Publications of Will T. Barnes ordered by citations

A list of publications authored or co-authored by Will T. Barnes, derived from the SAO/NASA Astrophysics Data System (ADS) and ordered by the numbers of citations. Publications above the horizontal line count towards the h-index.

Orcid ID: 0000-0001-9642-6089

285	The SunPy Project: Open Source Development and Status of the Version 1.0 Core Package SunPy Community, Barnes, Will T., Bobra, Monica G., Christe, Steven D., Freij, Nabil, Hayes, Laura A., Ireland, Jack, Mumford, Stuart, Perez-Suarez, David, Ryan, Daniel F., Shih, Albert Y., Chanda, Prateek, Glogowski, Kolja, Hewett, Russell, Hughitt, V. Keith, Hill, Andrew, Hiware, Kaustubh, Inglis, Andrew, Kirk, Michael S. F., Konge, Sudarshan, Mason, James Paul, Maloney, Shane Anthony, Murray, Sophie A., Panda, Asish, Park, Jongyeob, Pereira, Tiago M. D., Reardon, Kevin, Savage, Sabrina, Sipőcz, Brigitta M., Stansby, David, Jain, Yash, Taylor, Garrison, Yadav, Tannmay, Rajul & Dang, Trung Kien, 2020, ApJ, 890, 68
48	Inference of Heating Properties from "Hot" Non-flaring Plasmas in Active Region Cores. I. Single Nanoflares Barnes, W. T., Cargill, P. J. & Bradshaw, S. J., 2016, ApJ, 829, 31
41	aiapy: A Python Package for Analyzing Solar EUV Image Data from AIA Barnes, Will, Cheung, Mark, Bobra, Monica, Boerner, Paul, Chintzoglou, Georgios, Leonard, Drew, Mumford, Stuart, Padmanabhan, Nicholas, Shih, Albert, Shirman, Nina, Stansby, David & Wright, Paul, 2020, The Journal of Open Source Software, 5, 2801
33	Inference of Heating Properties from "Hot" Non-flaring Plasmas in Active Region Cores. II. Nanoflare Trains Barnes, W. T., Cargill, P. J. & Bradshaw, S. J., 2016, ApJ, 833, 217
29	SunPy: A Python package for Solar Physics Mumford, Stuart, Freij, Nabil, Christe, Steven, Ireland, Jack, Mayer, Florian, Hughitt, V., Shih, Albert, Ryan, Daniel, Liedtke, Simon, Pérez-Suárez, David, Chakraborty, Pritish, K, Vishnunarayan, Inglis, Andrew, Pattnaik, Punyaslok, Sipőcz, Brigitta, Sharma, Rishabh, Leonard, Andrew, Stansby, David, Hewett, Russell, Hamilton, Alex, Hayes, Laura, Panda, Asish, Earnshaw, Matt, Choudhary, Nitin, Kumar, Ankit, Chanda, Prateek, Haque, Md, Kirk, Michael, Mueller, Michael, Konge, Sudarshan, Srivastava, Rajul, Jain, Yash, Bennett, Samuel, Baruah, Ankit, Barnes, Will, Charlton, Michael, Maloney, Shane, Chorley, Nicky, Himanshu, Modi, Sanskar, Mason, James, Naman, Campos Rozo, Jose Ivan, Manley, Larry, Chatterjee, Agneet, Evans, John, Malocha, Michael, Bobra, Monica, Ghosh, Sourav, Airmansmith, Stańczak, Dominik, De Visscher, Ruben, Verma, Shresth, Agrawal, Ankit, Buddhika, Dumindu, Sharma, Swapnil, Park, Jongyeob, Bates, Matt, Goel, Dhruv, Taylor, Garrison, Cetusic, Goran, Jacob, Inchaurrandieta, Mateo, Dacie, Sally, Dubey, Sanjeev, Sharma, Deepankar, Bray, Erik, Rideout, Jai, Zahniy, Serge, Meszaros, Tomas, Bose, Abhigyan, Chicrala, André, Ankit, Guennou, Chloé, D'Avella, Daniel, Williams, Daniel, Ballew, Jordan, Murphy, Nick, Lodha, Priyank, Robitaille, Thomas, Krishan, Yash, Hill, Andrew, Eigenbrot, Arthur, Mampaey, Benjamin, Wiedemann, Bernhard, Molina, Carlos, Keşkek, Duygu, Habib, Ishtyaq, Letts, Joseph, Bazán, Juanjo, Arbolante, Quinn, Gomillion, Reid, Kothari, Yash, Sharma, Yash, Stevens, Abigail, Price-Whelan, Adrian, Mehrotra, Ambar, Kustov, Arseniy, Stone, Brandon, Dang, Trung, Arias, Emmanuel, Dover, Fionnlagh, Verstringe, Freek, Kumar, Gulshan, Mathur, Harsh, Babuschkin, Igor, Wimbish, Jaylen, Buitrago-Casas, Juan, Krishna, Kalpesh, Hiware, Kaustubh, Mangaonkar, Manas, Mendero, Matthew, Schoentgen, Mickaël, Gyenge, Norbert, Streicher, Ole, Mekala, Rajasekhar, Mishra, Rishabh, Srikanth, Shashank, Jain, Sarthak, Yadav, Tannmay, Wilkinson, Tessa, Pereira, Tiago, Agrawal, Yudhik, Jamescalixto, Yasintoda & Murray, Sophie, 2020, The Journal of Open Source Software, 5, 1832
19	Understanding Heating in Active Region Cores through Machine Learning. I. Numerical Modeling and Predicted Observables Barnes, W. T., Bradshaw, S. J. & Viall, N. M., 2019, ApJ, 880, 56
