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2,649 results for “optics”
Spectra and photometry for CSS161010: a luminous, fast blue optical transient with broad blueshifted hydrogen lines
<p><strong>CSS161010 spectra and photometry.</strong></p> <p><strong>Gutiérrez et al. 2024</strong></p> <p>This repository contains two zip folders with the photometry and spectra of the Fast blue optical transient, CSS161010.</p> <p><strong>G24_CSS161010_Photometry</strong> includes five tables as follows:</p> <ul> <li><strong>CSS161010_ATLASphot.dat </strong>--> ATLAS AB optical photometry.</li> <li><strong>CSS161010_DFOTphot.dat </strong>--> BV RI photometry obtained with DFOT in the Vega system.</li> <li><strong>CSS161010_Hphot.dat</strong> --> H photometry obtained from the Liverpool Telescope in the Vega system.</li> <li><strong>CSS161010_opticalphot.dat </strong>--> Optical photometry obtained with different instruments at several facilities.</li> <li><strong>CSS161010_Swiftphot.dat </strong>--> UV photometry obtained with Swift in the AB system.</li> </ul> <p><strong>G24_CSS161010_Spectra </strong>contains 12 spectra. The files' names have the following configuration:</p> <p>Target name (CSS161010) + observation date (JD) + Telescope name. </p> <p>CSS161010-2457679.64-NOT.txt<br>CSS161010-2457680.67-NOT.txt<br>CSS161010-2457681.59-NOT.txt<br>CSS161010-2457691.65-NOT.txt<br>CSS161010-2457692.66-NOT.txt<br>CSS161010-2457697.44-SALT.txt<br>CSS161010-2457697.73-Mag.txt<br>CSS161010-2457698.78-Mag.txt<br>CSS161010-2457711.88-LBT.txt<br>CSS161010-2457716.55-GTC.txt<br>CSS161010-2457729.58-GTC.txt<br>CSS161010-2457779.48-GTC.txt</p> <p>The last spectrum corresponds to the host galaxy.</p> <p>More details can be found in the paper (https://arxiv.org/abs/2408.04698).</p>
Influence of Feedback Phase on Time Delay Signature and Chaos Bandwidth in a Laser subject to Dual Optical Feedback
<p>This archive provides all the data and information needed to reproduce the simulation results from the paper titled "Influence of Feedback Phase on Time Delay Signature and Chaos Bandwidth in a Laser subject to Dual Optical Feedback". You can access the paper on ArXiv: https://arxiv.org/abs/2311.14449</p> <p> </p> <p> </p>
Dataset for: Dynamically patterning X-ray beam by a femtosecond optical laser
<p>This record contains the image and plot data for the paper "Dynamically patterning X-ray beam by a femtosecond optical laser".</p>
Data - Ultralow noise preamplified optical receiver using conventional single wavelength transmission
<p>This dataset contains measurement data and processing code for the results published in "Ultralow noise preamplified optical receiver using conventional single wavelength transmission". Raw measurement batches from the BER-measurement can be made available upon request, at rasmus.larsson@chalmers.se.</p> <p>This work was funded by the Swedish Research Council (grant VR-2015-00535).</p>
Debris Flow Dataset for Debris Flow Velocity Inversion based on Farneback Optical Flow
<p>A velocity inventory of large-scale debris flow flume experimental data, published by USGS (Logan, 2018), was generated using the Debris Flow Velocity Inversion Method based on optical flow model (Farnebäck<span>, 2003</span>). This dataset includes raw data from three debris flow experiments conducted in 2007, 2015, and 2017. Each dataset corresponds to three relevant results: perspective transformation, optical flow analysis, and front position detection.</p>
Optical and chemical properties of brown carbon aerosols at Fukue Island in 2019-2020
Open the record for dataset details and reuse information.
