# Resolving the Inner Parsec of the Blazar J1924-2914 with the Event Horizon Telescope

Sara Issaoun, Maciek Wielgus, Svetlana Jorstad, Thomas P. Krichbaum, Lindy Blackburn, Michael Janssen, Chi-Kwan Chan, Dominic W. Pesce, José L. Gómez, Kazunori Akiyama, et al.

► To cite this version:

Sara Issaoun, Maciek Wielgus, Svetlana Jorstad, Thomas P. Krichbaum, Lindy Blackburn, et al. Resolving the Inner Parsec of the Blazar J1924-2914 with the Event Horizon Telescope. The Astrophysical Journal, 2022, 934, 10.3847/1538-4357/ac7a40. insu-03874903

HAL Id: insu-03874903

https://insu.hal.science/insu-03874903

Submitted on 28 Nov 2022

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Resolving the Inner Parsec of the Blazar J1924–2914 with the Event Horizon Telescope

Sara Issaoun¹,²,³ ID, Maciek Wielgus⁴ ID, Svetlana Jorstad⁵ ID, Thomas P. Krichbaum⁴ ID, Lindy Blackburn¹,⁶ ID,
Michael Janssen⁴ ID, Chi-kwan Chan⁷,⁸ ID, Dominic W. Pesce¹,⁶ ID, José L. Gómez⁹ ID, Kazunori Akiyama⁶,¹⁰,¹¹ ID,
Monika Mościbrodzka² ID, Iván Martí-Vidal¹²,¹³ ID, Andrew Chael³,¹⁴ ID, Rocco Lico⁴,¹⁵,¹⁶ ID, Jun Liu (刘俊)⁴ ID,
Venkatessh Ramakrishnan¹⁷,¹⁸,¹⁹ ID, Mikhail Lisakov⁴ ID, Antonio Fuentes¹⁵ ID, Guang-Yao Zhao¹⁵ ID, Kotaro Moriyama¹⁰,²⁰,²¹ ID,
Avery E. Broderick²²,²³,²⁴ ID, Paul Tiede¹,⁶ ID, Nicholas R. MacDonald⁴ ID, Yosuke Mizuno²¹,²⁵,²⁶ ID, Efthalia Traianou⁴,⁹ ID,
Laurent Loinard²⁷,²⁸ ID, Jordy Davelaar²,²⁹,³⁰ ID, Mark Gurwell¹ ID, Ru-Sen Lu (路如森)⁴,³¹,³² ID, Antxon Alberdi¹⁵ ID,
Walter Alef⁴ ID, Juan Carlos Algaba³³ ID, Richard Anantua¹,⁶,³⁴ ID, Keiichi Asada³⁵ ID, Rebecca Azulay⁴,¹²,¹³ ID, Uwe Bach⁴ ID,
Anne-Kathrin Baczko⁴ ID, David Ball⁷ ID, Mislav Baloković³⁶ ID, John Barrett¹⁰ ID, Michi Bauböck³⁷ ID, Bradford A. Benson³⁸,³⁹ ID,
Dan Bintley⁴⁰,⁴¹ ID, Raymond Blundell¹ ID, Wilfred Boland⁴² ID, Katherine L. Bouman⁴³ ID, Geoffrey C. Bower⁴⁴,⁴⁵ ID,
Hope Boyce⁴⁶,⁴⁷ ID, Michael Bremer⁴⁸ ID, Christiaan D. Brinkerink² ID, Roger Brissenden¹,⁶ ID, Silke Britzen⁴ ID,
Dominique Broguiere⁴⁸ ID, Thomas Bronzwaer² ID, Sandra Bustamante⁴⁹ ID, Do-Young Byun⁵⁰,⁵¹ ID, John E. Carlstrom³⁹,⁵²,⁵³,⁵⁴ ID,
Chiara Ceccobello⁵⁵ ID, Koushik Chatterjee¹,⁶ ID, Shami Chatterjee⁵⁶ ID, Ming-Tang Chen⁴⁴ ID, Yongjun Chen (陈永军)³¹,⁵⁷ ID,
Ilje Cho¹⁵ ID, Pierre Christian⁵⁸ ID, Nicholas S. Conroy¹,⁵⁹ ID, John E. Conway⁵⁵ ID, James M. Cordes⁵⁶ ID,
Thomas M. Crawford³⁹,⁵² ID, Geoffrey B. Crew¹⁰ ID, Alejandro Cruz-Osorio²¹ ID, Yuzhu Cui²⁰,⁶⁰ ID,
Mariafelicia De Laurentis²¹,⁶¹,⁶² ID, Roger Deane⁶³,⁶⁴,⁶⁵ ID, Jessica Dempsey⁴⁰,⁴¹,⁶⁶ ID, Gregory Desvignes⁶⁷ ID, Jason Dexter⁶⁸ ID,
Sheperd S. Doeleman¹,⁶ ID, Vedant Dhruv³⁷ ID, Sergio Abraham Dzib Quijano⁴,⁴⁸ ID, Ralph P. Eatough⁴,⁶⁹ ID, Razieh Emami¹ ID,
Heino Falcke² ID, Joseph Farah⁷⁰,⁷¹ ID, Vincent L. Fish¹⁰ ID, Ed Fomalont⁷² ID, H. Alyson Ford⁷ ID, Raquel Fraga-Encinas² ID,
William T. Freeman⁷³,⁷⁴ ID, Per Friberg⁴⁰,⁴¹ ID, Christian M. Fromm⁴,²¹,⁷⁵ ID, Peter Galison⁶,⁷⁶,⁷⁷ ID, Charles F. Gammie³⁷,⁵⁹ ID,
Roberto García⁴⁸ ID, Olivier Gentaz⁴⁸ ID, Boris Georgiev²²,²³,²⁴ ID, Ciriaco Goddi⁷⁸,⁷⁹ ID, Roman Gold²¹,⁸⁰ ID,
Arturo I. Gómez-Ruiz⁸¹,⁸² ID, Minfeng Gu (顧敏峰)³¹,⁸³ ID, Kazuhiro Hada²⁰,⁶⁰ ID, Daryl Haggard⁴⁶,⁴⁷ ID, Michael H. Hecht¹⁰ ID,
Ronald Hesper⁸⁴ ID, Luis C. Ho (何子山)⁸⁵,⁸⁶ ID, Paul Ho³⁵,⁴¹ ID, Mareki Honma²⁰,⁶⁰,⁸⁷ ID, Chih-Wei L. Huang³⁵ ID, Lei Huang
(黃磊)³¹,⁸³ ID, David H. Hughes⁸¹ ID, Shiro Ikeda¹¹,⁸⁸,⁹⁹,⁹⁰ ID, C. M. Violette Impellizzeri⁷²,⁹¹ ID, Makoto Inoue³⁵ ID,
David J. James⁹² ID, Buell T. Jannuzi⁷ ID, Britton Jeter³⁵ ID, Wu Jiang (江悟)³¹ ID, Alejandra Jimenez-Rosales² ID,
Michael D. Johnson¹,⁶ ID, Abhishek V. Joshi³⁷ ID, Taehyun Jung⁵⁰,⁵¹ ID, Mansour Karami²²,²³ ID, Ramesh Karuppusamy⁴ ID,
Tomohisa Kawashima⁹³ ID, Garrett K. Keating¹ ID, Mark Kettenis⁹⁴ ID, Dong-Jin Kim⁴ ID, Jae-Young Kim⁴,⁴⁰,⁴¹,⁵⁰ ID,
Jongsoo Kim⁵⁰ ID, Junhan Kim⁷,⁴³ ID, Motoki Kino¹¹,⁹⁵ ID, Jun Yi Koay³⁵ ID, Prashant Kocherlakota²¹ ID, Yutaro Kofuji²⁰,⁸⁷ ID,
Patrick M. Koch³⁵ ID, Shoko Koyama³⁵,⁹⁶ ID, Carsten Kramer⁴⁸ ID, Michael Kramer⁴ ID, Cheng-Yu Kuo³⁵,⁹⁷ ID, Noemi La Bella² ID,
Tod R. Lauer⁹⁸ ID, Daeyoung Lee³⁷ ID, Sang-Sung Lee⁵⁰ ID, Po Kin Leung⁹⁹ ID, Aviad Levis⁴³ ID, Zhiyuan Li (李志远)¹⁰⁰,¹⁰¹ ID,
Rocco Lico⁴,¹⁵,¹⁶ ID, Greg Lindahl¹ ID, Michael Lindqvist⁵⁵ ID, Kuo Liu⁴ ID, Elisabetta Liuzzo¹⁰² ID, Wen-Ping Lo³⁵,¹⁰³ ID,
Andrei P. Lobanov⁴ ID, Colin Lonsdale¹⁰ ID, Jirong Mao (毛基榮)⁴⁰,⁴¹,¹⁰⁴,¹⁰⁵,¹⁰⁶ ID, Nicola Marchili⁴,¹⁰² ID, Sera Markoff¹⁰⁷,¹⁰⁸ ID,
Daniel P. Marrone⁷ ID, Alan P. Marscher⁵ ID, Satoki Matsushita³⁵ ID, Lynn D. Matthews¹⁰ ID, Lia Medeiros⁷,¹⁰⁹ ID,
Karl M. Menten⁴ ID, Daniel Michalik³⁹,¹¹⁰ ID, Izumi Mizuno⁴,⁴¹ ID, Yosuke Mizuno²¹,²⁵,²⁶ ID, James M. Moran¹,⁶ ID,
Cornelia Müller²,⁴ ID, Alejandro Mus¹²,¹³ ID, Gibwa Musoke²,¹⁰⁷ ID, Ioannis Myserlis¹¹¹ ID, Andrew Nadolski⁵⁹ ID,
Hiroshi Nagai¹¹,⁶⁰ ID, Neil M. Nagar¹⁷ ID, Masanori Nakamura³⁵,¹¹² ID, Ramesh Narayan¹,⁶ ID, Gopal Narayanan⁴⁹ ID,
Iniyan Natarajan⁶³,¹¹³ ID, Antonios Nathanail²¹,¹¹⁴ ID, Joey Neilsen¹¹⁵ ID, Roberto Neri⁴⁸ ID, Chunchong Ni²²,²³,²⁴ ID,
Aristeidis Noutsos⁴ ID, Michael A. Nowak¹¹⁶ ID, Junghwan Oh¹¹⁷ ID, Hiroki Okino²⁰,⁸⁷ ID, Héctor Olivares² ID,
Gisela N. Ortiz-León⁴ ID, Tomoaki Oyama²⁰ ID, Feryal Özel⁷ ID, Daniel C. M. Palumbo¹,⁶ ID, Georgios Filippos Paraschos⁴ ID,
Jongho Park³⁵,¹¹⁸ ID, Harriet Parsons⁴⁰,⁴¹ ID, Nimesh Patel¹ ID, Ue-Li Pen²²,²³,¹¹⁹,¹²⁰,¹²¹ ID, Vincent Piétu⁴⁸ ID,
Richard Plambeck¹²² ID, Aleksandar PopStefanija⁴⁹ ID, Oliver Porth²¹,¹⁰⁷ ID, Felix M. Pötzl⁴,¹²³ ID, Ben Prather³⁷ ID,
Jorge A. Preciado-López²² ID, Dimitrios Psaltis⁷ ID, Hung-Yi Pu³⁵,¹²⁴,¹²⁵ ID, Ramprasad Rao⁴⁴ ID, Mark G. Rawlings⁴⁰,⁴¹,¹²⁶ ID,
Alexander W. Raymond¹,⁶ ID, Luciano Rezzolla²¹,¹²⁷,¹²⁸ ID, Angelo Ricarte¹,⁶ ID, Bart Ripperda³⁰,¹²⁹ ID, Freek Roelofs¹,²,⁶ ID,
Alan Rogers¹⁰ ID, Eduardo Ros⁴ ID, Cristina Romero-Canizales³⁵ ID, Arash Roshanineshat⁷ ID, Helge Rottmann⁴ ID, Alan L. Roy⁴ ID,
Ignacio Ruiz¹¹¹ ID, Chet Ruszczky¹⁰ ID, Kazi L. J. Rygl¹⁰² ID, Salvador Sánchez¹¹¹ ID, David Sánchez-Arguelles⁸¹,⁸² ID,
Miguel Sanchez-Portal¹¹¹ ID, Mahito Sasada²⁰,¹³⁰ ID, Kaushik Satapathy⁷ ID, Tuomas Savolainen⁴,¹⁹,¹³¹ ID, F. Peter Schloerb⁴⁹ ID,
Karl-Friedrich Schuster⁴⁸ ID, Lijing Shao⁴,⁸⁶ ID, Zhiqiang Shen (沈志强)³¹,⁴⁰,⁴¹,⁵⁷ ID, Des Small⁹⁴ ID,
Bong Won Sohn⁴⁰,⁴¹,⁵⁰,⁵¹,¹³² ID, Jason SooHoo¹⁰ ID, Kamal Souccar⁴⁹ ID, He Sun (孙赫)⁴³ ID, Fumie Tazaki²⁰ ID,
Alexandra J. Tetarenko³,¹³³ ID, Paul Tiede¹,⁶ ID, Remo P. J. Tilanus²,⁷,⁹,¹³⁴ ID, Michael Titus¹⁰ ID, Pablo Torne⁴,¹¹¹ ID, Tyler Trent⁷ ID,
Sascha Trippe⁴⁰,⁴¹,¹³⁵ ID, Ilse van Bemmel⁹⁴ ID, Huib Jan van Langevelde⁹¹,⁹⁴,¹³⁶ ID, Daniel R. van Rossum² ID, Jesse Vos² ID,
Jan Wagner⁴ ID, Derek Ward-Thompson¹³⁷ ID, John Wardle¹³⁸ ID, Jonathan Weintroub¹,⁶ ID, Norbert Wex⁴ ID, Robert Wharton⁴ ID,
Kaj Wiik¹³⁹ ID, Gunther Witzel⁴ ID, Michael Wondrak²,¹⁴⁰ ID, George N. Wong¹⁰⁹,¹⁴¹ ID, Qingwen Wu (吴庆文)⁴⁰,⁴¹,¹⁴² ID,
Paul Yamaguchi¹ ID, Doosoo Yoon¹⁰⁷ ID, André Young² ID, Ken Young¹ ID, Ziri Younsi²¹,¹⁴³ ID, Feng Yuan (袁峰)³¹,⁴⁰,⁴¹,⁸³,¹⁴⁴ ID,
Ye-Fei Yuan (袁业飞)⁴⁰,⁴¹,¹⁴⁵ ID, J. Anton Zensus⁴ ID, Shuo Zhang¹⁴⁶ ID, and Shan-Shan Zhao³¹ ID
¹ Center for Astrophysics | Harvard & Smithsonian, 60 Garden Street, Cambridge, MA 02138, USA; sara.issaoun@cfa.harvard.edu

