Developer Medical
Resume:
Curriculum Vitae
DANIEL DOOKEE CHO, Ph.D.
Personal
Address: New York Presbyterian Hospital/Weill Cornell Medical College
*** **** **** ******, *** 1S, New York, NY 10021
Phone: 630-***-****
E mail: *****.*******@*****.***
Citizenship and VISA Status
South Korea, Green Card
Education
2014 Medical Physics Residency (Therapy) at the New York Presbyterian Hospital
Columbia University and Cornell University, New York, NY
CAMPEP accredited 2 years programs
(3 years of full time equivalent clinical experiences)
2005 Ph.D., Physics, University of Rochester, Rochester, NY
1996 Mandatory military service, South Korea
1994 M.Sc., Physics, Korea University, Seoul, South Korea
1992 B.S., Physics, Korea University, Seoul, South Korea
Position Held
2011 Postdoc and Physics Resident, Department of Radiation Oncology Weill Cornell
Medical College, Cornell University, New York, NY
2009 2011 Research Associate, Physics Department Brown University, Providence, RI
2005 2008 Research Associate, Physics Department Boston University, Boston, MA
License and Certification
Passed ABR part 1 (2013) and Eligible for part 2 (8/2014)
Plan to apply full certification (part 3) on 2015
Holding New York Medical Physics Permit
Publications and Presentations in Medical Physics
2014 AAPM accepted “Improving Radiotherapy Toxicity based on Artificial Neural
Network (ANN) for Head and Neck Cancer Patients”
2014 ASTRO accepted “Predicting Radiotherapy Outcome for Head and Neck Cancer
Patients using Artificial Neural Network (ANN)”
2013 AAPM presented “Beam Selection for 4π Non Coplanar Converging (4PiNC)
Delivery using a Genetic Algorithm (GA)”
2013 ASTRO presented “Optimizing 3D Conformal plans for 4π Non Coplanar
Converging (4PiNC) Beams using a Genetic Algorithm”
Experience: 2 Year Medical Physics Residency (2012 2014)
Treatment Equipment
Linac Monthly QA, Annual QA and Acceptance test
Pinnacle3 TPS commissioning
Patient specific IMRT QA using ion chamber, Film, Mapcheck and ArcCheck
CT simulator Monthly QA
Dosimetry
Conventional 3D CRT treatment planning using Pinnacle3 TPS and Brainlab TPS
IMRT treatment planning using Pinnacle3 TPS and Brainlab TPS
VMAT/RapidArc treatment planning using Pinnacle3 TPS and Brainlab TPS
MU Hand Calculations
Patient Chart Checks
Printing Plans using MOSAIQ Record and Verification System
Brachytherapy
Prostate, as well as brain, seed implants
Clinical treatment processes for Cylinder, MammoSite, Contura and Henschke techniques
HDR source calibrations
HDR treatment day QA checks
Intrabeam treatment processes and learn how to calibrate Intrabeam source
Inventory for brachytherapy sources
Special Techniques
Total body irradiation treatment (TBI) procedure and performing related dose calculations
The specific electron behavior and dosimetry for Total skin irradiation treatment (TSET)
The basic principle and dosimetry for Stereotactic Radiosurgery (SRS) and GammaKnife
Radiosurgery and participated in the treatment process
Data Management
Archive Brainlab patient data
Archive Pinnacle3 TPS institute
Treatment Planning System QA
Radiation Safety/Quality assurance
NRC and state regulations for radiation safety, personal monitoring and QA
Ionization chamber calibration and intercomparison and survey meter calibration checks
Attend meetings for quality management and continuous quality improvement programs
Professional Experience in Physics: Lead positions during 2005 2011
Lead Top Quark Physics Analysis at DØ, April 2007 2011
Lead Administrator of Computer Analysis Cluster at DØ, April 2008 2011
Global Vertex Algorithm Group Convener at DØ,March 2006 2011
Professional Experience in Physics: Experiments during 1998 2011
Developer of Top Quark Physics Algorithm and Analysis tools at DØ, 2007 2011
Manager/Developer of Computer Analysis Cluster at DØ, 2008 2011
Developer of Primary Vertex algorithm at DØ, 2006 2011
Developer of Silicon Tracking Trigger (STT) at DØ, 2005 2007
