0000000000925914

AUTHOR

Jim C. Visschers

showing 3 related works from this author

Continuous-wave cavity ring-down polarimetry

2020

We present a new cavity-based polarimetric scheme for highly sensitive and time-resolved measurements of birefringence and dichroism, linear and circular, that employs rapidly pulsed single-frequency continuous wave (CW) laser sources and extends current cavity-based spectropolarimetric techniques. We demonstrate how the use of a CW laser source allows for gains in spectral resolution, signal intensity, and data acquisition rate compared to traditional pulsed-based cavity ring-down polarimetry (CRDP). We discuss a particular CW-CRDP modality that is different from intensity-based cavity-enhanced polarimetric schemes as it relies on the determination of the polarization rotation frequency du…

Physics - Instrumentation and DetectorsPolarimetryGeneral Physics and AstronomyFOS: Physical sciencesApplied Physics (physics.app-ph)010402 general chemistry01 natural scienceslaw.inventionFinessesymbols.namesakeOpticslawPhysics - Chemical Physics0103 physical sciencesFaraday effectddc:530Physical and Theoretical ChemistrySpectral resolutionPhysicsChemical Physics (physics.chem-ph)Birefringence010304 chemical physicsbusiness.industryPhysics - Applied PhysicsInstrumentation and Detectors (physics.ins-det)LaserPolarization (waves)0104 chemical sciencesPhysics - Atmospheric and Oceanic PhysicsAtmospheric and Oceanic Physics (physics.ao-ph)symbolsContinuous wavebusinessPhysics - OpticsOptics (physics.optics)
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Rapid parameter estimation of discrete decaying signals using autoencoder networks

2021

Machine learning: science and technology 2(4), 045024 (2021). doi:10.1088/2632-2153/ac1eea

Signal Processing (eess.SP)FOS: Computer and information sciencesAccuracy and precisionComputer Science - Machine LearningComputer scienceddc:621.3FOS: Physical sciences01 natural sciencesSignalMachine Learning (cs.LG)010309 opticsExponential growthArtificial Intelligence0103 physical sciencesFOS: Electrical engineering electronic engineering information engineeringLimit (mathematics)Neural and Evolutionary Computing (cs.NE)Electrical Engineering and Systems Science - Signal Processing010306 general physicsSignal processingArtificial neural networkEstimation theoryComputer Science - Neural and Evolutionary ComputingAutoencoder621.3Human-Computer InteractionPhysics - Data Analysis Statistics and ProbabilityAlgorithmSoftwareData Analysis Statistics and Probability (physics.data-an)Machine Learning: Science and Technology
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Rapid parameter determination of discrete damped sinusoidal oscillations

2020

We present different computational approaches for the rapid extraction of the signal parameters of discretely sampled damped sinusoidal signals. We compare time- and frequency-domain-based computational approaches in terms of their accuracy and precision and computational time required in estimating the frequencies of such signals, and observe a general trade-off between precision and speed. Our motivation is precise and rapid analysis of damped sinusoidal signals as these become relevant in view of the recent experimental developments in cavity-enhanced polarimetry and ellipsometry, where the relevant time scales and frequencies are typically within the ∼1 − 10 µs and ∼1 − 100 MHz ranges, …

Signal Processing (eess.SP)Accuracy and precisionPhysics - Instrumentation and DetectorsAcousticsPolarimetryFOS: Physical sciences02 engineering and technologyApplied Physics (physics.app-ph)01 natural sciencesSignal010309 opticssymbols.namesakeOptics0103 physical sciencesFOS: Electrical engineering electronic engineering information engineeringElectrical Engineering and Systems Science - Signal ProcessingPhysicsbusiness.industrySpectral densityInstrumentation and Detectors (physics.ins-det)Physics - Applied Physics021001 nanoscience & nanotechnologyAtomic and Molecular Physics and OpticsMicrosecondFourier transformsymbols0210 nano-technologybusinessMatrix methodOptics (physics.optics)Physics - Optics
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