Lattice QCD strategy interpolates sub-physical mass data with OPE to obtain the inclusive anti-B_s to X_sc l nu decay rate, yielding 7% precision on limited ETMC ensembles via a new four-point correlator method.
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hep-lat 4years
2026 4verdicts
UNVERDICTED 4representative citing papers
The causal bootstrap computes rigorous bounds on smeared spectral functions from non-perturbative Euclidean data by optimizing over the convex set of compatible positive spectral densities and reducing dual problems to semidefinite programs for certain kernels.
Derives analytic integral-transform formulae to extract continuum and smeared spectral densities from Euclidean correlators, with O(a^2) lattice convergence and rigorous bounds for finite-volume effects.
Framework for exact and approximate kernel transformations between smeared spectral functions, including systematic error bounds computable from input data.
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Inclusive $\bar B_s\mapsto X_{\bar sc} \ell \bar \nu$ decays from lattice QCD: computational strategy and a first physical result
Lattice QCD strategy interpolates sub-physical mass data with OPE to obtain the inclusive anti-B_s to X_sc l nu decay rate, yielding 7% precision on limited ETMC ensembles via a new four-point correlator method.
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The Causal Bootstrap: Bounding Smeared Spectral Functions from Non-Perturbative Euclidean Data
The causal bootstrap computes rigorous bounds on smeared spectral functions from non-perturbative Euclidean data by optimizing over the convex set of compatible positive spectral densities and reducing dual problems to semidefinite programs for certain kernels.
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Spectral densities from Euclidean correlators via integral transforms: theoretical framework
Derives analytic integral-transform formulae to extract continuum and smeared spectral densities from Euclidean correlators, with O(a^2) lattice convergence and rigorous bounds for finite-volume effects.
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Kernel transformations and bounds for smeared spectral functions
Framework for exact and approximate kernel transformations between smeared spectral functions, including systematic error bounds computable from input data.