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Maximum-likelihood parameter estimation in terahertz time-domain spectroscopy

Laleh Mohtashemi, Paul Westlund, Derek G. Sahota, Graham B. Lea, Ian Bushfield, Payam Mousavi, J. Steven Dodge

2021Optics Express23 citationsDOIOpen Access PDF

Abstract

We present a maximum-likelihood method for parameter estimation in terahertz time-domain spectroscopy. We derive the likelihood function for a parameterized frequency response function, given a pair of time-domain waveforms with known time-dependent noise amplitudes. The method provides parameter estimates that are superior to other commonly used methods and provides a reliable measure of the goodness of fit. We also develop a simple noise model that is parameterized by three dominant sources and derive the likelihood function for their amplitudes in terms of a set of repeated waveform measurements. We demonstrate the method with applications to material characterization.

Topics & Concepts

Parameterized complexityWaveformEstimation theoryMeasure (data warehouse)OpticsNoise (video)Function (biology)Terahertz radiationAmplitudeLikelihood functionSet (abstract data type)PhysicsAlgorithmTerahertz spectroscopy and technologySignal-to-noise ratio (imaging)Maximum likelihoodMathematicsComputer scienceNoise measurementSimple (philosophy)BruitGoodness of fitTerahertz technology and applicationsSpectroscopy and Quantum Chemical StudiesSpectroscopy and Laser Applications