What is he best known for?
The fields of study he is best known for:
- Mathematical analysis
- Quantum mechanics
- Topology
Gerhard Keller spends much of his time researching Mathematical analysis, Piecewise, Invariant, Eigenvalues and eigenvectors and Statistical physics.
The Mathematical analysis study combines topics in areas such as Invariant measure, Spectrum and Pure mathematics.
His studies in Pure mathematics integrate themes in fields like Critical point and Central limit theorem.
His Piecewise research is multidisciplinary, relying on both Monotonic function and Bounded variation.
His work in the fields of Eigenvalues and eigenvectors, such as Spectral radius, intersects with other areas such as Common framework.
Gerhard Keller combines subjects such as Entropy, Dynamical systems theory and Stationary ergodic process with his study of Statistical physics.
His most cited work include:
- Ergodic Properties of Invariant Measures for Piecewise Monotonic Transformations (338 citations)
- Equilibrium States in Ergodic Theory (322 citations)
- Stability of the spectrum for transfer operators (298 citations)
What are the main themes of his work throughout his whole career to date?
Gerhard Keller mostly deals with Mathematical analysis, Pure mathematics, Piecewise, Invariant and Attractor.
The concepts of his Mathematical analysis study are interwoven with issues in Invariant measure and Eigenvalues and eigenvectors.
His study on Ergodic theory and Schwarzian derivative is often connected to Skew as part of broader study in Pure mathematics.
Gerhard Keller has included themes like Lattice, Monotonic function, Markov chain and Perturbation in his Piecewise study.
He interconnects Lyapunov exponent and Uniform boundedness in the investigation of issues within Invariant.
His Dynamical systems theory research includes themes of Hausdorff dimension and Statistical physics.
He most often published in these fields:
- Mathematical analysis (38.98%)
- Pure mathematics (27.97%)
- Piecewise (21.19%)
What were the highlights of his more recent work (between 2014-2021)?
- Combinatorics (16.95%)
- Pure mathematics (27.97%)
- Invariant (19.49%)
In recent papers he was focusing on the following fields of study:
Gerhard Keller mainly focuses on Combinatorics, Pure mathematics, Invariant, Measure and Skew.
His study in Pure mathematics is interdisciplinary in nature, drawing from both Point, Dynamical systems theory and Lyapunov exponent.
His research on Dynamical systems theory frequently links to adjacent areas such as Ergodic theory.
The study incorporates disciplines such as Point particle and Absolute continuity, Exponential growth, Mathematical analysis in addition to Invariant.
His study focuses on the intersection of Measure and fields such as Natural density with connections in the field of Product.
His studies deal with areas such as Statistical physics, Markov chain and Piecewise as well as Monotone polygon.
Between 2014 and 2021, his most popular works were:
- Dynamics on the graph of the torus parametrisation (36 citations)
- Periods and factors of weak model sets (16 citations)
- Dynamics of $\mathcal B$-free sets: a view through the window (10 citations)
In his most recent research, the most cited papers focused on:
- Mathematical analysis
- Quantum mechanics
- Topology
Gerhard Keller spends much of his time researching Haar measure, Invariant, Attractor, Torus and Pure mathematics.
His Haar measure research incorporates themes from Uniform distribution, Graph, Lattice, Parametrization and Point.
His Invariant research includes elements of Absolute continuity, Mathematical analysis, Lipschitz continuity and Point particle.
His Attractor research is multidisciplinary, incorporating elements of Statistical physics, Large deviations theory and Monotone polygon.
His studies examine the connections between Torus and genetics, as well as such issues in Mathematical proof, with regards to Discrete mathematics.
His Pure mathematics study combines topics from a wide range of disciplines, such as Dynamical systems theory and Lyapunov exponent.
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.
