Six scientists secure fellowships

One current undergraduate, and five alumni, from the Brandeis Sciences were honored with offers of National Science Foundation Graduate Research Fellowships in 2012. The fellowships, which are awarded based on a national competition, provide three full years of support for Ph.D. research and are highly valued by students and institutions. These students are:

  • Samuel McCandlish ’12 (Physics) , a current student who did research with Michael Hagan and Aparna Baskaran, resulting in a paper “Spontaneous segregation of self-propelled particles with different motilities” in Soft Matter (as a junior). He then switched to work with Albion Lawrence for his senior thesis research. Sam will speak about “Bending and Breaking Time Contours: a World Line Approach to Quantum Field Theory” at the Berko Symposium on May 14.  Sam has been offered a couple of other fellowships as well, so he’ll have a nice choice to make. Sam will be heading to Stanford in the fall to continue his studies in theoretical physics.
  • Briana Abrahms ’08 (Physics). After graduating from Brandeis, Briana followed her interests in ecological and conversation issues, and  in Africa as a research assistant with the Botswana Predator Conservation Trust, Briana previously described some of her experiences here in “Three Leopards and a Shower“. Briana plans to pursue as Ph.D. in Ecology at UC Davis.
  • Sarah Robinson ’07 (Chemistry). Sarah did undergraduate research with Irving Epstein on “Pattern formation in a coupled layer reaction-diffusion system”. After graduating, Sarah spent time with the Peace Corps in Tanzania, returning to study Neurosciene at UCSF.
  • Si Hui Pan ’10 (Physics) participated in a summer REU program at Harvard, and continued doing her honors thesis in collaboration with the labs at Harvard. Her award is to study condensed matter physics at MIT.
  • Elizabeth Setren ’10 was a Mathematics and Economics double major who worked together with Donald Shepard (Heller School) on the cost of hunger in the US. She has worked as an Assistant Economist at the Federal Reserve Bank of New York and her award is to study Economics at Harvard.
  • Michael Ari Cohen ’01 (Psychology) worked as a technology specialist for several years before returning to academia as  PhD student in the Energy and Resources Group at UC Berkeley.

Congratulations to all the winners!

Barry awarded Joseph Katz Fellowship from Argonne Natl Lab

Edward Francis Barry (PhD ’11) has recently been awarded the prestigious Argonne Scholar-Joseph Katz Postdoctoral Fellowship at Argonne National Laboratory. Ed began his scientific career studying the self-assembly of fd virus with Zvonimir Dogic, during the latter’s Junior Fellowship at the Rowland Institute at Harvard University. When Dogic joined the physics faculty at Brandeis, Ed also came to Brandeis as a Ph.D. student and helped to start the Dogic lab. Ed published seven papers describing various novel assemblages found in the fd system. Most notably, his 2010 Proceedings of the National Academy of Sciences paper describing the physical properties of colloidal membranes won the 2010 Cozzarelli Prize for scientific excellence. As the Katz fellow, Ed will be working between Argonne National Laboratory and the University of Chicago, where he is working with Experimental Condensed Matter Professor Heinrich Jaeger studying the self-assembly of monolayers composed of nanoparticles.

The Higgs boson – what it is and how you would find it

The Higgs Boson is an elementary particle predicted by the Standard Model of particle physics. It is associated with the Higgs mechanism that was developed with the contributions of physicists Brout, Englert, Guralnik, Hagen, Kibble and Higgs in 1964. This mechanism proposed an elegant solution to one of the standing problems in particle physics – how particles acquire mass. The elementary particles of nature have masses varying by many orders of magnitude. For instance, the top quark, the heaviest known particle yet, has a mass that is roughly 340000 times that of the electron. Neutrinos on the other hand, have masses that are constrained by experiment to only a small fraction of the electron mass. The Higgs mechanism suggests that all particles acquire their mass by the strength of their couplings to a field that permeates the whole universe – the Higgs field. The top quark does not get its higher mass because it is bigger in size; in fact it is probably no larger than an electron. It simply couples more strongly to the Higgs field to get its enormous mass at around 173 GeV. Photons do not couple to this field at all and hence are massless. The much sought after Higgs boson is the quanta of this hypothetical field, very similar to the photon being the quanta of the electromagnetic field. One of the main goals of the LHC physics program is to find evidence of this quanta, the Higgs boson.

