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GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run — Candidate data release

This material is part of several data products associated with GWTC-3, the third Gravitational-Wave Transient Catalog from the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration, the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration, and the <a href="https://gwcenter.icrr.u-tokyo.ac.jp/en/">KAGRA</a> Collaboration. For more information, see the paper (<a href="https://dcc.ligo.org/LIGO-P2000318/public">dcc.ligo.org/LIGO-P2000318/public</a>), the related material linked from this page, and the GWTC-3 data release documentation (<a href="https://www.gw-openscience.org/GWTC-3/">www.gw-openscience.org/GWTC-3/</a>). Candidate data release Data associated with candidates in GWTC-3. These are gravitational-wave candidates from the the third observing run (O3) of the Advanced LIGO and Advanced Virgo detectors that pass a false alarm rate threshold of 2/day. We upload a tar file (search_data.tar.gz) containing all the data and a python notebook (GWTC3_search_data.ipynb) that provides a description on how to use the files contained in the dataset. Associated with each candidate are the search analysis results and a localization (assuming that the source is astrophysical). Four search analysis pipelines have been used: the templated-based <a href="https://lscsoft.docs.ligo.org/gstlal/">GstLAL</a>, <a href="https://doi.org/10.1088/1361-6382/abe913">MBTA</a> and <a href="https://pycbc.org/">PyCBC</a>, plus the template-free <a href="https://gwburst.gitlab.io/">cWB</a>. Localizations from the template-based pipelines are calculated using <a href="https://lscsoft.docs.ligo.org/ligo.skymap/bayestar/index.html">Bayestar</a>, while cWB candidates are calculated by cWB itself. This release is primarily composed of results from the second part of O3 (O3b), but also includes a subset of results from the first part (O3a). A similar release was made for the previous <a href="https://doi.org/10.5281/zenodo.5117761">GWTC-2.1</a> that contained candidates from the first part of O3 (O3a) from GstLAL, MBTA and PyCBC. We include updated probabilities of astrophysical origin for these candidates: each search analysis has a o3a_pastro directory that contains these results. Since GWTC-2.1 did not include cWB results, this release includes cWB O3a candidates in addition to O3b: the cWB directory contains a subdirectory called o3a_events that contains the O3a results. The probability of astrophysical origin is calculated assuming a compact binary coalescence source, which may not always be appropriate for the template-free cWB analysis.    For more general background on gravitational-wave search analysis and sky maps, try the materials from a <a href="https://www.gw-openscience.org/workshops/">GW Open Data Workshop</a> or the <a href="https://doi.org/10.1088/1361-6382/ab685e">guide to LIGO–Virgo data analysis</a>.

GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run — Glitch modelling for events