13	Solar Active Region Heating Diagnostics from High-temperature Emission Using the MaGIXS Athiray, P. S., Winebarger, Amy R., Barnes, Will T., Bradshaw, Stephen J., Savage, Sabrina, Warren, Harry P., Kobayashi, Ken, Champey, Patrick, Golub, Leon & Glesener, Lindsay, 2019, ApJ, 884, 24
9	Geometric Assumptions in Hydrodynamic Modeling of Coronal and Flaring Loops Reep, Jeffrey W., Ugarte-Urra, Ignacio, Warren, Harry P. & Barnes, Will T., 2022, ApJ, 933, 106
7	Nanoflare Diagnostics from Magnetohydrodynamic Heating Profiles Knizhnik, K. J., Barnes, W. T., Reep, J. W. & Uritsky, V. M., 2020, ApJ, 899, 156
7	Understanding Heating in Active Region Cores through Machine Learning. II. Classifying Observations Barnes, W. T., Bradshaw, S. J. & Viall, N. M., 2021, ApJ, 919, 132
6	EISPAC - The EIS Python Analysis Code Weberg, Micah, Warren, Harry, Crump, Nicholas & Barnes, Will, 2023, The Journal of Open Source Software, 8, 4914
2	CHIANTI—An Atomic Database for Emission Lines—Paper. XVIII. Version 11, Advanced Ionization Equilibrium Models: Density and Charge Transfer Effects Dufresne, R. P., Del Zanna, G., Young, P. R., Dere, K. P., Deliporanidou, E., Barnes, W. T. & Landi, E., 2024, ApJ, 974, 71
1	Thermal Evolution of an Active Region Through Quiet and Flaring Phases as Observed by NuSTAR, XRT, and AIA Duncan, Jessie, Masek, Reed B., Shih, Albert Y., Glesener, Lindsay, Barnes, Will, Reeves, Katharine K., Zhang, Yixian, Hannah, Iain G. & Grefenstette, Brian W., 2024, ApJ, 966, 197
1	A Unified Framework for Manipulating N-dimensional Astronomical Data and Coordinate Transformations in Python: The NDCube 2 and Astropy APE-14 World Coordinate System APIs Ryan, Daniel F., Mumford, Stuart, Barnes, Will T., Baruah, Ankit Kumar, Bhope, Adwait, Buchlin, Éric, Freij, Nabil, Ginsburg, Adam, Hayes, Laura A., Homeier, Derek, Hughes, J. Marcus, Lowder, Chris, O'Steen, Richard, Pellorce, Baptiste, Robitaille, Thomas, Sharma, Yash, Stansby, David, Shih, Albert Y., Tollerud, Erik, Weberg, Micah J. & West, Matthew J., 2023, ApJ, 956, 44
1	Modeling Time-variable Elemental Abundances in Coronal Loop Simulations Reep, Jeffrey W., Unverferth, John, Barnes, Will T. & Chhabra, Sherry, 2024, ApJ, 970, L41
0	Understanding Heating Properties of Active Region Loops through Forward Modeling and Machine Learning Barnes, Will, Bradshaw, Stephen, Viall, Nicki & Mumford, Stuart, 2018, Catalyzing Solar Connections, p. 72
0	Simulation of Exoplanet Host Star Magnetic Activity on Stellar Cycle Timescales Farrish, A. O., Maruo, M., Barnes, W. T., Alexander, D., Bradshaw, S. & DeRosa, M., 2018, Comparative Climatology of Terrestrial Planets III: From Stars to Surfaces (Editors: LPI Editorial Board), LPI Contributions, 2065, p. 2043
0	Interoperability between Python Packages Ringuette, Rebecca, Barnes, Will, Friej, Nabil & Mumford, Stuart, 2023, Data, Analysis and Software in Heliophysics (DASH) 2023, p. 18
0	Sunxspex: A High-energy Spectral Analysis Tool in Python Cooper, Kristopher, Ryan, Daniel, Maloney, Shane, Hayes, Laura, Mumford, Stuart, Hannah, Iain, Shih, Albert, Barnes, Will, Bajnokova, Natalia & Setterberg, William, 2023, Data, Analysis and Software in Heliophysics (DASH) 2023, p. 41
0	Determining the Nanoflare Heating Frequency of an X-Ray Bright Point Observed by MaGIXS Mondal, Biswajit, Athiray, P. S., Winebarger, Amy R., Savage, Sabrina L., Kobayashi, Ken, Bradshaw, Stephen, Barnes, Will, Champey, Patrick R., Cheimets, Peter, Dudík, Jaroslav, Golub, Leon, Mason, Helen E., McKenzie, David E., Moore, Christopher S., Madsen, Chad, Reeves, Katharine K., Testa, Paola, Vigil, Genevieve D., Warren, Harry P., Walsh, Robert W. & Del Zanna, Giulio, 2024, ApJ, 967, 23
0	XRTpy: A Hinode-X-Ray Telescope Python Package Velasquez, Joy, Murphy, Nicholas, Reeves, Katharine, Slavin, Jonathan, Weber, Mark & Barnes, Will, 2024, The Journal of Open Source Software, 9, 6396