Presentations of Wess-Zumino-Witten Fusion Rings

The fusion rings of Wess-Zumino-Witten models are re-examined. Attention is drawn to the difference between fusion rings over Z (which are often of greater importance in applications) and fusion algebras over C. Complete proofs are given characterising the fusion algebras (over C) of the SU(r+1) and Sp(2r) models in terms of the fusion potentials, and it is shown that the analagous potentials cannot describe the fusion algebras of the other models. This explains why no other representation-theoretic fusion potentials have been found. Instead, explicit generators are then constructed for general WZW fusion rings (over Z). The Jacobi-Trudy identity and its Sp(2r) analogue are used to derive the known fusion potentials. This formalism is then extended to the WZW models over the spin groups of odd rank, and explicit presentations of the corresponding fusion rings are given. The analogues of the Jacobi-Trudy identity for the spinor representations (for all ranks) are derived for this purpose, and may be of independent interest.Comment: 32 pages, 3 figures, added references, minor additions to text. To be published in Rev. Math. Phy

Fusion of \ade Lattice Models

Fusion hierarchies of \ade face models are constructed. The fused critical $D$, $E$ and elliptic $D$ models yield new solutions of the Yang-Baxter equations with bond variables on the edges of faces in addition to the spin variables on the corners. It is shown directly that the row transfer matrices of the fused models satisfy special functional equations. Intertwiners between the fused \ade models are constructed by fusing the cells that intertwine the elementary face weights. As an example, we calculate explicitly the fused $2\times 2$ face weights of the 3-state Potts model associated with the $D_4$ diagram as well as the fused intertwiner cells for the $A_5$--$D_4$ intertwiner. Remarkably, this $2\times 2$ fusion yields the face weights of both the Ising model and 3-state CSOS models.Comment: 41 page

Cold Fusion: Training Seq2Seq Models Together with Language Models

Sequence-to-sequence (Seq2Seq) models with attention have excelled at tasks which involve generating natural language sentences such as machine translation, image captioning and speech recognition. Performance has further been improved by leveraging unlabeled data, often in the form of a language model. In this work, we present the Cold Fusion method, which leverages a pre-trained language model during training, and show its effectiveness on the speech recognition task. We show that Seq2Seq models with Cold Fusion are able to better utilize language information enjoying i) faster convergence and better generalization, and ii) almost complete transfer to a new domain while using less than 10% of the labeled training data

New Integrable Models from Fusion

Integrable multistate or multiflavor/color models were recently introduced. They are generalizations of models corresponding to the defining representations of the U_q(sl(m)) quantum algebras. Here I show that a similar generalization is possible for all higher dimensional representations. The R-matrices and the Hamiltonians of these models are constructed by fusion. The sl(2) case is treated in some detail and the spin-0 and spin-1 matrices are obtained in explicit forms. This provides in particular a generalization of the Fateev-Zamolodchikov Hamiltonian.Comment: 11 pages, Latex. v2: statement concerning symmetries qualified, 3 minor misprints corrected. J. Phys. A (1999) in pres

Statistical image fusion with generalised Gaussian and Alpha-Stable distributions

This paper describes a new methodology for multimodal image fusion based on non-Gaussian statistical modelling of wavelet coefficients of the input images. The use of families of generalised Gaussian and alpha-stable distributions for modelling image wavelet coefficients is investigated and methods for estimating distribution parameters are proposed. Improved techniques for image fusion are developed, by incorporating these models into the weighted average image fusion algorithm. The superior performance of the proposed methods is demonstrated using multimodal image datasets. © 2007 IEEE.This paper describes a new methodology for multimodal image fusion based on non-Gaussian statistical modelling of wavelet coefficients of the input images. The use of families of generalised Gaussian and alpha-stable distributions for modelling image wavelet coefficients is investigated and methods for estimating distribution parameters are proposed. Improved techniques for image fusion are developed, by incorporating these models into the weighted average image fusion algorithm. The superior performance of the proposed methods is demonstrated using multimodal image dataset

Fusion Algebras of Fermionic Rational Conformal Field Theories via a Generalized Verlinde Formula

We prove a generalization of the Verlinde formula to fermionic rational conformal field theories. The fusion coefficients of the fermionic theory are equal to sums of fusion coefficients of its bosonic projection. In particular, fusion coefficients of the fermionic theory connecting two conjugate Ramond fields with the identity are either one or two. Therefore, one is forced to weaken the axioms of fusion algebras for fermionic theories. We show that in the special case of fermionic W(2,d)-algebras these coefficients are given by the dimensions of the irreducible representations of the horizontal subalgebra on the highest weight. As concrete examples we discuss fusion algebras of rational models of fermionic W(2,d)-algebras including minimal models of the $N=1$ super Virasoro algebra as well as $N=1$ super W-algebras SW(3/2,d).Comment: 28 pages (Plain TeX), BONN-HE-93-0