This material is part of several data products associated with GWTC-3, the third Gravitational-Wave Transient Catalog from the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration, the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration, and the <a href="https://gwcenter.icrr.u-tokyo.ac.jp/en/">KAGRA</a> Collaboration. For more information, see the paper (<a href="https://dcc.ligo.org/LIGO-P2000318/public">dcc.ligo.org/LIGO-P2000318/public</a>), the related material linked from this page, and the GWTC-3 data release documentation (<a href="https://www.gw-openscience.org/GWTC-3/">www.gw-openscience.org/GWTC-3/</a>). Glitch model for GWTC-3 events Glitch model for events in the GWTC-3 catalog that used either <a href="https://git.ligo.org/lscsoft/bayeswave">BayesWave</a> glitch subtraction or linear noise subtraction. Each data file for events processed with BayesWave contain three channels: <ol> <li>The calibrated strain data, including any glitches that are present,</li> <li>A model of the glitches, produced using the BayesWave algorithm,</li> <li>The calibrated data with the glitch model subtracted, used for parameter estimation.</li> </ol> Each data file for events processed with linear noise subtraction contain one channel: <ol> <li>The calibrated data with the glitch linearly subtracted, used for parameter estimation.</li> </ol> LIGO Hanford data for events GW191109_010717, GW191113_071753, GW191127_050227, and GW191219_163120 was generated with BayesWave. The names and sample rates (in Hz) of the channels in these files are <ol> <li>H1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01 16384</li> <li>H1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01_glitch 16384</li> <li>H1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01_T1700406_v4 16384</li> </ol> LIGO Livingston data for events GW191109_010717, GW191219_16312, GW200105_162426, and GW200115_042309 was generated with BayesWave. The names and sample rates (in Hz) of the channels in these files are <ol> <li>L1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01 16384</li> <li>L1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01_glitch 16384</li> <li>L1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01_T1700406_v4 16384</li> </ol> Virgo data for event GW191105_143521 was generated with BayesWave. The names and sample rates (in Hz) of the channels in this file are <ol> <li>V1:Hrec_hoft_16384Hz 16384</li> <li>V1:Hrec_hoft_16384Hz_glitch 16384</li> <li>V1:Hrec_hoft_16384Hz_T1700406_v4 16384</li> </ol> LIGO Livingston data for event GW200129_065458 was generated with linear noise subtraction. The name and sample rate (in Hz) of the channel in this file is <ol> <li>L1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01_P1800169_v4 16384</li> </ol> How to download all files from this page If you would like to download all files on this page, we recommend <a href="https://gitlab.com/dvolgyes/zenodo_get">zenodo_get</a>: <pre><code class="language-bash">pip install zenodo_get zenodo-get RECORD_ID_OR_DOI </code></pre> where the record ID for the most recent version of this page is 5546679 and IDs for other versions can be found in the Versions section at the side of this page.   For more general background on gravitational-wave data quality, try the materials from a <a href="https://www.gw-openscience.org/workshops/">GW Open Data Workshop</a> or the <a href="https://doi.org/10.1088/1361-6382/ab685e">guide to LIGO–Virgo data analysis</a>.

opencc-by-4.0Jul 2021View details →

GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run - Candidate Data Release

Data associated with candidates in <a href="https://dcc.ligo.org/LIGO-P2100063/public">GWTC-2.1</a>. These are gravitational-wave candidates from the first half of the third observing run (O3a) of the Advanced LIGO and Virgo detectors that pass a false alarm rate threshold of 2/day. We upload a tar file (search_data_GWTC2p1.tar.gz) containing all the data and a python notebook (search_data.ipynb) which provides description on how to use the files contained in the dataset.

BHBH simulations from: Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations II: Double Compact Object Mergers