Higgs bosons, if they exist, can be created in proton – proton collisions at the LHC but would decay instantaneously. Any search for them has to be carried out by analyzing data for signatures of Higgs decay. This is not a trivial task however, because such decays are impossible to distinguish from some other well known Standard Model processes. Collision data from LHC would have to be analyzed, and deviations from known background processes would point towards some form of new physics and possibly the existence of the Higgs boson. One would then have to compare the rates in different Higgs decay channels to see if the observed rates match those from predictions for a Higgs decay.

In December 2011, ATLAS and CMS, the two main experiments at LHC, announced their 2011 Higgs search results which led to much hype in the physics world and the media – both experiments were indeed seeing some excess in several Higgs decay channels around 125 GeV. The mass of a proton is about 0.94 GeV, so the finding suggests a Higgs boson mass that is about 133 times heavier than the proton (notice the bump in the above plot from ATLAS at around 125 GeV).

However, it is still very early to come to a conclusive statement about a discovery. Standard Model backgrounds are subject to statistical fluctuations which show themselves at various levels in experiments. A discovery would only be claimed if the deviations from expected backgrounds are over 5 standard deviations. The results announced by CMS and ATLAS in December 2011 were 1.9 and 2.6 standard deviations above expected backgrounds respectively. Though this is interesting, it is far from sufficient to provide a conclusive answer about the existence of the Higgs boson. The search will have to continue in 2012 as more data from LHC becomes available, and physicists will finally be able to give a conclusive answer to either confirm or exclude the Standard Model Higgs boson, ending a puzzle that has been around for several decades.

Serdar Gozpinar is a 5th year graduate student in the high-energy physics group at Brandeis working on the ATLAS experiment at CERN.

A new twist on interfacial tension

In a mixture of two molecular components, the surface tension is defined as the energetic cost per unit area of moving molecules from the bulk and bringing them to the interface. The higher the magnitude of the surface tension, the greater the tendency of two components to demix. Surface tension allows trees to carry nutrients from the roots out to the branches, and water striders to walk on the surface of water.

The interface between hydrophobic and hydrophilic components has very high interfacial tension. A common way to adjust the magnitude of surface tension is to add amphiphilic molecules (like soaps), which contain both hydrophilic and hydrophobic components. These amphiphilic molecules prefer to be at the interface between the two components, and effectively lower the interfacial tension, allowing the components to mix more easily. This is how detergent causes oily stains to dissolve in water.

In a recently published article in Nature, an interdisciplinary team of researchers at Brandeis headed by Zvonimir Dogic, and consisting of experimental, theoretical, and computational physicists as well as biologists, has demonstrated a new way of controlling interfacial tension using a molecular property called chirality, or lack of mirror symmetry. The study was performed on a model system of two-dimensional colloidal membranes composed of the rod-like bacteriophage virus fd, which are about one micrometer in length and 7 nanometers in diameter. The electrostatically repulsive virus particles are condensed into membranes through the depletion mechanism by adding non-adsorbing polymer to a virus suspension. Because the fd rods are chiral, they tend to twist by a small angle with respect to neighboring rods. However, the geometry of the membrane prevents twisting in the structure’s interior; only along the perimeter can the rods twist. Thus, increasing the strength of chirality of the rods both lowers the energy of the rods along the membrane’s edge and increases the frustration of untwisted rods in the bulk, lowering the interfacial tension. This contrasts the standard method of controlling interfacial tension using amphiphilic molecules, since the rod-like particles are completely homogenous, and do not contain any hydrophilic components.

The strength of chiral interactions in fd is temperature sensitive; the rods are achiral at 60o C, and the strength of chirality increases with decreasing temperature. By increasing the strength of chiral interactions in-situ, the team of researchers was able to dynamically vary the membrane’s interfacial tension in order to drive a dramatic transition from a membrane to several twisted ribbon structures (Movie 1). The twisted ribbons have much more interfacial area than the membranes, but are much “twistier” structures, and are therefore favored when the strength of chirality is relatively high. Additionally, the team was able to drive the same membrane-to-ribbon transition using optical tweezers, as shown in Movie 2. Membranes and ribbons are only two of a myriad of structures that were observed in the fd system. This work presents a powerful new method to control the assembly of materials by tuning interfacial tension with chirality.

Shear-induced jamming

From breakfast cereals to sand on a beach, granular materials are all around us. Under different conditions, these materials can exhibit liquid-like behavior (flowing) as well as solid-like behavior. The transition between solid and liquid phases has been known as the jamming transition.

