Nilpotent Symmetries in Jackiw-Pi Model: Augmented Superfield Approach

We derive the complete set of off-shell nilpotent (s^2_{(a)b} = 0) and absolutely anticommuting (s_b s_{ab} + s_{ab} s_b = 0) Becchi-Rouet-Stora-Tyutin (BRST) (s_b) as well as anti-BRST symmetry transformations (s_{ab}) corresponding to the combined Yang-Mills and non-Yang-Mills symmetries of the (2 + 1)-dimensional Jackiw-Pi model within the framework of augmented superfield formalism. The absolute anticommutativity of the (anti-)BRST symmetries is ensured by the existence of two sets of Curci-Ferrari (CF) type of conditions which emerge naturally in this formalism. The presence of CF conditions enables us to derive the coupled but equivalent Lagrangian densities. We also capture the (anti-)BRST invariance of the coupled Lagrangian densities in the superfield formalism. The derivation of the (anti-)BRST transformations of the auxiliary field \rho is one of the key findings which can neither be generated by the nilpotent (anti-)BRST charges nor by the requirements of the nilpotency and/or absolute anticommutativity of the (anti-)BRST transformations. Finally, we provide a bird's-eye view on the role of auxiliary field for various massive models and point out few striking similarities and some glaring differences among them.Comment: LaTex file: 24 pages, no figures, minor modifications in the title and text, references expanded, version to appear in IJT

Augmented Superfield Approach to Non-Yang-Mills Symmetries of Jackiw-Pi Model: Novel Observations

We derive the off-shell nilpotent and absolutely anticommuting Becchi-Rouet-Stora-Tyutin (BRST) as well as anti-BRST symmetry transformations corresponding to the non-Yang-Mills symmetry transformations of (2 + 1)- dimensional Jackiw-Pi (JP) model within the framework of "augmented" superfield formalism. The Curci-Ferrari restriction, which is a hallmark of non-Abelian 1-form gauge theories, does not appear in this case. One of the novel features of our present investigation is the derivation of proper (anti-)BRST symmetry transformations corresponding to the auxiliary field \rho that can not be derived by any conventional means.Comment: LaTeX file, 17 pages, journal version, typos fixed, references modifie

Canonical brackets from continuous symmetries: Abelian 2-form gauge theory

We derive the canonical (anti-)commutation relations amongst the creation and annihilation operators of the various basic fields, present in the four (3 + 1)-dimensional (4D) free Abelian 2-from gauge theory, with the help of continuous symmetry transformations within the framework of Becchi-Rouet-Stora-Tyutin (BRST) formalism. We show that all the six continuous symmetries of the theory lead to the exactly the same non-vanishing (anti-)commutator amongst the creation and annihilation operators of the normal mode expansion of the basic fields of the theory.Comment: LaTeX file, 16 pages, No figure

On the Support Recovery of Jointly Sparse Gaussian Sources using Sparse Bayesian Learning

In this work, we provide non-asymptotic, probabilistic guarantees for successful recovery of the common nonzero support of jointly sparse Gaussian sources in the multiple measurement vector (MMV) problem. The support recovery problem is formulated as the Type-II maximum likelihood (ML) estimation of the variance hyperparameters of a joint sparsity inducing Gaussian prior on the source signals. We derive conditions under which the resulting nonconvex constrained optimization perfectly recovers the nonzero support of a joint-sparse Gaussian source ensemble with arbitrarily high probability. The support error probability decays exponentially with the number of MMVs at a rate that depends on the smallest restricted singular value and the nonnegative null space property of the self Khatri-Rao product of the sensing matrix. Our support consistency guarantee for the constrained Type-II ML solution extends to any global solution of the multiple sparse Bayesian learning (M-SBL) optimization whose nonzero coefficients lie inside a bounded interval. Our analysis confirms that nonzero supports of size as high as O($m^2$) are recoverable from $m$ measurements per sparse vector. For the case of noiseless measurements, we show that a single MMV is sufficient for perfect recovery of the $k$-sparse support by M-SBL, provided all subsets of $k + 1$ columns of the sensing matrix are linearly independent

A Hubbard model for ultracold bosonic atoms interacting via zero-point-energy induced three-body interactions

We show that for ultra-cold neutral bosonic atoms held in a three-dimensional periodic potential or optical lattice, a Hubbard model with dominant, attractive three-body interactions can be generated. In fact, we derive that the effect of pair-wise interactions can be made small or zero starting from the realization that collisions occur at the zero-point energy of an optical lattice site and the strength of the interactions is energy dependent from effective-range contributions. We determine the strength of the two- and three-body interactions for scattering from van-der-Waals potentials and near Fano-Feshbach resonances. For van-der-Waals potentials, which for example describe scattering of alkaline-earth atoms, we find that the pair-wise interaction can only be turned off for species with a small negative scattering length, leaving the $^{88}$Sr isotope a possible candidate. Interestingly, for collisional magnetic Feshbach resonances this restriction does not apply and there often exist magnetic fields where the two-body interaction is small. We illustrate this result for several known narrow resonances between alkali-metal atoms as well as chromium atoms. Finally, we compare the size of the three-body interaction with hopping rates and describe limits due to three-body recombination

