AbstractWilson-loop averages in Chern–Simons theory (HOMFLY polynomials) can be evaluated in different ways – the most difficult, but most interesting of them is the hypercube calculus, the only one applicable to virtual knots and used also for categorification (higher-dimensional extension) of the theory. We continue the study of quantum dimensions, associated with hypercube vertices, in the drastically simplified version of this approach to knot polynomials. At q=1 the problem is reformulated in terms of fat (ribbon) graphs, where Seifert cycles play the role of vertices. Ward identities in associated matrix model provide a set of recursions between classical dimensions. For q≠1 most of these relations are broken (i.e. deformed in a still...
The colored HOMFLY polynomials, which describe Wilson loop averages in Chern-Simons theory, possess ...
En 2000, Khovanov ouvre la voie au programme de catégorification en théorie des nœuds, définissant u...
We use deep neural networks to machine learn correlations between knot invariants in various dimensi...
AbstractWe claim that HOMFLY polynomials for virtual knots, defined with the help of the matrix-mode...
Virtual knots are associated with knot diagrams, which are not obligatory planar. The recently sugge...
We elaborate on the simple alternative [1] to the matrix-factorization construction of Khovanov-Roza...
AbstractVirtual knots are associated with knot diagrams, which are not obligatory planar. The recent...
We continue to develop the tensor-algebra approach to knot polynomials with the goal to present the ...
This dissertation has two parts, each motivated by an open problem related to the Jones polynomial. ...
Construction of (colored) knot polynomials for double-fat graphs is further generalized to the case ...
We investigate possibilities of generalizing the TBEM eigenvalue matrix model, which represents the ...
AbstractConstruction of (colored) knot polynomials for double-fat graphs is further generalized to t...
We construct and investigate the properties of a new extension of Khovanov homology to virtual links...
I Virtual link diagrams LD are a combinatorial de-scription of link diagrams in Fg; The virtual tref...
AbstractA very simple expression is conjectured for arbitrary colored Jones and HOMFLY polynomials o...
The colored HOMFLY polynomials, which describe Wilson loop averages in Chern-Simons theory, possess ...
En 2000, Khovanov ouvre la voie au programme de catégorification en théorie des nœuds, définissant u...
We use deep neural networks to machine learn correlations between knot invariants in various dimensi...
AbstractWe claim that HOMFLY polynomials for virtual knots, defined with the help of the matrix-mode...
Virtual knots are associated with knot diagrams, which are not obligatory planar. The recently sugge...
We elaborate on the simple alternative [1] to the matrix-factorization construction of Khovanov-Roza...
AbstractVirtual knots are associated with knot diagrams, which are not obligatory planar. The recent...
We continue to develop the tensor-algebra approach to knot polynomials with the goal to present the ...
This dissertation has two parts, each motivated by an open problem related to the Jones polynomial. ...
Construction of (colored) knot polynomials for double-fat graphs is further generalized to the case ...
We investigate possibilities of generalizing the TBEM eigenvalue matrix model, which represents the ...
AbstractConstruction of (colored) knot polynomials for double-fat graphs is further generalized to t...
We construct and investigate the properties of a new extension of Khovanov homology to virtual links...
I Virtual link diagrams LD are a combinatorial de-scription of link diagrams in Fg; The virtual tref...
AbstractA very simple expression is conjectured for arbitrary colored Jones and HOMFLY polynomials o...
The colored HOMFLY polynomials, which describe Wilson loop averages in Chern-Simons theory, possess ...
En 2000, Khovanov ouvre la voie au programme de catégorification en théorie des nœuds, définissant u...
We use deep neural networks to machine learn correlations between knot invariants in various dimensi...