The basic concept of jamming is pretty intuitive. A simple example of what can induce jamming is the following: compacting loose sand inside a container increases its density. When the container is removed, the sand can form a self-supporting pile, hence becoming jammed. Jamming has been studied extensively in numerical simulations of systems composed of idealized grains without frictional forces.  These studies find a critical density at which jamming occurs. Since these idealized granular materials are non-cohesive (no attractive forces between them)  they can become solids only through externally imposed pressure, such as through compaction, and therefore a critical density makes sense.  Real granular materials, however, have friction, and how this affects jamming is not well understood.

An experimental image of typical Shear Jammed state in a 2-D frictional granular material. The shear strain is applied in the horizontal direction. Red colored grains form the backbone of the system, which provides rigidity with respect to external shear

Newly published in Nature, are results of a collaboration between Prof. Bulbul Chakraborty’s group at Brandeis and Prof. Behringer’s group at Duke University, which show a new class of jammed states in frictional granular materials. This new class of “Shear-Jammed” states exhibits a richer phenomenology than previously seen. An initially unjammed or loose granular material can become jammed not just by increasing its density, but by applying shear strain on it while holding the density fixed. Shear-Jammed states are inherently anisotropic in their stress and grain-to-grain contact network (see photo above). The transition from an unjammed to shear-jammed state is clearly marked by a percolation of the strong force chains in all directions (see video below). The phenomenon of shear-jamming does not currently have a fundamental theoretical description. Ongoing work in Prof. Chakraborty’s group attempts to construct a theoretical framework for this non-equilibrium phase transition using a generalization of equilibrium statistical ensembles.

This video shows the evolution of the strong force cluster and transition from unjammed to fragile and eventually to SJ. The video shows experimental states created under pure shear. Green colored grains form the strong force cluster defined in the paper. Initially, the system is unjammed. As the fraction of force bearing grains increases with increasing strain, the strong force cluster percolates in the compressive (vertical) direction and we call the state fragile.  Eventually the system becomes percolated in all directions with sufficient number of force bearing grains. We call these states Shear Jammed.

see also:

Higgs Boson Search Webcast

Craig Blocker writes:

The Higgs boson has been sought for many years by high energy physics experiments.  It is the only particle in the standard model of particle physics that has not yet been observed and plays a crucial role since it gives mass to the other fundamental particles.

Tomorrow at 8:00 am EST (Tues., Dec. 13), CERN is giving a seminar (webcast) about the status of the search for the Higgs at the LHC by the two general purpose detector collaborations, ATLAS and CMS.  Although the data is not quite strong enough yet to claim a discovery, the evidence is becoming strong.

The Physics Department will show a web cast of this seminar in Abelson 131. The Brandeis high energy group has been a member of the ATLAS experiment for many years and has been instrumental in building parts of the detector that are key to this measurement.  I will be there to answer any questions.

Although it is early in the morning for most, if you are interested, please come to what should be a very interesting talk.


Eisenbud Lectures: “The Mathematics of Dynamic Random Networks”

This year’s Eisenbud Lectures in Mathematics and Physics will be given by Dr. Jennifer Chayes, Distinguished Scientist and Managing Director of Microsoft Research New England. Dr. Chayes is well known for her work on the phase transitions in combinatorial and computer science problems; she is a world expert on the study of random, dynamically growing graphs, which can be used to model real-world social and technological networks.

Dr. Chayes received her PhD in mathematical physics from Princeton.  After postdoctoral fellowships at Harvard and Cornell, she was on the faculty at UC Los Angeles before co-founding the theory group at Microsoft Research in Redmond, Washington.  In 2008 she co-founded Microsoft Research New England. She is a fellow of the American Association for the Advancement of Science, the Fields Institute, and the Association for Computing Machinery; she is also a National Associate of the National Academies.

The Eisenbud Lectures are the result of a generous donation by Leonard and Ruth-Jean Eisenbud, intended for a yearly set of lectures by an eminent physicist or mathematician working close to the interface of the two subjects. Dr. Chayes’ distinguished career working on fundamental issues in mathematics, physics, and computer science makes her an ideal speaker for this series.

The lectures will take place at 4 PM on Tuesday Nov. 29 and at 4:30 PM on Thursday Dec. 1. both in Abelson 131.  A full description of the lectures can be found below. Driving directions, maps, links to the MBTA, and so forth can be found at:  If you need parking, please contact Catherine Broderick at  A reception will be held after the first lecture on Tuesday November 29th from 5pm – 7pm in the Faculty Club Lounge at Brandeis.  All are welcome.

Everybody should come out to hear this year’s lectures!  They promise to be a lot of fun.