² Department of Astrophysics, Institute for Mathematics, Astrophysics and Particle Physics (IMAPP), Radboud University, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands; maciek.wielgus@gmail.com

³ NASA Hubble Fellowship Program, Einstein Fellow

⁴ Max-Planck-Institut für Radioastronomie, Auf dem Hügel 69, D-53121 Bonn, Germany

⁵ Institute for Astrophysical Research, Boston University, 725 Commonwealth Ave., Boston, MA 02215, USA

⁶ Black Hole Initiative at Harvard University, 20 Garden Street, Cambridge, MA 02138, USA

⁷ Steward Observatory and Department of Astronomy, University of Arizona, 933 N. Cherry Ave., Tucson, AZ 85721, USA

⁸ Data Science Institute, University of Arizona, 1230 N. Cherry Ave., Tucson, AZ 85721, USA

⁹ Instituto de Astrofísica de Andalucía-CfSIC, Glorieta de la Astronomía s/n, E-18008 Granada, Spain

¹⁰ Massachusetts Institute of Technology Haystack Observatory, 99 Millstone Road, Westford, MA 01886, USA

¹¹ National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan

¹² Departament d'Astronomia i Astrofísica, Universitat de València, C. Dr. Moliner 50, E-46100 Burjassot, València, Spain

¹³ Observatori Astronòmic, Universitat de València, C. Catedrático José Beltrán 2, E-46980 Paterna, València, Spain

¹⁴ Princeton Center for Theoretical Science, Jadwin Hall, Princeton University, Princeton, NJ 08544, USA

¹⁵ Instituto de Astrofísica de Andalucía-CSIC, Glorieta de la Astronomía s/n, E-18008 Granada, Spain

¹⁶ INAF-Istituto di Radioastronomia, Via P. Gobetti 101, I-40129 Bologna, Italy

¹⁷ Astronomy Department, Universidad de Concepción, Casilla 160-C, Concepción, Chile

¹⁸ Finnish Centre for Astronomy with ESO, FI-20014 University of Turku, Finland

¹⁹ Aalto University Metsähovi Radio Observatory, Metsähovintie 114, FI-02540 Kylmälä, Finland

²⁰ Mizusawa VLBI Observatory, National Astronomical Observatory of Japan, 2-12 Hoshigaoka, Mizusawa, Oshu, Iwate 023-0861, Japan

²¹ Institut für Theoretische Physik, Goethe-Universität Frankfurt, Max-von-Laue-Straße 1, D-60438 Frankfurt am Main, Germany

²² Perimeter Institute for Theoretical Physics, 31 Caroline Street North, Waterloo, ON, N2L 2Y5, Canada

²³ Department of Physics and Astronomy, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada

²⁴ Waterloo Centre for Astrophysics, University of Waterloo, Waterloo, ON, N2L 3G1, Canada

²⁵ Tsung-Dao Lee Institute, Shanghai Jiao Tong University, Shengrong Road 520, Shanghai, 201210, People's Republic Of China

²⁶ School of Physics and Astronomy, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, People's Republic of China

²⁷ Instituto de Radioastronomía y Astrofísica, Universidad Nacional Autónoma de México, Morelia 58089, México

²⁸ Instituto de Astronomía, Universidad Nacional Autónoma de México, CdMx 04510, México

²⁹ Department of Astronomy and Columbia Astrophysics Laboratory, Columbia University, 550 W 120th Street, New York, NY 10027, USA

³⁰ Center for Computational Astrophysics, Flatiron Institute, 162 Fifth Avenue, New York, NY 10010, USA

³¹ Shanghai Astronomical Observatory, Chinese Academy of Sciences, 80 Nandan Road, Shanghai 200030, People's Republic of China

³² Key Laboratory of Radio Astronomy, Chinese Academy of Sciences, Nanjing 210008, People's Republic of China

³³ Department of Physics, Faculty of Science, Universiti Malaya, 50603 Kuala Lumpur, Malaysia

³⁴ Department of Physics & Astronomy, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA

³⁵ Institute of Astronomy and Astrophysics, Academia Sinica, 11F of Astronomy-Mathematics Building, AS/NTU No. 1, Sec. 4, Roosevelt Rd, Taipei 10617, Taiwan, R.O.C.

³⁶ Yale Center for Astronomy & Astrophysics, Yale University, 52 Hillhouse Avenue, New Haven, CT 06511, USA

³⁷ Department of Physics, University of Illinois, 1110 West Green Street, Urbana, IL 61801, USA

³⁸ Fermi National Accelerator Laboratory, MS209, P.O. Box 500, Batavia, IL 60510, USA

³⁹ Department of Astronomy and Astrophysics, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637, USA

⁴⁰ East Asian Observatory, 660 N. A'ohoku Place, Hilo, HI 96720, USA

⁴¹ James Clerk Maxwell Telescope (JCMT), 660 N. A'ohoku Place, Hilo, HI 96720, USA

⁴² Nederlandse Onderzoekschool voor Astronomie (NOVA), P.O. Box 9513, 2300 RA Leiden, The Netherlands

⁴³ California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125, USA

⁴⁴ Institute of Astronomy and Astrophysics, Academia Sinica, 645 N. A'ohoku Place, Hilo, HI 96720, USA

⁴⁵ Department of Physics and Astronomy, University of Hawaii at Manoa, 2505 Correa Road, Honolulu, HI 96822, USA

⁴⁶ Department of Physics, McGill University, 3600 rue University, Montréal, QC H3A 2T8, Canada

⁴⁷ McGill Space Institute, McGill University, 3550 rue University, Montréal, QC H3A 2A7, Canada

⁴⁸ Institut de Radioastronomie Millimétrique, 300 rue de la Piscine, F-38406 Saint Martin d'Hères, France

⁴⁹ Department of Astronomy, University of Massachusetts, 01003, Amherst, MA, USA

⁵⁰ Korea Astronomy and Space Science Institute, Daedeok-daero 776, Yuseong-gu, Daejeon 34055, Republic of Korea

⁵¹ University of Science and Technology, Gajeong-ro 217, Yuseong-gu, Daejeon 34113, Republic of Korea

⁵² Kavli Institute for Cosmological Physics, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637, USA

⁵³ Department of Physics, University of Chicago, 5720 South Ellis Avenue, Chicago, IL 60637, USA

⁵⁴ Enrico Fermi Institute, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637, USA

⁵⁵ Department of Space, Earth and Environment, Chalmers University of Technology, Onsala Space Observatory, SE-43992 Onsala, Sweden

⁵⁶ Cornell Center for Astrophysics and Planetary Science, Cornell University, Ithaca, NY 14853, USA

⁵⁷ Key Laboratory of Radio Astronomy, Chinese Academy of Sciences, Nanjing 210008, People's Republic of China

⁵⁸ Physics Department, Fairfield University, 1073 North Benson Road, Fairfield, CT 06824, USA

⁵⁹ Department of Astronomy, University of Illinois at Urbana-Champaign, 1002 West Green Street, Urbana, IL 61801, USA

⁶⁰ Department of Astronomical Science, The Graduate University for Advanced Studies (SOKENDAI), 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan

⁶¹ Dipartimento di Fisica “E. Pancini”, Università di Napoli “Federico II”, Compl. Univ. di Monte S. Angelo, Edificio G, Via Cinthia, I-80126, Napoli, Italy

⁶² INFN Sez. di Napoli, Compl. Univ. di Monte S. Angelo, Edificio G, Via Cinthia, I-80126, Napoli, Italy

⁶³ Wits Centre for Astrophysics, University of the Witwatersrand, 1 Jan Smuts Avenue, Braamfontein, Johannesburg 2505, South Africa

⁶⁴ Department of Physics, University of Pretoria, Hatfield, Pretoria 0028, South Africa

⁶⁵ Centre for Radio Astronomy Techniques and Technologies, Department of Physics and Electronics, Rhodes University, Makhanda 6140, South Africa

⁶⁶ ASTRON, Oude Hoogeveensedijk 4, 7991 PD Dwingeloo, The Netherlands

⁶⁷ LESIA, Observatoire de Paris, Université PSL, CNRS, Sorbonne Université, Université de Paris, 5 place Jules Janssen, F-92195 Meudon, France

⁶⁸ JILA and Department of Astrophysical and Planetary Sciences, University of Colorado, Boulder, CO 80309, USA

⁶⁹ National Astronomical Observatories, Chinese Academy of Sciences, 20A Datun Road, Chaoyang District, Beijing 100101, People's Republic of China

⁷⁰ Las Cumbres Observatory, 6740 Cortona Drive, Suite 102, Goleta, CA 93117-5575, USA

⁷¹ Department of Physics, University of California, Santa Barbara, CA 93106-9530, USA

⁷² National Radio Astronomy Observatory, 520 Edgemont Road, Charlottesville, VA 22903, USA

⁷³ Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 32-D476, 77 Massachusetts Ave., Cambridge, MA 02142, USA

⁷⁴ Google Research, 355 Main St., Cambridge, MA 02142, USA
⁷⁵ Institut für Theoretische Physik und Astrophysik, Universität Würzburg, Emil-Fischer-Str. 31, D-97074 Würzburg, Germany

⁷⁶ Department of History of Science, Harvard University, Cambridge, MA 02138, USA

⁷⁷ Department of Physics, Harvard University, Cambridge, MA 02138, USA

⁷⁸ Dipartimento di Fisica, Università degli Studi di Cagliari, SP Monserrato-Sestu km 0.7, I-09042 Monserrato, Italy

⁷⁹ INAF—Osservatorio Astronomico di Cagliari, Via della Scienza 5, I-09047, Selargius, CA, Italy

⁸⁰ CP3-Origins, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Denmark

⁸¹ Instituto Nacional de Astrofísica, Óptica y Electrónica. Apartado Postal 51 y 216, 72000. Puebla Pue., México

⁸² Consejo Nacional de Ciencia y Tecnología, Av. Insurgentes Sur 1582, 03940, Ciudad de México, México

⁸³ Key Laboratory for Research in Galaxies and Cosmology, Chinese Academy of Sciences, Shanghai 200030, People's Republic of China

⁸⁴ NOVA Sub-mm Instrumentation Group, Kapteyn Astronomical Institute, University of Groningen, Landleven 12, 9747 AD Groningen, The Netherlands

⁸⁵ Department of Astronomy, School of Physics, Peking University, Beijing 100871, People's Republic of China

⁸⁶ Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871, People's Republic of China

⁸⁷ Department of Astronomy, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan

⁸⁸ The Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo, 190-8562, Japan

⁸⁹ Department of Statistical Science, The Graduate University for Advanced Studies (SOKENDAI), 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan

⁹⁰ Kavli Institute for the Physics and Mathematics of the Universe, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, 277-8583, Japan

⁹¹ Leiden Observatory, Leiden University, Postbus 2300, 9513 RA Leiden, The Netherlands

⁹² ASTRAVEO LLC, P.O. Box 1668, Gloucester, MA 01931, USA

⁹³ Institute for Cosmic Ray Research, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8582, Japan

⁹⁴ Joint Institute for VLBI ERIC (JIVE), Oude Hoogeveensedijk 4, 7991 PD Dwingeloo, The Netherlands

⁹⁵ Kogakuin University of Technology & Engineering, Academic Support Center, 2665-1 Nakano, Hachioji, Tokyo 192-0015, Japan

⁹⁶ Niigata University, 8050 Ikarashi-nino-cho, Nishi-ku, Niigata 950-2181, Japan

⁹⁷ Physics Department, National Sun Yat-Sen University, No. 70, Lien-Hai Road, Kaosiung City 80424, Taiwan, R.O.C.

⁹⁸ National Optical Astronomy Observatory, 950 N. Cherry Ave., Tucson, AZ 85719, USA

⁹⁹ Department of Physics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

¹⁰⁰ School of Astronomy and Space Science, Nanjing University, Nanjing 210023, People's Republic of China

¹⁰¹ Key Laboratory of Modern Astronomy and Astrophysics, Nanjing University, Nanjing 210023, People's Republic of China

¹⁰² Italian ALMA Regional Centre, INAF-Istituto di Radioastronomia, Via P. Gobetti 101, I-40129 Bologna, Italy

¹⁰³ Department of Physics, National Taiwan University, No.1, Sect. 4, Roosevelt Rd., Taipei 10617, Taiwan, R.O.C.

¹⁰⁴ Yunnan Observatory, Chinese Academy of Sciences, 650011 Kunming, Yunnan Province, People's Republic of China

¹⁰⁵ Center for Astronomical Mega-Science, Chinese Academy of Sciences, 20A Datun Road, Chaoyang District, Beijing, 100012, People's Republic of China

¹⁰⁶ Key Laboratory for the Structure and Evolution of Celestial Objects, Chinese Academy of Sciences, 650011 Kunming, People's Republic of China

¹⁰⁷ Anton Pannekoek Institute for Astronomy, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands

¹⁰⁸ Gravitation and Astroparticle Physics Amsterdam (GRAPPA) Institute, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands

¹⁰⁹ School of Natural Sciences, Institute for Advanced Study, 1 Einstein Drive, Princeton, NJ 08540, USA

¹¹⁰ Science Support Office, Directorate of Science, European Space Research and Technology Centre (ESA/ESTEC), Keplerlaan 1, 2201 AZ Noordwijk, The Netherlands

¹¹¹ Instituto de Radioastronomía Milimétrique, IRAM, Avenida Divina Pastora 7, Local 20, E-18012, Granada, Spain

¹¹² National Institute of Technology, Hachinohe College, 16-1 Uwanotai, Tamonoki, Hachinohe City, Aomori 039-1192, Japan

¹¹³ South African Radio Astronomy Observatory, Observatory 7925, Cape Town, South Africa

¹¹⁴ Department of Physics, National and Kapodistrian University of Athens, Panepistimiopolis, GR 15783 Zografos, Greece

¹¹⁵ Villanova University, Mendel Science Center Rm. 263B, 800 E Lancaster Ave, Villanova PA 19085, USA

¹¹⁶ Physics Department, Washington University CB 1105, St Louis, MO 63130, USA

¹¹⁷ Sejong University, Seoul, Republic of Korea

¹¹⁸ EACOA Fellow, Institute of Astronomy and Astrophysics, Academia Sinica, 11F of Astronomy-Mathematics Building, AS/NTU No. 1, Sec. 4, Roosevelt Rd, Taipei 10617, Taiwan, R.O.C.

¹¹⁹ Canadian Institute for Theoretical Astrophysics, University of Toronto, 60 St. George Street, Toronto, ON, M5S 3H8, Canada

¹²⁰ Dunlap Institute for Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON, M5S 3H4, Canada

¹²¹ Canadian Institute for Advanced Research, 180 Dundas St West, Toronto, ON, M5G 1Z8, Canada

¹²² Radio Astronomy Laboratory, University of California, Berkeley, CA 94720, USA

¹²³ Department of Physics, University College Cork, Kane Building, College Road, Cork T12 K8AF, Ireland

¹²⁴ Department of Physics, National Taiwan Normal University, No. 88, Sec. 4, Tingzhou Rd., Taipei 116, Taiwan, R.O.C.

¹²⁵ Center of Astronomy and Gravitation, National Taiwan Normal University, No. 88, Sec.4, Tingzhou Road, Taipei 116, Taiwan, R.O.C.

¹²⁶ Gemini Observatory, 670 N. A'ohoku Place, Hilo, HI 96720, USA

¹²⁷ Frankfurt Institute for Advanced Studies, Ruth-Moufang-Strasse 1, D-60438 Frankfurt, Germany

¹²⁸ School of Mathematics, Trinity College, Dublin 2, Ireland

¹²⁹ Department of Astrophysical Sciences, Peyton Hall, Princeton University, Princeton, NJ 08544, USA

¹³⁰ Hiroshima Astrophysical Science Center, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8526, Japan

¹³¹ Aalto University Department of Electronics and Nanoengineering, PL 15500, FI-00076 Aalto, Finland

¹³² Department of Astronomy, Yonsei University, Yonsei-ro 50, Seodaemun-gu, 03722 Seoul, Republic of Korea

¹³³ Department of Physics and Astronomy, Texas Tech University, Lubbock, Texas 79409-1051, USA

¹³⁴ Netherlands Organisation for Scientific Research (NWO), Postbus 93138, 2509 AC Den Haag, The Netherlands

¹³⁵ Department of Physics and Astronomy, Seoul National University, Gwanak-gu, Seoul 08826, Republic of Korea

¹³⁶ University of New Mexico, Department of Physics and Astronomy, Albuquerque, NM 87131, USA

¹³⁷ Jeremiah Horrocks Institute, University of Central Lancashire, Preston PR1 2HE, UK

¹³⁸ Physics Department, Brandeis University, 415 South Street, Waltham, MA 02453, USA

¹³⁹ Tuorla Observatory, Department of Physics and Astronomy, University of Turku, Finland

¹⁴⁰ Radboud Excellence Fellow of Radboud University, Nijmegen, The Netherlands

¹⁴¹ Princeton Gravity Initiative, Princeton University, Princeton, New Jersey 08544, USA

¹⁴² School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, People's Republic of China

¹⁴³ Mullard Space Science Laboratory, University College London, Holmbury St. Mary, Dorking, Surrey, RH5 6NT, UK

¹⁴⁴ School of Astronomy and Space Sciences, University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, People's Republic of China
¹⁴⁵ Astronomy Department, University of Science and Technology of China, Hefei 230026, People's Republic of China

¹⁴⁶ Bard College, 30 Campus Road, Annandale-on-Hudson, NY 12504, USA

Received 2022 March 8; revised 2022 June 17; accepted 2022 June 17; published 2022 August 2

## Abstract

The blazar J1924–2914 is a primary Event Horizon Telescope (EHT) calibrator for the Galactic center’s black hole Sagittarius A*. Here we present the first total and linearly polarized intensity images of this source obtained with the unprecedented 20 µas resolution of the EHT. J1924–2914 is a very compact flat-spectrum radio source with strong optical variability and polarization. In April 2017 the source was observed quasi-simultaneously with the EHT (April 5–11), the Global Millimeter VLBI Array (April 3), and the Very Long Baseline Array (April 28), giving a novel view of the source at four observing frequencies, 230, 86, 8.7, and 2.3 GHz. These observations probe jet properties from the subparsec to 100 pc scales. We combine the multifrequency images of J1924–2914 to study the source morphology. We find that the jet exhibits a characteristic bending, with a gradual clockwise rotation of the jet projected position angle of about 90° between 2.3 and 230 GHz. Linearly polarized intensity images of J1924–2914 with the extremely fine resolution of the EHT provide evidence for ordered toroidal magnetic fields in the blazar compact core.