Developer of electron/photon identification algorithm at DØ, 1999 2004
Developer of τ identification algorithm at DØ, 2000 2001
Developer of Monte Carlo software (DØgstar) at DØ, 1998 2000
Operating systems worked on: UNIX/Linux, VAX/VMS, MS WINDOWS
Programming languages: Fortran, Pascal, C/C++, Python, ROOT
Teaching Experience
Advising PhD. students at Brown University, 2006 2008
Teaching Assistant at University of Rochester,1997 1998
Invited Talks
2011 Rencontres de Moriond : QCD and High Energy Interactions: “Searches for New
Physics in Top Events at the Tevatron,” La Thuile, Aosta Valley, Italy March 20 27
2009 Top@Tevatron 4 LHC at UC Davis Nov. 20, 21: “Top related new physics searches
at the Tevatron; the possible anomaly in the top forward backward asymmetry; and the
possibility of studying boosted top at the Tevatron” to prepare for LHC
2008 16th International Workshop on Deep Inelastic Scattering and Related Subjects:
“Top Cross Section and Production Measurements at the Tevatron,” Apr. 7 11
2007 Aspen Winter Conference On Particle Physics: New Physics at Electroweak Scales
and New Signals at Hadron Colliders: “SM Higgs Searches at the Tevatron,” Jan. 8 13
Contributed Talks with Students
General Meeting of the American Physical Society, Apr. 30 May 3, 2011, Anaheim,
California, given by JeongKu Lim, “Search for a fourth generation t’ quark that decays to
W boson + jet”
General Meeting of the American Physical Society, May 2 5, 2009, Denver, Colorado,
given by Sehwook Lee, “Measurement of the ttbar Production Cross Section in the
Lepton+Jets Channel with Lifetime Tagging”
General Meeting of the American Physical Society, April 14 17, 2007 Jacksonville,
Florida, given by Hwidong Yoo, “Measurement of the ttbar Production Cross Section in
the Lepton+Jets Channel with Lifetime Tagging”
General Meeting of the American Physical Society, April 14 17, 2007 Jacksonville,
Florida, given by Hwidong Yoo, “Measurement of the ttbar Production cross section at DØ
using event kinematics”
Joint Meeting Of Pacific Region Particle Physics Communities, Oct. 29 Nov 3,
2006,Honolulu, Hawaii, given by Maren Vaupel, “Measurement of the ttbar Production
Cross Section Using Kinematic Variables and a search for resonant ttbar production”
General Meeting of the American Physical Society, April 20 23, 2002, Albuquerque, New
Mexico, D.K.Cho, “Monte Carlo Study of Resolution in Electron and Photon Position in the
DØ Central Calorimeter for Run II”
Research Experience and Current Projects
Postdoc Researcher & Physics Resident: Weill Cornell Medical School,
2011 2014
Predicting Radiotherapy Outcome for Head and Neck Cancer Patients using
Artificial Neural Network (ANN): Advanced head and neck (H&N) cancer is an
aggressive cancer commonly treated with a combination of surgery, radiation and/or
chemotherapy. However, these cancers have a poor outcome due to local recurrences
and distant metastasis. In addition, such treatments may result in serious normal tissues
complications such as necrosis/fistula etc. Therefore this is very useful that physician can
estimate the outcomes based on the knowledge of information the patient provided and
choose the proper treatment for local control, distant metastasis and the level of toxicity.
Although outcome prediction can be done statistically, it is very hard to consider multiple
correlations simultaneously for individual patients. Since an artificial neural network
(ANN), on the other hand, can combine variables into a predictive model during training
and consider all possible correlations of variables, I built an ANN to predict outcomes for
high risk H&N patients based on data from 73 patients with advanced H&N cancer treated
with external beam radiotherapy and/or chemotherapy at our institution. The technique I
used is already very popular and well defined method in high energy physics. Since I was
working in developing algorithms to utilize the ANN to find specific solutions, i.e.
