Noise reduction algorithm for Glueball correlators

We present an error reduction method for obtaining glueball correlators from monte carlo simulations of SU(3) lattice gauge theory. We explore the scalar and tensor channels at three different lattice spacings. Using this method we can follow glueball correlators to temporal separations even up to 1 fermi. We estimate the improvement over the naive method and compare our results with existing computations.Comment: 6 pages, 4 tables and 2 figures, computations at larger volumes added, article partially rewritten, main conclusions unchange

Heavy light tetraquarks from Lattice QCD

We present preliminary results from a lattice calculation of tetraquark states in the charm and bottom sector of the type $ud\bar{b}\bar{b}$, $us\bar{b}\bar{b}$, $ud\bar{c}\bar{c}$ and $sc\bar{b}\bar{b}$. These calculations are performed on $N_f = 2 + 1 + 1$ MILC ensembles with lattice spacing of $a = 0.12~\mathrm{fm}$ and $a=0.06~\mathrm{fm}$. A relativistic action with overlap fermions is employed for the light and charm quarks while a non-relativistic action with non-perturbatively improved coefficients is used in the bottom sector. Preliminary results provide a clear indication of presence of energy levels below the relevant thresholds of different tetraquark states. While in double charm sector we find shallow bound levels, our results suggest deeply bound levels with double bottom tetraquarks.Comment: Corrected threshold for the $ud\bar{c}\bar{c}$ tetraquark state. Proceedings of the 35th International Symposium on Lattice Field Theory, 18-24 June 2017, Granada, Spain. TIFR preprint no : TIFR/TH/17-3

Semi-supervised learning of order parameter in 2D Ising and XY models using Conditional Variational Autoencoders

We investigate the application of deep learning techniques employing the conditional variational autoencoders for semi-supervised learning of latent parameters to describe phase transition in the two-dimensional (2D) ferromagnetic Ising model and the two-dimensional XY model. For both models, we utilize spin configurations generated using the Wolff algorithms below and above the critical temperatures. For the 2D Ising model we find the latent parameter of conditional variational autoencoders is correlated to the known order parameter of magnetization more efficiently than their correspondence in variational autoencoders used previously. It can also clearly identify the restoration of the $\mathbb{Z}_2$ symmetry beyond the critical point. The critical temperature extracted from the latent parameter at larger lattices are found to be approaching its correct value. Similarly, for the 2D XY model, we find our chosen network with the latent representation of conditional variational autoencoders is equally capable of separating the two phases between the high and low temperatures, again at the correct critical temperature with reasonable accuracy. Together these results show that the latent representation of conditional variational autoencoders can be employed efficiently to identify the phases of condensed matter systems, without their prior knowledge.Comment: 9 pages, 8 figure

Spectroscopy of Charmed and Bottom Hadrons using Lattice QCD

We present preliminary results on the light, charmed and bottom baryon spectra using overlap valence quarks on the background of 2+1+1 flavours HISQ gauge configurations of the MILC collaboration. These calculations are performed on three different gauge ensembles at three lattice spacings (a ~ 0.12 fm, 0.09 fm and 0.06 fm) and for physical strange, charm and bottom quark masses. The SU(2) heavy baryon chiral perturbation theory is used to extrapolate baryon masses to the physical pion mass and the continuum limit extrapolations are also performed. Our results are consistent with the well measured charmed baryons. We predict the masses of many other states which are yet to be discovered.Comment: 8 pages, Proceedings of the 35th International Symposium on Lattice Field Theory (Lattice 2017