speed cameras and stereo-imaging techniques. Several infrared lights are being used to illuminate the tank and the cameras because the Artemia cannot see or are impartial to longer wavelengths of light. The apparatus is kept in the dark to ensure that the brine shrimp are only responding to the stimulus of the green LED. In order to capture 3D data, we have constructed a hexagonal tank that holds the shrimp. Three cameras are positioned near adjacent faces of the hexagon; these different perspectives provide the necessary information to resolve a single 3D perspective of the system.

20150702_085040   14135928screenshot   14135928bgcopy   imgout

Every frame in each video from the three cameras is then altered so individual animals can be detected and their 3D position in the swarm can be resolved as time progresses. Information can be taken from each image based off of the contrast between a light brine shrimp and the dark background.

After each individual is detected, the stereo-matching is done which combines the 2D data from each camera into one 3D data structure. Until relatively recently, this kind of data was very hard to take. Each of the three cameras in the apparatus captures ten frames every second and each frame contains the position of hundreds of Artemia. Processing all of the information that we are collecting requires a lot of computing power. I am now stereo-matching the particles and tracking the Artemia in 3D. Soon we will take and analyze different sets of data that may provide insight into the dynamics of the collective behavior of brine shrimp.

Gone Batty

Deep in the heart of Panama, nestled amongst the rainforest flora and flanking the Panama Canal, is the little town of Gamboa. And here in this little mysterious town exists a gem of the Smithsonian that is famous for its groundbreaking work in tropical biology. The Smithsonian Tropical Research Institute (or STRI) has been dedicated to studying tropical habitats and wildlife since 1923, hosting over 1,500 scientists per year. I have been lucky enough to become part of this amazing institution, and alongside Professor Alex Trillo and STRI Staff scientist Rachel Page, I have been working with Trachops cirrhosus, the Fringe-Lipped Bat in field experiments to study their preference for prey species based on auditory stimuli. My name is Samantha Siomko, and this is the story of how I became Batgirl.

Trachops Who?


It’s dinner time! (Photo Credit: Christian Ziegler)

Trachops cirrhosus, or the fringe-lipped bat, has been the focus of many studies here at STRI because of the unique relationship with its favorite prey: frogs. Trachops hunt by eavesdropping on frog calls, using auditory cues from the frog’s mating calls to locate them. This is useful when studying their behavior, because we can use playbacks of frog calls in the field to lure the bats to what they think is a meal. Trachops are very social bats, living in roosts of dozens of individuals in caves, tunnels, hollowed trees, etc. They hunt using echolocation as well as auditory and visual cues to locate prey. Spanning all across Central and South America, from southern Mexico to Brazil, they prefer lowland tropical forests with plenty of open area to fly.


El Experimento

Dr. Trillo is interested in the sensory mechanisms that enable predators to find their prey. In this specific experiment, we investigate how bats choose which frog to prey upon when these frogs call from a mixed species group. Previous studies on insects and wildebeests show that individuals are preyed upon less when in a group of their own species. However, many frogs call from a mixed species group. Trachops show equal preference for both of the frog calls used in experimentation, the Hourglass Treefrog (Dendropsophus ebraccatus) and the Tungara Frog (Engystomops pustulosus). We are trying to quantify whether bats prefer to attack the more prevalent species, or if is it easier for them to locate and attack a frog when it is the sole member of its species in a group. The hypothesis is that, when in a mixed group such as this, a predator will be able to more easily pinpoint and attack the less common species, because it can be more easily distinguished from others in a group. If you can imagine how much easier it is to keep track of an orange fish in a pool of black fish, or vice versa, you have a good handle on the “oddity effect”.


