Lattice phenomenology of heavy quarks using dynamical fermions

The Standard Model of particle physics is believed to be only the low energy limit of a more fundamental theory. In order to determine its range of validity, a major part of theoretical and experimental efforts in physics is dedicated to precision tests of the Standard Model. Lattice QCD is a non-perturbative, first-principles approach to Quantum Field Theory. It plays an important role in flavor physics by providing calculations of non-perturbative strong interaction contributions to weak processes involving quarks. Measurements of hadronic quantities can be used to constrain the Standard Model as well as theories Beyond the Standard Model. The first part of this thesis contains theoretical developments regarding non-perturbative renormalization. A new renormalization scheme, RI/mSMOM, for fermion bilinear operators in QCD at non-vanishing quark mass is presented. In order to investigate the properties of the mSMOM scheme, an explicit one-loop computation in perturbation theory using dimensional regularization is performed. Numerically, vertex functions are generated on the lattice, with an appropriate projector, based on the RI/SMOM scheme and the renormalization factors are extracted. Quantities measured include renormalization of the axial current ZA, required to renormalize the axial current entering the computation of the decay constant and the renormalization of the bag parameter. The second part of this report focuses on flavor physics phenomenology on the lattice. It presents results of the first run of the RBC/UKQCD charm project with (2+1)-flavor Domain Wall fermions. Observables and matrix elements are measured on lattices with Iwasaki gauge action. There are two ensembles at the physical point with inverse lattice spacings 1.73 and 2.36 GeV and a third finer ensemble at 2.76 GeV as well as four other auxiliary ensembles with smaller volumes and heavier pion masses which are used to perform the continuum extrapolations. The quantities measured in the region of the charm quark mass are meson masses, decay constants, the matrix element of the OV V +AA operator, the neutral D-meson mixing parameter B and the SU(3) breaking ratio ξ

Higher-order interactions in statistical physics and machine learning: A model-independent solution to the inverse problem at equilibrium

The problem of inferring pair-wise and higher-order interactions in complex systems involving large numbers of interacting variables, from observational data, is fundamental to many fields. Known to the statistical physics community as the inverse problem, it has become accessible in recent years due to real and simulated 'big' data being generated. Current approaches to the inverse problem rely on parametric assumptions, physical approximations, e.g. mean-field theory, and ignoring higher-order interactions which may lead to biased or incorrect estimates. We bypass these shortcomings using a cross-disciplinary approach and demonstrate that none of these assumptions and approximations are necessary: We introduce a universal, model-independent, and fundamentally unbiased estimator of all-order symmetric interactions, via the non-parametric framework of Targeted Learning, a subfield of mathematical statistics. Due to its universality, our definition is readily applicable to any system at equilibrium with binary and categorical variables, be it magnetic spins, nodes in a neural network, or protein networks in biology. Our approach is targeted, not requiring fitting unnecessary parameters. Instead, it expends all data on estimating interactions, hence substantially increasing accuracy. We demonstrate the generality of our technique both analytically and numerically on (i) the 2-dimensional Ising model, (ii) an Ising-like model with 4-point interactions, (iii) the Restricted Boltzmann Machine, and (iv) simulated individual-level human DNA variants and representative traits. The latter demonstrates the applicability of this approach to discover epistatic interactions causal of disease in population biomedicine.Comment: 25 pages, 25 figures. Comments welcom

Machine learning determination of dynamical parameters::The Ising model case

We train a set of Restricted Boltzmann Machines (RBMs) on one- and two-dimensional Ising spin configurations at various values of temperature, generated using Monte Carlo simulations. We validate the training procedure by monitoring several estimators, including measurements of the log-likelihood, with the corresponding partition functions estimated using annealed importance sampling. The effects of various choices of hyper-parameters on training the RBM are discussed in detail, with a generic prescription provided. Finally, we present a closed form expression for extracting the values of couplings, for every $n$-point interaction between the visible nodes of an RBM, in a binary system such as the Ising model. We aim at using this study as the foundation for further investigations of less well-known systems.Comment: 31 page

