Faculty of Science

Department of Physics



Research Page of Nikolay Kolev


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Research Statement

Being a Physicist

In all physics fields – well established and newly developed, conservative and fashionable, relating to elementary particles, material properties or biological systems – there is one common passion that I believe is shared by all physicists: to understand at least a tiny new bit of how the natural world ticks.

Every physical system is governed by laws, and although it was earlier believed (e.g. Richard Feynmann supported this opinion) that two systems exhibiting similar behavior do not have more in common except that they are described by same or similar equations, the abstract studies of systems and properties themselves turn out to be very fruitful, especially at the boundary between different fields or sciences. Behaviors are observed (common phenomena like chaos, scaling, or renormalization) and patterns are established, common for seemingly unrelated and with very distant components phenomena. The search for such common patterns and behaviors becomes extremely important nowadays, when several multidisciplinary scientific fields are flourishing (nanotechnologies, biophysics, computational chemistry). Apart from making possible the utilization of already established models and procedures of one field into another (there is the well-known case of M. Gell-Mann developing group theory from scratch for particle physics applications, being unaware that the apparatus was already well developed in mathematics), these common behaviors and patterns make us wonder whether it is just pure coincidence, and admire the harmony of the natural world exhibited through them.

International Linear Collider and Taus

The proposed International Linear electron-positron Collider (ILC) would be the next natural step in our attacks on the mechanisms governing particle interactions at the high energy limits. Whatever new physics will be discovered at the LHC, the ILC would be in general capable of more precise and detailed measurements. It would be able to provide more exact answers to questions we already ask (do supersymmetry or extra dimensions exist, what is the composition and properties of dark matter) and to start answering questions that themselves will be asked by the results of the LHC.

As a continuation of a project started by colleagues from TAMU and again in collaboration with them, we started an ILC project which will also rely on tau signatures of supersymmetric signals in the coannihilation region. Currently we are reproducing previous results, learning how to use the ILC java integrated simulation and reconstruction environment and performing initial simulations with background and signal events at new beam energies.

Large Hadron Collider and Taus

In one of the most steadily developing fields during the last few decades - high energy particle physics - we are in the Large Hadron Collider (LHC) age. The LHC starts operations in 2008 and its experiments carry serious expectations as to the discovery of the long-sought Higgs, but also the discovery of new physics beyond the Standard Model.

Supersymmetry (SUSY) is a leading candidate to extend the Standard model and opens a unique possibility for unification of fundamental interactions. Furthermore, SUSY produces a candidate for the astronomically observed dark matter in the Universe – the lightest neutralino.

Recent theoretical analyses show that there are three distinct regions of the SUSY parameter space which explain the dark matter content of the universe ~ 23%. One of these regions appears for smaller values of particle masses and therefore will be easily accessible at the LHC. This region is called the stau-neutralino coannihilation region. In this region the stau mass and the neutralino mass are very close. Both these particles were thermally available at the same time in the early Universe. SUSY particles from this region will be copiously produced at the LHC. The signal from the region is characterized by the existence of the low PT tau lepton due to the small mass difference DeltaM between stau and netralino and 5 to 15 GeV. The detection of the signal from this region will allow us to explain the dark matter content of the universe and properly connect cosmology with particle physics.

I have worked on how we can detect such SUSY events in the cosmologically-allowed region using the minimal supergravity (mSUGRA) model. The stau coannihilation region exist in all SUSY models, but we have chosen the mSUGRA model because it is simple and well motivated. My recent work successfully shows that using hadronically decaying taus, the mass difference can be determined with an uncertainty of 12% for DeltaM = 10 GeV, with additional uncertainty of 14% if the gluino mass has an uncertainty of 5%, at 10 fb-1 luminosity at the LHC, if tau leptons can be identified with PT > 20 GeV.

The analysis also crucially depends on the efficiency of tau identification of these low-PT taus and its fake rate. Some investigation was completed recently in this respect. As all the rest of my LHC research, this was done in collaboration with colleagues from Texas A&M University. The project is ongoing.