The data for all BHBH simulations shown in "Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations II: Double Compact Object Mergers".  Broekgaarden et al. (2021, submitted, preprint: <a href="https://arxiv.org/abs/2112.05763">https://arxiv.org/abs/2112.05763</a>)   Contents:  <ul> <li>18 zip files that each contain an hdf5 file with the raw data for one of the simulations from Table 1 in the paper. The only exception is the fiducial.zip file and the unstableCaseBB.zip file, which contain both the fiducial (model A) and 'optimistic CE' (model K) data file and the "unstable case BB" (model E)  and "unstable case BB + optimistic CE" (model F) files. These zip files are:  <ul> <li>fiducial.zip,  the Fiducial model (A) and Optimistic CE model (K)</li> <li>massTransferEfficiencyFixed_0_25.zip, the \(\beta\) = 0.25 model (B) </li> <li>massTransferEfficiencyFixed_0_5.zip, the \(\beta\) = 0.5 model (C) </li> <li>massTransferEfficiencyFixed_0_75.zip, the \(\beta\) = 0.75 model (D)</li> <li>unstableCaseBB.zip, the unstable case BB mass transfer model (E) and unstable case BB & optimistic CE model (F) </li> <li>alpha0_1 zip, the \(\alpha = 0.1\) model (G) </li> <li>alpha0_5.zip, the \(\alpha = 0.5\) model (H) </li> <li>alpha2_0.zip, the \(\alpha = 2.0\) model (I) </li> <li>alpha10_0.zip, the \(\alpha = 10.0\) model (J) </li> <li>rapid.zip, the rapid SN model (L) </li> <li>maxNSmass2_0.zip, the max \(m_{\rm{NS}} = 2\, \rm{M}_{\odot}\) model (M) </li> <li>maxNSmass3_0.zip, the max \(m_{\rm{NS}} = 3\, \rm{M}_{\odot}\) model (N)</li> <li>noPISN.zip, the no PISN model (O) </li> <li>ccSNkick_100km_s.zip, the \(\sigma_{\rm{cc}}\)= 100 km/s model (P) </li> <li>ccSNkick_30km_s.zip, the \(\sigma_{\rm{cc}}\)= 30 km/s model (Q)</li> <li> noBHkick.zip, the no BH SN kick model (R)</li> <li>wolf_rayet_multiplier_0_1.zip, the model with Wolf-Rayet wind factor \(f_{\rm{WR}} = 0.1\) (S)</li> <li>wolf_rayet_multiplier_5.zip, the model with Wolf-Rayet wind factor \(f_{\rm{WR}} = 5\) (T)  </li> </ul> </li> <li>2 more zip files containing csv files with the summarized rates to create Figures 1, 2 and 3, which do not require downloading the entire dataset, but instead use these csv files with the summarized rates:  <ul> <li>csvFilesForFigure1_DCOpaper.zip # contains the files to recreate figure 1 with the merger rates per metallicity for BH-BH, BH-NS and NS-NS: <ul> <li>formationRatesTotalAndPerChannel_BHBH_.csv</li> <li>formationRatesTotalAndPerChannel_BHNS_.csv</li> <li>formationRatesTotalAndPerChannel_NSNS_.csv</li> </ul> </li> <li>csvFilesForFigure2_and_3_DCOpaper.zip # contains the files to recreate figure 2 with the merger rates for intrinsic and GW detection weighted, containing the csv files with names:  <ul> <li>rates_MSSFR_Models_BHBH_AllDCOsimulation.csv</li> <li>rates_MSSFR_Models_NSNS_AllDCOsimulation.csv</li> <li>rates_MSSFR_Models_BHNS_AllDCOsimulation.csv</li> </ul> </li> </ul> </li> </ul>   Details of how to use the data (a readme),  as well as scripts to reproduce all results, plots, and figures from the paper are given in the accompanying Github repository <a href="https://github.com/FloorBroekgaarden/Double-Compact-Object-Mergers">https://github.com/FloorBroekgaarden/Double-Compact-Object-Mergers</a>  If you use this data, please cite  Broekgaarden et al. (2021): see <a href="https://ui.adsabs.harvard.edu/abs/2021arXiv211205763B/abstract">https://ui.adsabs.harvard.edu/abs/2021arXiv211205763B/abstract</a>

opencc-by-4.0Apr 2022View details →

GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run - Glitch modelling for events

