Renormalization of Tamm-Dancoff Integral Equations

During the last few years, interest has arisen in using light-front Tamm-Dancoff field theory to describe relativistic bound states for theories such as QCD. Unfortunately, difficult renormalization problems stand in the way. We introduce a general, non-perturbative approach to renormalization that is well suited for the ultraviolet and, presumably, the infrared divergences found in these systems. We reexpress the renormalization problem in terms of a set of coupled inhomogeneous integral equations, the ``counterterm equation.'' The solution of this equation provides a kernel for the Tamm-Dancoff integral equations which generates states that are independent of any cutoffs. We also introduce a Rayleigh-Ritz approach to numerical solution of the counterterm equation. Using our approach to renormalization, we examine several ultraviolet divergent models. Finally, we use the Rayleigh-Ritz approach to find the counterterms in terms of allowed operators of a theory.Comment: 19 pages, OHSTPY-HEP-T-92-01

Application of Pauli-Villars regularization and discretized light-cone quantization to a single-fermion truncation of Yukawa theory

We apply Pauli-Villars regularization and discretized light-cone quantization to the nonperturbative solution of (3+1)-dimensional Yukawa theory in a single-fermion truncation. Three heavy scalars, including two with negative norm, are used to regulate the theory. The matrix eigenvalue problem is solved for the lowest-mass state with use of a new, indefinite-metric Lanczos algorithm. Various observables are extracted from the wave functions, including average multiplicities and average momenta of constituents, structure functions, and a form factor slope.Comment: 21 pages, 7 figures, RevTeX; published version: more extensive data in the tables of v

Nonperturbative Light-Front QCD

In this work the determination of low-energy bound states in Quantum Chromodynamics is recast so that it is linked to a weak-coupling problem. This allows one to approach the solution with the same techniques which solve Quantum Electrodynamics: namely, a combination of weak-coupling diagrams and many-body quantum mechanics. The key to eliminating necessarily nonperturbative effects is the use of a bare Hamiltonian in which quarks and gluons have nonzero constituent masses rather than the zero masses of the current picture. The use of constituent masses cuts off the growth of the running coupling constant and makes it possible that the running coupling never leaves the perturbative domain. For stabilization purposes an artificial potential is added to the Hamiltonian, but with a coefficient that vanishes at the physical value of the coupling constant. The weak-coupling approach potentially reconciles the simplicity of the Constituent Quark Model with the complexities of Quantum Chromodynamics. The penalty for achieving this perturbative picture is the necessity of formulating the dynamics of QCD in light-front coordinates and of dealing with the complexities of renormalization which such a formulation entails. We describe the renormalization process first using a qualitative phase space cell analysis, and we then set up a precise similarity renormalization scheme with cutoffs on constituent momenta and exhibit calculations to second order. We outline further computations that remain to be carried out. There is an initial nonperturbative but nonrelativistic calculation of the hadronic masses that determines the artificial potential, with binding energies required to be fourth order in the coupling as in QED. Next there is a calculation of the leading radiative corrections to these masses, which requires our renormalization program. Then the real struggle of finding the right extensions to perturbation theory to study the strong-coupling behavior of bound states can begin.Comment: 56 pages (REVTEX), Report OSU-NT-94-28. (figures not included, available via anaonymous ftp from pacific.mps.ohio-state.edu in subdirectory pub/infolight/qcd

Enhancing agent-based simulation of mechanized tunneling by leveraging data exchange with machine learning models

Agent-based simulation (ABS) and machine learning (ML) can be combined to model and analyze complex systems. ABS involves creating agents that simulate decision-making processes in real-world systems, while ML uses data-based algorithms to handle big data and gain insights into these systems. This paper proposes a method to exchange data between an ABS model of a mechanized tunneling project and an ML prediction model to improve the simulation’s outcomes. In mechanized tunneling projects, the initial estimation of project duration often deviates significantly from the actual duration due to unplanned disturbances, leading to increased costs. To address this issue, simulation models developed during the planning phase can be updated with real-time data to make them useful in real-time scenarios. Here, ML models are employed to train sensor data from the tunnel boring machine (TBM) to predict the ring-building duration parameter of the ABS accurately for the next steps. This enhances the estimation of the total tunnel construction duration. This approach is adaptable to various applications depending on data availability. The paper concludes by suggesting further research directions for leveraging data exchange to enhance modeling capabilities in complex systems

CXCR2 mediates NADPH oxidase-independent neutrophil extracellular trap formation in cystic fibrosis airway inflammation.

Upon activation, neutrophils release DNA fibers decorated with antimicrobial proteins, forming neutrophil extracellular traps (NETs). Although NETs are bactericidal and contribute to innate host defense, excessive NET formation has been linked to the pathogenesis of autoinflammatory diseases. However, the mechanisms regulating NET formation, particularly during chronic inflammation, are poorly understood. Here we show that the G protein-coupled receptor (GPCR) CXCR2 mediates NET formation. Downstream analyses showed that CXCR2-mediated NET formation was independent of NADPH oxidase and involved Src family kinases. We show the pathophysiological relevance of this mechanism in cystic fibrosis lung disease, characterized by chronic neutrophilic inflammation. We found abundant NETs in airway fluids of individuals with cystic fibrosis and mouse cystic fibrosis lung disease, and NET amounts correlated with impaired obstructive lung function. Pulmonary blockade of CXCR2 by intra-airway delivery of small-molecule antagonists inhibited NET formation and improved lung function in vivo without affecting neutrophil recruitment, proteolytic activity or antibacterial host defense. These studies establish CXCR2 as a receptor mediating NADPH oxidase-independent NET formation and provide evidence that this GPCR pathway is operative and druggable in cystic fibrosis lung disease