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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 investigate the leading power corrections to the decay rates and distributions in the decay $B \rightarrow X_s \ell^+ \ell^- $ in the standard model (SM) using heavy quark expansion (HQE) in $(1/m_b)$ and a phenomenological model…
Hamiltonian Monte Carlo (HMC) is a Markov chain algorithm for sampling from a high-dimensional distribution with density $e^{-f(x)}$, given access to the gradient of $f$. A particular case of interest is that of a $d$-dimensional Gaussian…
For big data analysis, high computational cost for Bayesian methods often limits their applications in practice. In recent years, there have been many attempts to improve computational efficiency of Bayesian inference. Here we propose an…
Astrometric surveys provide the opportunity to measure the absolute magnitudes of large numbers of stars, but only if the individual line-of-sight extinctions are known. Unfortunately, extinction is highly degenerate with stellar effective…
Equilibrium statistics of Hamiltonian systems is correctly described by the microcanonical ensemble. Classically this is the manifold of all points in the N-body phase space with the given total energy. Due to Boltzmann-Planck's principle,…
Bayesian neural networks (BNNs) are a principled approach to modeling predictive uncertainties in deep learning, which are important in safety-critical applications. Since exact Bayesian inference over the weights in a BNN is intractable,…
We have used Monte Carlo simulation techniques to obtain the magnetic phase diagram of the double exchange Hamiltonian. We have found that the Berry's phase of the hopping amplitude has a negligible effect in the value of the magnetic…
A method is proposed to handle the sign problem in the simulation of systems having indefinite or complex-valued measures. In general, this new approach, which is based on renormalisation blocking, is shown to yield statistical errors…
The real-world data of power networks is often inaccessible due to privacy and security concerns, highlighting the need for tools to generate realistic synthetic network data. Existing methods leverage geographic tools like OpenStreetMap…
We present a practical implementation of a Monte Carlo method to estimate the significance of cross-correlations in unevenly sampled time series of data, whose statistical properties are modeled with a simple power-law power spectral…
We here apply the recently developed initiator density matrix quantum Monte Carlo (i-DMQMC) to a wide range of chemical environments using atoms and molecules in vacuum. i-DMQMC samples the exact density matrix of a Hamiltonian at finite…
We study the static and dynamic properties of bromine electrosorption onto single-crystal silver (100) electrodes by Monte Carlo simulation. At room temperature the system displays a second-order phase transition between a low-coverage…
An efficient method for computing thermodynamic equilibrium states at the micromagnetic length scale is introduced, using the Markov chain Monte Carlo method. Trial moves include not only rotations of vectors, but also a change in their…
The photon spectrum in the inclusive electromagnetic radiative decays of the $B$ meson, $B \to X_{s} \gamma$ plus $B \to X_{d} \gamma$, is studied using a data sample of $(382.8 \pm 4.2) \times 10^6$ $\Upsilon(4S) \to B\overli\ ne{B}$…
We propose an approach to lossy source coding, utilizing ideas from Gibbs sampling, simulated annealing, and Markov Chain Monte Carlo (MCMC). The idea is to sample a reconstruction sequence from a Boltzmann distribution associated with an…
We present a comprehensive phenomenological analysis of the calorimetric electron capture (EC) decay spectrum of $^{163}$Ho as measured by the HOLMES experiment. Using high-statistics data, we unfold the instrumental energy resolution from…
This paper proposes a symbolic-numeric Bayesian filtering method for a class of discrete-time nonlinear stochastic systems to achieve high accuracy with a relatively small online computational cost. The proposed method is based on the…
We calculate the electron spectrum of semileptonic decays of B-mesons into non-charmed hadrons. The shape of the spectrum obtained from QCD sum rules is in general agreement with quark model calculations. At high electron energies the…
Uncertainty estimation in deep models is essential in many real-world applications and has benefited from developments over the last several years. Recent evidence suggests that existing solutions dependent on simple Gaussian formulations…