We present a novel technique for the determination of the topological susceptibility (related to the variance of the distribution of global topological charge) from lattice gauge theory simulations, based on maximum-likelihood analysis of the Markov-
chain Monte Carlo time series. This technique is expected to be particularly useful in situations where relatively few tunneling events are observed. Restriction to a lattice subvolume on which topological charge is not quantized is explored, and may lead to further improvement when the global topology is poorly sampled. We test our proposed method on a set of lattice data, and compare it to traditional methods.
Composite dark matter candidates, which can arise from new strongly-coupled sectors, are well-motivated and phenomenologically interesting, particularly in the context of asymmetric generation of the relic density. In this work, we employ lattice cal
culations to study the electromagnetic form factors of electroweak-neutral dark-matter baryons for a three-color, QCD-like theory with Nf = 2 and 6 degenerate fermions in the fundamental representation. We calculate the (connected) charge radius and anomalous magnetic moment, both of which can play a significant role for direct detection of composite dark matter. We find minimal Nf dependence in these quantities. We generate mass-dependent cross-sections for dark matter-nucleon interactions and use them in conjunction with experimental results from XENON100, excluding dark matter candidates of this type with masses below 10 TeV.
We give an update on simulation results for the decay constants f_B, f_{B_s}, f_D and f_{D_s}. These decay constants are important for precision tests of the standard model, in particular entering as inputs to the global CKM unitarity triangle fit. T
he results presented here make use of the MILC (2+1)-flavor asqtad ensembles, with heavy quarks incorporated using the clover action with the Fermilab method. Partially quenched, staggered chiral perturbation theory is used to extract the decay constants at the physical point. In addition, we give error projections for a new analysis in progress, based on an extended data set.