*Unified Astronomy Thesaurus concepts: Active galactic nuclei (16); Active galaxies (17); Blazars (164); Jets (870); High energy astrophysics (739); Very long baseline interferometry (1769); Radio interferometry (1346)*

## 1. Introduction

The radio source J1924–2914 (PKS 1921–293, OV–236) is a radio-loud quasar at a redshift $z = 0.353$ (Wills & Wills 1981; Jones et al. 2009). The source exhibits strong optical variability and is highly polarized (Wills & Wills 1981; Pica et al. 1988; Worrall & Wilkes 1990). While it is extremely compact at long radio wavelengths, very long baseline interferometry (VLBI) observations at centimeter wavelengths were able to resolve a persistent core–jet structure elongated in a northern direction (e.g., Preston et al. 1989; Shen et al. 1997; Tingay et al. 1998; Kellermann et al. 1998). The source is a part of the 15 GHz Monitoring Of Jets in Active galactic nuclei with VLBA Experiments (MOJAVE) source sample<fnref n="147" /> and shows a prominent 10 mas scale jet (see Lister et al. 2018). Imaging and Gaussian-component model fitting of observations at frequencies between 5 and 43 GHz conducted between 1994 and 2000 indicated a sharp bend of the inner jet from northeast to north with increasing frequency (Shen et al. 1999, 2002). Motions of individual components across multiple years were observed further downstream in the jet, but not yet in the VLBI core region on submilliarcsecond scales.

Early 230 GHz observations with the prototype Event Horizon Telescope (EHT) at three geographical sites (Hawai'i, California, and Arizona) provided a first model of the resolved structure in the inner jet of J1924–2914 via model fitting of amplitudes and closure phases (Lu et al. 2012). The individual components are extended in a direction consistent with the millimeter-wavelength inner jet morphology. However, without (quasi-)simultaneous multifrequency observations, these observations alone cannot link the compact millimeter structures to the large-scale centimeter jet. Furthermore, with a very limited $(u,v)$ coverage, these observations were unable to reconstruct an image of the source and track its detailed time variability.

Recently, the highly sensitive Atacama Large Millimeter/ submillimeter Array (ALMA) was equipped for millimeter VLBI via the ALMA Phasing Project (APP; Matthews et al. 2018; Goddi et al. 2019). In 2017, ALMA participated in its first VLBI science campaign jointly with the Global Millimeter VLBI Array (GMVA) at 86 GHz and the EHT at 230 GHz. In addition to its sensitivity, ALMA provides valuable north–south baselines to the predominantly east–west geometry of the GMVA. These observations enabled a first image of J1924–2914 at 86 GHz (project code MB007; Issaoun et al. 2019). With participation of ALMA at 230 GHz, the EHT Collaboration imaged the horizon-scale emission of M87* (EHTC et al. 2019a, 2019b, 2019c, 2019d, 2019e, 2019f), as well as central regions of the blazar 3C 279 (Kim et al. 2020) and the radio galaxy Cen A (Janssen et al. 2021). The first EHT millimeter images of linearly polarized emission in M87* were published recently (EHTC et al. 2021a, 2021b). In this paper, we present the first total-intensity and linear-polarization images of J1924–2914 at 230 GHz obtained with the EHT and make comparisons to the near-contemporaneous GMVA results from Issaoun et al. (2019) and Very Long Baseline Array (VLBA) observations at 2.3 and 8.7 GHz (Hunt et al. 2021).

The EHT array achieves a resolution of ~20 µas. At the J1924–2914 redshift of $z = 0.353$ (Jones et al. 2009), this corresponds to a linear scale<fnref n="148" /> of 0.1 pc or, in Schwarzschild radius units $R_S = 2GM_* / c^2$, about $10^3 (M_* / 10^9 M_\odot)^{-1} R_S$. No robust mass estimate for J1924–2914’s central black hole was found in the literature. The EHT results reported in this paper are the highest-resolution images of a blazar’s linear polarization ever obtained at millimeter wavelengths, likely probing a region within the gravitational sphere of influence of the central supermassive black hole (e.g., Kormendy & Ho 2013).

The paper is structured as follows. In Section 2, we summarize the observations and data processing. We present our total-intensity and polarimetric images in Section 3 and discuss the theoretical implications in Section 4. A summary is given in Section 5.

<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /></figure>

<footnote n="147">¹⁴⁷ http://www.physics.purdue.edu/astro/MOJAVE/sourcepages/1921-293.shtml</footnote>

<footnote>Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.</footnote>

<footnote n="148">¹⁴⁸ For the cosmological parameters we have assumed $H_0 = 67.7$ km s⁻¹ Mpc⁻¹, $\Omega_m = 0.307$, and $\Omega_\Lambda = 0.693$ (Wright 2006; Planck Collaboration et al. 2016).</footnote>
<figure><img src="image_4.png" /><figcaption>**Figure 1.** EHT (u, v) coverage on 2017 April 5, 6, 7, 10, and 11 (from left to right) for J1924–2914. Each colored point corresponds to a single VLBI scan of ~5 min. The 2017 April 10 observations only consisted of two consecutive scans. In Chile, ALMA participated in the observations on 2017 April 6, 7, and 11, while APEX participated for all days. In Hawaii, the SMA and JCMT both participated for all observing days. Dashed circles indicate fringe spacings characterizing the instrumental resolution of 50 µas and 25 µas. “Chile” denotes stations ALMA and APEX. “Hawaii” denotes stations SMA and JCMT.</figcaption></figure>

## 2. Observations and Data Processing

### 2.1. 230 GHz EHT

Observations of J1924–2914 were carried out by the EHT on 2017 April 5, 6, 7, 10, and 11, interleaved among observations of Sagittarius A* (EHTC et al. 2022a), for which J1924–2914 was used as an active galactic nucleus (AGN) calibrator source, along with the blazar NRAO 530 (S. Jorstad et al. 2022, in preparation). Eight stations at six geographic sites took part in the observations: ALMA and the Atacama Pathfinder Experiment (APEX) telescope in Chile; the Large Millimeter Telescope Alfonso Serrano (LMT) in Mexico; the IRAM 30 m telescope (PV) in Spain; the Submillimeter Telescope (SMT) in Arizona; the James Clerk Maxwell Telescope (JCMT) and the Submillimeter Array (SMA) in Hawaii; and the South Pole Telescope (SPT) in Antarctica.

The signals were recorded onto Mark6 recorders at a rate of 32 Gbps in two ~2 GHz subbands centered at 227.1 and 229.1 GHz (hereafter low and high bands, respectively), using dual right-hand and left-hand circularly polarized feeds (RCP ad LCP, respectively) for all stations except ALMA and JCMT. ALMA recorded dual linear polarization, which was subsequently converted at the correlation stage to a circular basis by PolConvert (Martí-Vidal et al. 2016; Goddi et al. 2019). The JCMT observed a single circular polarization component during the campaign (predominantly RCP for 2017 April 5 and 6 and LCP for 2017 April 7, 10, and 11). In Figure 1, we show the resulting EHT (u, v) coverage for each observing day. Good (u, v) coverage on 2017 April 5–7 and 11 facilitated a detailed VLBI imaging of the source at 230 GHz. Due to the very sparse snapshot coverage on 2017 April 10 and the static properties of the source on short timescales (see Section 3), observations on 2017 April 10 were combined with those of 2017 April 11 for analysis.

After observation, the data were shipped to the MIT Haystack Observatory and the Max-Planck-Institut für Radioastronomie in Bonn for correlation, see EHTC et al. (2019b) for details. The resulting data were calibrated using two separate VLBI data reduction pipelines (Blackburn et al. 2019; Janssen et al. 2019) to ensure robustness of the results. Their consistency has been studied in detail in EHTC et al. (2019c), and an example of cross-pipeline comparisons is presented in Appendix A. For the science results presented in this paper we use the EHT-HOPS pathway (Blackburn et al. 2019; EHTC et al. 2019c) complemented by updated postprocessing (most notably with revised a priori flux density

<table><caption>**Table 1**

Leakage Calibration D-terms Assumed For Stations Without a Co-Located Site</caption><thead><tr><td>Station</td><td>D<sub>R</sub>(%)</td><td>D<sub>L</sub>(%)</td></tr></thead><tbody><tr><td>LMT</td><td>2.5 + 3.5i</td><td>- 1.0 + 1.5i</td></tr><tr><td>SMT</td><td>2.8 + 9.0i</td><td>- 3.5 + 10.0i</td></tr><tr><td>PV</td><td>- 13.0 + 3.5i</td><td>15.0 + 0.0i</td></tr></tbody></table>

**Note.** Constraints on SPT D-terms are discussed in Appendix B.

calibration; EHTC et al. 2022b). For further information concerning the observations, data collection, processing, and validation, see EHTC et al. (2019b, 2019c).

The polarimetric calibration follows the procedures described in EHTC et al. (2021a). Similarly to the M87* polarimetric analysis, JCMT has been flagged from the data for polarimetric imaging of J1924–2914 due to its single polarization configuration. This has no effect on the (u, v) coverage as all baselines to Hawaii are fulfilled by the co-located SMA, which observed in full polarization at all times. For the polarization leakage (D-term) calibration of the stations with a co-located site (ALMA & APEX, SMA & JCMT), we used the D-terms reported in Appendix D of EHTC et al. (2021a), which were obtained through a robust multisource fit to the EHT data using `polsolve` (Martí-Vidal et al. 2021). For the remaining stations (except SPT), the values adopted are derived based on the results reported in Appendix E of EHTC et al. (2021a) and are presented in Table 1. The SPT D-terms were fitted as part of analysis presented in this paper. A consistency test of the assumed leakage coefficients and constraints on the SPT D-terms are given in Appendix B.

Detections were obtained for J1924–2914 on all participating baselines of the EHT for all observing days. In Figure 2, we show an example of the signal-to-noise ratio (S/N) and correlated flux density on our EHT baselines for 2017 April 7 (low band), which corresponds to the observing day with the best (u,v) coverage. The baselines to ALMA provide extremely high S/N of several hundreds for data averaged in 5 min intervals, the corresponding APEX baselines offer a S/N about an order of magnitude lower. The data shown in the bottom panel of Figure 2 have been calibrated using a priori calibration information (system temperatures, antenna gains and opacities) provided for the telescopes. The consistency of measurements on the primary (to the sensitive ALMA or SMA) and redundant (to APEX or JCMT, co-located with ALMA and SMA, respectively) baselines verifies the 10%
<figure><img src="image_5.png" /><figcaption>**Figure 2.** Top: S/N for the EHT low-band observations of J1924–2914 on 2017 April 7, as a function of projected baseline length. Baselines are color-coded following Figure 1. The circle (diamond) markers denote primary (redundant) baselines. Bottom: Complementary plot for the visibility amplitudes after a priori calibration, in units of Jansky.</figcaption></figure>

accuracy of the flux density calibration and indicates a good self-consistency of the data set. A network calibration procedure was additionally applied to obtain the final data set (Blackburn et al. 2019), further improving gain calibration of sites with a co-located station by assuming a total compact flux density provided by ALMA (Goddi et al. 2021).

