Two proofs show Kinoshita graph is knotted despite simple edge removals.
problem Proving the Kinoshita graph is knotted despite edge removals.
method Two classical knot theory theorems.
result Kinoshita graph is knotted.
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48 results for “Kinoshita graph”
New signatures for knotted graphs linked to classical knot signatures.
problem Defining invariants for knotted trivalent graphs.
method Using branched covers to define and relate new signatures to classical knot signatures.
result Computable invariants for Kinoshita's knotted theta graph.
The Kinoshita graph is the most famous example of a Brunnian theta graph, a nontrivial spatial theta graph with the property that removing any edge yields an unknot. We produce a new family of diagrams of spatial theta graphs with the property that removing any edge results in the unknot. The family is parameterized by…
The purely cosmetic surgery conjecture is true for the Kinoshita-Terasaka and Conway knot familiesmath.GT
Two knot families meet cosmetic surgery conjecture.
problem Cosmetic surgery conjecture in knot theory.
method Analyzing Kinoshita-Terasaka and Conway knot families.
result All nontrivial members of both knot families satisfy the conjecture.
Study proves nontrivial knots can't undergo cosmetic surgeries.
problem Cosmetic surgeries on nontrivial knots.
method Calculated finite type invariant of order 3.
result Nontrivial knots do not admit chirally cosmetic surgeries.
In this paper we compute the reduced HOMFLY-PT homologies of the Conway and the Kinoshita-Terasaka knots and show that they are isomorphic.
A {\em balanced} spatial graph has an integer weight on each edge, so that the directed sum of the weights at each vertex is zero. We describe the Alexander module and polynomial for balanced spatial graphs (originally due to Kinoshita \cite{ki}), and examine their behavior under some common operations on the graph. We…
In this paper, we study on knots and closed incompressible surfaces in the 3-sphere via Morse functions. We show that both of knots and closed incompressible surfaces can be isotoped into a "related Morse position" simultaneously. As an application, we have following results. *Smallness of Montesinos tangles with lengt…
We illustrate from the viewpoint of braiding operations on WZNW conformal blocks how colored HOMFLY polynomials with multiplicity structure can detect mutations. As an example, we explicitly evaluate the (2,1)-colored HOMFLY polynomials that distinguish a famous mutant pair, Kinoshita-Terasaka and Conway knot.
Details of quantum knot invariant calculations using a specific SU(3)_q-module are given which distinguish the Conway and Kinoshita-Teresaka pair of mutant knots. Features of Kuperberg's skein-theoretic techniques for SU(3)_q invariants in the context of mutant knots are also discussed.
We prove a folklore theorem of W. Thurston which provides necessary and sufficient conditions for primality of a certain class of theta-curves. Namely, a theta-curve in the 3-sphere with an unknotted constituent knot U is prime if and only if lifting the third arc of the theta-curve to the double branched cover over U …
A symmetric union of two knots is a classical construction in knot theory which generalizes connected sum, introduced by Kinoshita and Terasaka in the 1950s. We study this construction for the purpose of finding an infinite family of hyperbolic non-fibered three-bridge knots of constant determinant which satisfy the we…
Using a combinatorial approach described in a recent paper of Manolescu, Ozsváth, and Sarkar we compute the Heegaard-Floer knot homology of all knots with at most 12 crossings as well as the invariant for knots through 11 crossings. We review the basic construction of \cite{MOS}, giving two examples that can be wor…
We explore certain restrictions on knots in the three-sphere which admit non-trivial Seifert fibered surgeries. These restrictions stem from the Heegaard Floer homology for Seifert fibered spaces, and hence they have consequences for both the Alexander polynomial of such knots, and also their knot Floer homology. In pa…
Study theta-curves on torus in 3-sphere, classifying them.
problem Classify theta-curves on torus in 3-sphere.
method Analyze nontrivial knots and essential arcs, compute constituent knots, identify structure.
result Complete classification of torus theta-curves up to isotopy and homeomorphism.
In an earlier paper, we introduced a collection of graded Abelian groups $\HFKa(Y,K)$ associated to knots in a three-manifold. The aim of the present paper is to investigate these groups for several specific families of knots, including the Kinoshita-Terasaka knots and their ``Conway mutants''. These results show that …
The Price twist creates three 4-manifolds from a 4-sphere.
problem Understanding the properties of a non-simply connected 4-manifold created from a 4-sphere.
method Cutting and pasting operation on a -knot in a 4-manifold.
result The non-simply connected 4-manifold is studied for Kinoshita type -knots.
