We present physical results obtained from simulations using 2+1 flavors of domain wall quarks and the Iwasaki gauge action at two values of the lattice spacing a, (a −1 = 1.73 (3) GeV and a −1 = 2.28 (3) GeV). On the coarser lattice, with 24 3 × 64 × 16 points (where the 16 corresponds to L s , the extent of the 5 th dimension inherent in the domain wall fermion (DWF) formulation

We present physical results for a variety of light hadronic quantities obtained via a combined analysis of three 2+1 flavour domain wall fermion ensemble sets. For two of our ensemble sets we used the Iwasaki gauge action with β = 2.13 (a −1 = 1.75(4) GeV) and β = 2.25 (a −1 = 2.31(4) We also obtain values for the SU(2) chiral perturbation theory effective couplings,l 3 = 2.91(23) stat (7) sys andl 4 = 3.99(16) stat (9) sys .GeV3

We present a new class of statistical error reduction techniques for Monte-Carlo simulations. Using covariant symmetries, we show that correlation functions can be constructed from inexpensive approximations without introducing any systematic bias in the final result. We introduce a new class of covariant approximation averaging techniques, known as all-mode averaging (AMA), in which the approximation takes account of contributions of all eigenmodes through the inverse of the Dirac operator computed from the conjugate gradient method with a relaxed stopping condition. In this paper we compare the performance and computational cost of our new method with traditional methods using correlation functions and masses of the pion, nucleon, and vector meson in N f = 2 + 1 lattice QCD using domain-wall fermions. This comparison indicates that AMA significantly reduces statistical errors in Monte-Carlo calculations over conventional methods for the same cost.

We investigate the continuum spectrum of the SU (2) gauge theory with N f = 2 flavours of fermions in the fundamental representation. This model provides a minimal template which is ideal for a wide class of Standard Model extensions featuring novel strong dynamics that range from composite (Goldstone) Higgs theories to several intriguing types of dark matter candidates, such as the SIMPs. We improve our previous lattice analysis [1] by adding more data at light quark masses, at two additional lattice spacings, by determining the lattice cutoff via a Wilson flow measure of the w 0 parameter, and by measuring the relevant renormalisation constants non-perturbatively in the RI'-MOM scheme. Our results for the lightest isovector states in the vector and axial channels, in units of the pseudoscalar decay constant, are m V /F PS ∼ 13.1(2.2) and m A /F PS ∼ 14.5(3.6) (combining statistical and systematic errors).In the context of the composite (Goldstone) Higgs models, our result for the spin-one resonances are m V > 3.2(5) TeV and m A > 3.6(9) TeV, which are above the current LHC constraints. In the context of dark matter models, for the SIMP case our results indicate the occurrence of a compressed spectrum at the required large dark pion mass, which implies the need to include the effects of spin-one resonances in phenomenological estimates.

As part of the UKQCD and RBC collaborations' N f ¼ 2 þ 1 domain-wall fermion phenomenology programme, we calculate the first two moments of the light-cone distribution amplitudes of the pseudoscalar mesons and K and the (longitudinally polarized) vector mesons , K Ã , and . We obtain the desired quantities with good precision and are able to discern the expected quark-mass dependence of SU(3)-flavor breaking effects. An important ingredient of the calculation is the nonperturbative renormalization of lattice operators using a regularization-independent momentum scheme.

2We determine the neutral kaon mixing matrix element B K in the continuum limit with 2+1 flavors of domain wall fermions, using the Iwasaki gauge action at two different lattice spacings. These lattice fermions have near exact chiral symmetry and therefore avoid artificial lattice operator mixing.We introduce a significant improvement to the conventional NPR method in which the bare matrix elements are renormalized non-perturbatively in the RI-MOM scheme and are then converted into the MS scheme using continuum perturbation theory. In addition to RI-MOM, we introduce and implement four non-exceptional intermediate momentum schemes that suppress infrared non-perturbative uncertainties in the renormalization procedure. We compute the conversion factors relating the matrix elements in this family of RI-SMOM schemes and MS at one-loop order.Comparison of the results obtained using these different intermediate schemes allows for a more reliable estimate of the unknown higher-order contributions and hence for a correspondingly more robust estimate of the systematic error. We also apply a recently proposed approach in which twisted boundary conditions are used to control the Symanzik expansion for off-shell vertex functions leading to a better control of the renormalization in the continuum limit.We control chiral extrapolation errors by considering both the NLO SU(2) chiral effective theory, and an analytic mass expansion. We obtain B MS K (3 GeV) = 0.529(5) stat (15) χ (2) FV (11) NPR . This corresponds toB RGI K = 0.749(7) stat (21) χ (3) FV (15) NPR . Adding all sources of error in quadrature we obtainB RGI K = 0.749(27) combined , with an overall combined error of 3.6%.3

“Social sensing” is a form of crowd-sourcing that involves systematic analysis of digital communications to detect real-world events. Here we consider the use of social sensing for observing natural hazards. In particular, we present a case study that uses data from a popular social media platform (Twitter) to detect and locate flood events in the UK. In order to improve data quality we apply a number of filters (timezone, simple text filters and a naive Bayes ‘relevance’ filter) to the data. We then use place names in the user profile and message text to infer the location of the tweets. These two steps remove most of the irrelevant tweets and yield orders of magnitude more located tweets than we have by relying on geo-tagged data. We demonstrate that high resolution social sensing of floods is feasible and we can produce high-quality historical and real-time maps of floods using Twitter.

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