Our Papers 
=================

| 8. |paper5|_
| Nature Astronomy (2024)
|
| *We apply the* ``SimBIG`` *to analyze the SDSS-III: BOSS CMASS galaxies using two clustering statistics beyond the standard power spectrum: the bispectrum and a summary of the galaxy field based on a convolutional neural network. We constrain the cosmic expansion (H0) and growth rate (S8) 1.5 and 1.9 times more tightly than power spectrum analyses.* 


| 7. |paper4|_
| PRD accepted (2024)
|
| *We apply the* ``SimBIG`` *to analyze the masked power spectra of SDSS-III: BOSS CMASS galaxies.* 


| 6. |paper3|_
| PRD 109, 3528 (2024)
|
| *We apply the* ``SimBIG`` *to analyze the skew spectra of SDSS-III: BOSS CMASS galaxies.* 


| 5. |paper2|_
| PRD 109, 3534 (2024)
|
| *We apply the* ``SimBIG`` *to analyze the bispectrum of SDSS-III: BOSS CMASS galaxies.* 


| 4. |paper1|_
| PRD 109, 3535 (2024)
|
| *We apply the* ``SimBIG`` *to analyze the wavelet scattering transform of SDSS-III: BOSS CMASS galaxies.* 


| 3. |paper0|_
| PRD 109, 3536 (2024)
|
| *We apply the* ``SimBIG`` *to conduct a field-level inference of SDSS-III: BOSS CMASS galaxies based on convolutional neural networks.* 


| 2. |letter|_
| PNAS 120, 42 (2023)
|
| *We present the* ``SimBIG`` *framework and apply it to analyze the power spectrum of SDSS-III: BOSS CMASS galaxies.  We demonstrate that we can rigorously analyze galaxy clustering down to non-scales (k=0.5 h/Mpc) and extract additional cosmological information beyondc current standard anlayses.* 


| 1. |mocha|_
| JCAP 2023, 4 (2022)
|
| *We present the mock challenge used to validate the* ``SimBIG`` *framework.  The mock challenge consists of 1,500 test simulations constructed using forward models with different N-body simulation, halo finder, and galaxy-halo connection. With these simulations, we rigorously validate the accuarcy and precision of the posteriors inferred from* ``SimBIG`` 


.. _paper5: https://www.nature.com/articles/s41550-024-02344-2
.. |paper5| replace:: Cosmological constraints from non-Gaussian and nonlinear galaxy clustering using the SimBIG inference framework

.. _paper4: https://ui.adsabs.harvard.edu/abs/2024arXiv240404228M/abstract
.. |paper4| replace:: SimBIG: Cosmological Constraints using Simulation-Based Inference of Galaxy Clustering with Marked Power Spectra

.. _paper3: https://arxiv.org/abs/2401.15074
.. |paper3| replace:: SimBIG: Cosmological Constraints from the Redshift-Space Galaxy Skew Spectra

.. _paper2: https://arxiv.org/abs/2310.15243
.. |paper2| replace:: SimBIG: The First Cosmological Constraints from the Non-Linear Galaxy Bispectrum

.. _paper1: https://arxiv.org/abs/2310.15250
.. |paper1| replace:: SimBIG: Galaxy Clustering Analysis with the Wavelet Scattering Transform

.. _paper0: https://arxiv.org/abs/2310.15256
.. |paper0| replace:: SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering

.. _letter: https://www.pnas.org/doi/10.1073/pnas.2218810120
.. |letter| replace:: A forward modeling approach to analyzing galaxy clustering with SimBIG

.. _mocha: https://iopscience.iop.org/article/10.1088/1475-7516/2023/04/010
.. |mocha| replace:: SimBIG: mock challenge for a forward modeling approach to galaxy clustering