Motivated by the study of ribbon knots we explore symmetric unions, a beautiful construction introduced by Kinoshita and Terasaka 50 years ago. It is easy to see that every symmetric union represents a ribbon knot, but the converse is still an open problem. Besides existence it is natural to consider the question of un…
Every element in the first cohomology group of a 3--manifold is dual to embedded surfaces. The Thurston norm measures the minimal `complexity' of such surfaces. For instance the Thurston norm of a knot complement determines the genus of the knot in the 3--sphere. We show that the degrees of twisted Alexander polynomial…
Study of symmetric unions of knots with new inequality and epimorphism results.
problem Understanding the genera of symmetric unions of knots.
method Introduced symmetric unions inspired by earlier work, showed an identity between twisted Alexander polynomials and genera, and established an epimorphism between knot groups.
result Obtained an inequality concerning the genera of symmetric unions and provided a positive answer to an old problem.
We found a unique 4D plane that can't be simplified.
problem Finding an irreducible embedded projective plane in .
method Constructing a specific geometric shape in 4D space.
result The constructed projective plane is irreducible.
New lower bound for knot genus using Links-Gould invariant.
problem Finding a tighter lower bound for knot genus.
method Representation theory of to prove degree of Links-Gould polynomial bounds Seifert genus.
result The Links-Gould polynomial provides a new lower bound on knot genus, detecting specific knots like Kinoshita-Terasaka and Conway.
Constructs -ifications of Khovanov homology and proves compatibility with HOMFLY--PT.
problem Distinguishing knots with identical Khovanov and HOMFLY--PT homologies.
method Elementary construction within Bar-Natan's framework for tangles, defining -action on -ifications.
result New structures distinguish knots with identical homologies, e.g., Conway and Kinoshita-Terasaka knots.
A new invariant for links generalizes Alexander polynomial for sl_3.
problem Defining a non-abelian generalization of the Alexander polynomial.
method Using quantum representations and Laurent polynomials.
result Established a direct relation between and the Alexander polynomial.
New proof of Khovanov homology invariance via Conway mutation.
problem Invariance of Khovanov homology under Conway mutation.
method Elementary proof using Clifford module structure and rational closures.
result Mutation invariance of δ-graded knot Floer homology for a large class of tangles.
Motivated by the study of ribbon knots we explore symmetric unions, a beautiful construction introduced by Kinoshita and Terasaka in 1957. For symmetric diagrams we develop a two-variable refinement of the Jones polynomial that is invariant under symmetric Reidemeister moves. Here the two variables and $…
Paper provides new Alexander ideal-based obstruction to 0-concordance of knotted surfaces.
problem Tackles the 0-concordance problem for knotted surfaces in .
method Uses Alexander ideals to induce a homomorphism and prove non-sliceness.
result Alexander ideal determines 0-concordance classes and non-sliceness.
The Morse-Novikov number MN(L) of a smooth link L in the three-dimensional sphere is by definition the minimal possible number of critical points of a regular circle-valued Morse function on the link complement (the term regular means that the Morse function must have nice behaviour in a tubular neighbourhood of L). No…
New knots found with same determinant but no symmetric relation.
problem Determining if knots with the same determinant are symmetrically related.
method Constructing a family of knots with the same determinant but no symmetric relation.
result No two knots in the family are symmetrically related.
Line graph transformation aids graph isomorphism tests by excluding challenging graph properties.
problem Limited theoretical understanding of line graph transformation's impact on GNN models.
method Examined CFI and strongly regular graphs, showing line graph transformation helps WL tests distinguish these graphs.
result Line graph transformation aids WL tests in distinguishing challenging graph properties.
Proposes MGMN for end-to-end graph similarity learning.
problem Lack of cross-level interactions in graph similarity learning.
method Multi-level graph matching network (MGMN) combining node-graph matching and siamese graph neural networks.
result MGMN outperforms state-of-the-art models on graph-graph classification and regression tasks.
GWNN uses graph wavelets for efficient graph CNNs.
problem Spectral graph CNNs' high computational cost and lack of interpretability.
method Graph wavelet transform for efficient graph convolution.
result GWNN significantly outperforms spectral graph CNNs.
