We describe how the James Webb Space Telescope (JWST) Near-Infrared Spectrograph's (NIRSpec's) detectors will be read out, and present a model of how noise scales with the number of multiple non-destructive reads samplingup-the-ramp. We believe that this noise model, which is validated using real and simulated test data, is applicable to most astronomical near-infrared instruments. We describe some non-ideal behaviors that have been observed in engineering grade NIRSpec detectors, and demonstrate that they are unlikely to affect NIRSpec sensitivity, operations, or calibration. These include a HAWAII-2RG reset anomaly and random telegraph noise (RTN). Using real test data, we show that the reset anomaly is: (1) very nearly noiseless and (2) can be easily calibrated out. Likewise, we show that large-amplitude RTN affects only a small and fixed population of pixels. It can therefore be tracked using standard pixel operability maps.
The newest 256 x 256 InSb arrays (CRC-590 and CRC-463 multiplexers) from Santa Barbara Research Center have reached a milestone in low noise performance. Using the Fowler-saxnpling technique to acquire data, we have achieved 10-13 e multiply sampled read-out (MSR) noise with the new arrays. With this remarkably low noise performance, background limited performance occurs at relatively small signal levels, viz. a few percent of full-well depth. The signal-to-noise capability of infrared detectors operating in both read noise and background limited performance is an important parameter for evaluating the efficacy of various data sampling methods. This paper provides a theoretical analysis of the ultimate signal-to-noise ratio achievable in read noise and background limited performance for Fowler-sampling and line-fitting. The results of this analysis agree very well with a numerical simulation of the two multiple-sampling techniques.We find both Fowler-sampling and line-fitting are superior to correlated double sampling (CDS) in read-noise limited performance (assuming the read-noise is dominated by white noise). Both sampling methods provide the expected jns&mpi improvement over CDS. Fowler-sampling's performance is a function of its duty cycle, the ratio of time spent sampling to the total observing time. It achieves its best performance at a duty cycle of 2/3, i.e. sampling the "pedestal" and "signal" levels each for 1/3 of the total observing time. At this optimum duty cycle, Fowler-sampling is approximately 6% inferior to line-fitting.For background limited performance, the noise of the detector is dominated by the shot noise of the photons. The difficulty with any non-destructive, multiple-sampling method is that successive signal measurements are correlated in their noise. We find that the best theoretical signal-to-noise is achieved with correlated double sampling. The signal-to-noise for line-fitting is approximately 9% inferior to that for CDS. The signal-to-noise for Fowler-sampling approaches the signal-to-noise for CDS as the duty cycle approaches its minimum value of one sample pair.We conclude that both line-fitting and Fowler-sampling are the best sampling methods covering the whole performance regime, providing large improvement in the read-noise dominated regime and approaching CDS capability in the photon-noise dominated regime.
In an era where mutational profiles inform treatment options, it is critical to know the extent to which tumor biopsies represent the molecular profile of the primary and metastatic tumor. Head and neck squamous cell carcinoma (HNSCC) arise primarily in the mucosal lining of oral cavity and oropharynx. Despite aggressive therapy the 5-year survival rate is at 50%. The primary objective of this study is to characterize the degree of intratumor mutational heterogeneity in HNSCC. We used multi-region sequencing of paired primary and metastatic tumor DNA of 24 spatially distinct samples from seven patients with HNSCC of larynx, floor of the mouth (FOM) or oral tongue. Full length, in-depth sequencing of 202 genes implicated in cancer was carried out. Larynx and FOM tumors had more than 69.2% unique SNVs between the paired primary and metastatic lesions. In contrast, the oral tongue HNSCC had only 33.3% unique SNVs across multiple sites. In addition, HNSCC of the oral tongue had fewer mutations than larynx and FOM tumors. These findings were validated on the Affymetrix whole genome 6.0 array platform and were consistent with data from The Cancer Genome Atlas (TCGA). This is the first report demonstrating differences in mutational heterogeneity varying by subsite in HNSCC. The heterogeneity within laryngeal tumor specimens may lead to an underestimation of the genetic abnormalities within tumors and may foster resistance to standard treatment protocols. These findings are relevant to investigators and clinicians developing personalized cancer treatments based on identification of specific mutations in tumor biopsies.
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