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

25 Scopus citations


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
Issue number6
StatePublished - 2009


  • 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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