A hierarchy of semidefinite programs provides rigorous bounds on spectral density functionals from Monte Carlo data subject to reflection positivity, converging to statistical error limits.
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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.
SVD truncation of the exp(-ωt) kernel reconstructs smeared spectral functions from lattice correlators with controlled uncertainties and approaches the Mellin transform in the continuum limit.
Radiative corrections applied to MINERvA antineutrino data yield updated values for the nucleon axial-vector form factor G_A and axial radius.
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Certified spectral functions from lattice Monte Carlo data
A hierarchy of semidefinite programs provides rigorous bounds on spectral density functionals from Monte Carlo data subject to reflection positivity, converging to statistical error limits.
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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 reconstruction from Euclidean lattice correlators through singular value decomposition
SVD truncation of the exp(-ωt) kernel reconstructs smeared spectral functions from lattice correlators with controlled uncertainties and approaches the Mellin transform in the continuum limit.
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Nucleon axial-vector form factor and radius from radiatively-corrected antineutrino scattering data
Radiative corrections applied to MINERvA antineutrino data yield updated values for the nucleon axial-vector form factor G_A and axial radius.