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Dataset results
8 results for “semiconductor quantum dots”
Dataset underlying the manuscript: MAViS: Modular Autonomous Virtualization System for Two-Dimensional Semiconductor Quantum Dot Arrays
<p>Datasets underlying the manuscript. Information on how to run the scripts is detailed in the README file.</p>
Supporting data for "Quantum simulation of a Fermi-Hubbard model using a semiconductor quantum dot array"
<p>Supporting data and analysis scripts for Fig. 3b of "Quantum simulation of a Fermi-Hubbard model using a semiconductor quantum dot array", ArXiv:1702.07511 (preprint) and 10.1038/nature23022 (publication)</p> <p>This dataset contains a readme file as well as three zipped folders that contain (1) raw data sets of all relevant measurements, as well as (2) matlab files to plot fitted data and the extracted parameters and (3) the code that uses the extracted parameters to plot the fan diagram.</p>
Quantum cryptography with highly entangled photons from semiconductor quantum dots
<p>Measurement data used within the main manuscript and the supplementary material.</p>
Data and analysis for the paper "Nonlocal measurement of quasiparticle charge and energy relaxation in proximitized semiconductor nanowires using quantum dots"
<p>This repository contains the raw data and analysis code used to generate the figures in the manuscript <em>Nonlocal measurement of quasiparticle charge and energy relaxation in proximitized semiconductor nanowires using quantum dots</em>. </p> <p><a href="https://journals.aps.org/prb/abstract/10.1103/PhysRevB.106.064503">Link to publication</a></p> <p><a href="https://arxiv.org/abs/2110.05373">Link to arXiv</a></p>
Ultrafast electric control of cavity mediated single-photon and photon-pair generation with semiconductor quantum dots
<p>Dataset of the publication "Ultrafast electric control of cavity mediated single-photon and photon-pair generation with semiconductor quantum dots" (10.1103/PhysRevB.104.085308)</p>
Raw data: Coherent control of a high-orbital hole in a semiconductor quantum dot
<p>This is the raw data supporting the findings in the research article titled "<em>Coherent control of a high-orbital hole in a semiconductor quantum dot</em>". DOI: 10.1038/s41565-023-01442-y</p>
Theoretical analysis of four-wave mixing on semiconductor quantum dot ensembles with quantum light
<p>Dataset of the publication "Theoretical analysis of four-wave mixing on semiconductor quantum dot ensembles with quantum light" H. Rose, S. Grisard, A. V. Trifonov, R. Reichhardt, M. Reichelt, M. Bayer, I. A. Akimov, and T. Meier, Proc. SPIE 12419, Ultrafast Phenomena and Nanophotonics XXVII, 124190H (2023). ( <a href="https://doi.org/10.1117/12.2647700">https://doi.org/10.1117/12.2647700</a> ). The zip file includes the data on which the plots shown in figures 1 and 2 are based.</p>
The influence of inhomogeneities and defects on novel Quantum Well and Quantum Dot based Infrared -emitting Semiconductor Lasers
<p><strong>Semiconductor Science and Technology article.</strong></p> <p>In this paper we discuss the development of new semiconductor materials and approaches to overcome the fundamental limitations of well established (Al,In)GaAs/InP and InGaAsP/InP infrared-emitting lasers. We consider three approaches; dilute-nitride InGaAsN-based structures; InAs-based quantum dot/dash structures and the most recently emerging dilute-bismide (GaAsBi, InGaAsBi), all of which may be grown on either GaAs or InP substrates. These material systems provide a range of possibilities for band engineering and strain control, thereby giving new routes to improve device efficiency, overcoming existing limitations of device performance and to develop range of new cost-efficient devices with improved characteristics. However, all of these approaches have common difficulties related to establishing optimised growth conditions to produce high quality material for device fabrication. Particularly, in this paper we compare and contrast the effects of inhomogeneous carrier distribution in these systems and discuss the influence of this on the physical properties of lasers developed using these approaches.</p> <p>The authors dedicate this paper to the memory of Professor Naci Balkan (Essex) and Professor Jeff Hosea (Surrey) both of whom made significant contributions to the development of new semiconductor materials including the dilute nitrides and bismides as discussed in the paper. We are also pleased to acknowledge the many collaborators who have contributed to the development of the materials and devices considered in this work, including; Tyndall National Institute (Ireland), Philipps-Universität Marburg (Germany), University of Sheffield (UK), Universität Würzburg (Germany), Fujitsu Laboratories Ltd (Japan), Infineon Technologies AG (Germany) and the Center for Physical Sciences and Technology (Lithuania). We gratefully acknowledge funding from EPSRC (grants EP/H005587/1, EP/G064725/1, EP/N021037/1) and the EU-FP7 “BIANCHO” project (FP7-257974).</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.