S. Zhang

ORCID: 0000-0003-3071-3362
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About
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Research Areas
  • Radio Astronomy Observations and Technology
  • Superconducting and THz Device Technology
  • Solid-state spectroscopy and crystallography
  • Cosmology and Gravitation Theories
  • Computational Fluid Dynamics and Aerodynamics
  • Control Systems in Engineering
  • Iterative Learning Control Systems
  • Galaxies: Formation, Evolution, Phenomena
  • Astrophysics and Star Formation Studies
  • Hydraulic and Pneumatic Systems
  • Geophysics and Gravity Measurements
  • Magnetic Properties and Applications
  • Superconducting Materials and Applications
  • Scientific Research and Discoveries
  • Navier-Stokes equation solutions
  • Particle Accelerators and Free-Electron Lasers
  • Particle accelerators and beam dynamics
  • Fluid Dynamics and Turbulent Flows

California Institute of Technology
2022-2024

Brookhaven National Laboratory
1988-2022

Harvard University
2022

Fermi National Accelerator Laboratory
2022

University of Chicago
2022

Abstract We characterize Galactic dust filaments by correlating BICEP/Keck and Planck data with polarization templates based on neutral hydrogen (H i ) observations. Dust is important for both our understanding of astrophysical processes in the interstellar medium (ISM) search primordial gravitational waves cosmic microwave background (CMB). In diffuse ISM, H strongly correlated partly organized into that are aligned local magnetic field. analyze deep at 95, 150, 220 GHz, over...

10.3847/1538-4357/acb64c article EN cc-by The Astrophysical Journal 2023-03-01

We derive an estimator for the lensing potential from galaxy number counts which contains a linear and quadratic term. show that this has much larger signal-to-noise ratio than corresponding intensity mapping. This is due to additional term in count angular power spectrum present already at order. estimate future photometric surveys. Particularly high redshifts, $z\gtrsim 1.5$, signal noise can become of order 30. Therefore, surveys would be excellent means measure tomographic spectra.

10.48550/arxiv.2203.16556 preprint EN other-oa arXiv (Cornell University) 2022-01-01
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