The Parameterized Complexity of Packing Arc-Disjoint Cycles in Tournaments

Given a directed graph $D$ on $n$ vertices and a positive integer $k$, the Arc-Disjoint Cycle Packing problem is to determine whether $D$ has $k$ arc-disjoint cycles. This problem is known to be W[1]-hard in general directed graphs. In this paper, we initiate a systematic study on the parameterized complexity of the problem restricted to tournaments. We show that the problem is fixed-parameter tractable and admits a polynomial kernel when parameterized by the solution size $k$. In particular, we show that it can be solved in $2^{\mathcal{O}(k \log k)} n^{\mathcal{O}(1)}$ time and has a kernel with $\mathcal{O}(k)$ vertices. The primary ingredient in both these results is a min-max theorem that states that every tournament either contains $k$ arc-disjoint triangles or has a feedback arc set of size at most $6k$. Our belief is that this combinatorial result is of independent interest and could be useful in other problems related to cycles in tournaments

Increasing Superconducting Tc's by a Factor of 1000 with StripeLike Hopping Anisotropies

We have studied the enhancement of the superconducting transition temperature, Tc, in a t-J-U model of electrons moving on a square lattice in which anisotropic electronic hopping is introduced. The inclusion of such hopping mimics, in a approximate fashion, a potentially important characteristic of materials possessing stripelike charge and spin correlations. For this model we have calculated Tc for singlet pairing using the non self-consistent Thouless criterion, and find a dramatic enhancement of Tc induced by hopping anisotropies. Further, the maximum increase in Tc is obtained when the system is pushed towards the extreme anisotropy limit, that is, when the hopping of electrons is confined to occur in 1+0^+ dimensions. We demonstrate that in this limit the increase in Tc, with respect to the isotropic system, can be of the order of 1000. We have also determined that in the extreme anisotropy limit the superconducting gap is an equal mixture of s and d pairing symmetries (two choices of such a combination being s + d and s + id) owing to the reduced (square to rectangular) symmetry of the system in the presence of hopping anisotropies. Thus, the presence of d-wave superconducting features in materials whose symmetry is very different from that of a two-dimensional square lattice, with the anisotropy produced by the appearance of stripes, is not unexpected.Comment: 8 pages (Revtex), 4 eps figure

Investigation of the Thermoelectric Properties of ZnV2_{2}O4_{4} Compound in High Temperature Region

In the present work, we report the experimental thermopower ($\alpha$) data for ZnV$_{2}$O$_{4}$ compound in the high temperature range 300-600 K. The value of $\alpha$ is found to be $\sim$184 and $\sim$126 $\mu$V/K at $\sim$300 and $\sim$600 K, respectively. The temperature dependent behavior of $\alpha$ is almost linear in the measured temperature range. To understand the large and positive $\alpha$ value observed in this compound, we have also investigated the electronic and thermoelectric properties by combining the \textit{ab-initio} electronic structures calculations with Boltzmann transport theory. Within the local spin density approximation plus Hubbard U, the anti-ferromagnetic ground state calculation gives an energy gap $\sim$0.33 eV for U=3.7 eV, which is in accordance with the experimental results. The effective mass for holes in the valance band is found nearly four times that of electrons in conduction band. The large effective mass of holes are mainly responsible for the observed positive and large $\alpha$ value in this compound. There is reasonably good matching between calculated and experimental $\alpha$ data in the temperature range 300-410 K. The power factor calculation shows that thermoelectric properties in high temperature region can be enhanced by tuning the sample synthesis conditions and suitable doping. The estimated value of \textit{figure-of-merit}, ZT, at different absolute temperature suggest that ZnV$_{2}$O$_{4}$ compound can be a good thermoelectric material in high temperature range.Comment: 10 pages, 8 figures, 1 table (to appear in J. Phys. D: Appl. Phys.

Detecting Adversarial Samples from Artifacts

Deep neural networks (DNNs) are powerful nonlinear architectures that are known to be robust to random perturbations of the input. However, these models are vulnerable to adversarial perturbations--small input changes crafted explicitly to fool the model. In this paper, we ask whether a DNN can distinguish adversarial samples from their normal and noisy counterparts. We investigate model confidence on adversarial samples by looking at Bayesian uncertainty estimates, available in dropout neural networks, and by performing density estimation in the subspace of deep features learned by the model. The result is a method for implicit adversarial detection that is oblivious to the attack algorithm. We evaluate this method on a variety of standard datasets including MNIST and CIFAR-10 and show that it generalizes well across different architectures and attacks. Our findings report that 85-93% ROC-AUC can be achieved on a number of standard classification tasks with a negative class that consists of both normal and noisy samples.Comment: Submitted to ICML 201

Automatic Phone Slip Detection System

Mobile phones are becoming increasingly advanced and the latest ones are equipped with many diverse and powerful sensors. These sensors can be used to study different position and orientation of the phone which can help smartphone manufacture to track about their customers handling from the recorded log. The inbuilt sensors such as the accelerometer and gyroscope present in our phones are used to obtain data for acceleration and orientation of the phone in the three axes for different phone vulnerable position. From the data obtained appropriate features are extracted using various feature extraction techniques. The extracted features are then given to classifier such as neural network to classify them and decide whether the phone is in a vulnerable position to fall or it is in a safe position .In this paper we mainly concentrated on various case of handling the smartphone and classified by training the neural network.Comment: Accepted for publication in Springer LNE