Demonstration of bias-controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors

Woo Yong Jang, Majeed M. Hayat, J. Scott Tyo, Ram S. Attaluri, Thomas E. Vandervelde, Yagya D. Sharma, Rajeev Shenoi, Andreas Stintz, Elizabeth R Cantwell, Steven C. Bender, Sang Jun Lee, Sam Kyu Noh, Sanjay Krishna

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

The quantum-confined Stark effect in intersublevel transitions present in quantum-dots-in-a-well (DWELL) detectors gives rise to a midIR spectral response that is dependent upon the detector's operational bias. The spectral responses resulting from different biases exhibit spectral shifts, albeit with significant spectral overlap. A postprocessing algorithm was developed by Sakoǧlu et al. that exploited this bias-dependent spectral diversity to predict the continuous and arbitrary tunability of the DWELL detector within certain limits. This paper focuses on the experimental demonstration of the DWELL-based spectral tuning algorithm. It is shown experimentally that it is possible to reconstruct the spectral content of a target electronically without using any dispersive optical elements for tuning, thereby demonstrating a DWELL-based algorithmic spectrometer. The effects of dark current, detector temperature, and bias selection on the tuning capability are also investigated experimentally.

Original languageEnglish (US)
Pages (from-to)674-683
Number of pages10
JournalIEEE Journal of Quantum Electronics
Volume45
Issue number6
DOIs
StatePublished - 2009

Keywords

  • Algorithmic spectrometer
  • Filtering algorithms
  • IEEE
  • Optical detectors
  • Prediction algorithms
  • Quantum dots
  • Quantum-dots-in-a-well (DWELL) detectors
  • Spectral sensors
  • Spectral tuning
  • Stark effect
  • Tuning

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Condensed Matter Physics
  • Electrical and Electronic Engineering

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