This material is part of several data products associated with GWTC-2.1, the deep extended catalog of compact binary coalescences observed by the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration and the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration during the first half of the third observing run. For further information, see the paper (<a href="https://dcc.ligo.org/LIGO-P2100063/public">dcc.ligo.org/LIGO-P2100063/public</a>), the related material linked from this page, and the GWTC-2.1 data release documentation (<a href="https://www.gw-openscience.org/GWTC-2.1/">www.gw-openscience.org/GWTC-2.1/</a>). Glitch model for GWTC-2.1 events Glitch model for events in the GWTC_2.1 catalog that used <a href="https://git.ligo.org/lscsoft/bayeswave">BayesWave</a> glitch subtraction. This includes LIGO Livingston Observatory (L1) data for the following events: <ul> <li>GW190413_134308</li> <li>GW190425_081805</li> <li>GW190503_185404</li> <li>GW190513_205428</li> <li>GW190514_065416</li> <li>GW190701_203306</li> <li>GW190924_021846</li> </ul> Each data file contains three channels: <ol> <li>the calibrated strain data, including any glitches that are present,</li> <li>a model of the glitches, produced using the BayesWave algorithm,</li> <li>the calibrated data with the glitch model subtracted, used for parameter estimation</li> </ol> For the L1 data for all events, these channels have the following names and sample rates (in Hz): <ol> <li>L1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01 16384</li> <li>L1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01_glitch 16384</li> <li>L1:DCS-CALIB_STRAIN_CLEAN_SUB60HZ_C01_T1700406_v4 16384</li> </ol> How to download all files from this page If you would like to download all files on this page we recommend <a href="https://gitlab.com/dvolgyes/zenodo_get">zenodo_get</a>: <pre><code class="language-bash">pip install zenodo_get zenodo-get RECORD_ID_OR_DOI</code></pre> where the record ID for the most recent version of this page is 6477075 and IDs for other versions can be found in the Versions section at the side of this page.   For more general background on gravitational-wave data quality, try the materials from a <a href="https://www.gw-openscience.org/workshops/">GW Open Data Workshop</a> or the guide to <a href="https://doi.org/10.1088/1361-6382/ab685e">LIGO-Virgo data analysis</a>.

opencc-by-4.0Jun 2022View details →

Main Sequence + Compact Object binary candidates from Gaia DR3 astrometric and spectroscopic excess noise

MS+CO systems selected from Gaia DR3 via inferred periods and mass ratios derived from astrometric and spectroscopic errors. The sample is split into a bronze list (significant astrometric and spectroscopic RUWE, mass ratio > 1 and companion mass > 3 Msun).  A subset of these is chosen as a silver list (propagating errors on mass ratio and companion mass to deselect systems which are not significantly above the previous criteria) Finally, a gold list is constructed from the subset of the silver list which shows no evidence of being significantly brighter than a single MS star and with no significant excess photometric noise. We include the most relevant Gaia data for the system, as well as our inferred spectroscopic and photometric errors and RUWEs, and the inferred periods and mass ratios. Gaia's DR3 source id, and the ra, dec position are included and thus other Gaia data, or data from other astronomical catalogs, can be found for these systems. The catalog and the underlying methods are explained in more detail in <a href="https://arxiv.org/abs/2206.04392">Andrew et al. 2022</a>.

opencc-by-4.0Dec 2021View details →

Text-fig. 2. Scanning electron micrographs of non-angiosperm remains (a–d) and insect remains (e–f) from Zliv-Řídká Blana locality. a: Eopolytrichium sp. small leafy shoot, no. NM-F 3631; b: Taxon 1, single tip of a young fern frond with circinate vernation, no. NM-F 4130; c: Taxon 2, fern with simple leaves and circinate vernation, no. NM-F 3459; d: Pagiophyllum sp., small needle-like leaf, no. NM-F 4132; e: Microcarpolithes hexagonalis, a faecal pellet/coprolite with subcylindrical shape, no. NMF 4520; f: Palaeoaldrovanda splendens, pieces of compact walls formed by rectangular cells, no. NM-F 3237. in Plant Mesofossils From The Late Cretaceous Klikov Formation, The Czech Republic

Text-fig. 2. Scanning electron micrographs of non-angiosperm remains (a–d) and insect remains (e–f) from Zliv-Řídká Blana locality. a: Eopolytrichium sp. small leafy shoot, no. NM-F 3631; b: Taxon 1, single tip of a young fern frond with circinate vernation, no. NM-F 4130; c: Taxon 2, fern with simple leaves and circinate vernation, no. NM-F 3459; d: Pagiophyllum sp., small needle-like leaf, no. NM-F 4132; e: Microcarpolithes hexagonalis, a faecal pellet/coprolite with subcylindrical shape, no. NMF 4520; f: Palaeoaldrovanda splendens, pieces of compact walls formed by rectangular cells, no. NM-F 3237.

