Publications by authors named "D N Spergel"

Article Synopsis
  • A neural network model was developed to predict the evolution of cosmological -body simulations, suggesting it effectively approximates the Green's function relating initial conditions to outcomes in complex, nonlinear scenarios.
  • The model was tested against various simpler configurations, demonstrating good generalization and the ability to learn physical principles from random Gaussian training data, which highlighted its strengths and weaknesses.
  • However, the model struggled with initial conditions that it wasn't trained on, specifically those involving transverse modes, and it achieved high accuracy when compared to traditional simulation methods for density and momentum power spectra, outperforming a fast simulation method called COLA.
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Complex astrophysical systems often exhibit low-scatter relations between observable properties (e.g., luminosity, velocity dispersion, oscillation period).

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We introduce a Bayesian neural network model that can accurately predict not only if, but also when a compact planetary system with three or more planets will go unstable. Our model, trained directly from short N-body time series of raw orbital elements, is more than two orders of magnitude more accurate at predicting instability times than analytical estimators, while also reducing the bias of existing machine learning algorithms by nearly a factor of three. Despite being trained on compact resonant and near-resonant three-planet configurations, the model demonstrates robust generalization to both nonresonant and higher multiplicity configurations, in the latter case outperforming models fit to that specific set of integrations.

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Cosmological neutrinos have their greatest influence in voids: These are the regions with the highest neutrino to dark matter density ratios. The marked power spectrum can be used to emphasize low-density regions over high-density regions and, therefore, is potentially much more sensitive than the power spectrum to the effects of neutrino masses. Using 22 000 N-body simulations from the Quijote suite, we quantify the information content in the marked power spectrum of the matter field and show that it outperforms the standard power spectrum by setting constraints improved by a factor larger than 2 on all cosmological parameters.

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Any successful alternative gravity theory that obviates the need for dark matter must fit our cosmological observations. Measurements of microwave background polarization trace the large-scale baryon velocity field at recombination and show very strong O(1) baryon acoustic oscillations. Measurements of the large-scale structure of galaxies at low redshift show much weaker features in the spectrum.

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