What is he best known for?
The fields of study he is best known for:
- Algebra
- Mathematical analysis
- Combinatorics
His main research concerns Combinatorics, Discrete mathematics, Pure mathematics, Algebra and Symmetric group.
His biological study spans a wide range of topics, including Free group, Entropy and Computational complexity theory.
The various areas that Anatoly Vershik examines in his Discrete mathematics study include Iterated function, Random walk, Compact space and Metric.
Mathematical physics is closely connected to Mathematical analysis in his research, which is encompassed under the umbrella topic of Pure mathematics.
Anatoly Vershik combines subjects such as Trivial representation and Real form with his study of Algebra.
His Symmetric group study combines topics from a wide range of disciplines, such as Irreducible representation, Asymptotic analysis, Regular representation and Unitary representation.
His most cited work include:
- Random Walks on Discrete Groups: Boundary and Entropy (550 citations)
- A new approach to representation theory of symmetric groups (283 citations)
- Asymptotic theory of characters of the symmetric group (220 citations)
What are the main themes of his work throughout his whole career to date?
Anatoly Vershik mainly focuses on Pure mathematics, Combinatorics, Discrete mathematics, Symmetric group and Algebra.
His Pure mathematics research is multidisciplinary, incorporating elements of Measure, Mathematical analysis and Group.
His work in Group tackles topics such as Boundary which are related to areas like Random walk.
His research integrates issues of Convex polytope, Convex set and Path space in his study of Combinatorics.
His biological study spans a wide range of topics, including Lebesgue measure and Compact space.
He usually deals with Symmetric group and limits it to topics linked to Representation theory and Young tableau and Limit.
He most often published in these fields:
- Pure mathematics (50.34%)
- Combinatorics (30.82%)
- Discrete mathematics (26.71%)
What were the highlights of his more recent work (between 2016-2021)?
- Pure mathematics (50.34%)
- Combinatorics (30.82%)
- Path space (7.53%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Pure mathematics, Combinatorics, Path space, Ergodic theory and Invariant.
He is involved in the study of Pure mathematics that focuses on Symmetric group in particular.
Anatoly Vershik combines subjects such as Representation theory, Mathematical proof, Limit and Duality with his study of Combinatorics.
His work carried out in the field of Path space brings together such families of science as Partition and Combinatorial method.
Anatoly Vershik has researched Ergodic theory in several fields, including Discrete mathematics, Entropy and Invariant measure.
His Invariant research includes elements of Hyperplane, Statement and Automorphism.
Between 2016 and 2021, his most popular works were:
- The theory of filtrations of subalgebras, standardness, and independence (8 citations)
- Asymptotics of the Partition of the Cube into Weyl Simplices and an Encoding of a Bernoulli Scheme (6 citations)
- Asymptotics of the Partition of the Cube into Weyl Simplices and an Encoding of a Bernoulli Scheme (6 citations)
In his most recent research, the most cited papers focused on:
- Algebra
- Mathematical analysis
- Vector space
His primary areas of study are Path space, Pure mathematics, Combinatorics, Ergodic theory and Partition.
His Path space study integrates concerns from other disciplines, such as Entropy, Invariant measure and Series.
His Pure mathematics research incorporates elements of Group, Metric, Measure, Independence and Boundary.
The study incorporates disciplines such as Semigroup, Commutative property, Algebraic geometry, Probability measure and Random walk in addition to Boundary.
His work on Automorphism as part of general Combinatorics research is frequently linked to Universal graph, thereby connecting diverse disciplines of science.
His Partition research incorporates themes from Stochastic process and Combinatorial method.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
