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Simultaneous Estimation of Noise and Signal in Cosmic Microwave Background Experiments

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Pedro G. Ferreira, Andrew H. Jaffe

Astrophysics · Submitted 15 Sep 1999

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim Given a time-ordered data set we propose a formalism and method for estimating the signal and associated errors without prior knowledge of the noise power spectrum.

how it is stated · asserted 0.96 read the record →

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arXiv IDastro-ph/9909250 (version 1)
Pith IDTJIHRJJL, Pith's permanent record of this paper and its review
CitationAndrew H. Jaffe, Pedro G. Ferreira. "Simultaneous Estimation of Noise and Signal in Cosmic Microwave Background Experiments." arXiv:astro-ph/9909250 (1999). https://pith.science/paper/TJIHRJJL
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Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 3,606 input tokens, $0.0002 reported.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.16 · human participants 0.01 · controlled comparison 0.11 · randomized assignment 0.01 · states quantitative result 0.05 · compares with prior results 0.86 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

To correctly analyse data sets from current microwave detection technology, one is forced to estimate the sky signal and experimental noise simultaneously. Given a time-ordered data set we propose a formalism and method for estimating the signal and associated errors without prior knowledge of the noise power spectrum. We derive the method using a Bayesian formalism and relate it to the standard methods; in particular we show how this leads to a change in the estimate of the noise covariance matrix of the sky signal. We study the convergence and accuracy of the method on two mock observational strategies and discuss its application to a currently-favoured calibration procedure.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 To correctly analyse data sets from current microwave detection technology, one is forced to estimate the sky signal and experimental noise simultaneously. background 1.00 0.12 0.10 asserted 1.00
s1 Given a time-ordered data set we propose a formalism and method for estimating the signal and associated errors without prior knowledge of the noise power spectrum. contribution 0.96 0.91 0.26 asserted 0.96
s2 We derive the method using a Bayesian formalism and relate it to the standard methods; in particular we show how this leads to a change in the estimate of the noise covariance matrix of the sky signal. method 0.93 0.95 0.21 asserted 1.00
s3 We study the convergence and accuracy of the method on two mock observational strategies and discuss its application to a currently-favoured calibration procedure. contribution 0.91 0.95 0.12 asserted 0.95

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from simulation or computation 0.58.

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  • T body sentences
  • C citations
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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

To correctly analyse data sets from current microwave detection technology, one is forced to estimate the sky signal and experimental noise simultaneously. Given a time-ordered data set we propose a formalism and method for estimating the signal and associated errors without prior knowledge of the noise power spectrum. We derive the method using a Bayesian formalism and relate it to the standard methods; in particular we show how this leads to a change in the estimate of the noise covariance matrix of the sky signal. We study the convergence and accuracy of the method on two mock observational strategies and discuss its application to a currently-favoured calibration procedure.

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