Related papers: Das ist der HAMMER: Consistent new physics interpr…
Hamiltonian Monte Carlo (HMC) is a popular Markov Chain Monte Carlo (MCMC) algorithm to sample from an unnormalized probability distribution. A leapfrog integrator is commonly used to implement HMC in practice, but its performance can be…
Because quarks in hadronic states are subjected to strong QCD forces, it is not straight-forward to apply calculation obtained at the quark level to physical processes involving hadrons. In this paper we present a new approach to treat the…
The flavor-changing neutral current decays of heavy bottom quark, alongside the flavor-changing charged current processes mediated by $b \to (c, u)$ in semileptonic $B$ decays are emerged as powerful tools for exploring physics beyond the…
We present new methods for lensing reconstruction from CMB temperature fluctuations which have smaller mean-field and reconstruction noise bias corrections than current lensing estimators, with minimal loss of signal-to-noise. These biases…
We provide analysis of the convergence properties and applicability extensions of flat-histogram algorithms, with a particular focus on the Wang-Landau algorithms (exemplified by converging stochastic approximation Monte Carlo (SAMC)) and…
Hamiltonian Monte Carlo (HMC) has been widely adopted in the statistics community because of its ability to sample high-dimensional distributions much more efficiently than other Metropolis-based methods. Despite this, HMC often performs…
Hamiltonian Monte Carlo (HMC) is a powerful Markov chain Monte Carlo (MCMC) method for performing approximate inference in complex probabilistic models of continuous variables. In common with many MCMC methods, however, the standard HMC…
Hamiltonian Monte Carlo has emerged as a standard tool for posterior computation. In this article, we present an extension that can efficiently explore target distributions with discontinuous densities. Our extension in particular enables…
Charmless semileptonic decays, ${\bar{B}} \to X_u \ell \bar{\nu}$, are studied in a sample of 232 million $B\bar{B}$ decays recorded with the BaBar detector, in events where the decay of the second $B$ meson is fully reconstructed.…
Neutrino mass constraints are a primary focus of current and future large-scale structure (LSS) surveys. Non-linear LSS models rely heavily on cosmological simulations -- the impact of massive neutrinos should therefore be included in these…
The Homotopy Analysis Method (HAM) is a widely used analytical approach for solving nonlinear problems, yet its theoretical foundation lacks rigorous justification, and its intrinsic correlation with perturbation theory remains ambiguous,…
Theoretical predictions in high energy physics are routinely provided in the form of Monte Carlo generators. Comparisons of predictions from different programs and/or different initialization set-ups are often necessary. MC-TESTER can be…
The increasing number of flavour anomalies calls for the investigation of new processes where tensions similar to the observed ones could emerge. Observables sensitive to physics beyond the Standard Model need to be identified. We discuss…
We present a new Subset Simulation approach using Hamiltonian neural network-based Monte Carlo sampling for reliability analysis. The proposed strategy combines the superior sampling of the Hamiltonian Monte Carlo method with…
We study the benefits and limits of parallelised Markov chain Monte Carlo (MCMC) sampling in cosmology. MCMC methods are widely used for the estimation of cosmological parameters from a given set of observations and are typically based on…
We perform model-independent statistical analyses of three scenarios accommodating New Physics (NP) in Delta F=2 flavour-changing neutral current amplitudes. In a scenario in which NP in B_d-B_d-bar and B_s-B_s-bar is uncorrelated, we find…
In the last few years we have been developing a Monte Carlo simulation method to cope with systems of many electrons and ions in the Born-Oppenheimer (BO) approximation, the Coupled Electron-Ion Monte Carlo Method (CEIMC). Electronic…
There is substantial empirical evidence about the success of dynamic implementations of Hamiltonian Monte Carlo (HMC), such as the No U-Turn Sampler (NUTS), in many challenging inference problems but theoretical results about their behavior…
We report updates on two analyses of inclusive semileptonic B decays based on a dataset of 89 million BB events recorded with the BABAR detector at the Y(4S) resonance. Events are selected by fully reconstructing the decay of one B meson…
The B_s to mu+ mu- decay plays an outstanding role in tests of the Standard Model and physics beyond it. The LHCb collaboration has recently reported the first evidence for this decay at the 3.5 sigma level, with a branching ratio in the…