The setup

Each night we set up six speakers, five of which are playing one species’ call (the common species) and one of which is playing a call of the other species (the rare species). We switch the rare species each night. We use infrared cameras to record visits to one of the speakers playing a common and a rare call, and the videos are then analyzed to determine the number of bat predatory visits. Frog models are also used to satisfy the bats’ use of echolocation cues. Shown below is a Trachops cirrhosus bat visiting one of the speakers. Bats are not the only species that use frog mating calls to locate prey. A species of blood-sucking midge is also attracted to frog calls, but they will attack E. pustulosus with more frequency than D. ebraccatus. We also test the midge’s preferences for common versus rare individuals in mixed-group species. Flies attracted to a speaker are captured on fly paper, and the number of individuals who are attracted to that species’ call are determined.

Why is this important? If the less common species is singled out more often in a mixed-species chorus, this would influence the locations from which frog species calls and whether they should actually call on a certain night depending on the species in the chorus. Having to account for this would influence a frog’s reproductive success as well as overall survival, which is especially important in the light of amphibian decline and a recent reduction in population numbers.

When Cultures Collide

My time down here is extra special because of Dr. Trillo’s vision to start a “Bi-national Internship.” This means I get to work with a Panamanian student, allowing for the two of us to exchange information that we would otherwise not be exposed to. Sara Vasquez and I have become fast friends, and she has already taught me so much about species names and Panamanian history and how to properly cut up a pineapple (seriously, there’s a very specific way to do it). It has so far been an amazing opportunity to work alongside her, and I hope she is learning as much from me as I am from her.


Working hard in the Batmobile!

More Batty Adventures

We sometimes get the chance to help out other researchers here at STRI, especially when they need to capture wild bats in order to study their behavior in a flight cage. To do this, we help put up mist nets, thin nets covered in pockets to hold tangled bats, over bat flyways. There is always a need for extra hands to help out with this, and I get the opportunity to interact with all types of bat species, which is one of the most exciting parts. I mean, look at their little faces. What’s not to love?


Almost free, little guy


A Proboscis Bat (Rhynchonycteris naso) ready to be released


Bats aren’t the only cool thing we see here. On a regular basis, I come across strange and wonderful species, giants frogs, sloths, anteaters and scorpions the size of your hand! Panama has more biodiversity than you could imagine.


Cute baby python


A big ol’ Leptodactylus pentadactylus

Having the opportunity to come here has been incredibly humbling, and I am so glad I was given the chance to experience all of these amazing things and work with all of these amazing people. Holding a bat in your hand can be a life changing experience. Being able to actually look at one of these elusive creatures in the eyes and feel the membrane of their wings is such a great experience. These are intelligent, amazing creatures worthy of more respect than they get. But I know that, as long as places like STRI exist and as long as there are people who care so much about them, there is still hope for these wonderful creatures.

Other photo credits: Michael Caldwell

Chefs, Scientists, Tomato, Tomahto

Whatley Lab

Beginning research is a lot like beginning to cook. You have this vague idea of what you’d like to eat, but little knowledge of how to get there. You look to the experts for guidance, and hope to live up to the great expectations set before you. To say I was excited for my summer of research here at Gettysburg College would be an understatement. Amidst the excitement and anticipation, there was little time to account for the logistics of college living, things like grocery shopping or cooking. Until this summer, I failed to appreciate both the convenience of servo and my mother’s meals. Being from an Italian family of eight, preparing a meal meant being given some small task that your Mom didn’t want to do, like peeling the bag of potatoes, making a salad, or cutting up some carrots. You were never given something particularly hard to do. There wasn’t really anything to mess up, and if you did, you had your mother there to clean up after you. You never actually understand the entire process, it’s just something that happens everyday. That is until you’re on your own cooking, without Mom there, that you realize you weren’t ever really cooking. But once you learn to cook, truly learn to cook, you might just find yourself falling in love with it.

Endless amounts of petri dishes

Endless LB Plates

At first you’re hesitant to substitute a ripe banana for an egg, but you eventually feel confident enough in your own abilities to try it out. It tastes a little different, but it cooks just fine. In time, you learn how to baste, blanch, and broil. You migrate from pasta and jarred sauce to making it from scratch, like Mom always did. You learn that sauteing and searing are not the same thing. You may even learn the hard way that searing a piece of meat with butter doesn’t work as well as oil. And as time unfolds you begin to remember the recipes, understand the lingo, and make better meals. With practice and patience, many failed recipes and flavorless meals, you eventually get better. Don’t get me wrong, you still may make the perfect casserole, but forget to preheat the oven. Or leave the sugar cookies in the oven until they look more like ginger snaps and taste more like dog treats. Even the best chefs are familiar with failure, but that’s just in the nature of cooking.