## 2.2. 86 GHz GMVA+ALMA

Observations of J1924–2914 at 86 GHz (λ3.5 mm) were obtained with the GMVA+ALMA on 2017 April 3 in conjunction with observations of Sagittarius A* published in Issaoun et al. (2019). The array was composed of eight VLBA antennas, the Green Bank Telescope, the Yebes 40 m telescope, the IRAM 30 m telescope, the Effelsberg 100 m telescope, and ALMA. The data were recorded with a bandwidth of 256 MHz at a data rate of 4 Gbps over a 12 h track, of which 8 h included ALMA. The total recorded time on J1924–2914 was about 2 hr. In the left panel of Figure 3 we show the (u, v) coverage of these observations. These observations yield images with a beam size of (122 × 88) µas at 36°. The data reduction, processing, and imaging followed a similar pathway to the EHT data, and are described in more detail in Issaoun et al. (2019). Analysis of this data set was challenging because of the large uncertainties in the amplitude gain calibration and low phase stability of the complex visibilities. The 86 GHz image of J1924–2914 presented in this work was reconstructed with the *eht-imaging* library using only closure quantities (Chael et al. 2016, 2018) to overcome the calibration problems and was originally published in Issaoun et al. (2019). Linear-polarization imaging at 86 GHz did not yield robust results that could be interpreted confidently.

<figure><img src="image_6.png" /><figcaption>**Figure 3.** Left: The (u,v) coverage of the 86 GHz observations on 2017 April 3, with the GMVA+ALMA. Right: The (u,v) coverage of the VLBA observations at 8.7 and 2.3 GHz.</figcaption></figure>

## 2.3. 2.3 and 8.7 GHz VLBA

Observations of J1924–2914 at 2.3 and 8.7 GHz were carried out as part of the International Celestial Reference Frame survey with the VLBA (Hunt et al. 2021). The observations were executed in astrometric and geodetic modes, thus providing high positional accuracy. The target was observed simultaneously at the two frequencies, as is customary for geodetic observations. To reduce any variability-induced offset, we select the observation that is closest in time to the EHT observations reported here, on 2017 April 28. The target was observed by all 10 stations of the VLBA, where 16 intermediate frequency subbands were recorded, with 4 centered at 2.3 GHz and 12 at 8.7 GHz, for a total bandwidth of 128 and 384 MHz at the respective frequencies. In the right panel of Figure 3 we show the (u,v) coverage of these observations. Observations were recorded in right-hand circular polarization mode only, at a data rate of 2 Gbps. For further information on observation and data calibration, refer to Hunt et al. (2021). The calibrated data were imaged using the CLEAN algorithm implemented in the DIFMAP software package (Shepherd 1997, 2011). The beam sizes are (9.58 × 3.58)mas at −5° and (2.45 × 0.94)mas at −3° for the 2.3 and 8.7 GHz observations, respectively. We iterated the reconstruction process using a hybrid imaging loop, consisting of CLEAN and a phase self-calibration cycle, with a stopping criterion of obtaining three times the noise floor of the residual image. The final images are presented in Section 4.1 as part of the multifrequency analysis.

# 3. EHT Image Analysis Results

## 3.1. Total Intensity

The total-intensity analysis was performed on four individual observing epochs, 2017 April 5, 6, 7, and 10+11. The three imaging software packages used for the analysis of the EHT observations of M87* (EHTC et al. 2019d) were employed to reconstruct total-intensity images of J1924–2914: the regularized maximum likelihood (RML) software *eht-imaging* (Chael et al. 2016, 2018) and *SMILI* (Akiyama et al. 2017b, 2017a); and the CLEAN algorithm implemented in the DIFMAP software package (Shepherd 1997, 2011). Following the development of posterior-exploration techniques for the M87* polarization results (EHTC et al. 2021a), we utilized two Markov chain Monte Carlo framework algorithms in addition to the imaging methods: DMC (Pesce 2021) and Themis (Broderick et al. 2020a, 2020b). The reconstructions typically combine both low- and high-band data sets, given the very
<figure><img src="image_7.png" /><figcaption>**Figure 4.** Representative images of J1924–2914 from the 2017 April 7 EHT observations produced using DIFMAP, eht-imaging, and SMILI, and the mean posterior images from DMC and Themis. To simplify visual comparisons and display the images at similar resolutions, the images are restored with circular Gaussian beams of various sizes (due to varying intrinsic levels of superresolution across softwares) for an effective resolution matching the EHT beam of 20 µas.</figcaption></figure>

small fractional bandwidth difference and high inter-band consistency reported in EHTC et al. (2019c) and EHTC et al. (2021a).

The total-intensity structure of J1924–2914 at 230 GHz is very resilient to various user-based choices in the imaging process, leading to an easily recoverable three-component structure shown in Figures 4 and 5. While the reconstructed source morphology appears robust, the total compact flux density within the 200 µas field of view and in the three components is more ambiguous. An upper limit is provided by the simultaneous connected-element interferometric-ALMA measurements reported in Goddi et al. (2021), that is around 3.2 Jy, with small day-to-day variations below 0.1 Jy, within the calibration uncertainties. Different analysis pipelines recover anything between 2.0 and 3.2 Jy within the 200 µas field of view. Furthermore, the algorithms differ in their detailed approach to the image reconstruction. As an example, SMILI favors image sparsity, keeping brightness in a compact substructures, while DMC does not encourage sparsity in any way, possibly allowing for more flux density to be distributed throughout the field of view as a dynamic range-limited noise floor. Additionally RML methods typically assume compact imaging priors, discouraging emission further away from the core. For these reasons in Figure 4 SMILI and DMC have similar total brightness, but the main three-component structure appears significantly dimmer in the DMC reconstruction. Furthermore, the total compact flux density ambiguity is a particularly severe problem for the EHT array, which for the observations of J1924–2914 has no baselines in the range between 2 Mλ and 0.6 Gλ, a single SMT–LMT baseline in the range 0.6-1.5 Gλ and no coverage between 1.5 and 2.8 Gλ. Hence, constraining structures larger than ~100 µas is extremely challenging with EHT data.

Monitoring by the SMA<fnref n="149" /> shows that the total compact flux density at 1.3 mm remained in the 3.2 ± 1.0 Jy range since 2013 until the end of 2021; hence the EHT 2017 observations should correspond to a representative state of the source in this low luminosity period. In early 2009 the source went through a flaring phase, when the total flux density went up to about 10 Jy. The proto-EHT VLBI results reported by Lu et al. (2012) correspond to this period. Interestingly, while there is much more flux density in the 2009 data set on short baselines (about 6 Jy at 0.6 Gλ), the 2009 and 2017 data sets show a nearly consistent correlated flux of ~1 Jy on the shared Hawaii–SMT

baseline (3-3.5 Gλ in both epochs). This suggests that the 2009 flare event could be related to a more extended region, possibly further downstream from the 1.3 mm VLBI core region.

In Table 2, we show the reduced $\chi^2$ calculated for the low-band data sets averaged in 120 s bins, as a metric of the fit quality to closure quantities (closure phases—$\chi^2_{CP}$, log closure amplitudes—$\chi^2_{LCA}$; Thompson et al. 2017; Blackburn et al. 2020) and visibility amplitudes ($\chi^2_{AMP}$) for the final representative (or “fiducial”) images from all methods and all observing days. The best reconstructions from the imaging methods based on least-squares fitting to closure quantities and the mean images from the posterior-exploration methods were chosen as the fiducial images. The eht-imaging and DMC models exhibit the best values in the $\chi^2$ metric with consistently good performance for all days, and hence we focus on those two software packages in the subsequent quantitative analysis. In Figure 4, we show the fiducial images for all methods for the 2017 April 7 observations, restored to a resolution of 20 µas. In Figure 5, we show the method-averaged images across our four observing epochs (2017 April 10 and 11 are combined). The method-averaging procedure reduces the impact of method-specific systematics and provides a more conservative image-domain representation of the source, highlighting image features consistently reconstructed across different algorithms. However, the averaged image may fit the visibility-domain observations to a lesser degree than the individual reconstructions, and hence more quantitative studies typically rely on the analysis of individual pipelines (e.g., EHTC et al. 2019d; Kim et al. 2020; EHTC et al. 2021a). The stability and robustness of the J1924–2914 image and derived amplitude gains were also confirmed in EHTC et al. (2022b) for the purpose of the calibrator gain transfer for the imaging of Sgr A* (EHTC et al. 2022c). We verified that imaging merged data sets from separate days generally leads to a decrease in the fit quality, which justifies the choice to analyze observing days separately.

The total-intensity structure of J1924–2914 is very stable across the duration of the EHT 2017 campaign. Examples of this consistency are shown in Figure 6, where we plot closure phases (Thompson et al. 2017; Blackburn et al. 2020) from the EHT observations of J1924–2914 on two triangles along with the fits obtained by the eht-imaging pipeline for different observing days. In particular, the left panel of Figure 6 presents closure phases on the sensitive ALMA–LMT–SMA triangle, showing good agreement of the models obtained for 2017 April 6, 7, and 11. The SMA–SMT–SPT closure phases (middle

<footnote n="149">¹⁴⁹ http://sma1.sma.hawaii.edu/callist/callist.html?plot = 1924-292</footnote>
<figure><img src="image_8.png" /><figcaption>**Figure 5.** Method-average images of J1924–2914 from the 2017 EHT observations. The results of three imaging methods (eht-imaging, SMILI, DIFMAP) and two posterior-exploration methods (DMC and Themis) were averaged for each of the four observing epochs. The lowest contour corresponds to 10% of the peak intensity, with increasing contours in steps of 10%. The CLEAN nominal beam of 20 µ as FWHM is shown as a representative resolution of the average images, hereafter referred to as the EHT beam.</figcaption></figure>

panel of Figure 6) are consistent in the first part of the track, but about GMST = 4 h the models diverge, with 2017 April 5 and 10–11 indicating a rapid closure phase growth, and 2017 April 6 and 7 a rapid decrease in the closure phase. After GMST = 5 h, the models are consistent again, as the phase is wrapping with a 360° period. There is some evidence for structural evolution between 2017 April 5–7 and April 10–11; however, such phase degeneracies on triangles involving long baselines can be caused by small structural changes in the image domain, such as single microarcsecond-scale relative motion of the components (Kim et al. 2020). We quantify the image structure evolution in Section 3.4. Furthermore, we can track down the degeneracy seen in the middle panel of Figure 6 to the absolute phase ambiguity seen on baselines between SPT and SMT/LMT/Hawaii. In Figure 7 we show that the same degeneracy can be seen on a single day between our five imaging pipelines, all fitting the available data well and resulting in very similar models, e.g., eht-imaging and DMC images seen in Figure 4.