opencc-by-4.0Dec 2021View details →

Text-fig. 2. CT slices on Block 2. Details of other skeletal parts (a). The familiar shape of an ammonite (a, c). Holes, cracks and empty cavities in both the limestone matrix and within the vertebrate fossil (b, c). Heterogeneity of the 'tuffeau' limestone, the more porous areas of the matrix clearly distinguishable from the more compact ones (c). Ferric nodules (c). in Hidden Treasures Uncovered: Successful Detection Of Fossils Below The Surface In Large Limestone Blocks Using A Standard Medical X-Ray Ct Scanner

Text-fig. 2. CT slices on Block 2. Details of other skeletal parts (a). The familiar shape of an ammonite (a, c). Holes, cracks and empty cavities in both the limestone matrix and within the vertebrate fossil (b, c). Heterogeneity of the 'tuffeau' limestone, the more porous areas of the matrix clearly distinguishable from the more compact ones (c). Ferric nodules (c).

opencc-by-4.0Jun 2024View details →

Translaminar Fracture in a Mini-Protruded Compact Tension Specimen: A Dataset of Micro-Scale Tomograms of a Thin-Ply Carbon Fibre-Epoxy Composite acquired via Synchrotron Radiation Computed Tomography During In-Situ Loading

In this study, we developed a scaled-down “mini-protruded compact tension specimen” to facilitate in-situ tensile testing coupled with synchrotron radiation computed tomography (SRCT). This innovative design provides valuable insights into in-situ translaminar damage mechanisms, significantly enhancing the accuracy of data used in finite element models. The specimen is made of HS40 carbon fibres and ThinPregTM 736LT epoxy resin, with the layup of [902/0/902/0/902/0/902]. The translaminar fracture experiments were conducted under continuous loading and scanning using ultra-fast SRCT at the Swiss Light Source (SLS) TOMCAT beamline (Paul Scherrer Institut in Villigen, Switzerland). A polychromatic beam with an energy of 24 keV was used. The achieved voxel size was 800 nm, and 1000 projections per scan and 2 ms exposure time were acquired per scan. The GigaFRoST camera served as the detector. The scans were reconstructed into 3D volumes using the SLS’s in-house absorption-based algorithm (Gridrec) for critical loading steps during a test—both before and after a load drop (detailed in the accompanying Excel file). The tensile loading was exerted on the specimen at a rate of 0.2 mm/min until failure during scanning with the Deben CT500.

FIGURE 4. P and S in BoneProfileR: The next step to quantify, model, and statistically compare bone section compactness profiles

FIGURE 4. P and S values ffor radial compactness analysis of (A, B) Erinaceus europaeus and (C, D) Eryops megacephalus femur using the flexit model.

FIGURE 3 in BoneProfileR: The next step to quantify, model, and statistically compare bone section compactness profiles

FIGURE 3. Posterior distribution of K1 and K2 parameters of the flexit model applied on Erinaceus europaeus femur (A, B) and on Eryops megacephalus femur (C, D). A -1000 to +1000 uniform prior distribution was used. K1 = K2 = 1 shown in interrupted line is the logistic equation.

FIGURE 2 in BoneProfileR: The next step to quantify, model, and statistically compare bone section compactness profiles

FIGURE 2. Comparison of logistic and flexit fits (A, B) of the Erinaceus europaeus femur shown in Figure 1A and (C, D) of the Eryops megacephalus femur shown in Figure 1B. Table 1 shows the AIC and Akaike weight values for these models.

