Zobrazeno 1 - 10
of 411
pro vyhledávání: '"Seljak, Uros"'
Weak Lensing (WL) surveys are reaching unprecedented depths, enabling the investigation of very small angular scales. At these scales, nonlinear gravitational effects lead to higher-order correlations making the matter distribution highly non-Gaussia
Externí odkaz:
http://arxiv.org/abs/2403.03490
We develop a new and simple method to model baryonic effects at the field level relevant for weak lensing analyses. We analyze thousands of state-of-the-art hydrodynamic simulations from the CAMELS project, each with different cosmology and strength
Externí odkaz:
http://arxiv.org/abs/2401.15891
Autor:
Sullivan, James M., Seljak, Uros
We introduce a global, gradient-free surrogate optimization strategy for expensive black-box functions inspired by the Fokker-Planck and Langevin equations. These can be written as an optimization problem where the objective is the target function to
Externí odkaz:
http://arxiv.org/abs/2310.00745
For many scientific inverse problems we are required to evaluate an expensive forward model. Moreover, the model is often given in such a form that it is unrealistic to access its gradients. In such a scenario, standard Markov Chain Monte Carlo algor
Externí odkaz:
http://arxiv.org/abs/2309.11490
Field-level inference provides a means to optimally extract information from upcoming cosmological surveys, but requires efficient sampling of a high-dimensional parameter space. This work applies Microcanonical Langevin Monte Carlo (MCLMC) to sample
Externí odkaz:
http://arxiv.org/abs/2307.09504
Autor:
Dai, Biwei, Seljak, Uros
We propose Multiscale Flow, a generative Normalizing Flow that creates samples and models the field-level likelihood of two-dimensional cosmological data such as weak lensing. Multiscale Flow uses hierarchical decomposition of cosmological fields via
Externí odkaz:
http://arxiv.org/abs/2306.04689
Autor:
Robnik, Jakob, Seljak, Uroš
Stochastic sampling algorithms such as Langevin Monte Carlo are inspired by physical systems in a heat bath. Their equilibrium distribution is the canonical ensemble given by a prescribed target distribution, so they must balance fluctuation and diss
Externí odkaz:
http://arxiv.org/abs/2303.18221
Publikováno v:
JCAP Volume 2023, Issue 08, id.004, 33 pp
Local primordial non-Gaussianity (LPNG) is predicted by many non-minimal models of inflation, and creates a scale-dependent contribution to the power spectrum of large-scale structure (LSS) tracers, whose amplitude is characterized by $b_{\phi}$. Kno
Externí odkaz:
http://arxiv.org/abs/2303.08901
We develop Microcanonical Hamiltonian Monte Carlo (MCHMC), a class of models which follow a fixed energy Hamiltonian dynamics, in contrast to Hamiltonian Monte Carlo (HMC), which follows canonical distribution with different energy levels. MCHMC tune
Externí odkaz:
http://arxiv.org/abs/2212.08549
We present growth of structure constraints from the cosmological analysis of the power spectrum multipoles of SDSS-III BOSS DR12 galaxies. We use the galaxy power spectrum model of Hand et al. (2017), which decomposes the galaxies into halo mass bins
Externí odkaz:
http://arxiv.org/abs/2211.16794