Sweeping away barriers to interdisciplinary research:recommendations based on X-Net project outcomes - March 2024

X-Net is an interdisciplinary research network whose main aim is to understand barriers to interdisciplinary research, before offering solutions to overcome them. X-Net recommends a 13-step programme of targeted multi-level interventions drawn from evidence gathered by the network in 2022- 2023. The 13 interventions would deeply weave interdisciplinarity into UK scientific research culture and free the flow of ideas and expertise across traditional disciplinary boundaries and sectors

Overcoming barriers to cross-disciplinary research

Interdisciplinary research can create many scientific opportunities but may also face challenges and barriers. X-Net’s main objective is helping interdisciplinary scientists to overcome those barriers providing guidance and resources, particularly to early career researchers. We organised an online workshop “Overcoming barriers to cross-disciplinary research” (6th July, 2022) with the purpose of identifying the main obstacles of interdisciplinary research (IDR) in the UK. The workshop incorporated a pre-workshop anonymous survey that allowed participants to identify and share some of their personal experiences of cross-disciplinary research. The workshop then used these experiences to find themes or challenges in common. It also allowed participants to consider, through action learning, what specific cross-disciplinary barrier(s) they sought advice on. The survey questionnaire was designed to focus on the opinions of individual scientists regarding the barriers or incentives for interdisciplinary research and to receive diverse perspectives. Researchers with early or ongoing experience in interdisciplinarity entering biomedical sciences from STEM were approached for their opinions

A TGFβ-ECM-Integrin signalling axis drives structural reconfiguration of the bile duct to promote polycystic liver disease

: The formation of multiple cysts in the liver occurs in a number of isolated monogenic diseases or multisystemic syndromes, during which bile ducts develop into fluid-filled biliary cysts. For patients with polycystic liver disease (PCLD), nonsurgical treatments are limited, and managing life-long abdominal swelling, pain, and increasing risk of cyst rupture and infection is common. We demonstrate here that loss of the primary cilium on postnatal biliary epithelial cells (via the deletion of the cilia gene Wdr35) drives ongoing pathological remodeling of the biliary tree, resulting in progressive cyst formation and growth. The development of cystic tissue requires the activation of transforming growth factor-β (TGFβ) signaling, which promotes the expression of a procystic, fibronectin-rich extracellular matrix and which itself is perceived by a changing profile of integrin receptors on the cystic epithelium. This signaling axis is conserved in liver cysts from patients with either autosomal dominant polycystic kidney disease or autosomal dominant polycystic liver disease, indicating that there are common cellular mechanisms for liver cyst growth regardless of the underlying genetic cause. Cyst number and size can be reduced by inhibiting TGFβ signaling or integrin signaling in vivo. We suggest that our findings represent a therapeutic route for patients with polycystic liver disease, most of whom would not be amenable to surgery

Comparative transcriptome in large-scale human and cattle populations:Comparative transcriptome in humans and cattle

BACKGROUND: Cross-species comparison of transcriptomes is important for elucidating evolutionary molecular mechanisms underpinning phenotypic variation between and within species, yet to date it has been essentially limited to model organisms with relatively small sample sizes. RESULTS: Here, we systematically analyze and compare 10,830 and 4866 publicly available RNA-seq samples in humans and cattle, respectively, representing 20 common tissues. Focusing on 17,315 orthologous genes, we demonstrate that mean/median gene expression, inter-individual variation of expression, expression quantitative trait loci, and gene co-expression networks are generally conserved between humans and cattle. By examining large-scale genome-wide association studies for 46 human traits (average n = 327,973) and 45 cattle traits (average n = 24,635), we reveal that the heritability of complex traits in both species is significantly more enriched in transcriptionally conserved than diverged genes across tissues. CONCLUSIONS: In summary, our study provides a comprehensive comparison of transcriptomes between humans and cattle, which might help decipher the genetic and evolutionary basis of complex traits in both species. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-022-02745-4