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J. Siegel

5 papers hereh-index 423 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author3

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • astro-ph.CO4
  • astro-ph.GA1
same name
  • J. Siegel — 13 papers, h 20
  • J. Siegel — 8 papers, h 38
  • J. Siegel — 2 papers, h 2
  • J. Siegel — 2 papers, h 6
  • J. Siegel — 1 paper, h 5
  • J. Siegel — 1 paper, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedThe suppression of the matter power spectrum: strong feedback from X-ray gas mass fractions, kSZ effect profiles, and galaxy-galaxy lensing

5 citations · 6 across the 4 of their papers we have counts for

collaborators
Showing 2025Show all

3 papers · 1 filter

astro-ph.CO2025★ 1 cited

Confronting cosmic shear astrophysical uncertainties: DES Year 3 revisited

Leah Bigwood, Jamie McCullough, Jared Siegel +19

Cosmology from weak gravitational lensing has been limited by astrophysical uncertainties in baryonic feedback and intrinsic alignments. By calibrating these effects using external…

astro-ph.CO2025★ 5 cited

The suppression of the matter power spectrum: strong feedback from X-ray gas mass fractions, kSZ effect profiles, and galaxy-galaxy lensing

Jared Siegel, Leah Bigwood, Alexandra Amon +6

Baryon feedback redistributes gas relative to the underlying dark matter distribution and suppresses the matter power spectrum on small scales, but the amplitude and scale dependen…

astro-ph.CO2025

The kinetic Sunyaev Zeldovich effect as a benchmark for AGN feedback models in hydrodynamical simulations: insights from DESI + ACT

Leah Bigwood, Masaya Yamamoto, Jared Siegel +7

Baryonic feedback remains one of the largest uncertainties in cosmological hydrodynamical simulations, with different prescriptions producing divergent predictions for the fraction…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.