We eat everyday, but rarely realize the work behind the food placed in front of us. Everyone cares about what they eat because it’s a necessity in life, but not everyone cares about how their food got to their plate. At least I know that I didn’t. The same holds true for research. We all care when a young boy falls sick in a hospital from exposure to antibiotic resistant bacteria in his catheter, but seldom are we concerned with the research that leads scientists and doctors to this conclusion. Its why people scratch their head when I tell them I work with naturally occurring biofilms and bacteria (and enjoy it). They say “so what,” but, as a scientist, I know that there’s no “so what” about it. If you have no application for your project, you’ve lost sight of its purpose, but, on the other hand, if you disregard all the intricate steps taken to get there, I’d argue the purpose is lost as well. While I once only appreciated the final result of a well-made meal, this summer I’ve developed a love and appreciation for the process and art of cooking, and the process and art of science.

Amanda slaving over a hot Bunsen Burner

Amanda slaving over a hot Bunsen Burner

Kelly divvying up the LB broth

Kelly divvying up the LB broth

The transition from cooking at home to cooking on my own is a lot like the transition from weekly lab classes to actual research. I work with naturally occurring biofilms in built environments, and there is a certain novelty to working with unidentified samples. However, with that novelty comes a certain frustration similar to making a meal without a recipe. I have a few vague recipes that work with slightly different ingredients, with temperatures that may or may not be optimized for what I am working on. Sometimes I’ll make adjustments to these and cross my fingers that they work, but there’s not exactly a picture on Pinterest for comparison. In the end, all of the small pieces of the meal may or may not even mix well together. Again, I have this vague idea of the meal I’d like to make, but know relatively little about how exactly to get there. This summer, I’ve found that research is about getting into the nitty-gritty details, while always keeping the final dish in mind.

Survival Assay Experiment

A nice view of the kitchen

If only we all liked to cook as much as we like to eat.

The Search for Spots


Our relationship with our Sun can be described as complicated. The existence of life on our planet is completely dependent upon it, but it can also prove to be problematic at times through unpredictable surges of harmful energy, known as flares. While our atmosphere deflects the bulk of this energy away from us, some still manages to break through with potential to damage electrical systems, resulting in blackouts.This can also be dangerous to our many orbital satellites and on-duty astronauts. It therefore benefits us to understand our Sun in an attempt to better predict when these hazardous phenomena may occur. Studies have revealed that flares correlate with sunspots, visibly darker areas on the Sun’s surface.

Our Sun. The dark blobs are sunspots.

Our Sun. The dark blobs are sunspots. Credit: NASA SDO

This solar activity is a result of the differential rotation of the Sun (meaning the surface of the Sun rotates slower at the poles than at the equator) combined with convection currents throughout the body; this results in a tangling of its magnetic field lines, which in turn results in the sunspots and flares.

Differential Rotation. The red lines indicate the changing magnetic field lines.

Differential Rotation. The red lines indicate the changing magnetic field lines.

Eventually, these lines become so twisted that the Sun’s magnetic field resets its polarity, starting the whole process over. For our Sun, the magnetic poles reverse approximately once every 11 years, with a total cycle of 22 years.

Our Work

We are attempting to understand magnetic activity by observing the stellar cycles of other stars similar to ours, particularly of known spotted stars in open cluster NGC 6811.

NGC 6811

NGC 6811 – image taken (by us!) in Flagstaff.

NGC 6811 is visible in our night sky during the summer, between the constellations Lyra and Cygnus, and is approximately 4000 light years away. Because of its distance from us, each star that we are interested in is much dimmer than what the human eye can see, and the entire cluster looks very tiny in the sky (the cluster could be blocked by a half moon); it is therefore nearly impossible to directly observe starspots.