Graphons of Line Graphsstat.ML
The paper explores graphons of line graphs from sparse finite graphs.
problem Estimating graph limits from sparse finite graphs.
method Mapping finite graphs to their line graphs and analyzing graphs with the square-degree property.
result Graphons of line graphs can distinguish between sparse graphs like star graphs and superlinear preferential attachment graphs.
edGNN improves graph embeddings for directed labeled graphs.
problem Improving node and graph embeddings for directed labeled graphs.
method edGNN is a GNN designed for directed labeled graphs, leveraging both topology and labels.
result edGNN is as powerful as the Weisfeiler-Lehman algorithm for graph isomorphism.
Graph CNNs adapt to varying graph structures for better performance.
problem Fixed graph structures limit the performance of Graph CNNs on real data.
method Adaptive graph learning and distance metric learning for efficient graph construction.
result Adaptive Graph CNNs improve convergence speed and predictive accuracy on various graph datasets.
MxPool learns graph features from diverse graphs using a hierarchical structure.
problem Learning graph features from diverse graphs with varying properties and sizes.
method MxPool uses a multiplex structure with multiple graph convolution/pooling networks in a hierarchical learning structure.
result MxPool outperforms state-of-the-art methods on graph classification benchmarks.
Study the geometry of graph product extension graphs.
problem Properties of graph products.
method Introduce and study the extension graph of graph products of groups.
result Extension graph is isomorphic to crossing graph of a quasi-median graph and exhibits asymptotic dimension similar to quasi-trees.
Graph neural network learns graph distances effectively.
problem Maintaining graph distance metric properties.
method GRAPH-BERT based semi-supervised distance metric learning.
result GB-DISTANCE outperforms existing methods.
UGRAPHEMB embeds graphs into vectors preserving their proximity, achieving competitive results.
problem Graph-level representation learning in an unsupervised and inductive manner.
method UGRAPHEMB uses graph-graph proximity to embed graphs into a vector space. MSNA generates multi-scale node attention for graph-level embedding.
result UGRAPHEMB achieves competitive accuracy in graph classification, similarity ranking, and visualization tasks.
Quasi-transitive graphs quasi-isometric to planar graphs can be upgraded to Cayley graphs.
problem Quasi-transitive graphs quasi-isometric to planar graphs need to be upgraded to Cayley graphs.
method Upgrading a planar graph to a Cayley graph.
result Quasi-transitive graphs quasi-isometric to planar graphs can be upgraded to Cayley graphs.
Deep Divergence Graph Kernels learn graph representations without supervision.
problem Learning graph representations without feature engineering or labeled graphs.
method Unsupervised method using cross-graph attention networks and divergence scores.
result Learned representations achieve competitive results on graph classification tasks.
Paper proposes a new graph embedding framework to improve graph analytics.
problem Graph embedding often fails to capture the distribution of latent codes.
method Adversarial graph autoencoder framework that combines topological structure and node content.
result ARGA and ARVGA outperform baselines in link prediction, clustering, and visualization.
GRAPH-BERT uses only attention for graph representation learning.
problem Graph neural networks over-rely on graph links and suffer from performance issues.
method GRAPH-BERT uses only attention mechanism without graph convolution or aggregation, trained on sampled subgraphs.
result GRAPH-BERT outperforms existing GNNs in learning effectiveness and efficiency.
Customized-GNN generates model-specific for each graph.
problem Graphs in the same dataset have distinct structures.
method Proposes Customized-GNN framework to generate model-specific for each graph.
result Demonstrates effectiveness on various graph classification benchmarks.
Graph embedding leaks sensitive graph properties and subgraphs.
problem Privacy risks in graph embedding sharing.
method Three inference attacks and a defense mechanism.
result High accuracy in inferring graph properties and subgraphs.
Graph ConvNets outperform RNNs in graph learning tasks.
problem Designing neural networks for graphs with variable length.
method Compare graph RNN and ConvNet architectures, propose extensions, and conduct controlled experiments.
result Graph ConvNets are more accurate and faster than graph RNNs.
Characterizes graphs with leveled embeddings and introduces new graph invariants.
problem Understanding the properties of leveled embeddings in spatial graphs.
method Characterization of graphs with leveled embeddings, introduction of new invariants.
result Characterization of graphs with low level number and determination of specific invariants for complete graphs and complete bipartite graphs.
HGP-SL pools and learns graph structure for hierarchical representation learning.
problem Graph pooling is overlooked in GNN models, limiting hierarchical representation learning.
method Integrates graph pooling and structure learning into a unified module.
result HGP-SL improves graph classification performance on benchmarks.