Identification of Top Quark using its basic properties of measurements from detector, I
applied this technique to Radiation Therapy. The individual patient data consisted of age,
sex, site, stage, pathology, the chemotherapy, RT technique, time of completion, dose of
RT, addition of brachytherapy, surgery and any additional variable that was considered
relevant in patient outcome. In the first step I digitized the data based on the significance
and fed them to ANN as input nodes. We defined 22 hidden nodes (for the 11 input
nodes) to take care of the correlations of input nodes. We estimated three individual
outcomes, the status of local control and the status of distant metastasis as well as the
expectation of the level of toxicity after radiation treatment. For local control outcome the
accuracy for all combined set was 90.4% (training set: 94.1%, validation set: 90.9%, test
set: 90.9%). For distant metastasis outcome the accuracy for all combined set was 91.8%
(training set: 92.2%, validation set: 90.9%, test set: 90.9%). For toxicity estimations, I
trained the data within 10% of errors of outcome and in the end we have the toxicity
estimation with 74% of accuracy. So that I proved in principle that ANN can be a very
useful tool for predicting the RT outcomes for high risk H&N patients and it is applicable to
any other cases.
This works will be shown in 2014 ASTRO “Predicting Radiotherapy Outcome for Head and
Neck Cancer Patients using Artificial Neural Network (ANN)” and 2014 AAPM “Improving
Radiotherapy Toxicity based on Artificial Neural Network (ANN) for Head and Neck Cancer
Patients.”
Optimizing 3D Conformal plans for 4π Non Coplanar Converging (4PiNC)
Beams using a Genetic Algorithm (GA): We have proposed a novel 4PiNC beam
delivery system (paper in preparation), in which the X ray source aims at the isocenter but
rotates around a point on the superior inferior axis in a conical fashion. Since this 4PiNC
beam delivery can significantly improve the plan quality for radiotherapy, I investigated an
automatic beam optimization algorithm for the proposed system to select the beams that
produce the best planning target volume (PTV) coverage while sparing the organs at risk
(OARs). Mathematically, each rotation of the proposed 4PiNC system forms a cone
where the vertex is the isocenter and the base is the area bounded by the circular
trajectory of the x ray source. By changing the cone angle, this system allows hundreds of
non coplanar beams to be delivered without couch rotation. I developed a genetic
algorithm (GA) to select the beams among hundreds of available beams that will minimize
the cost function of predefined importance factors including PTV coverage, conformity
index and dose to OARs. For each generation, the GA produces a number of offspring by
randomly turning on or off a group of randomly selected beams from the parent. The cost
function for each offspring is evaluated and the offspring with the minimum cost function
is selected as the parent for the next generation. This process is repeated until all preset
OAR constraints are met. We tested this GA on a prostate (600cGyx5) case and a
pancreas (650cGyx5) case using 179 4PiNC beams distributed among 5 cone angles (
40, 20, 0, 20, 40). Two beam openings were examined: PTV, i.e., the beam eye view
conformed to the PTV or (2) PTV OAR which is similar to (1) except that the OAR was
blocked. Traditional IMRT plans were also produced for both cases using the same OAR
constraints. Mean PTV dose (DPTV) and V95 of all plans were calculated for comparison.
Each plan was renormalized to max out the OAR dose constraints. For the prostate case,
the PTV optimization selected 68 beams and produced a 3D conformal plan (DPTV =
3048 cGy, V95 = 93%) comparable to the IMRT plan (DPTV = 3117 cGy, V95 = 95%).
The PTV OAR optimization selected 136 beams and had the best OAR sparing but the
PTV coverage was insufficient (DPTV = 3553 cGy, V95 = 63%). For the pancreas case,
the PTV plan (85 beams, DPTV = 3305 cGy, V95 = 90%) was also comparable to the
IMRT plan (DPTV = 3297 cGy, V95 = 90%). The developed GA provides a simple but
effective method for selecting good 4PiNC beams that are conformed to PTV with minimal
OAR exposure. The selected beams can produce 3D conformal plans comparable to
traditional IMRT plans. This GA can also be used to select beams for 4PiNC IMRT
planning to reduce the computation burden for IMRT optimization. We are currently
comparing 4PiNC 3D conformal plans with VMAT plans for other treatment sites and
submitting the paper as well as developing the algorithms with ANN technique. This work
were shown in 2013 ASTRO “Optimizing 3D Conformal plans for 4π Non Coplanar
Converging (4PiNC) Beams using a Genetic Algorithm” and 2013 AAPM “Beam Selection
for 4π Non Coplanar Converging (4PiNC) Delivery using a Genetic Algorithm (GA).”