NGC 6811 in the night sky - everything we study (and more) is within the red circle

NGC 6811 in the night sky – everything we study (and more) is within the tiny red circle (center). Credit: Sloan Digital Sky Survey

However, we can see overall changes in their apparent brightness to determine changes in average starspot amounts (more starspots = darker surface). To study the stellar cycles of our stars, we are using data from our own Gettysburg College observatory from 2007 as well as from the NURO Observatory in Flagstaff, AZ from 2013, 2014, and our own trip in late June of this year.

The NURO 'scope

The NURO ‘scope

These data were taken using a 31″ diameter telescope which tracked our stars throughout the night as a CCD semiconductor chip processed the collected light into a digital image. We can then use a computer program to determine how bright each star is in relation to some unchanging stars to determine the differential magnitude of each star.

Controlling NURO

Controlling NURO

Finally, we will plot the differential magnitudes over time to see how they change to determine the stellar activity for each star.

KIC9654919 Sample Data Sheet

KIC9654919 Sample Data Sheet – they x-axis represents time in Julian Date, the y-axis represents the difference in magnitude between the target star and a comparison star.

For a glimpse into our research and our trip to Arizona, check out the gallery below!

SciPy 2015: Live from Austin, Texas

SciPy 2015: Live from Austin, Texas


This summer I was given the awesome opportunity to visit Austin, TX for the annual SciPy conference hosted by the University of Texas. This conference focuses, as it’s name might imply, on scientific uses for the Python programming language. This included data science talks, data visualization talks, machine learning talks, as well as a variety of tutorials that ranged from basic to advanced applications of the language.


The AT&T Conference Center on the University of Texas campus hosted the 2015 SciPy conference

For the three days that I was there I got to see three awesome keynote speakers which were the Chief Data Scientist from the NY Times, the creator of Pandas (a core scientific package for Python), and the Director of Research in the Physical Sciences for University of Washington’s eScience institute. Outside of the keynote talks, I focused on learning more about data visualization, efficient data structures for “big data,” and calculation optimization in Python. One of the coolest tools I learned about was a visualization tool called VisPy that can handle advanced graphical renderings. I was fortunate enough to also attend a few talks for fun that didn’t directly relate to my research. I chose to spend those talks learning more about machine learning and general astrophysical applications of python.


This is a close up of a plot of 1000 signal plots generated using VisPy, a powerful visualization tool that uses the GPU as opposed to the CPU to render graphics

While at the conference, one of the special events I attended was the job fair. There were tons of companies from industries ranging from software development to finance. I have been interested in computational finance for the past few years, so I focus a lot of my attention towards those companies. I was fortunate enough to interview with three quantitative finance firms, AQR, D.E. Shaw, and Jump Trading and many of the skills that I have learned in my summer research experiences through HHMI and Gettysburg College were quite impressive to their recruiters. I was one of a handful of undergraduates at the conference and almost certainly the only one with multiple summer research experiences. Those experiences, depending on the outcome of the job applications, could directly lead to an employment opportunity which just shows the power and usefulness of the interdisciplinary research program at Gettysburg.


D. E. Shaw & Co., L.P. is a global investment management firm founded in 1988 by David E. Shaw and based in New York City


AQR Capital Management is an investment management firm founded in 1998 by former Goldman Sachs portfolio manager Clifford S. Asness along with partners David Kabiller, John Liew and Robert Krail

Outside of the conference I was able to get to see as much of Austin as I could walk to. I toured many of the local restaurants including the famous Torchy’s Tacos as well as the Clay Pit.

IMG_20150707_183349IMG_20150707_183355  IMG_20150709_165357 IMG_20150709_165445

These places both boasted some of the finest food I have ever had. Torchy’s Tacos, as you can guess specialized in Tacos and I ended up eating an unnamed item from the secret menu. As suspect as that might sound, I can assure you it was the best taco I’ve ever had in my life. The Clay Pit was a much more traditional dining experience than Torchy’s but the food was equally good. I hadn’t experienced much Indian food up until that point but it is a place I would definitely visit any time I’m in Austin.