GlueX, Exotic Mesons, Calorimetry

While looking at higher and higher energies in an attempt to find answers about the fundamental interactions (in the context of the Grand Unification for example), we still have many unanswered questions within the range of energies that have been available for decades. The nature of confinement in the strong interaction theory (Quantum Chromodynamics) is one of these questions. A leading model is the flux tube model, in which additional mesons with exotic quantum numbers arise (the so called exotic mesons). GlueX is an international collaboration which is designing an experiment in Hall D of Jefferson Lab in search of the gluonic degrees of freedom and exotic mesons.

My contribution to the GlueX project consists of participation in the Barrel Calorimeter design and optimization, initial design of the tables and interface for the calibration and parameters database, and managing the computer resources of the SPARRO group (the participant from the Department of Physics of the University of Regina). This involved GEANT Monte Carlo simulations, simulation data analysis, and gaining a lot of knowledge about calorimetry (electromagnetic calorimetry specifically). I no longer participate in GlueX.

Strongly Correlated Systems and Superconductivity

As complicated as it may seem, particle physics is somewhat simpler and can provide more direct answers and has more developed theory than condensed matter physics and especially strongly correlated systems, in which electron correlations are not a small perturbation to the Hamiltonian. In many such systems there are additional complications from the strong interplay of different degrees of freedom (charge and orbital ordering, magnetic, etc.), which make their study especially interesting and challenging. I have participated in the study of several such systems in the Texas Center for Superconductivity at the University of Houston, most with Raman spectroscopy, but also taking part in magnetic and electron microscopy measurements.

Computers and Simulations as Useful Tools

Although computer simulations are often regarded as preliminary tools helping in design and development of particle detectors, they are invaluable tool in getting at least qualitative knowledge about particle interactions and especially the signatures they may produce in detectors.

Several computer simulations programs are widely used in particle physics. Probably the most widely used and well-known is the GEANT full simulation. I have performed a couple of studies with the FORTRAN version GEANT 3 (including my B.S. Thesis) and am currently learning the object-oriented GEANT 4.

There are an abundance of fast detector simulations, which are specific for each detector, and I have gained experience with several of them.

A common required step before doing the detector simulation is the production of the particles in the specific experiment by an event generator. Several such generators are widely used and have certain features that make them suitable for specific tasks. The most general to my knowledge is Pythia, but in the course of my work have most extensively used Isajet.

Current particle physics experiments are very computation intensive. The data storage, transfer, and analysis challenges are enormous. The need to share data and results requires more and more sophisticated and better organized environments such as grids. Object oriented programming seems to be winning the battle over the more restricting and perhaps code-maintenance intensive (but also more numerically efficient) FORTRAN versions. Clusters with batch queuing systems are everywhere, often with grid tools and web interfaces incorporated. The computation aspects in particle physics are of essential importance in any experiment, and I have luckily been involved in many such aspects (developing a GUI for a reconstruction package, gaining experience with the installation and management of the OpenShop framework for GlueX, etc.). I am very interested in the new alternatives available for computational physicists and open to new ideas and implementations.

Since the computation part is essential to particle physics, it is always an open project for me.

Biophysical Connection - Polymers and Foodwebs

As weird as the notion of physicists in biology, ecosystems and polymer science would have sounded 30 years ago, physicists are seriously invading other sciences and interdisciplinary fields. I have completed a couple of academic projects – one on polymers (involving a Monte Carlo simulation with the pivot algorithm to extract some properties in a 3-D cubic phase), and one on foodwebs (essentially making a model of a simple ecosystem and observing the resulting relations between systems given the basic rules and laws of “who eats who”). I still enjoy looking at these simulations in my spare time and read new papers on the topics occasionally. I find it fascinating that concepts like scaling, random number distributions, and chaos, can be productive in environments so different from those in which they were discovered for the first time.

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