Data for "In-situ Measurements of Light Diffusion in an Optically Dense Atomic Ensemble"
<p>The files uploaded here include the data shown in Figures 3.c), 4.a) and 4.b) of the article "In-situ Measurements of Light Diffusion in an Optically Dense Atomic Ensemble", that can be found in: arXiv:2409.11117 </p> <p>Four datasets are included: </p> <p>df_diffusion.csv --> Figure 3.c</p> <p>df_vtransport.csv --> Figure 4.a </p> <p>df_ttransport.csv --> Inset figure 4.a </p> <p>df_decay.csv --> Figure 4.b</p> <p> </p>
Input SAR and Optical images for DIL-SDS model
<p>This dataset contains the input SAR and Optical images used in the DIL-SDS model, described in the https://github.com/yongjingmao/DIL_SDS. </p>
Data from: Primary production calculations for sea ice from bio-optical observations in the Baltic Sea
Bio-optics is a powerful approach for estimating photosynthesis rates, but has seldom been applied to sea ice, where measuring photosynthesis is a challenge. We measured absorption coefficients of chromophoric dissolved organic matter (CDOM), algae, and non-algal particles along with solar radiation, albedo and transmittance at four sea-ice stations in the Gulf of Finland, Baltic Sea. This unique compilation of optical and biological data for Baltic Sea ice was used to build a radiative transfer model describing the light field and the light absorption by algae in 1-cm increments. The maximum quantum yields and photoadaptation of photosynthesis were determined from 14C-incorporation in photosynthetic-irradiance experiments using melted ice. The quantum yields were applied to the radiative transfer model estimating the rate of photosynthesis based on incident solar irradiance measured at 1-min intervals. The calculated depth-integrated mean primary production was 5 mg C m–2 d–1 for the surface layer (0–20 cm ice depth) at Station 3 (fast ice) and 0.5 mg C m–2 d–1 for the bottom layer (20–57 cm ice depth). Additional calculations were performed for typical sea ice in the area in March using all ice types and a typical light spectrum, resulting in depth-integrated mean primary production rates of 34 and 5.6 mg C m–2 d–1 in surface ice and bottom ice, respectively. These calculated rates were compared to rates determined from 14C incorporation experiments with melted ice incubated in situ. The rate of the calculated photosynthesis and the rates measured in situ at Station 3 were lower than those calculated by the bio-optical algorithm for typical conditions in March in the Gulf of Finland by the bio-optical algorithm. Nevertheless, our study shows the applicability of bio-optics for estimating the photosynthesis of sea-ice algae.
Negative Vessel Remodeling in Stargardt Disease Quantified with Volume-Rendered Optical Coherence Tomography Angiography
<p>Data underlying the figures in the publication “Negative Vessel Remodeling in Stargardt Disease Quantified with Volume-Rendered Optical Coherence Tomography Angiography”, published in Retina, <strong>2021</strong>. Doi: 10.1097/IAE.0000000000003110</p> <p>Table of contents:</p> <p><strong>1. Dataset 1</strong>; Excel sheet containing the source data of the publication.</p>
Data and code for figures: Coherent Terahertz-to-Microwave Link Using Electro-Optic-Modulated Turing Rolls
<p>This dataset contains the figures and data presented in the paper <Coherent Terahertz-to-Microwave Link Using Electro-Optic-Modulated Turing Rolls>.</p>
8-day Vegetation optical depth (VOD) and normalised difference vegetation index (NDVI)- based estimated degree of curing (DOC) for Australia
<p>This is a gridded degree of curing (DOC) dataset over Australia based on vegetation optical depth (VOD) and normalised difference vegetation index (NDVI) that can reasonably reproduce groundbased observations in space and time.</p> <p>The gridded DOC data is produced via estimation models using the VOD dataset from AMSR-E (0.1 degree; 8-day) and NDVI dataset from MODIS Terra MOD09A1 (0.005 degree; 8-day). The estimation models are derived from the calibration and evaluation of VOD and NDVI datset with field observed DOC over Australia. Matlab was used for the calibration and evaluation of these models.</p> <p>There are 2 variations based on the following estimation models: DOC_M1 = 145.57-260.82(NDVI)+137.19(VOD)(NDVI) DOC_M2 = 48.70+147.60(VOD)-259.95(VOD)(NDVI) The domain covered is Australia with a 0.05 degree spatial resolution. Temporal resolution is 8-day composites from 04/07/2002 to 26/06/2011 .</p> <p>These experiments were executed by Waisin Chaivaranont of the ARC Centre of Excellence for Climate System Science (ARCCSS) research program "The role of land surface forcing and feedbacks for regional climate".</p>
FIGURE 5 in <p><strong>Nomenclatural and taxonomic problems related to</strong> <strong>the electronic publication of new nomina and nomenclatural acts in zoology, with brief comments on optical discs and on the situation in botany</strong></p>
FIGURE 5. Accompanying letters of four documents received by the Paris Museum library: facsimiles of PDFs of (a–c) three works published by Parasites & Vectors (Andrade Filho et al. 2009, Freeman & Sommerville 2010, Poinar 2009) and (d) a work published by BMC evolutionary Biology (Tan et al. 2012), letter received on 14 January 2013.