## 3.2. Linear Polarization

Due to the high consistency between all five methods in the total-intensity imaging, we employed one RML imaging method (eht-imaging) and one posterior-exploration method (DMC) exhibiting particularly good values of $\chi^2$ (see Table 2) to streamline the polarimetric imaging and analysis. Both software packages have been extensively tested, including their performance on polarimetric reconstructions of synthetic images (see Appendix J of EHTC et al. 2021a). We focus on the three observing days that include the sensitive ALMA array (2017 April 6, 7, and 11). Additionally, the presence of ALMA in the array enables a straightforward calibration of the absolute electric vector position angle (EVPA). In the right panel of Figure 6 we demonstrate the consistency of the RML models with the polarimetric data. We are using the absolute value of the Fourier-domain fractional polarization $\tilde{m}$ (Johnson et al. 2015),

$$ \tilde{m} = \frac{\hat{Q} + i \hat{U}}{\hat{I}} \qquad (1) $$

on the very sensitive ALMA–LMT baseline, where $\hat{I}$, $\hat{Q}$, and $\hat{U}$ are Fourier-domain Stokes components of the radiation field. Given the rotation measure value of $\sim 4 \times 10^4$ rad m$^{-2}$

reported in Goddi et al. (2021), we expect that Faraday rotation effects do not affect the observed EVPA by more than 5 deg at the observing frequency of 230 GHz.

In Figure 8, we show the fiducial polarimetric images of J1924–2914 for the three days with ALMA and two analysis pipelines. The linearly polarized emission is localized in the VLBI core (the brightest and southernmost component C0; see Section 3.4) and inbetween the second and third total-intensity components along the jet direction. In these two regions, the resolved image-domain fractional polarization reaches $\sim 20\%$. While the EVPAs seen in the outer jet components are mainly aligned parallel to the jet axis, the EVPA pattern in the core region rotates in a fan-like pattern, causing depolarization in the image-integrated results. These features are persistent for all observing days and across methods.

We can characterize the image-integrated linear polarization (over a 200 µas field of view) with the following metrics. First, the intensity-weighted average polarization fraction across the resolved EHT image (we blur models with a 15 µas circular Gaussian beam) is given by

$$ \langle|m|\rangle = \frac{\sum_k \sqrt{Q_k^2 + U_k^2}}{\sum_k I_k} = \frac{\sum_k P_k}{\sum_k I_k}. \qquad (2) $$

Here $I$, $Q$, and $U$ are the image-domain Stokes parameters, and the sums are taken over all pixels in the image. In the first panel of Figure 9 we show $\langle|m|\rangle$ across observing days and imaging pipelines to be about 20%–30%. In Figure 8 we see that the largest contribution to $\langle|m|\rangle$ comes from the core region.

A second metric is the coherently averaged polarization fraction $m_{net}$, representing the unresolved fractional polarization in the 200 µas field of view,

$$ m_{net} = \frac{\sum_k Q_k + i \sum_k U_k}{\sum_k I_k}. \qquad (3) $$

In the middle and bottom panels of Figure 9 we show the absolute values $|m|_{net}$ and EVPAs of $m_{net}$ at about 6% and $-50$ deg, respectively. Comparing these results with the ALMA measurements reported by Goddi et al. (2021) we find overall good consistency, in particular with the DMC pipeline. This indicates that the polarized emission unresolved by ALMA with $\sim$ arcsecond resolution is mostly confined to the narrow field of view of the EHT. The large difference between
<table><caption>**Table 2**

Reduced $\chi^2$ Values on Closure Quantities and Visibility Amplitudes After Self-calibrating to the Stokes *I* Images</caption><thead><tr><th>Date</th><th>Data Product</th><th>DIFMAP</th><th>eht-imaging</th><th>SMILI</th><th>DMC</th><th>Themis</th></tr></thead><tbody><tr><td rowspan="3">2017 April 5</td><td>$\chi^2_{AMP}$</td><td>0.346</td><td>0.343</td><td>0.551</td><td>0.342</td><td>0.485</td></tr><tr><td>$\chi^2_{CP}$</td><td>1.211</td><td>1.087</td><td>1.338</td><td>1.802</td><td>1.264</td></tr><tr><td>$\chi^2_{logCA}$</td><td>1.009</td><td>0.838</td><td>1.702</td><td>2.539</td><td>1.377</td></tr><tr><td rowspan="3">2017 April 6</td><td>$\chi^2_{AMP}$</td><td>1.226</td><td>0.579</td><td>2.13</td><td>0.791</td><td>1.143</td></tr><tr><td>$\chi^2_{CP}$</td><td>1.850</td><td>0.910</td><td>0.935</td><td>1.074</td><td>1.350</td></tr><tr><td>$\chi^2_{logCA}$</td><td>2.128</td><td>0.978</td><td>3.901</td><td>1.337</td><td>2.026</td></tr><tr><td rowspan="3">2017 April 7</td><td>$\chi^2_{AMP}$</td><td>1.018</td><td>0.663</td><td>1.00</td><td>0.545</td><td>1.115</td></tr><tr><td>$\chi^2_{CP}$</td><td>2.013</td><td>0.674</td><td>2.912</td><td>0.828</td><td>2.024</td></tr><tr><td>$\chi^2_{logCA}$</td><td>1.983</td><td>1.191</td><td>1.791</td><td>1.286</td><td>2.031</td></tr><tr><td rowspan="3">2017 April 10+11</td><td>$\chi^2_{AMP}$</td><td>1.994</td><td>1.171</td><td>1.111</td><td>0.914</td><td>1.671</td></tr><tr><td>$\chi^2_{CP}$</td><td>2.895</td><td>1.123</td><td>1.437</td><td>1.211</td><td>3.592</td></tr><tr><td>$\chi^2_{logCA}$</td><td>3.806</td><td>1.700</td><td>1.907</td><td>1.708</td><td>3.134</td></tr></tbody></table>

**Note.** Reduced $\chi^2$ are calculated using a total error budget containing thermal noise plus an additional complex systematic error corresponding to 2% of the observed visibility amplitude.

$|m|_{net}$ and $\langle|m|\rangle$ is related to the large EVPA variation in the image, as seen in the core component in Figure 8.

### 3.3. Circular Polarization

As DMC is a posterior-exploration code performing full-Stokes modeling (Pesce 2021), we can use the recovered posterior distributions to determine whether the 230 GHz images contain statistically significant detections of circular polarization. Moreover, in contrast to other analysis methods that we consider, DMC explores relative R/L complex polarimetric station gains as parameters of the fitted image, thus providing more robustness against systematic uncertainties in the polarimetric a priori flux density calibration. We measure the detection confidence in the resolved image as the ratio between the local mean posterior and the local posterior standard deviation of the estimated circular polarization, evaluated based on 1000 images drawn from the posterior distribution. Our confidence does not exceed $2\sigma$ at any location in the image on any observing day. The distribution of net (image-averaged) circular polarization is also consistent with zero, in agreement with the findings of Goddi et al. (2021). For comparison, the same procedure determines the confidence in the source structure corresponding to over $30\sigma$ when applied to Stokes *I* images, and about $10\sigma$ when applied to linear-polarization images.

### 3.4. Image Components Feature Extraction

In Figure 10 we show a diagram of the different components in total intensity and linear polarization on which image-domain-based feature extraction was performed across observing days and methods. We identify the brightest total-intensity component at the south-eastern end of the jet as the VLBI core C0, following the image morphology at lower frequencies, and the other total-intensity features as the first jet component C1, and the second jet component C2. The components showing the highest linear polarization are P0 in the core region and the jet component P1; the latter is located between C1 and C2.

In case of DMC, similarly as in Section 3.3, we consider 1000 images drawn from the posterior distribution. For each image,

we perform an image-domain brightness maxima search, identifying them with the maxima of components indicated in Figure 10. We then define binary masks around each extremum to compute the total flux density corresponding to each component (Figure 11), and the positions of the flux density centroids (Figure 12). The error bars reflect the 68% confidence intervals of individual measured quantities extracted from DMC posteriors. DMC enables parameter extraction for all epochs, apart from EVPA measurements on April 5, which is the day without ALMA participation and hence lacks the absolute EVPA calibration. Additionally we show a similar measurement obtained from a single eht-imaging reconstruction per day (markers without the error bars in Figures 11–12). The total-intensity eht-imaging results are available for all epochs, while polarization results are only available for the days with ALMA.

In Figure 11, we present the total-intensity and polarization properties of the components identified in Figure 10 across the four observing days. We show the variation in the total flux density, linear-polarization flux density, and EVPA integrated over each component across the EHT observing campaign extracted from the eht-imaging and DMC imaging results. The southernmost component C0 has the highest total flux density and is assumed to be the 230 GHz VLBI core. For the component-integrated EVPA, we also compare the results with the image-integrated EVPA measured from simultaneous interferometric-ALMA observations in Goddi et al. (2021). We notice a bias between component flux densities identified with eht-imaging and DMC, with the former returning values larger by about 25% for C0 and C1 components. We attribute the effect to imaging algorithm systematics, particularly to sparsity-based regularization employed for the eht-imaging reconstructions (see the discussion in Section 3.1). Given the associated uncertainties, there are no strong indications of the time evolution of the component flux density on the timescale of our EHT observations. The core component C0 is about 2 times brighter than C1 and C2, the latter two showing similar flux densities. While P0 has a higher polarized flux density than P1, the EVPA varies by about 90 deg across the compact P0 core component, consistently between days and
<figure><img src="image_9.png" /><figcaption>**Figure 6.** Consistency between observations and the RML images obtained with eht-imaging (continuous lines). Left: Closure phases on the sensitive ALMA–LMT–SMA triangle, exhibiting large variation related to the evolution of the triangle geometry during the Earth’s rotation. Middle: Closure phases on the very extended SMA–SMT–SPT triangle. A degeneracy between models fitted to different days can be observed, with hints of the structural evolution between days. Right: Fractional Fourier polarization (Equation (1)) on the sensitive ALMA–LMT baseline. The errors are dominated by the systematic uncertainty corresponding to 2% of the Stokes *I* visibility.</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>**Figure 7.** Comparison of observed closure phases on the LMT–SPT–APEX triangle on 2017 April 7 with predictions from the models shown in Figure 4. The observations taken after GMST = 3 are shown twice, with a 360 deg phase shift.</figcaption></figure>

methods (see Figure 8), adding destructively in Figure 11. When we add absolute values of the linear polarization instead of coherently adding complex numbers, we find about 0.1 Jy in the *P0* region for images blurred to a 15 µas resolution. There is also a notable EVPA rotation trend observed in both the *P0* and *P1* components and not observed in the ALMA-only data (bottom panel of Figure 11). While this feature is not very statistically significant and may be a statistical fluke, it may also indicate some systematic VLBI calibration bias. However, the bias in the absolute EVPA calibration, which follows the ALMA QA2 calibration (Goddi et al. 2021), would be expected to impact all EHT sources in a similar fashion, and an opposite trend in EVPA was found for M87* (EHTC et al. 2021a). As

the net EVPA of VLBI images is consistent with the ALMA- only measurements (at least for the DMC images; see Figure 9), this implies that the EVPA shift of the components is compensated by the change in the residual net EVPA within the field of view. Hence, if the effect is systematic, it appears to be related to the imaging or parameter extraction algorithms, rather than to the data calibration. In any case, we conclude that a < 20 deg consistency between the ALMA-only data and the sum of the VLBI components is overall reassuring and constrains the contribution from the systematic errors.

