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| GRB 220527A , the SIMBAD biblio (27 results) | C.D.S. - SIMBAD4 rel 1.8 - 2026.10.16CEST17:35:11 |
| Bibcode/DOI | Score |
in Title|Abstract| Keywords |
in a table | in teXt, Caption, ... | Nb occurence | Nb objects in ref |
Citations (from ADS) |
Title | First 3 Authors |
|---|---|---|---|---|---|---|---|---|---|
| 2022GCN.32129....1U | 85 | T | 1 | ~ |
GRB 220527A: AGILE detection. |
URSI A., PIANO G., PITTORI C., et al. | |||
| 2022GCN.32130....1F | 85 | T | 1 | ~ |
GRB 220527A: Fermi GBM Final Localization. |
FERMI GBM TEAM | |||
| 2022GCN.32131....1B | 85 | T | 1 | ~ |
GRB 220527A: Fermi-LAT detection. |
BISSALDI E., SCOTTON L. and AXELSSON M. | |||
| 2022GCN.32132....1E | 85 | T | 1 | ~ |
GRB 220527A: Swift ToO observations. |
EVANS P.A. | |||
| 2022GCN.32133....1M | 85 | T | 1 | ~ |
GRB 220527A: Fermi GBM Observation. |
MANGAN J., DUNWOODY R. and MEEGAN C. | |||
| 2022GCN.32135....1S | 85 | T | 1 | ~ |
GRB 220527A: Swift-XRT afterglow detection. |
SBARUFATTI B., BEARDMORE A.P., OSBORNE J.P., et al. | |||
| 2022GCN.32136....1T | 85 | T | 1 | ~ |
GRB 220527A: Swift/UVOT detection. |
TOHUVAVOHU A. | |||
| 2022GCN.32138....1I | 85 | T | 1 | ~ |
GRB 220527A: MITSuME Akeno optical observation. |
IMAI Y., SATO S., HOSOKAWA R., et al. | |||
| 2022GCN.32139....1Y | 85 | T | 1 | ~ |
GRB 220527A: CALET Gamma-Ray Burst Monitor detection. |
YAMAOKA K., YOSHIDA A., SAKAMOTO T., et al. | |||
| 2022GCN.32140....1G | 85 | T | 1 | ~ |
GRB 220527A: AstroSat CZTI detection. |
GOPALAKRISHNAN R., PRASAD V., WARATKAR G., et al. | |||
| 2022GCN.32141....1X | 85 | T | 1 | ~ |
GRB 220527A: NOT optical photometry and spectroscopic redshift. |
XU D., ZHU Z.P., IZZO L., et al. | |||
| 2022GCN.32143....1D | 85 | T | 1 | ~ |
GRB 220527A: MeerLICHT afterglow observations. |
DE WET S., GROOT P.J. and VREESWIJK P.M. | |||
| 2022GCN.32145....1D | 85 | T | 1 | ~ |
GRB 220527A: REM optical/NIR observations. |
D'AVANZO P., FUGAZZA D., MELANDRI A., et al. | |||
| 2022GCN.32146....1L | 85 | T | 1 | ~ |
GRB 220527A: AST3-3 Yaoan Optical Observation. |
LI Z., YUAN X., WANG L., et al. | |||
| 2022GCN.32152....1L | 85 | T | 1 | ~ |
Konus-Wind observation of GRB 220527A. |
LYSENKO A., FREDERIKS D., RIDNAIA A., et al. | |||
| 2022GCN.32158....1Z | 85 | T | 1 | ~ |
GRB 220527A: Lick 3m Optical Observations. |
ZHENG W., BRINK T.G. and FILIPPENKO A.V. | |||
| 2022GCN.32159....1N | 85 | T | 1 | ~ |
GRB 220527A: MITSuME Akeno continued optical observation. |
NIWANO M., SATO S., TATEDA M., et al. | |||
| 2022GCN.32169....1R | 85 | T | 1 | ~ |
GRB 220527A: A BdHN I with a clear UPE phase. |
RUFFINI R., AIMURATOV Y., BECERRA L., et al. | |||
| 2023ApJS..266...31L | 17 | D | 4 | 153 | 4 | Revisiting the Spectral Energy Correlations of GRBs with Fermi Data. I. Model-wise Properties. | LI L. | ||
| 2024RAA....24b5006W | 18 | D | 2 | 64 | ~ | Time-resolved Spectral Properties of Fermi-GBM Bright Long Gamma-Ray Bursts. | WANG W.-K., XIE W., GAO Z.-F., et al. | ||
| 2024ApJ...965...72M | 18 | D | 2 | 144 | ~ | Distributions of Energy, Luminosity, Duration, and Waiting Times of Gamma-Ray Burst Pulses with Known Redshift Detected by Fermi/GBM. | MACCARY R., GUIDORZI C., AMATI L., et al. | ||
| 2024MNRAS.533..743W | 108 | D | C | 3 | 190 | ~ | Constraints from Fermi observations of long gamma-ray bursts on cosmological parameters. | WANG H. and LIANG N. | |
| 2024ApJ...972....1L | 18 | D | 1 | 90 | ~ | Magnetization Factors of Gamma-Ray Burst Jets Revealed by a Systematic Analysis of the Fermi Sample. | LI A., GAO H., LAN L., et al. | ||
|
2024A&A...690A.261G |
18 | D | 2 | 216 | ~ | New results on the gamma-ray burst variability-luminosity relation. | GUIDORZI C., MACCARY R., TSVETKOVA A., et al. | ||
| 2025A&A...693A.156M | 19 | D | 1 | 77 | ~ | Gamma-ray burst spectral-luminosity correlations in the synchrotron scenario. | MEI A., OGANESYAN G. and MACERA S. | ||
| 2025ApJ...980..241A | 19 | D | 1 | 185 | ~ | GRB 221009A and the Apparently Most Energetic Gamma-Ray Bursts. | ATTEIA J.-L., BOUCHET L., DEZALAY J.-P., et al. | ||
|
2025A&A...702A.173Z |
19 | D | 1 | 89 | ~ | Unsupervised machine learning classification of gamma-ray bursts based on the rest-frame prompt emission parameters. | ZHU S.-Y., SHAO L., TAM P.-H.T., et al. |