New observations in the BRST analysis of dynamical non-Abelian 2-form gauge theory

We generalize the usual gauge transformations connected with the 1-form gauge potential to the Becchi-Rouet-Stora-Tyutin (BRST) and anti-BRST symmetry transformations for the four (3+1)-dimensional (4D) topologically massive non-Abelian gauge theory that incorporates the famous (B\wedge F) term where there is an explicit topological coupling between 1-form and 2-form gauge fields. A novel feature of our present investigation is the observation that the (anti-)BRST symmetry transformations for the auxiliary 1-form field (K_\mu) and 2-form gauge potential (B_{0i}) are not generated by the (anti-)BRST charges that are derived by exploiting all the relevant (anti-)BRST symmetry transformations corresponding to all the fields of the present theory. This observation is a new result because it is drastically different from the application of the BRST formalism to (non-)Abelian 1-form and Abelian 2-form as well as 3-form gauge theories.Comment: LaTeX file, 11 pages, journal-versio

A digital interface for Gaussian relay networks: lifting codes from the discrete superposition model to Gaussian relay networks

For every Gaussian relay network with a single source-destination pair, it is known that there exists a corresponding deterministic network called the discrete superposition network that approximates its capacity uniformly over all SNR's to within a bounded number of bits. The next step in this program of rigorous approximation is to determine whether coding schemes for discrete superposition models can be lifted to Gaussian relay networks with a bounded rate loss independent of SNR. We establish precisely this property and show that the superposition model can thus serve as a strong surrogate for designing codes for Gaussian relay networks. We show that a code for a Gaussian relay network, with a single source-destination pair and multiple relay nodes, can be designed from any code for the corresponding discrete superposition network simply by pruning it. In comparison to the rate of the discrete superposition network's code, the rate of the Gaussian network's code only reduces at most by a constant that is a function only of the number of nodes in the network and independent of channel gains. This result is also applicable for coding schemes for MIMO Gaussian relay networks, with the reduction depending additionally on the number of antennas. Hence, the discrete superposition model can serve as a digital interface for operating Gaussian relay networks.Comment: 5 pages, 2010 IEEE Information Theory Workshop, Cair