FIGURE 1 in BoneProfileR: The next step to quantify, model, and statistically compare bone section compactness profiles

FIGURE 1. Example of background and foreground automatic detection in (A) Erinaceus europaeus femur, and (B) Eryops megacephalus femur. Centers were automatically detected in (A) and manually positioned in (B). Here, sections are segmented in 100 concentric circles and 60 slices for measures of global and radial compactness. Details on bone section preparation can be found in Laurin et al. (2004) and Quémeneur et al. (2013).

◂Fig.15 Scanning electron micrographs (SEM) showing transverse rows of dentition on Dinaride Zospeum and Iberozospeum radulae; (a) Z. pretneri, (NMBE 553290), Gornja Cerovačka pećina, Croatia, transverse rows of teeth on long, slender basal plates (bp), rachidian (r) and lateral teeth (l), arrows indicate medial grooves on mesocones of individual teeth; (b) Z. isselianum, NMBE 553389, Turjeva jama, Slovenia, ibid.; (c) Iberozospeum sp. (RMNH.MOL.234,116), Cueva a Sul, straight transverse rows of small, seemingly bi-cuspid lateral teeth (l) with reduced mesocones on compact basal plates; (d) ibid., close up view of rachidian teeth (r), lateral fang-like teeth (l) and transitional teeth (t); (e) I. vasconicum, (AJC 1848), Cueva Ermita de Sandaili, rachidian teeth (r) flanked by 4-cuspid lateral teeth (l), C. ibazoricum-like in form; (f) Iberozospeum sp. (RMNH. MOL.234108), Cueva la Torcona, lateral teeth showing reduced mesocones (me) flanked by long, fang-like endo- and ectocones (e), rachidian tooth (r) (flipped over in upper righthand corner of image); (g) I. zaldivarae (AJC 1876a), Cueva de Las Paúles, transverse rows of teeth showing varying cusp lengths; (h) ibid., close up view (left to right) of marginal (m) and transitional teeth (t) on short, compact basal plates (bp). — Magnification varies for each perspective, see scale bars; all Figs taken by M. Ruppel, (ret.) Goethe University Frankfurt am Main in Molecular investigation and description of Iberozospeum n. gen., including the description of one new species (Eupulmonata, Ellobioidea, Carychiidae)

◂Fig.15 Scanning electron micrographs (SEM) showing transverse rows of dentition on Dinaride Zospeum and Iberozospeum radulae; (a) Z. pretneri, (NMBE 553290), Gornja Cerovačka pećina, Croatia, transverse rows of teeth on long, slender basal plates (bp), rachidian (r) and lateral teeth (l), arrows indicate medial grooves on mesocones of individual teeth; (b) Z. isselianum, NMBE 553389, Turjeva jama, Slovenia, ibid.; (c) Iberozospeum sp. (RMNH.MOL.234,116), Cueva a Sul, straight transverse rows of small, seemingly bi-cuspid lateral teeth (l) with reduced mesocones on compact basal plates; (d) ibid., close up view of rachidian teeth (r), lateral fang-like teeth (l) and transitional teeth (t); (e) I. vasconicum, (AJC 1848), Cueva Ermita de Sandaili, rachidian teeth (r) flanked by 4-cuspid lateral teeth (l), C. ibazoricum-like in form; (f) Iberozospeum sp. (RMNH. MOL.234108), Cueva la Torcona, lateral teeth showing reduced mesocones (me) flanked by long, fang-like endo- and ectocones (e), rachidian tooth (r) (flipped over in upper righthand corner of image); (g) I. zaldivarae (AJC 1876a), Cueva de Las Paúles, transverse rows of teeth showing varying cusp lengths; (h) ibid., close up view (left to right) of marginal (m) and transitional teeth (t) on short, compact basal plates (bp). — Magnification varies for each perspective, see scale bars; all Figs taken by M. Ruppel, (ret.) Goethe University Frankfurt am Main

opencc-by-4.0May 2018View details →

Images and supporting data for high-resolution μCT of a mouse embryo using a compact laser-driven x-ray betatron source