In Figure 12, we present the relative distance of the individual total-intensity and polarization component centroids from the core *C0* across the EHT observing campaign. There is no systematic offset between centroids of *C0* and *P0*, indicating that most likely they correspond to the same physical core component. However, the peak brightness location of *P0* is shifted to the east with respect to the peak brightness of *C0* (see also the discussion in Section 4.3). We see no significant motion of the components between 2017 April 5 and 11, particularly *C1* is well constrained and on all days and for both pipelines its distance from the core remains consistent within 2 µas. For J1924–2914, the observed motion of 1 µas/day corresponds to an apparent velocity of 8c, which translates to an upper limit on apparent velocity $\beta_{app}(C1) < 2.7$ c. Kinematic analysis at 15 GHz (Lister et al. 2019) resulted in apparent velocities of three features, yielding $\beta = 7$ c at a distance of 5 mas from the core, and two features on the submilliarcsecond scale, moving with $\beta = 2.6$ c and $\beta = 0.2$ c. While a direct comparison of the apparent velocities seen at 15 and 230 GHz is difficult in view of the bent jet morphology and different regions being probed, let us engage in some plausible speculation about this. The wider range of apparent velocity estimated in the innermost region may suggest jet bending and a smaller jet inclination of the innermost region (bending away from the line of sight). In this regime, $\beta_{app} \approx \theta/(1 - \beta)$ and thus small intrinsic variations of $\theta$ can result in relatively large variations of the apparent velocity. At present, the physical origin of the relative large variation of the component speeds along the jet is unclear. It could be due to component motion
<figure><img src="image_11.png" /><figcaption>**Figure 8.** Fiducial polarimetric images of J1924–2914 produced by the RML imaging method eht-imaging and the posterior-exploration method DMC. The results are shown for the three J1924–2914 observation days that included ALMA. The total intensity is shown on a gray scale with black contours indicating 25, 50 and 75% of the peak total intensity. White contours indicate 25, 50, and 75% of the peak polarization intensity. The ticks show the orientation of the EVPA, their length indicates linear-polarization intensity magnitude, and their color indicates fractional linear polarization. Cuts were made to omit all regions in the images where Stokes *I*<10% of the peak brightness and *P*<20% of the peak polarized brightness. The images are all displayed with a field of view of 128 µas, and all images are blurred with a circular Gaussian beam of 18 µas.</figcaption></figure>

along spatially bent trajectories, but intrinsic jet acceleration combined with regions of slower velocity or even stationarity (shocks) also cannot be excluded. Future more detailed kinematic studies will be required to clarify this.

We also note a peculiarity seen in Figure 12, resulting mostly from the DMC analysis: there is marginal evidence that, while component C2 separates from the core and moves downstream, the motion of the P1 centroid goes in the opposite direction, approaching the VLBI core. Whether this is due to pattern motion or is a projection effect in a rotating jet remains at this time an open question. We can only place very loose upper limits on the apparent velocities with respect to C0, $β_{app}(C2) < 13$ c, $β_{app}(P1) < 27$ c with a hint of acceleration, which may be related to the transverse shock discussed in Section 4.4, rather than to the overall acceleration pattern expected in the inner part of the ejected jet.

# 4. Discussion

## 4.1. Multifrequency Images of the Bent Jet

In Figure 13, we show multifrequency images of J1924–2914 from close in time observations in April 2017 with the VLBA (2.3 and 8.7 GHz), the GMVA+ALMA (86 GHz), and the EHT (230 GHz). Ranging two orders of magnitude in frequency, these images show jet structure spanning from subparsec to 100 parsec scales. The EHT image of J1924–2914 provides an unprecedented view of the inner parsec of this blazar.

The projected position angle (PA) of the jet gradually rotates counterclockwise with increasing distance from the jet base. In the 2.3 GHz VLBA image the PA is 50° ± 5° east of north at about 20 mas from the core and the jet bends toward the north–south direction closer to the core, consistently with the jet orientation in the nonsimultaneous 1.6 GHz image at 5–10 mas from the core (Shen et al. 1999). At 8.7 GHz we find a PA of 25° ± 5° at about 5 mas from the core, consistent with the archival VLBA monitoring results at 15 GHz, showing a persistent jet orientation at a PA of about 30° in the epochs from 1995 to 2013 at angular scales ~5 mas (Kellermann et al. 1998; Pushkarev et al. 2017). The same MOJAVE observations hint at more variability of the jet PA on the smallest resolved scales ~1 mas. Observations by Shen et al. (2002) with the VLBA between 1994 and 2000 across four frequencies (5, 12, 15, and 43 GHz) showed a consistent PA orientation of 30° at 5 GHz with a clockwise shift of about 51°–67° at 43 GHz. At 86 GHz a possible bent jet structure is seen, with the inner jet oriented with a PA of about –40° less than 0.3 mas from the core, and an apparent transition to a northeast direction further out. The –40° PA with respect to the core is consistent with the PA of the single jet component located ~400 µas from the core, imaged from 2018 April GMVA observations (see Figure 4 of Issaoun et al. 2021). 2018 images at 86 GHz do not indicate jet bending. At 230 GHz, the component C1 is located at a PA of –45° and C2 at a PA of –35° with respect to the core C0. This morphology can potentially be explained by a helical structure in the jet (Conway & Murphy 1993; Steffen et al. 1995). Such a helical jet structure
<figure><img src="image_12.png" /><figcaption>**Figure 9.** Image-averaged linear-polarimetric properties of the source. Blue points with error bars represent 68% confidence intervals from the DMC posterior distributions. Green points without error bars correspond to a single measurement from the eht-imaging images. Red points correspond to ALMA measurements from Goddi et al. (2021). For the sake of clarity a small horizontal shift has been added between the markers representing different methods within the same day.</figcaption></figure>

can be caused by an orbiting lower-mass secondary black hole around a stable primary central black hole, as also proposed for 4C 73.18 (Roos et al. 1993) and OJ 287 (e.g., Dey et al. 2021; Gómez et al. 2022), precession caused by a wobbling disk (Britzen et al. 2018), or a large-scale accretion flow that is tilted with respect to the black hole spin axis (e.g., as in M81; Martí-Vidal et al. 2011).

Alternatively, the jet could be showing a sharp bend related to a collision between the jet and a dense cloud in the external medium (e.g., as in 3C 120; Gómez et al. 2000, 2001), although the lack of clear signatures of jet disruption render this interpretation less likely. Instabilities in a relativistic jet constitute another possible origin of the bent structure. There are two main types of instabilities that can be responsible for this bending: (1) the Kelvin-Helmholtz (KH) instability; and (2) the current-driven (CD) kink instability. KH instabilities develop through the shear between two different flow components, e.g., the fast jet spine and the slow jet sheath and/or the wind and external medium (Mizuno et al. 2007; Sironi et al. 2021). The nonaxisymmetric helical mode can produce bent structures in

<figure><img src="image_13.png" /><figcaption>**Figure 10.** Schematic of the total-intensity (C0, C1, and C2) and linear-polarization (P0 and P1) components in the EHT images of J1924–2914 at 230 GHz. We show the method-average total-intensity and linear-polarization image of our best observation day, 2017 April 7. Linear-polarization contours are shown in cyan, denoting regions of 25, 50, and 75% of the peak linearly polarized intensity. Guiding contours in the total intensity are shown in white, denoting regions from 20% to 90% of the peak total intensity, in steps of 10%. The nominal EHT beam is shown as a white circle in the lower right.</figcaption></figure>

relativistic jets (Hardee 2000; Lobanov & Zensus 2001). This instability grows in the kinetic energy dominated region; therefore the region far from the jet base is a preferred site. The CD kink instability was also shown to generate helically twisted jet structures (McKinney & Blandford 2009; Mizuno et al. 2012; Davelaar et al. 2020). This instability is excited by the existence of a helical magnetic field, which is predicted by the jet formation theory and simulations (e.g., Pudritz et al. 2012), and is expected to grow in the magnetically dominated region near the jet base. The toroidal magnetic fields would create a twisted polarization pattern like the one we observe in the P0 component at the VLBI core in Figure 8.

## 4.2. Brightness Temperatures

We measure the observer frame brightness temperatures $T_B$ of the VLBI core by performing Gaussian model fitting in DIFMAP at each frequency, and estimating the core size and flux density. The results are presented in Table 3, with $T_B$ calculated as

$$T_B = 1.22 \times 10^{12} \frac{F_\nu}{\nu^2 \theta^2}, \quad (4)$$

where the units of $F_\nu$, $\nu$, and $\theta$ are as given in Table 3. Apart from that, nonsimultaneous MOJAVE data at 15 GHz give a core brightness temperature ~$10^{12}$ K in 2012, and an apparent brightness temperature in excess of $10^{12}$ K was found at 1.6 GHz (Shen et al. 1999). The reported brightness temperatures are generally lower limits if the cores are not resolved. Nevertheless, the trend of the brightness temperature decreasing with the frequency seems robust and consistent with signatures of an accelerating (sub)parsec-scale jet (Lee et al. 2016). However, this interpretation is only straightforward if the change in inclination angle in the bent jet does not cause significant changes in the Doppler factor. The 230 GHz brightness temperature is
<figure><img src="image_14.png" /><figcaption>**Figure 11.** Total-intensity and linear-polarization properties of the individual components identified in Figure 10. The different colors correspond to the different total-intensity (circles) and linear-polarization (squares) components. Points with error bars represent 68% confidence intervals from the DMC posterior distributions. Points without error bars correspond to a single measurement from the eht-imaging images. For the sake of clarity, a small horizontal shift has been added between the markers representing different methods and components within the same day.</figcaption></figure>

consistent with the visibility-domain brightness temperature limit obtained from the flux density values observed on the longest baselines (Lobanov 2015), which, in our case, reach about 8.5 Gλ, as well as with the prior estimates by Lu et al. (2012). The observed value is related to the fluid frame brightness temperature $T'_B$ via

$$T'_{B} = T_{B} \frac{1+z}{\delta} \qquad (5)$$

with a Doppler factor $\delta$ and Lorentz factor $\Gamma$

$$\delta = \frac{1}{\Gamma(1 - \beta \cos \theta)}; \quad \Gamma = (1 - \beta^2)^{-1/2} \qquad (6)$$

with velocity $\beta$ and viewing angle $\theta$. While we do not have strong limits on the jet velocity and inclination (which also varies with the angular scale as the jet is bent), Paliya et al. (2017) suggests $\Gamma = 12$ ($\beta > 0.996 c$), and it is enough that $\theta < 20$ deg and $\beta > 0.6 c$ in order to obtain $\delta > 2$. This implies that the intrinsic

<figure><img src="image_15.png" /><figcaption>**Figure 12.** Relative distance of the total-intensity (C1, C2) and linear-polarization (P0, P1) components from the VLBI core C0 across the EHT observing campaign. The component labels follow that of the schematic in Figure 10. For the sake of clarity, a small horizontal shift has been added between the markers representing different methods and components within the same day.</figcaption></figure>

brightness temperature at 230 GHz is likely lower than the equipartition temperature $T_{eq}$, $T'_B < T_{eq} = 5 \times 10^{10}$ K, indicating a magnetically dominated inner jet (Readhead 1994), likely dominated by the helical magnetic field. The brightness temperature $T'_B$ is also significantly lower than the inverse-Compton limit of $\sim 5 \times 10^{11}$ K (Kellermann & Pauliny-Toth 1969). These findings are comparable to the ones reported for 3C 279 by Kim et al. (2020) from observations in the same EHT run. Low brightness temperatures at 230 GHz were also reported for other EHT sources, Cen A (resolved at about 200 $R_S$ scale; Janssen et al. 2021) and M87* (resolved at about 3.5 $R_S$ scale; EHTC et al. 2019a).

