Search arXiv⌕ Search

arXiv · hep-lat/0508028

Ghost condensation on the lattice

Abstract

We perform a numerical study of ghost condensation -- in the so-called Overhauser channel -- for SU(2) lattice gauge theory in minimal Landau gauge. The off-diagonal components of the momentum-space ghost propagator G^{cd}(p) are evaluated for lattice volumes V = 8^4, 12^4, 16^4, 20^4, 24^4 and for three values of the lattice coupling: β= 2.2, 2.3, 2.4. Our data show that the quantity ϕ^b(p) = ε^{bcd} G^{cd}(p) / 2 is zero within error bars, being characterized by very large statistical fluctuations. On the contrary, |ϕ^b(p)| has relatively small error bars and behaves at small momenta as L^{-2} p^{-z}, where L is the lattice side in physical units and z \approx 4. We argue that the large fluctuations for ϕ^b(p) come from spontaneous breaking of a global symmetry and are associated with ghost condensation. It may thus be necessary (in numerical simulations at finite volume) to consider |ϕ^b(p)| instead of ϕ^b(p), to avoid a null average due to tunneling between different broken vacua. Also, we show that ϕ^b(p) is proportional to the Fourier-transformed gluon field components {\widetilde A}_μ^b(q). This explains the L^{-2} dependence of |ϕ^b(p)|, as induced by the behavior of | {\widetilde A}_μ^b(q) |. We fit our data for |ϕ^b(p)| to the theoretical prediction (r / L^2 + v) / (p^4 + v^2), obtaining for the ghost condensate v an upper bound of about 0.058 GeV^2. In order to check if v is nonzero in the continuum limit, one probably needs numerical simulations at much larger physical volumes than the ones we consider. As a by-product of our analysis, we perform a careful study of the color structure of the inverse Faddeev-Popov matrix in momentum space.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Attilio Cucchieri, Tereza Mendes, Antonio Mihara. 2005-11-02. Ghost condensation on the lattice. https://doi.org/10.1103/physrevd.72.094505

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Accurate Sampling from Diffusion Models

A new proposal called DM-SMC (Diffusion Model - Sequential Monte Carlo) is investigated, which samples ensembles defined in terms of an action, using diffusion models trained on samples from the ensemble. The SMC setup allows for accurate sampling in spite of an approximate diffusion model and the finite stepsize used in the numerical solution of the stochastic process. Improved update strategies are also investigated. Results are presented for a $Z_2$ symmetric scalar field theory in 2 dimensions near its 2nd order phase transition.

hep-lat↗

Decomposition of the axial-vector current in a finite box

We consider the matrix element of the axial-vector current between two nucleon states in a finite box. Starting from the chiral Lagrangian density with nucleon and Delta-isobar degrees of freedom, we study the finite-volume effects at the one-loop level. We show that the standard decomposition into the axial-vector and pseudoscalar form factor is incomplete in a finite box. We derive expressions for the complete set of in-box form factors at one loop, and demonstrate how to extract the full set from lattice correlation functions. We verify that the axial Ward identity holds in the chiral limit. We derive the one-loop expressions for the pseudoscalar form factor and verify that the in-box axial Ward identity away from the chiral limit is fulfilled also. Selected numerical results are shown for two flavor-SU(2) lattice ensembles. Sizable finite-volume effects are observed, with an important role for the Delta-isobar. We discuss the implications of our results for lattice studies of the axial-vector current. We conclude that full finite-box results are crucial for a precise determination of the form factors.

hep-lat↗

A variational framework for variance reduction in lattice field theory

The signal-to-noise problem limits the reach of many lattice calculations. We present a variational framework that recasts it as a transport problem: the loss of signal reflects a mismatch between the distribution one samples and the one needed to measure an observable, and can be reduced by transporting configurations to close that gap. The optimal transport is typically determined either through a stochastic estimator based on Langevin dynamics or by parametrising it as a normalising flow trained with automatic differentiation. We discuss how the framework brings these methods under a common variational principle and present results for scalar theories.

hep-lat↗