Merging Galaxy Clusters


A day in the lab. Actually, every day. Actually, not so much in a lab…

Hello! We are Andre Hinds and Paul Lessard, assistants in Dr. Johnson’s astrophysics lab. Our project is working toward the goals of creating viable statistics to analyze galactic clustering, and of identify merging cluster systems in astronomical surveys, such as the Sloan Digital Sky Survey (SDSS). The long-term application of this project is to constrain the model for gravitational interactions on huge scales. We know, for example, how a ball will interact with the Earth if it is thrown off a cliff with a given speed, but the model that governs that interaction breaks down when applied to extremely large scales, such as those of merging galaxy clusters.

My (Paul) work on the project has revolved around the compiling of a list of known galaxy cluster mergers and obtaining relevant data (2-dimensional position and recessional velocity) for as many galaxies in these clusters as possible. This was done by means of a literature search. I started my search in the latest data release from SDSS, where I created a query to search through the entire database to find all galaxies within a radius referred to as R200 of a central galaxy. These central galaxies, called Brightest Cluster Galaxies (BCG’s), were all taken from another database called the MaxBCG catalog. I then ran a function in MATLAB to find all of the clusters that were within a certain distance from one another. However, while there were plenty of clusters that were within this radius of each other, they were almost exclusively understudied due to the observationally expensive nature of obtaining recessional velocities; most clusters had less than 5 galaxies with recorded recessional velocities.

From here I turned to the Merging Cluster Collaboration, a research group who study the evolution of galaxy cluster mergers. Using data published by their members has provided me with many more results. At the present, I have obtained data for 4000 galaxies across 19 merging clusters. From this data, I have calculated velocity dispersions for each cluster, a value which provides insight into the cluster’s mass. This is because a higher velocity dispersion correlates to higher velocities within the cluster, and if the velocities are higher, than there must be more mass within the cluster to keep everything bound.

sample bubble plot

Sample Bubble Plot. Larger circles correspond to a higher recessional velocity

My ongoing work involves graphically organizing this data into velocity histograms and bubble plots for use in preliminarily identifying the members of each merging sub-cluster within the mergers. Once this leg of the project has finished, my work will shift back to the velocity dispersions, as I will begin studying and modelling the mass functions of the galaxy clusters. Mass functions describe the number density of clusters above a threshold mass M, and can be used as a critical test of theories of structure formation in the universe.

sample histogram

Sample velocity histogram.

My (Andre) work this summer has been centered on developing a mathematical statistic to determine clustering in data sets. The bases of the his statistic has been the nearest neighbor principle meaning that by comparing a data point to its neighboring two points, you can determine whether or not the point is close to its neighbors relative to the average spacing of the entire data set. In the simple case, position data can be projected on to the x or y-axis and observed for clustering. The complex case will take a xy-vector and project the data onto various axes to test for clustering in various cluster orientations. The statistic, once determined arithmetically, must then be programmed to accept simulated cluster data. The simulation data was put together by our collaborator from NASAs’ Goddard Flight Center and is representative of known cluster dynamics. The center is more densely populated than the edges and the primary galaxy interaction is gravitational as opposed to collisional. The simulation data is far more complete than what can be obtained observationally but with the additional information we have a complete understanding of the simulated merger. This is done so that the statistic can be shown to provide the correct interpretation of data that we already understand. The simulation from NASA also has a few different initial parameters such as the clusters mass and the incident of the collision. Currently my statistics functional form is being fine tuned for optimum sensitivity and minimum error while working with small samples of the larger simulated data set. We use a subset of our simulation because the entire simulated data set represents a perfectly sampled cluster, which is next to impossible to achieve observationally. Observational data also only has x and y position and redshift (z velocity), where as our data has x, y, and z positions and velocities. The simulation also allows us to look at the time evolution of mergers which can’t be done observationally because the time scales are far greater than observable (hundreds of millions of years long), but the statistic I’m developing should give some insight into what point in the evolution we are observing.