Research Associate: Brown University, 2009 2011
• Search for ttbar Resonances: I have worked on a search for a narrow width heavy
resonance decaying into top quark pairs (X ttbar) in ppbar collisions at a center of mass
energy s = 1.96 TeV. The Top quark has by far the largest mass of all the known fermions.
Heavy, yet unknown resonances may play a role in the production of top pairs and add a
resonant part to the Standard Model mechanism. Such resonant production is possible for
massive Z like bosons in extended gauge theories, Kaluza Klein states of the gluon or Z
boson, axigluons, topcolor and other theories beyond the Standard Model. Independent of
the exact model, a narrow width resonance should be visible in the ttbar invariant mass
distribution. A wide resonance will be very hard to observe in the ttbar spectrum. For this
search I considered the lepton+jets final state. The event signature is one isolated electron
or muon with high transverse momentum, large transverse energy imbalance due to the
undetected neutrino, and at least three jets, two of which result from the hadronization of b
quarks. I have analyzed about 5.3 fb 1 of DØ data taken during August 2002 to September
2009 at Fermilab, Illinois. The signal to background ratio was improved by identifying b jets
using a neural network based b tagging algorithm. After b tagging, the dominant physics
background for a resonance signal is non resonant Standard Model ttbar production.
Smaller contributions arise from the direct production of W bosons in association with three
or more jets (W +jets), as well as instrumental background originating from multijets
processes with jet faking isolated leptons. I compared the distribution of the total observed
invariant mass in data with templates for expected Standard Model backgrounds and
narrow resonance signals of various masses. This work is described in “Search for a
Narrow ttbar Resonance in ppbar Collisions at s = 1.96 TeV,” V. M. Abazov et al. [DØ
Collaboration], Phys. Rev. D 85, 051101 (2012) [ arXiv:1111.1271 [hep ex]].
• Search for t': I have worked on searching for pair production of a new heavy particle that
decays to Wb final states in the lepton+jets channel. Measurements of the partial width of
the Z boson to invisible final states at LEP exclude the existence of a fourth neutrino flavor
with mass less than half the Z boson mass. This is often interpreted as an exclusion of a
fourth generation of fermions. However, the χ2 of the global electroweak fit does not get
worse when a fourth generation of fermions is included with a neutral lepton with a mass
that is a few GeV above half the mass of the Z boson. The up type quark of this fourth
generation, t’, can either decay to its down type partner, b’ or to a q quark plus a W boson
where q=d, s, b. Another source of a heavy new particle that decays to Wb is the partner, T,
of the t quark that is predicted by little Higgs models. The T can be pair produced in ppbar
collisions if its mass is not too high and the decay T Wq is expected to have a branching
fraction of about 50%. For this search I used pair production of a narrow fourth generation
t’ quark as the benchmark process. We assumed that the b’ quark is not light enough for
the decay t’ Wb’ to be kinematically allowed so that the t’ quark always decays to Wq.
The results are produced using about 5.3 fb 1 of DØ data taken during August 2002 to
September 2009 at Fermilab, Illinois.
This work has been published in “Search for a fourth generation t’ quark in ppbar collisions
at s=1.96 TeV,” V. Abazov, et al[DØ Collaboration], Phys Rev
Lett.107.082001[arXiv:1104.4522v1].
The preliminary result was shown in the conference for the 35th International Conference
on High Energy Physics: ICHEP 2010, Paris, France, 21 28 Jul 2010 (the proceeding of
”Searches for Massive t’ quarks decaying to W + q at the Tevatron” (PoS
ICHEP2010:402,2010) ) and the final result was shown in the international conference:
Rencontres de Moriond: QCD and High Energy Interactions for “Searches for New Physics
in Top Events at the Tevatron,” La Thuile, Aosta Valley, Italy March 20 27,2011.
Research Associate: Boston University, 2005 2009
Search for Charged Higgs Boson: An the extension of measurements of top
quark cross section provided an opportunity to search for charged higgs bosons from top
quark decays in ttbar events. Using one lepton (electron e or muon µ) and at least three
jets, where one of the top quarks decays to a W boson and a b quark (as in the Standard
Model (SM)) and the other top quark to a H boson and a b quark, our signal considers
events in which the W boson decays leptonically (e, µ or τ, with the τ decaying to an e or
µ and two neutrinos), while the charged Higgs decays to a τ and a neutrino and the τ
decays to a neutrino and hadrons. The final state therefore consists of an isolated lepton
(e or µ) with large transverse momentum (pT ), significant missing transverse energy
(missing ET) from the escaping neutrinos, and at least three jets: two from b quarks and
one from the decay of the τ . The goal is to measure the branching ratio of B(t H+b)
under the constraint B(t W +b)+ B(t H+b) = 1. Using 0.9 fb 1 of lepton+jets data
collected with the DØ detector at the Fermilab Tevartron ppbar collider, we found no
evidence for a H signal. Hence we excluded B(t H+b) > 0.24 for mH = 80 GeV and B(t
H+b) > 0.19 for mH = 155 GeV at the 95% C.L.