A high resolution x-ray CT scan of an embryonic mouse sample was performed with the betatron x-ray source produced by a laser wakefield accelerator. This data deposition includes all of the raw images of the mouse sample, information regarding their indexing, featured slices of the tomogram and some further raw data regarding the x-ray source characterisation.

opencc-by-4.0Aug 2018View details →

Research data supporting "Duplex-Specific Nuclease-Amplified Detection of MicroRNA Using 2 Compact Quantum Dot−DNA Conjugates"

Raw research data supporting the publication: Wang, Y. et al., 2018, ACS Applied Materials & Interfaces, "Duplex-Specific Nuclease-Amplified Detection of MicroRNA Using 2 Compact Quantum Dot−DNA Conjugates", DOI: 10.1021/acsami.8b07250.

opencc-by-4.0Feb 2019View details →

VGAM: Compact and Low Power Mass Spectrometer-based Instrumentation for Volcanic Gas Monitoring

Compact mass spectrometers can provide simultaneous multi-species analysis with high sensitivity and precision. For volcanic gas monitoring in situ, instrumental mass spectrometry requires reliability and ruggedness combined with low power usage and portability. The Volcanic Gas Analytical Monitor (VGAM) is capable of quantitative molecular analysis of a variety of atmospheric and volcanic gases in a single sensor by ion trap mass spectrometry. These gases include: H 2 , He, H 2 O, N 2 , O 2 , Ar, NO, N 2 O, CO, CO 2 , H 2 S, SO, SO 2 , and CH 4 . Unlike previous field instruments using magnetic sector and quadrupole mass spectrometers (MS) with vacuums backed by compact turbomolecular pumps, the VGAM uses a low-power autoresonant ion trap MS and NEG-Ion vacuum that operate at only 25 W total power, which is often the power requirement for just the mass spectrometer. Ratio- metric mass spectral response is combined with total pressure measurements to report absolute partial pressures. Data are generated in real time and are recorded to internal flash memory. Relatively low power (&lt;1 Watt) data telemetry to remote sites is possible. Analysis of volcanic plumes, fumaroles, and solfatara fields is accomplished by direct inlet of gases, after trapping as much excess water vapor in both the external and internal foreline as possible. We report herein on the VGAM auto-run and post-processing procedures, initial calibration results for CO 2 , and the results of a brief field deployment at Sulphur Banks solfatara field, Kilauea Volcano, Hawaii.

opencc-by-4.0Apr 2024View details →

Cryo-EM/Cryo-ET raw images and tilt series for the figures in the paper entitled "Angle Between DNA Linker and Nucleosome Core Particle Regulates Array Compaction by Individual-Particle Cryo-Electron Tomography"

Cryo-EM and cryo-ET raw images and tilt-series for the 3D reconstructions showed in the Figures of the paper entilted "Angle between DNA linker and nucleosome core particle regulates array compaction by individual-particle cryo-electron tomography"

opencc-by-4.0Sep 2024View details →

IAM_COMPACT_Study_1_Fit_for_55

This dataset contains the underling raw data of IAM COMPACT "Study 1 - Fit-for-55". This study aims to answer the research question, "how does the implementation of the updated national energy and climate plan compare to the cost-optimal EU plan?" However, due to delays in the release of the National Energy and Climate Plans (NECPs) by EU member states and limitations in the models used to represent specific national policies, this study compares cost-optimal model scenarios to achieve the EU emissions mitigation targets with EU-wide modelling of the Fit-for-55 policy package. The first scenario includes sector-level policies outlined in the Fit-for-55 policy packages, while the second scenario imposes emissions constraints on overall GHG and CO2 emissions without including any sectoral policies, in order to compare the cost-effective measures with sectoral policies. Results of the study have been documented in D4.5 National regional global mitigation pathways (DOI <a href="../doi/10.5281/zenodo.13767329">10.5281/zenodo.13767329</a>)