andre 1

Timestep 0. Let graph shows clear clustering along the x-axis; right graph shows singular group along y-axis.

andre 5

Scatter plot for Timestep 0: The scatter shows clear clustering in the x-direction, which agrees with what our statistic tells us

andre 2

Timestep 40. As time progresses, the peaks on the x-axis get closer, implying that clusters are moving together.

andre 6

Scatter plot for Timestep 40. Although closer than at Timestep 0, there is obvious clustering along the x-direction, which agrees with what the statistic tells us

andre 3

Timestep 65. The merger along the x-axis has coalesced into one group

andre 7

Scatter plot for Timestep 65. There is no clear clustering along any axes of merger, which agrees with the statistic for this timestep

andre 4

Timestep 100. As the clusters separate, we can see a slight space between the peaks on the x-axis, implying two distinct sub-clusters

andre 8

Scatter plot for Timestep 100. Although not readily apparent, there does appear to be a slight separation, which is more apparent when looking at the statistic for this timestep.

In the future, Paul’s work determining viable cluster data sets will be used in conjunction with the statistic that I’m working on to determine clustering (and axes thereof) in any rich data set. The stage of the clustering will also be determined by using the statistic, allowing us to have an idea of how clustering progresses over time.

A Day in the Life: Humming Fish in Cape Cod

Hello! I’m Ally Siegel, a rising senior at Gettysburg College. Unlike most of the Gettysburg researchers I am spending the entire summer away from campus in Cape Cod. I could not imagine a better place to do research for the summer. There are countless beautiful beaches, sunsets, lighthouses, bike paths, and amazing 75 degree weather days. Amid all of these tourist attractions a scientific community thrives at the Marine Biological Laboratory. Over 300 scientists travel to this institution from all around the world during summers for their research. In my lab alone, the Grass Laboratory, there are 10 different graduate students and post-docs, each conducting their own individual experiments. This leads to an exciting and unique environment for collaboration and learning about different areas of research.

nobska lighthouse

Nobska lighthouse, just a short bike ride from the MBL campus

A typical day in Woods Hole starts at 8am when I check on the midshipman fish we are working with. Their tanks are in the Marine Resources Center, where most of the researchers keep their animals. This makes the building like a mini aquarium including bamboo shark, cuttlefish, squid, and octopus. The male midshipman we study vocalize, humming at night to attract females. To study this behavior we day-night reverse them so that their tanks are dark from 8am to 4pm. At 8am I also turn on a hydrophone that we use to record the fish humming.

Midshipman fish

Midshipman fish

The enclosure around the midshipman tanks used to keep their light exposure to a minimum from 8am to 4pm

The enclosure around the midshipman tanks used to keep their light exposure to a minimum from 8am to 4pm

After that I head to breakfast in Swope, the cafeteria on campus. The tables here overlook a beautiful pond filled with sail boats and even houseboats.

eel pond

Scenic Eel Pond

After breakfast I head to lab where I usually work on my project, trying to map the brain areas involved in humming. To accomplish this we use an antibody that will bind to pS6, a phosphorylated protein only present in electrically active cells. We collect brains from fish determined to be humming or not humming (as controls). Midshipman brains are just a few centimeters long. While frozen we cut them into over two hundred thin sections that are reacted with the pS6 antibody tagged with a green fluorescent marker. Then we can use a microscope the see where the antibody is within the section, showing which regions are active in humming versus non-humming fish.

Staining shown in nerve cells in the vocal motor nucleus and vocal pacemaker nucleus of a humming midshipman

Staining shown in nerve cells in the vocal motor nucleus and vocal pacemaker nucleus of a humming midshipman

After work the science doesn’t end! Most labs and courses at the MBL host a lecturer weekly, making different talks available to the MBL community everyday. Aside from attending lectures, the evenings are a perfect time to explore the many beaches!

A sunset from Nobska beach

A sunset from Nobska beach