This work is described in “Search for Charged Higgs Bosons in Decays of Top Quarks,”
V. M. Abazov et al. [DØ Collaboration], Phys. Rev. D 80, 051107 (2009)
[arXiv.org:0906.5326 [hep ex]].
This work has been shown in the conference for third International Workshop on
Prospects for Charged Higgs Discovery at Colliders : Uppsala University, Sweden, 27 30
Sep 2010 and the result was published in the proceeding of ” Review of charged Higgs
searches at the Tevatron” (FERMILAB CONF 10 540E)
Top Cross Section: I measured the top quark pair production cross section in proton
antiproton collisions at s =1.96 TeV by applying a topological discriminant with newly
developed simultaneous fit methods and by counting events tagged with a b tagging
algorithm using e+jets and µ+jets final states from 1 fb 1 of data. We presented these
results at DPF ’06 and Moriond ’07, and published the analysis in Physical Review Letters
in May 2008. We combined the cross section measurements from both techniques to
obtain the most precise published measurement of the top pair production cross section.
By comparing the measured cross section to predictions, we checked whether the top
quark conforms with expectations of the standard model. This comparison has provided
the first such independent constraint on the top quark mass.
This work is described in “Measurement of the ttbar production cross section in ppbar
collisions at s = 1.96 TeV,” V. M. Abazov et al. [DØ Collaboration], Phys. Rev. Lett. 100,
192004 (2008) [arXiv:0803.2779 [hep ex]].
The work has been shown in the conference for 16th International Workshop on Deep
Inelastic Scattering and Related Subjects (DIS 2008), London, England, 7 11 Apr 2008
and the result was published in the proceeding of “Top cross section and production
measurements at the Tevatron,” (London 2008, Deep inelastic scattering)
This work was done with a student and described in his Ph.D. thesis: “Top Quark Pair
Production Cross Section In the Lepton+Jets Channel using b tagging at DØ” H. D. Yoo,
FERMILAB THESIS 2008 13, Brown University.
I maintained the code to create one of the final data analysis formats for the top physics
group, and provided support of data samples for several analysis teams measurement
of W helicity in ttbar lepton+jets final states, charged higgs searches, measurement of top
charge and top mass using kinematic templates.
Vertex Group: As vertex group convener, I was working on improvements of the
Adaptive Primary Vertex (APV) algorithm and its certification. Because of the high
luminosity in Tevatron Run IIb, many poorly and falsely reconstructed tracks interfere with
finding the primary vertex, and we therefore developed a new algorithm to reduce the
number of false primary vertices and to speed up the reconstruction at the same time.
This work is contained in: “b Jet Identification in the DØ Experiment,” V. M. Abazov et al.
[DØ Collaboration] (Ms. Ref. No.: NIMA D 10 00158 Nucl. Instrum. Meth. A). We were
working on optimizing the algorithm using new Layer 0 silicon detectors, the SVX tagging
algorithm and multivertexing algorithms as well.
Study of Silicon Track Trigger (STT): The STT finds tracks in the DØ silicon
microstrip tracker as part of the level 2 trigger. I have studied the performance of the STT
using b enriched data samples and normal dijet samples. Based on this study, I
determined criteria for impact parameter significance to be used to get optimal
performance of the STT. STT triggers are an important part of the trigger list for DØ in
RunIIb.
