相关论文: The Boosted Potential

We investigate the dependence of the mass function of dark-matter haloes on their environment within the cosmic web of large-scale structure. A dependence of the halo mass function on large-scale mean density is a standard element of…

In 'modified' gravity the observed acceleration of the universe is explained by changing the gravitational force law or the number of degrees of freedom in the gravitational sector. Both possibilities can be tested by measurements of…

Existing expressions in the literature appear to indicate that Doppler boosting, due to our proper motion with respect to the isotropic frame of the universe, can amplify stochastic gravitational wave backgrounds whose energy spectra…

According to D\"oring and Isham the spectral topos corresponds to any quantum system. The description of a system in the topos becomes similar to this given by classical theory, up to multiplication of observables. Logic of the emergent…

Extracting maximum cosmological information from current and upcoming large-scale structure data requires going beyond summary statistics as currently used in likelihood-based inference. Simulation-Based Inference (SBI) promises to enable…

Primordial non-Gaussianity generated by additional fields during inflation offers a compelling observational target. Heavy fields imprint characteristic oscillatory signals in non-Gaussian correlation functions of the inflaton, a process…

A viable alternative to the dark energy as a solution of the cosmic speed up problem is represented by Extended Theories of Gravity. Should this be indeed the case, there will be an impact not only on cosmological scales, but also at any…

Context. New-generation cosmological simulations are providing huge amounts of data, whose analysis becomes itself a cutting-edge computational problem. In particular, the identification of gravitationally bound structures, known as halo…

This paper establishes a precise high-dimensional asymptotic theory for boosting on separable data, taking statistical and computational perspectives. We consider a high-dimensional setting where the number of features (weak learners) $p$…

Boosting is a general method of generating many simple classification rules and combining them into a single, highly accurate rule. In this talk, I will review the AdaBoost boosting algorithm and some of its underlying theory, and then look…

We consider the problem of system identification of partially observed linear time-invariant (LTI) systems. Given input-output data, we provide non-asymptotic guarantees for identifying the system parameters under general heavy-tailed noise…

Local-type primordial non-Gaussianity (PNG), predicted by many non-minimal models of inflation, creates a scale-dependent contribution to the power spectrum of large-scale structure (LSS) tracers. Its amplitude is characterized by the…

We present a statistical perspective on boosting. Special emphasis is given to estimating potentially complex parametric or nonparametric models, including generalized linear and additive models as well as regression models for survival…

Cosmological parameter estimation from forthcoming experiments promise to reach much greater precision than current constraints. As statistical errors shrink, the required control over systematic errors increases. Therefore, models or…

In this paper, we conduct a statistical analysis of various cosmological models within the framework of f (R) gravity theories, motivated by persistent challenges in modern cosmology, such as the unknown mechanisms driving the late-time…

We introduce a novel way to combine boosting with Gaussian process and mixed effects models. This allows for relaxing, first, the zero or linearity assumption for the prior mean function in Gaussian process and grouped random effects models…

The statistical properties of dark matter halos, the building blocks of cosmological observables associated with structure in the universe, offer many opportunities to test models for cosmic acceleration, especially those that seek to…

We introduce a class of interatomic potential models that can be automatically generated from data consisting of the energies and forces experienced by atoms, derived from quantum mechanical calculations. The resulting model does not have a…

We develop an empirical potential for silicon which represents a considerable improvement over existing models in describing local bonding for bulk defects and disordered phases. The model consists of two- and three-body interactions with…

Halo Models of large scale structure provide powerful and indispensable tools for phenomenological understanding of the clustering of matter in the Universe. While the halo model builds structures out of the superposition of haloes,…