Introduction
Note: please use Teguia (or Teguia Tabuguia) if you want to call me by my name. My first name is Bertrand.
I have a Ph.D. (Dr. rer. nat.) in Mathematics, in the field of Computer Algebra (2020), a master's degree in Mathematics (2018), and another in Computer Engineering (2016).
I am a Postdoctoral Researcher in the Non-Linear Algebra group of Bernd Sturmfels at the Max Planck Institute For Mathematics in the Sciences, Leipzig, Germany.
Research Interests: my research interests combine Symbolic Computation, Computer Programming, Differential Algebra, Algorithmic Number Theory, Algebraic Geometry, and the applications of all that in other scientific areas.
Check this website menu to learn more about my background.
Address: Inselstraße 22, 34132 Leipzig, Germany
Office: F3 07
Email: email@bertrandteguia.com
MPI MiS group member webpage: https://www.mis.mpg.de/nlalg/members/bertrand-teguia-tabuguia.html
UniKassel web page: http://www.mathematik.uni-kassel.de/~bteguia/
Tel: +49 341 9959 768
Download my CV
Bertrand Teguia T.
'Magic' in symbolic computing
I invite you to read an informal presentation on computations based on Mathematics and computer programming in Computer Algebra.
1. Formal power series in Maxima 5.44: PDF, Html
2. Formal power series in Maple 2019: PDF
You can try some computations with my Maple library if you wish to:
Download my implementations at The new FPS package.
News
Invited speaker: I will attend ACA 2022 in Instanbul, Turkey. I will give a talk for the session about ``D-finite Functions and Beyond: Algorithms, Combinatorics, and Arithmetic''.
Some commands added to FPS: AddHolonomicDE, MulHolonomicDE, and SelfOpHolonomicDE. We are still in the univariate case. Assume you have n (valued positive integer) holonomic DEs DE1, ..., DEn, in the dependent variables y1(t), ...,yn(t), respectively. Then you can compute a differential equation for the sum z(t)=y1(t)+y2(t)+...+yn(t) as follows:
FPS:-AddHolonomicDE([DE1,...,DEn],[y1(t),...,yn(t)],z(t));
Similarly for the product z(t)=y1(t)*y2(t)*...*yn(t), one uses
FPS:-MulHolonomicDE([DE1,...,DEn],[y1(t),...,yn(t)],z(t));
Now, if you have a differential equation DE in the dependent variable y(t), and you want to compute a differential equation for a polynomial expression z=p(y(t)), you can proceed as follows:
FPS:-SelfOpHolonomicDE(DE,y(t),z=p(y));
The efficiency is ... :)! Check it out and compare it with other approaches. It is basically the same philosophy as FPS:-HolonomicDE, namely: find the basis!