This work is contained in: “The DØ Run II impact parameter trigger,” T. Adams et al.
arXiv: physics/0701195 (Submitted to Nucl. Instrum. Meth. A), and “The upgraded DØ
detector,” V. M. Abazov et al. [DØ Collaboration] Nucl. Instrum. Meth. A 565, 463 (2006)
[arXiv:physics/0507191]
Technicolor Analysis: I have carried out a search for Techniparticles (ρT W + πT
), predicted by extended technicolor models, using data from 388 pb 1 of integrated
luminosity at s =1.96 TeV. Using b tagging and advanced neural network techniques, we
found that the data are consistent with backgrounds from the standard model. Hence, we
set a 95% confidence level upper limit on the production cross section multiplied by
branching ratio for techniparticle production for a grid of techniparticle mass points for the
ρT mass in the range 155 GeV–220 GeV. This result was shown at LHC’06 and was
published in Physical Review Letters.
This work is described in “Search for techniparticles in e + jets events at DØ,” V. M.
Abazov et al. [DØ Collaboration] Phys. Rev. Lett. 98, 221801 (2007) [arXiv:hep
ex/0612013]
This work has been shown in the conference for the 33rd International Conference on
High Energy Physics (ICHEP 06), Moscow, Russia, 26 Jul 2 Aug 2006 and the result
was published in the proceeding of “Some searches for new physics with the DØ
detector” (Moscow 2006, ICHEP 1159 1162)
Research Assistant: University of Rochester, 1998 2005
DØ Physics Analysis: I was co leader of the Tau Subgroup within the
•
Top/Higgs Physics Group, responsible for optimizing τ lepton identification
algorithms in ttbar events. This was a new effort within DØ, which, although
technically very challenging, increased substantially the scope of Run II top
data analysis (according to the standard model, approximately 21% ttbar
production involves at least one τ lepton in the decay chain). For my thesis, I
worked on the measurement of the ttbar cross section in the e+jets channel in
data from Run II. Using kinematic templates, I developed a random grid search
method to reduce systematic uncertainties, and participated in a b tagging
analysis using a muon tagging technique to enhance the purity of the signal.
Also, I developed a neural network analysis technique to improve
discrimination of signal from background using relationships among kinematic
variables in top decay, and cross checked this using a kinematic template
method (topological method).
This topological method and contributions have been applied to this paper :
“Measurement of the ttbar Production Cross Section in ppbar Collisions at s = 1.96 TeV
using Kinematic Characteristics of Lepton+Jets Events,” V. M. Abazov et al. [DØ
Collaboration], Phys. Lett. B 626, 45 (2005) [arXiv:0504043 [hep ex]].
P.S. Unfortunately, the start of data taking with the upgraded detector was delayed,
mainly because of funding problems and readiness of the accelerator at Fermilab, which
also delayed my progress towards a Ph.D. by almost three years.
VLPC Cassette Testing: Our group’s primary hardware contribution to the DØ
Upgrade was to provide the VLPC cassettes to read out the central fiber tracker (77,000
readout channels) and the preshower detectors (24,000 readout channels). A total of 99
cassettes were produced, with 12 spares, each supplying 1024 channels of readout. The
cassettes are complex precision devices, whose construction required overcoming many
technical challenges. Their performance is crucial to the successful operation of the fiber
tracker and the preshower counters, two of DØ’s critical subsystems.
Along with other Rochester personnel, I worked on the testing and characterization of the
cassette. By the end of 2001, all cassettes were completed, fully characterized, and
installed in DØ, including those needed for the preshower detectors.
Great care was taken to optimize the performance of each finished cassette. This was
essential, given the limited light output from the fiber tracker. On average, there were only
1.5 substandard channels per cassette, which translates into an overall pass rate of
99.9%, well within initial expectations.
This work is contained in “The upgraded DØ detector,” V. M. Abazov et al. [DØ
Collaboration] Nucl. Instrum. Meth. A 565, 463 (2006) [arXiv:physics/0507191]
Contributions to Run II Software Infrastructure: I provided major
•
contributions to software development in the areas of offline reconstruction,
object ID, Monte Carlo (both GEANT based and fast simulation). I contributed
in a variety of ways to the upgrade of DØ software by assuming responsibility
for the calorimetry aspects of the DØ Run II Monte Carlo DØGSTAR.
