No CMB-consistent CPL dark energy model can simultaneously fit both the BAOtr and DESI datasets; the 3.7-sigma disagreement at z=0.51 sets an irreducible floor.
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Causal convolutional neural networks reconstruct neutron star observables for static, Keplerian, and rotating configurations in about 50 milliseconds per equation of state, compared to 30 minutes with traditional RNS calculations.
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On the origin of the BAOtr-DESI tension
No CMB-consistent CPL dark energy model can simultaneously fit both the BAOtr and DESI datasets; the 3.7-sigma disagreement at z=0.51 sets an irreducible floor.
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Reconstruction of fast-rotating neutron star observables with the neural network
Causal convolutional neural networks reconstruct neutron star observables for static, Keplerian, and rotating configurations in about 50 milliseconds per equation of state, compared to 30 minutes with traditional RNS calculations.