Studie Entwicklungsstand Quantencomputer
Study development of quantum computer
PI: Rainer Steinwandt
Funding Agency: Saarland University (GER)
German Federal Office for Information Security
Linking Within-Host and Between-Host
Infectious Disease Dynamics
PI: Necibe Tuncer
Funding Agency: National Science Foundation
Emerging Side-Channel Resistant and
Resource-Friendly Elliptic Curve
Algorithms and Architectures
PI: Reza Azarderakhsh/Co-PI: Koray Karabina
Funding Agency: US Army
Dr. Tim Ford, has written a new
textbook entitles, Separable Algebra.
Due to be published on October 20, 2017,
this book presents a comprehensive
introduction to the theory of separable
algebras over commutative rings.
Azumaya algebras, the henselization of
local rings, and Galois theory are
rigorously introduced and treated.
Essential connections are drawn
between the theory of separable
algebras and Morita theory, the theory
of faithfully flat descent, cohomology,
derivations, differentials, reflexive lattices,
maximal orders, and class groups.
Lianfen Qian, Suojin Wang
Computational Statistics & Data Analysis
Sandor Nagydobai Kiss, Paul Yiu
Connecting Orbits for Compact Infinite
R. de la Llave, J.D. Mireles James
SIAM Journal on Applied Dynamical Systems
A Ph.D. student must pass two of the three qualifying exams, before becoming a Ph.D. candidate.
Upcoming Qualifying Exam Schedule for Fall 2017 :
Analysis: Tuesday, August 22, 2017 SE215, 2pm-5pm
Probability/Statistics : Thursday, August 24, SE 215 2pm-5pm
Algebra: Monday, August 28, 2017, SE215, 2pm-5pm
Topics covered in the Ph.D. Qualifying Exams:
Algebra Exam: group theory, Sylow theorems, the structure of finitely-generated abelian groups, ring theory, Euclidean rings, UFDs, polynomial rings, vector spaces, modules, linear transformations, eigenvalues, minimal polynomials, matrices of linear transformations, Galois theory, and finite fields.
Analysis Exam: the real numbers, metric space topology, uniform convergence, Arzela-Ascoli Theorem, differentiation and Riemann integration of single-variable functions, power series, Stone-Weierstrass Theorem, measure theory, Lebesgue integral, convergence theorems for the Lebesgue integral, absolute continuity, the Fundamental Theorem of Calculus.
Probability & Statistics Exam: Advanced topics in Probability and Statistics: Borel-Cantelli lemma, normal and Poisson distributions, Chi-square and exponential distributions, t and F distributions, Markov and Chebyshev inequalities, convergence in distribution, in probability and almost surely, law of large numbers, central limit theorem, delta method, Slutsky lemma, LSE, MLE, BLUE, sufficient statistics, Cramer-Rao inequality, Fisher information matrix, hypothesis tests via likelihood ratio test and Bayes test.
The Probability & Statistics Exam will be divided into three parts. Total 3 hours.
Part 1 (Elementary part). This part consists of 10 elementary Probability and Stat questions. These will be the same (or very similar) questions that are given for Actuarial Exam. Students are expected to successfully complete at least 80% of these problems.
Part 2 (Advanced part). This part consists of 3-5 advanced problems from Probability Theory and Math Stat classes. Students are expected to successfully complete at least 60% of these problems.
Part 3 (Proofs). This part contains 3-5 statements from the predetermined list of about 20 basic well known facts in Probability and Statistics with fairly simple proofs (less than a page). Important: the students are given the list of questions ahead of time and the grading is strict with no partial credits. Students are expected to successfully complete at least 80% of these problems.
Note: the syllabus in any particular section of the Introductory Abstract Algebra, Introductory Analysis, and Mathematical Probability/Statistics courses might differ slightly from the subject material listed above.
Topics in Algebra, 2nd ed., by Herstein, Chapters 2-5, 6.1-6.3, and 7.
Algebra, 3rd ed., by Lang, Chapters 1-6.
Abstract Algebra, 3rd ed., by Dummit and Foote, Chapters 1-5, 7-9, and 13-14, excluding 9.6 and 14.9.
Introduction to Analysis, by Maxwell Rosenlicht, Chapters 2-7.
Real Mathematical Analysis, by Charles Pugh, Chapters 1-4.
Real Analysis, 3rd ed., by H.L. Royden, Chapters 3, 4, 5.
Principles of Mathematical Analysis, 3rd ed., by Rudin, Chapters 2-8 and 11.
Measure and Integral, by Wheeden amd Zygmund, Chapters 3-5.
A Probability Path by Resnick
Probability theory by Shiryaev
Measure Theory and Probability Theory by Athreya and Lahiri
Mathematical Statistics by Bickel and Doksum
Statistical Inference by Casella
For information contact:
Prof. Yuan Wang, Graduate Director
Department of Mathematical Sciences
Florida Atlantic University
777 Glades RD
Boca Raton, FL 33431