Skip to main content
Powered by ShareScore

Find research datasets worth reusing

Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.

2

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

2 results for “Einstein Field Equation”

Learn how ShareScore rates datasets ↗
zenodo40/100

Gauge structure of the Einstein field equations in Bondi-like coordinates: convergence tests data

<p>This dataset is the result of the runs performed for the paper &quot;Gauge structure of the Einstein field equations in Bondi-like coordinates&quot;. The data can be used to reproduce the convergence plots, as well as to compare with the data obtained if one performs the same runs independently.</p> <p>&nbsp;</p> <p>To perform&nbsp;independently the runs that produce the data, the PITTNullCode included has to be used. More details on how to proceed with this can be found in the ancillary files of&nbsp;https://arxiv.org/abs/2111.14794 at the directory &quot;anc/numerics/README&quot;.</p>

opencc-by-4.0Nov 2021View details →
zenodo36/100

Combined Calculation of the Yang-Mills Equation and Einstein Field Equation

<p>In this paper, we present a comprehensive analysis and calculation of the combined Yang-Mills equation and Einstein field equation. These equations are two of the fundamental building blocks of modern physics. The Einstein field equation describes gravity as the curvature of spacetime, while the Yang-Mills equation describes the dynamic interactions in quantum field theory. By combining these two equations, we aimed to explore a deeper connection between general relativity and quantum field theory. The calculations include symbolic and numerical evaluations of both equations. First, the Einstein field equation was expressed in matrix form to compute the curvature of spacetime and its relationship to the distribution of matter. Subsequently, we symbolically computed the Yang-Mills equation to describe the interactions of the fields. These symbolic expressions were then combined to obtain an extended equation that integrates the effects of the Yang-Mills fields on the curvature of spacetime. Through numerical calculations, the terms of both equations were evaluated using real physical constants. The Einstein field equation demonstrated that the cosmological constant has the most significant influence on the curvature of spacetime, while the gravitational constant, due to its minuscule size, has only a minor effect. The Yang-Mills equation provided numerical values representing the interactions of the fields, particularly regarding the dynamics of gluons in the quark-gluon plasma.</p> <p>&nbsp;</p> <p>Combination of the Yang-Mills Equation with the Einstein Field Equation: By combining both equations, we were able to conduct a detailed analysis of the interactions of quantum fields with the curvature of spacetime. This combination is of particular interest as it could potentially provide new insights into the structure of the universe, dark matter, and the dynamics of particles in extreme gravitational fields.</p> <p>&nbsp;</p> <p>Central Formula of the Work:</p> <p>&nbsp;</p> <p>G_{\mu\nu} + \Lambda g_{\mu\nu} = \frac{8\pi G}{c^4} T_{\mu\nu}, \quad D_{\mu}F^{\mu\nu} = J^{\nu}</p> <p>&nbsp;</p> <p>The numerical calculations were verified using various validation methods, including NumPy, absolute error validation, and the math.isclose function. All calculations passed these tests, confirming the accuracy of the symbolic and numerical expressions. Notably, the calculation of the eigenvalues of the Yang-Mills field strength tensor provides indications of the presence of a mass gap. This is crucial for understanding the behavior of quarks and gluons in extreme states, as they occur in particle accelerators or in the early universe. Our results suggest that the combination of the Yang-Mills equation with the Einstein field equation could provide new insights into fundamental physical processes. This work lays the foundation for future investigations, particularly regarding the simulation of complex interactions and their experimental validation in high-energy experiments.</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Dec 2023View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated datasets

Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record

ScienceDex for faculty

Your academic CV and NIH biosketch

Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.