Craig McNeile

We extend the Worldline Monte Carlo approach to computationally simulating the Feynman path integral of non-relativistic multi-particle quantum-mechanical systems. We show how to generate an arbitrary number of worldlines distributed according to the (free) kinetic part of the multi-particle quantum dynamics and how to simulate interactions between worldlines in the ensemble. We test this formalism with two- and three-particle quantum mechanical systems, with both long range Coulomb-like interactions between the particles and external fields acting separately on the particles, in various spatial dimensionality. We extract accurate estimations of the ground state energy of these systems using the late-time behaviour of the propagator, validating our approach with numerically exact solutions obtained via straightforward diagonalisation of the Hamiltonian. Systematic benchmarking of the new approach, presented here for the first time, shows that the computational complexity of Wordline Monte Carlo scales more favourably with respect to standard numerical alternatives. The method, which is general, numerically exact, and computationally not intensive, can easily be generalised to relativistic systems.

We present results for the dominant light-quark connected contribution to the long-distance window of the hadronic vacuum polarization (HVP) contribution to the muon g − 2 from lattice quantum chromodynamics. Specifically, with a new determination of the lattice scale on MILC’s physical-mass HISQ ensembles, using the Ω − baryon mass, we obtain a result of a μ l l , LD ( conn ) = 400.2 ( 2.3 ) stat ( 3.7 ) syst [ 4.3 ] total × 10 − 10 . Summing this result with our recent determinations of the light-quark connected contributions to the short- and intermediate-distance windows, we obtain a subpercent precision determination of the light-quark-connected contribution to HVP of a μ l l ( conn ) = 655.2 ( 2.3 ) stat ( 3.9 ) syst [ 4.5 ] total × 10 − 10 . Finally, as a consistency check, we verify that an independent analysis of the full contribution is in agreement with the sum of individual windows. We discuss our future plans for improvements of our HVP calculations to meet the target precision of the Fermilab g − 2 experiment.

We present complete results for the hadronic vacuum polarization (HVP) contribution to the muon anomalous magnetic moment a μ in the short- and intermediate-distance window regions, which account for roughly 10% and 35% of the total HVP contribution to a μ , respectively. In particular, we perform lattice-QCD calculations for the isospin-symmetric connected and disconnected contributions, as well as corrections due to strong-isospin breaking. For the short-distance window observables, we investigate the so-called log-enhancement effects as well as the significant oscillations associated with staggered quarks in this region. For the dominant, isospin-symmetric light-quark-connected contribution, we obtain a μ l l , SD ( conn ) = 48.139 ( 11 ) stat ( 91 ) syst [ 92 ] total × 10 − 10 and a μ l l , W ( conn ) = 206.90 ( 14 ) stat ( 61 ) syst [ 63 ] total × 10 − 10 . We use Bayesian model averaging to fully estimate the covariance matrix between the individual contributions. Our determinations of the complete window contributions are a μ SD = 69.05 ( 1 ) stat ( 21 ) syst [ 21 ] total × 10 − 10 and a μ W = 236.45 ( 17 ) stat ( 83 ) syst [ 85 ] total × 10 − 10 . This work is part of our ongoing effort to compute all contributions to HVP with an overall uncertainty at the few-permille level. Published by the American Physical Society 2025

Telecom services are at the core of today's societies' everyday needs. The availability of numerous online forums and discussion platforms enables telecom providers to improve their services by exploring the views of their customers to learn about common issues that the customers face. Natural Language Processing (NLP) tools can be used to process the free text collected. One way of working with such data is to represent text as numerical vectors using one of many word embedding models based on neural networks. This research uses a novel dataset of telecom customers' reviews to perform an extensive study showing how different word embedding algorithms can affect the text classification process. Several state-of-the-art word embedding techniques are considered, including BERT, Word2Vec and Doc2Vec, coupled with several classification algorithms. The important issue of feature engineering and dimensionality reduction is addressed and several PCA-based approaches are explored. Moreover, the energy consumption used by the different word embeddings is investigated. The findings show that some word embedding models can lead to consistently better text classifiers in terms of precision, recall and F1-Score. In particular, for the more challenging classification tasks, BERT combined with PCA stood out with the highest performance metrics. Moreover, our proposed PCA approach of combining word vectors using the first principal component shows clear advantages in performance over the traditional approach of taking the average.

An accurate calculation of the leading-order hadronic vacuum polarization (LOHVP) contribution to the anomalous magnetic moment of the muon ( a μ ) is key to determining whether a discrepancy, suggesting new physics, exists between the Standard Model and experimental results. This calculation can be expressed as an integral over Euclidean time of a current-current correlator G ( t ) , where G ( t ) can be calculated using lattice QCD or, with dispersion relations, from experimental data for e + e − → hadrons . The BMW/DMZ collaboration recently presented a hybrid approach in which G ( t ) is calculated using lattice QCD for most of the contributing t range, but using experimental data for the largest t (lowest energy) region. Here we study the advantages of varying the position t = t 1 separating lattice QCD from data-driven contributions. The total LOHVP contribution should be independent of t 1 , providing both a test of the experimental input and the robustness of the hybrid approach. We use this criterion and a correlated fit to show that Fermilab/HPQCD/MILC lattice QCD results from 2019 strongly favor the CMD-3 cross section data for e + e − → π + π − over a combination of earlier experimental results for this channel. Further, the resulting total LOHVP contribution obtained is consistent with the result obtained by BMW/DMZ, and supports the scenario in which there is no significant discrepancy between the experimental value for a μ and that expected in the Standard Model. We then discuss how improved lattice results in this hybrid approach could provide a more accurate total LOHVP across a wider range of t 1 values with an uncertainty that is smaller than that from either lattice QCD or data-driven approaches on their own.