FIGURE 2 in <p><strong>Nomenclatural and taxonomic problems related to</strong> <strong>the electronic publication of new nomina and nomenclatural acts in zoology, with brief comments on optical discs and on the situation in botany</strong></p>
FIGURE 2. First page of Yamaguchi et al. (2012) under two different versions: (a) PDF dated 8 March 2012, downloaded from the BMC website on 6 November 2012; (b) paper facsimile dated 8 March 2012, received by the Paris Museum library before 5 November 2012 (two pages on one, successive pages printed upside down).
FIGURE 4 in <p><strong>Nomenclatural and taxonomic problems related to</strong> <strong>the electronic publication of new nomina and nomenclatural acts in zoology, with brief comments on optical discs and on the situation in botany</strong></p>
FIGURE 4. Four pages of Bargues et al. (2011) under two different versions: (a) page 11 of PDF dated 12 July 2011, downloaded from the BMC website on 11 November 2012, showing its fig. 8 with its correct legend; (b–d) pages 6, 9 and 15 of paper facsimile dated 12 July 2011, received by the Paris Museum library before 5 November 2012, showing its fig. 2 (legend of fig. 2 in PDF, tree of fig. 8 in PDF), its fig. 4 (legend of fig. 4 in PDF, photograph of fig. 10 in PDF) and its fig. 10 (legend and photograph of fig. 10 in PDF).
FIGURE 3. Page 9 in <p><strong>Nomenclatural and taxonomic problems related to</strong> <strong>the electronic publication of new nomina and nomenclatural acts in zoology, with brief comments on optical discs and on the situation in botany</strong></p>
FIGURE 3. Page 9 of Malm & Johanson (2011) under two different versions: (a) PDF dated 12 January 2011, downloaded from the BMC website on 11 November 2012; (b) paper facsimile dated 12 January 2011, received by the Paris Museum library before 5 November 2012 (compared to the PDF, throughout the printed document blue was replaced by violet and red by orange).
FIGURE 6 in <p><strong>Nomenclatural and taxonomic problems related to</strong> <strong>the electronic publication of new nomina and nomenclatural acts in zoology, with brief comments on optical discs and on the situation in botany</strong></p>
FIGURE 6. First page of PDFs of Tan et al. (2012) under two different versions, both dated 9 July 2012, as downloaded from the BMC website on: (a) 6 November 2012 (prepublication); (b) 16 December 2012 (final publication). In (b), the small boxes surrounded with green are taken from pages 18 (dates) and 19 (DOI and reference).
FIGURE 7 in <p><strong>Nomenclatural and taxonomic problems related to</strong> <strong>the electronic publication of new nomina and nomenclatural acts in zoology, with brief comments on optical discs and on the situation in botany</strong></p>
FIGURE 7. Four figures of prepublication of Tan et al. (2012), as downloaded from the BMC website on 6 November 2012. Note than fig. 3 and 4 are identical but with different legends.
Data accompanying "Coherent optical communications using coherence-cloned Kerr soliton microcombs"
<p>This dataset contains measurement data and digital signal processing (DSP) code for the results presented in "Coherent optical communications using coherence-cloned Kerr soliton microcombs". </p> <p> The program code included in this dataset is distributed under a GPLv3 license.</p>
Field measurements of aquatic optics parameters for Lake Mulargia (Sardinia, Italy)
<p>This dataset contains aquatic optics parameters (remote sensing reflectance, backscattering depth profiles, absorption coefficients, Water Quality Parameters-WQP) of Lake Mulargia (Sardinia, Italy) collected by ENAS and CNR.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.