During the past decade, dynamic random networks have become increasingly important in communication and information technology.  Vast, self-engineered networks, like the Internet, the World Wide Web, and online social networks, have facilitated the flow of information, and served as media for social and economic interaction.  I will discuss both the mathematical challenges and opportunities that exist in describing these networks:  How do we model these networks – taking into account both observed features and incentives?  What processes occur on these networks, again motivated by strategic interactions and incentives, and how can we influence or control these processes?  What algorithms can we construct on these networks to make them more valuable to the participants?  In this talk, I will review the general classes of mathematical problems which arise on these networks, and present a few results which take into account mathematical, computer science and economic considerations.  I will also present a general theory of limits of sequences of networks, and discuss what this theory may tell us about dynamically growing networks.

LECTURE 1:  Models and Behavior of the Internet,  the World Wide Web and Online Social Networks
Although the Internet, the World Wide Web and online social networks have many distinct features, all have a self-organized structure, rather than the engineered architecture of previous networks, such as phone or transportation systems.  As a consequence of this self-organization, these networks have a host of properties which differ from those encountered in engineered structures:  a broad “power-law” distribution of connections (so-called “scale-invariance”), short paths between two given points (so-called “small world phenomena” like “six degrees of separation”), strong clustering (leading to so-called “communities and subcultures”), robustness to random errors, but vulnerability to malicious attack, etc.    During this lecture, I will first review some of the distinguishing observed features of these networks, and then discuss some of the models which have been devised to explain these features.  I will also discuss processes and algorithms on these networks, focusing on a few particular examples.

LECTURE 2:  Convergent Sequences of Networks
In the second lecture of this series, I will abstract some of the lessons of the first lecture.  Inspired by dynamically growing networks, I will ask how we can characterize general sequences of graphs in which the number of nodes grows without bound.   In particular, I will define various natural notions of convergence for a sequence of graphs, and show that, in the case of dense graphs and even some sparse graphs, many of these notions are equivalent.  I will also give a construction for a function representing the limit of a sequence of graphs.  I’ll review examples of some simple growing network models, and illustrate the corresponding limit functions.  I will also discuss the relationship between these convergent sequences and some notions from mathematical statistical physics.

Dynamics of double-strand break repair

In a new paper in the journal Genetics, former Brandeis postdoc Eric Coïc and undergrads Taehyun Ryu and Sue Yen Tay from Professor of Biology Jim Haber’s lab, along with grad student Joshua Martin and Professor of Physics Jané Kondev, tackle the problem of understanding the dynamics of homologous recombination after double strand breaks in yeast. According to Haber,

The accurate repair of chromosome breaks is an essential process that prevents cells from undergoing gross chromosomal rearrangements that are the hallmark of most cancer cells.  We know a lot about how such breaks are repaired.  The ends of the break are resected and provide a platform for the assembly of many copies of the key recombination protein, Rad51.  Somehow the Rad51 filament is then able to facilitate a search of the entire DNA of the nucleus to locate identical or nearly identical (homologous) sequences so that the broken end can pair up with this template and initiate local copying of this segment to patch up the chromosome break.  How this search takes place remains poorly understood.

The switching of budding yeast mating type genes has been a valuable model system in which to study the molecular events of broken chromosome repair, in real time.  It is possible to induce synchronously a site-specific double-strand break (DSB) on one chromosome, within the mating-type (MAT) locus.  At opposite ends of the same chromosome are two competing donor sequences with which the broken ends of the MAT sequence can pair up and copy new mating-type sequences into the MAT locus.

Normally one of these donors is used 9 times more often than the other.  We asked if this preference was irrevocable or if the bias could be changed by making the “wrong” donor more attractive – in this case by adding more sequences to that donor so that it shared more and more homology with the broken ends at MAT.  We found that the competition could indeed be changed and that adding more homologous sequences to the poorly-used donor increased its use.

In collaboration with Jané Kondev’s lab we devised both a “toy” model and a more rigorous thermodynamic model to explain these results.  They suggest that the Rad51 filament carrying the broken end of the MAT locus collides on average 4 times before with the preferred donor region before it actually succeeds in carrying out the next steps in the process that lead to repair and MAT switching.

Dynamics of homology searching during gene conversion in Saccharomyces cerevisiae revealed by donor competition Eric Coïc , Joshua Martin, Taehyun Ryu, Sue Yen Tay, Jané Kondev and James E. Haber. Genetics. 2011 Sep 27 2011 Sep 27

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