Lattice QCD pseudo-distributions at m_π=358 MeV are inverted via multidimensional Gaussian process regression to reconstruct the full kinematic dependence of GPDs H^{u-d} and E^{u-d} while directly extracting double distributions.
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Presents a new ensemble regression hyperoptimisation procedure for PDF fitting that combines multiple statistically equivalent methodologies into one PDF set accounting for hyperparameter variation.
Alternative truncation-based procedure for smeared spectral density extraction from lattice correlators using SVD-style decomposition to decouple noise from signal.
Kinematically enhanced nucleon interpolators improve precision of renormalized quark matrix elements by an order of magnitude at 2.5 GeV with no observed lattice spacing dependence on CLS ensembles.
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Reconstructing the full kinematic dependence of GPDs from pseudo-distributions
Lattice QCD pseudo-distributions at m_π=358 MeV are inverted via multidimensional Gaussian process regression to reconstruct the full kinematic dependence of GPDs H^{u-d} and E^{u-d} while directly extracting double distributions.
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Hyperoptimisation algorithm for the next generation of PDF determinations: ensemble regression with an unbiased selection model
Presents a new ensemble regression hyperoptimisation procedure for PDF fitting that combines multiple statistically equivalent methodologies into one PDF set accounting for hyperparameter variation.
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Extraction of spectral densities from lattice correlators: decoupling signal from noise
Alternative truncation-based procedure for smeared spectral density extraction from lattice correlators using SVD-style decomposition to decouple noise from signal.
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Kinematic enhancement for nucleon interpolators
Kinematically enhanced nucleon interpolators improve precision of renormalized quark matrix elements by an order of magnitude at 2.5 GeV with no observed lattice spacing dependence on CLS ensembles.