Machine learning enhanced <i>in situ</i> electron beam lithography of photonic nanostructures

Schlischka, Marvin; Shih, Ching-Wen; Donges, Jan N.; Pengerla, Monica; Limame, Imad; Schall, Johannes; Bremer, Lucas; Rodt, Sven; Reitzenstein, Stephan

doi:10.1039/d2nr03696g

Cited by 6 publications

(3 citation statements)

References 49 publications

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“…While the marker-based approaches require marker fabrication steps and extensive precharacterization, the in situ EBL technique enables simple preselection of QDs during a prior CL mapping step in an easy-one-coordinate system. In return, the dwell time per pixel during the mapping procedure is strongly constrained since the sample is already coated with a resist, a problem that can be mitigated by using in situ EBL with machine learning . Still, the flexibility in terms of illumination time during optical imaging provides an essential advantage for the marker-based methods, especially in the case of darker QDs (e.g., in the telecom O- and C-band), and additionally, the PL-based approach is more flexible in the choice of different excitation schemes.…”

Section: Discussionmentioning

confidence: 99%

“…An additional challenge lies in the requirement for the sample to be spin-coated with an EBL-resist during QD preselection via CL mapping. This introduces restrictions for the exposure time and the overall handling of the sample, an issue which, however, can be tackled by using machine learning enhanced in situ EBL . The so-achieved uncertainty for the QD position is 8.68 nm based on the same 2D Gaussian fit process described for the CL imaging.…”

Section: Qd Localization and Sample Structuring Via In Situ Electron ...mentioning

confidence: 99%

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Assessing the Alignment Accuracy of State-of-the-Art Deterministic Fabrication Methods for Single Quantum Dot Devices

Madigawa,

Donges,

Gaál

et al. 2024

ACS Photonics

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The realization of efficient quantum light sources relies on the integration of self-assembled quantum dots (QDs) into photonic nanostructures with a spectral alignment high spatial positioning accuracy. In this work, we present a comprehensive investigation of the QD position accuracy, obtained using two marker-based QD positioning techniques, photoluminescence (PL) and cathodoluminescence (CL) imaging, as well as using the marker-free in situ electron beam lithography (in situ EBL) technique. We employ four PL imaging configurations with three different image processing approaches and compare them with CL imaging. We fabricate circular mesa structures based on the obtained QD coordinates from both PL and CL image processing to evaluate the final positioning accuracy. This yields final position offset of the QD relative to the mesa center of μ x = (−40 ± 58) nm and μ y = (−39 ± 85) nm with PL imaging and μ x = (−39 ± 30) nm and μ y = (25 ± 77) nm with CL imaging, which are comparable to the offset μ x = (20 ± 40) nm and μ y = (−14 ± 39) nm obtained using the in situ EBL method. We discuss the possible causes of the observed offsets, which are significantly larger than the QD localization uncertainty obtained from simply imaging the QD light emission from an unstructured wafer. Our study highlights the influences of the image processing technique and the subsequent fabrication process on the final positioning accuracy for a QD placed inside a photonic nanostructure.

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Section: Discussionmentioning

confidence: 99%

Section: Qd Localization and Sample Structuring Via In Situ Electron ...mentioning

confidence: 99%

Assessing the Alignment Accuracy of State-of-the-Art Deterministic Fabrication Methods for Single Quantum Dot Devices

Madigawa,

Donges,

Gaál

et al. 2024

ACS Photonics

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“…To enable the controlled and scalable integration of single self-assembled QDs into photonic quantum devices, advanced nanofabrication technologies have been developed. For example, deterministic lithography techniques based on lowtemperature optical imaging 12 and cathodoluminescence (CL) spectroscopy 13 have been used to integrate single QDs into micropillars, 14 microlenses, 15 circular Bragg gratings, 16 and waveguide systems. 11 Here, we develop and use a marker-based scalable integration solution combining cryogenic CL spectroscopy and high-resolution electron beam lithography to deterministically embed two single InGaAs QDs into an IQPC based on GaAs/AlGaAs heterostructures.…”

Section: ■ Introductionmentioning

confidence: 99%

Scalable Deterministic Integration of Two Quantum Dots into an On-Chip Quantum Circuit

Yang

Schall

et al. 2023

ACS Photonics

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Integrated quantum photonic circuits (IQPCs) with deterministically integrated quantum emitters are critical elements for scalable quantum information applications and have attracted significant attention in recent years. However, scaling them up toward fully functional photonic circuits with multiple deterministically integrated quantum emitters to generate photonic input states remains a great challenge. In this work, we report on a monolithic prototype IQPC consisting of two preselected quantum dots deterministically integrated into nanobeam cavities at the input ports of a 2 × 2 multimode interference beam splitter. The on-chip beam splitter exhibits a splitting ratio of nearly 50/50 and the integrated quantum emitters have high single-photon purity, enabling on-chip Hanbury Brown and Twiss (HBT) experiments, depicting deterministic scalability. Overall, this marks a cornerstone toward scalable and fully functional IQPCs.

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Accurate prediction of magnetocaloric effect in NiMn-based Heusler alloys by prioritizing phase transitions through explainable machine learning

Tang,

Cao,

et al. 2024

Rare Met.

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Machine learning enhanced in situ electron beam lithography of photonic nanostructures

Abstract: We report on the deterministic fabrication of quantum devices aided by machine-learning-based image processing. The goal of the work is to demonstrate that pattern recognition based on specifically trained machine...

Cited by 6 publications

References 49 publications

Assessing the Alignment Accuracy of State-of-the-Art Deterministic Fabrication Methods for Single Quantum Dot Devices

Assessing the Alignment Accuracy of State-of-the-Art Deterministic Fabrication Methods for Single Quantum Dot Devices

Scalable Deterministic Integration of Two Quantum Dots into an On-Chip Quantum Circuit

Accurate prediction of magnetocaloric effect in NiMn-based Heusler alloys by prioritizing phase transitions through explainable machine learning

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