Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2023MF-Box: multifidelity and multiscale emulation for the matter power spectrum1citations
  • 2023The CAMELS Project: Expanding the Galaxy Formation Model Space with New ASTRID and 28-parameter TNG and SIMBA Suites28citations

Places of action

Chart of shared publication
Fernandez, M. A.
1 / 1 shared
Shelton, Christian R.
1 / 1 shared
Villaescusa-Navarro, Francisco Antonio
1 / 2 shared
Gebhardt, Matthew
1 / 1 shared
Pandey, Shivam
1 / 2 shared
Hernquist, Lars
1 / 2 shared
Shao, Helen
1 / 1 shared
Croft, Rupert
1 / 1 shared
Chen, Nianyi
1 / 1 shared
Dave, Romeel
1 / 1 shared
Chart of publication period
2023

Co-Authors (by relevance)

  • Fernandez, M. A.
  • Shelton, Christian R.
  • Villaescusa-Navarro, Francisco Antonio
  • Gebhardt, Matthew
  • Pandey, Shivam
  • Hernquist, Lars
  • Shao, Helen
  • Croft, Rupert
  • Chen, Nianyi
  • Dave, Romeel
OrganizationsLocationPeople

article

MF-Box: multifidelity and multiscale emulation for the matter power spectrum

  • Fernandez, M. A.
  • Bird, Simeon
  • Shelton, Christian R.
Abstract

<jats:title>ABSTRACT</jats:title><jats:p>We introduce MF-Box, an extended version of MFEmulator, designed as a fast surrogate for power spectra, trained using N-body simulation suites from various box sizes and particle loads. To demonstrate MF-Box’s effectiveness, we design simulation suites that include low-fidelity (LF) suites (L1 and L2) at 256 and $100 \,{Mpc\, ~}h^{-1}$, each with 1283 particles, and a high-fidelity (HF) suite with 5123 particles at $256 \,{Mpc\, ~}h^{-1}$, representing a higher particle load compared to the LF suites. MF-Box acts as a probabilistic resolution correction function, learning most of the cosmological dependencies from L1 and L2 simulations and rectifying resolution differences with just three HF simulations using a Gaussian process. MF-Box successfully emulates power spectra from our HF testing set with a relative error of $ 3~{{\per\ cent}}$ up to $k7 \, h {Mpc}{^{-1}}$ at z ∈ [0, 3], while maintaining a cost similar to our previous multifidelity approach, which was accurate only up to z = 1. The addition of an extra LF node in a smaller box significantly improves emulation accuracy for MF-Box at $k2 \, h {Mpc}{^{-1}}$, increasing it by a factor of 10. We conduct an error analysis of MF-Box based on computational budget, providing guidance for optimizing budget allocation per fidelity node. Our proposed MF-Box enables future surveys to efficiently combine simulation suites of varying quality, effectively expanding the range of emulation capabilities while ensuring cost efficiency.</jats:p>

Topics
  • simulation