Verification of the software at the physics simulation level was carried out through studies
of energy deposition in both active and inert material. I worked with other Rochester
colleagues to find and correct errors in definitions of materials in GEANT volumes
describing the geometry. This was crucial for gaining a realistic simulation option for the
production of events in different phases of the development of the full DØ analysis
system. Our detailed Monte Carlo simulations have provided a means for studying
various aspects of shower development, and for correcting and calibrating energy for the
new detector configuration. We scrutinized the effect of additional material in the detector
(especially the pre shower detectors and the solenoid magnet) on calorimeter response in
central and forward regions. These studies were discussed in DØ Notes 3535, 3536, and
3661, and indicated that, to retrieve the resolution of Run I, the energy deposited in the
pre shower detector had to be made available for reconstruction of electromagnetic
showers. Prior to this analysis, the need for reading out the pre shower analog signals
was not generally accepted within DØ. This work is contained in “The upgraded DØ
detector,” V. M. Abazov et al. [DØ Collaboration] Nucl. Instrum. Meth. A 565, 463 (2006)
[arXiv:physics/0507191]
Specific recent contributions include:
Testing and debugging electromagnetic (EMID) and jet (JETID) identification algorithms.
Development of τ identification techniques for τ analysis tools, including tagging
overlaps of τ objects with electron, muon, and b jet candidates.
Optimization of position resolutions in EM layers of the calorimeter, thereby facilitating
vertex pointing algorithms in both central and forward regions of the detector.
Implementation and fine tuning of the fast simulation of electromagnetic energy response
of the calorimeter.
List of first author publications
“Optimization of Beam Selection for 4π Non coplanar Converging (4PiNC) Delivery using
a Modified Genetic Algorithm (GA),” D.Cho, et. al, (in preparation 2014)
“Implementation of 4π Non Coplanar Converging (4PiNC) Beams using a Conical
Delivery Geometry,” J.Chang, et. al, (in preparation 2014)
“Search for a Narrow ttbar Resonance in ppbar Collisions at s = 1.96 TeV,” V. M.
Abazov et al. [DØ Collaboration], Phys. Rev. D 85, 051101 (2012) [ arXiv:1111.1271
[hep ex]]
“Search for a fourth generation t’ quark in ppbar collisions at s=1.96 TeV,” V. Abazov, et
al[DØ Collaboration], Phys. Rev. Lett. 107, 082001 (2011) [arXiv:1104.4522v1]
“b Jet Identification in the DØ Experiment,” V. M. Abazov et al. [DØ Collaboration] (Ms.
Ref. No.: NIMA D 10 00158 Nucl. Instrum. Meth. A) (2010)
“Search for Charged Higgs Bosons in Decays of Top Quarks,” V. M. Abazov et al. [DØ
Collaboration], Phys. Rev. D 80, 051107 (2009) [arXiv.org:0906.5326 [hep ex]]
“Measurement of the ttbar production cross section in ppbar collisions at s = 1.96 TeV,”
V. M. Abazov et al. [DØ Collaboration], Phys. Rev. Lett. 100, 192004 (2008)
[arXiv:0803.2779 [hep ex]]
“The DØ Run II impact parameter trigger,” T. Adams et al. arXiv: physics/0701195
(Submitted to Nucl. Instrum. Meth. A) (2007)
“Search for techniparticles in e + jets events at DØ,” V. M. Abazov et al. (2007) [DØ
Collaboration] Phys. Rev. Lett. 98, 221801 (2007) [arXiv:hep ex/0612013]
“The upgraded DØ detector,” V. M. Abazov et al. [DØ Collaboration] Nucl. Instrum. Meth.
A 565, 463 (2006) [arXiv:physics/0507191]
Referees
Albert Sabbas, Ph.D., DABR, Physicist, Department of Radiation Oncology at New York
Presbyterian Hospital of Cornell University (email:*******@***.*** TEL:212-***-****)
Fridon Kulidzhanov, Ph.D., DABR, Physicist, Department of Radiation Oncology at New
York Presbyterian Hospital of Cornell University (email:********@***.*** TEL:212 746
3602)
Samuel Trichter, M.S.C., DABR, Physicist, Department of Radiation Oncology at New
York Presbyterian Hospital of Cornell University (email:*******@***.*** TEL:212 746
3639)
Lucy Nedialkova, Ph.D., DABR, Physicist, Department of Radiation Oncology at New
York Presbyterian Hospital of Cornell University (email:*******@***.*** TEL:212 746
3636)
Jenghwa Chang, Ph.D., Associate Professor and Director of Centralized Treatment
Planning in Radiation Oncology at New York Presbyterian Hospital of Cornell University
(email:*******@***.*******.*** TEL:646-***-****)
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