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Search Publications by: Joseph Fowler (Assoc)

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Displaying 51 - 54 of 54

Advanced Code-Division Multiplexers for Superconducting Detector Arrays

February 11, 2012
Author(s)
Kent D. Irwin, Hsiao-Mei Cho, William B. Doriese, Joseph W. Fowler, Gene C. Hilton, Michael D. Niemack, Carl D. Reintsema, Daniel R. Schmidt, Joel N. Ullom, Leila R. Vale
Multiplexers based on the modulation of superconducting quantum interference devices are now regularly used in multi-kilopixel arrays of superconducting detectors for astrophysics, cosmology, and materials analysis. Over the next decade, much larger arrays

Optimization of the TES-bias circuit for a multiplexed microcalorimeter array

January 27, 2012
Author(s)
William B. Doriese, Bradley K. Alpert, Joseph W. Fowler, Gene C. Hilton, Alex S. Hojem, Kent D. Irwin, Carl D. Reintsema, Daniel R. Schmidt, Greg Stiehl, Daniel S. Swetz, Joel N. Ullom, Leila R. Vale
In the detector-bias circuit of a transition-edge-sensor (TES) microcalorimeter, the TES-shunt resistor (Rsh) and the thermal conductance to the cryogenic bath (G) are often considered to be interchangeable knobs with which to control detector speed

Optimization and analysis of code-division multiplexed TES microcalorimeters

January 20, 2012
Author(s)
Joseph W. Fowler, William B. Doriese, Gene C. Hilton, Kent D. Irwin, Daniel R. Schmidt, Greg Stiehl, Daniel S. Swetz, Joel N. Ullom, Leila R. Vale
We are developing code-division multiplexing (CDM) readout systems for TES arrays for good scalability to large multiplexing factors. We report high energy resolution x-ray measurements made through four-channel CDM that employ a flux-summing architecture

Predicted Energy Resolution of a Running-Sum Algorithm for Microcalorimeters

December 1, 2011
Author(s)
Bradley K. Alpert, William B. Doriese, Joseph W. Fowler, Joel N. Ullom
The energy resolution of a high-pulse-rate filtering algorithm recently introduced by Hui Tan et al., based on running sums of TES microcalorimeter output streams, is predicted from average pulse shape and noise autocovariance. We compare with empirical