Convolutional neural network-reconstructed velocity for kinetic SZ detection

@article{Tanimura2022ConvolutionalNN,
  title={Convolutional neural network-reconstructed velocity 
for kinetic SZ detection},
  author={Hideki Tanimura and Nabila Aghanim and V. Bonjean and Saleem Zaroubi},
  journal={Astronomy \& Astrophysics},
  year={2022}
}
We report the detection of the kinetic Sunyaev-Zel’dovich (kSZ) e ff ect in galaxy clusters with a 4.9 σ significance using the latest 217GHz Planck map from data release 4. For the detection, we stacked the Planck map at the positions of 30431 galaxy clusters from the Wen-Han-Liu (WHL) catalog. To align the sign of the kSZ signals, the line-of-sight velocities of galaxy clusters were estimated with a machine-learning approach, in which the relation between the galaxy distribution around a… 

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References

SHOWING 1-3 OF 3 REFERENCES

A&A proofs: manuscript

  • Phys. Rev. Lett., 109,
  • 2005

Deep Learning with Python

After familiarizing with Keras, we will illustrate the skill of deep learning on some well-understood case study machine learning problems from the UCI Machine learning repository

A&A proofs: manuscript no. kszcnn