### 4.3. Superresolved Millimeter Core

With RML-based imaging methods we may expect to achieve superresolution in regularized fitted images (Honma et al. 2014). Indeed, with eht-imaging we consistently find the C0 component as an elliptical feature of major and minor
<figure><img src="image_16.png" /><figcaption>**Figure 13.** Multifrequency images of J1924–2914 from the 2017 April observations. From left to right: the 230 GHz 2017 April 7 EHT image; the 86 GHz 2017 April 3 GMVA+ALMA image; and 8.7 and 2.3 GHz images taken on 2017 April 28 with the VLBA. The contours delimit regions from 10% to 90% of the peak brightness temperature, in steps of 10%. To make all the features visible, the EHT image and lower-frequency images have different intensity ranges. The EHT image is that of Figure 5 and follows the brightness temperature range on the left, whereas the three images at lower frequencies have the brightness temperature range of the color bar on the right. The white circles in the lower left of each panel denote the nominal instrument resolution. The dashed squares delimit the field of view of the preceding higher frequency image.</figcaption></figure>

<table><caption>**Table 3**

Properties of the VLBI Core at Each Observing Frequency From DIFMAP Gaussian-component Fitting</caption><tr><td>ν (GHz)</td><td>2.3</td><td>8.7</td><td>86.2</td><td>229.1</td></tr><tr><td>F<sub>ν</sub> (Jy)</td><td>2.2</td><td>4.3</td><td>0.4</td><td>0.5</td></tr><tr><td>θ (mas)</td><td>0.82</td><td>0.56</td><td>...</td><td>0.01</td></tr><tr><td>T<sub>B</sub> (10<sup>11</sup> K)</td><td>7.6</td><td>7.8</td><td>2.8</td><td>1.2</td></tr></table>

**Note.**

a A 15 µas resolution limit calculated using the residual map noise was used.

FWHMs equal to 15 µas and 10 µas, respectively, and a major axis PA of about 45 deg, perpendicular to the position angle of C1, which we associate with the PA of the subparsec-scale jet. Superresolved images obtained with an RML-based reconstruction method, with no subsequent blurring, are shown in Appendix A. In all images in Figure 8, the polarized component P0 appears to have a crescent-like shape around the core C0, with a large fractional polarization of about 15% and a depolarized intrusion on the west side of the core feature. Within the P0 structure, the EVPA rotates by at least 90 deg around the core, consistently across days and methods (see Figure 8). We interpret this as a signature of the presence of toroidal magnetic fields in the core (Molina et al. 2014). The inner depolarization could be a resolution effect related to the size of the beam, averaging over the spatially varying EVPA within the VLBI core region; however the depolarization toward the west requires a different explanation. It is possible that the innermost jet is launched in the western direction, and hence because the material in the jet is partially obscuring the view onto the jet base, the Faraday depth is greater on the west side of the core, causing depolarization. The western orientation of the inner jet is consistent with the trend of the bend direction seen across all angular scales. An alternative explanation is a conical shock (Lind & Blandford 1985), which can reproduce similar geometrical features in the EVPA orientation, particularly in the presence of a tangled magnetic field component (Cawthorne 2006). In this interpretation the core in our images would need to be associated with the optically thin jet plasma.

Simultaneous interferometric-ALMA observations of J1924–2914 give spectral indices of -0.5 ± 0.10 at 93 GHz, and -0.75 ± 0.10 at 220 GHz (Goddi et al. 2021). These values suggest an optically thin source, and as the emission is dominated by the core component, this could imply an

optically thin core, contrary to the standard model of a radio jet, in which the core emission corresponds to the photosphere of the optically thick region (Blandford & Königl 1979). Such optically thin emission is expected if the source is observed at a frequency higher than the synchrotron self-absorption turnover. In this case the VLBI core would appear resolved, and the polarization substructure would become observable.

## 4.4. Jet Features

The two total-intensity jet features C1 and C2 appear at PAs of -47 deg and -36 deg, respectively, with a change consistent with the direction of the jet bending. Additionally, we find a polarized component P1, located between C1 and C2. The EVPA in the P1 component is ordered and aligned in a pattern parallel to the jet. This is indicative of a transverse magnetic field component, implying a toroidal or helical magnetic field topology, and this provides a simple and natural explanation for the presence of the P1 offset from C1 and C2. It is possible that C2 is a relativistic transverse shock in the jet, which enhances the magnetic field in the plane of compression, perpendicularly to the shock propagation direction (Hughes et al. 1985). In this case, some of the polarization associated with P1 could be associated with this shock structure. The separation between the linearly polarized and total-intensity features could be a consequence of the presence of substructure within the shock, e.g., a forward and reverse shock, one being more polarized than the other (Gómez et al. 1997; Laskar et al. 2019). There is some weak indication of P1 and C2 motion in opposite directions supporting this interpretation (see Figure 12). Linear-polarization maps in 15 GHz with MOJAVE indicate that in the most upstream region the EVPA is aligned with the 230 GHz jet PA (Lister et al. 2018). This suggests a similar origin of the 15 GHz polarization features as transverse shock features in the upstream jet, unresolved at 15 GHz. Further away from the core, the 15 GHz maps show the EVPA aligning with the mas scale jet orientation, strengthening this interpretation.

## 5. Summary

In this paper, we presented the first 1.3 mm VLBI total-intensity and polarimetric images of the blazar J1924–2914 with the EHT. The EHT enabled the highest-resolution polarimetric imaging of a quasar to date, corresponding to a linear resolution of ~0.1 pc. These unprecedented images of the inner parsec of J1924–2914 reveal a compact total-intensity
structure of three distinct components oriented in a northwest direction, with a fan-like EVPA pattern in the VLBI core (the southernmost component). We did not find significant motion of component C1, closest to the core, with an upper limit of 2c on the apparent velocity. In the superresolved core region, we notice a rotation of the EVPA, suggestive of the presence of toroidal magnetic fields in the core region. We have shown that J1924–2914 is a bright and very compact source at mm wavelengths, displaying very little variability on a timescale of several days—these features render it possibly the best available EHT calibrator positioned close to Sgr A* on the sky.

We compared our EHT images with quasi-simultaneous images of J1924–2914 at longer wavelengths obtained with the GMVA and the VLBA. We observed a clockwise rotation of the jet direction in J1924–2914 as we go from long to short observing wavelengths, with an apparent bend of the jet in 3.5 mm. The rotation of the PA with the frequency could be indicative of a helical jet structure. Several scenarios have been proposed for helical jets in other sources, such as a putative supermassive black hole binary in the core, or a tilted large-scale accretion flow compared to the black hole spin axis, or shock regions as the jet interacts with the external medium. All these scenarios predict a time variability of the PA at individual frequencies, which we do not see in the ~20 yr timescale of the MOJAVE 15 GHz observations on angular scales of ~5 mas. Monitoring on longer timescales, particularly at higher frequencies, will be needed to further understand the helical structure.

The narrow fractional bandwidth of the EHT 2017 observations ($\Delta\nu/\nu < 2\%$), and a scale separation between observations by different arrays prevented us from studying the spatially resolved spectral index and rotation measure. EHT observations in 2018 and later provide a wider bandwidth ($\Delta\nu/\nu > 6\%$), alleviating this shortcoming (EHTC et al. 2019b). There are plans for expanding the EHT array and enabling 345 GHz observations (Doeleman et al. 2019), which should further improve both the resolution and the dynamic range of the J1924–2914 images.

Finally, J1924–2914 is a source of γ-ray radiation identified in the Fermi-LAT catalog (Abdollahi et al. 2020). Given that with the EHT at 1.3 mm we see detailed structure of the source total intensity and linear polarization on an extreme scale of ~0.1 pc, the source may be an excellent target to study the relation between high-energy emission and jet morphology and kinematics at millimeter wavelengths. Interestingly, the most recent 230 GHz SMA monitoring data from the beginning of 2022 show a steep brightness rise to the largest values seen in a decade.

We thank the anonymous reviewer for their thoughtful and helpful comments. The Event Horizon Telescope Collaboration thanks the following organizations and programs: the Academy of Finland (projects 274477, 284495, 312496, 315721); the Agencia Nacional de Investigación y Desarrollo (ANID), Chile via NCN19_058 (TITANs) and Fondecyt 3190878, the Alexander von Humboldt Stiftung; an Alfred P. Sloan Research Fellowship; Allegro, the European ALMA Regional Centre node in the Netherlands, the NL astronomy research network NOVA and the astronomy institutes of the University of Amsterdam, Leiden University and Radboud University; the black hole Initiative at Harvard University, through a grant (60477) from the John Templeton Foundation; the China

Scholarship Council; Consejo Nacional de Ciencia y Tecnología (CONACYT, Mexico, projects U0004-246083, U0004-259839, F0003-272050, M0037-279006, F0003-281692, 104497, 275201, 263356); the Delaney Family via the Delaney Family John A. Wheeler Chair at Perimeter Institute; Dirección General de Asuntos del Personal Académico-Universidad Nacional Autónoma de México (DGAPA-UNAM, projects IN112417 and IN112820); the European Research Council Synergy Grant “BlackHoleCam: Imaging the Event Horizon of Black Holes” (grant 610058); the Generalitat Valenciana postdoctoral grant APOSTD/2018/177 and GenT Program (project CIDEGENT/2018/021); MICINN Research Project PID2019-108995GB-C22; the Gordon and Betty Moore Foundation (grant GBMF-3561); the Istituto Nazionale di Fisica Nucleare (INFN) sezione di Napoli, iniziative specifiche TEONGRAV; the International Max Planck Research School for Astronomy and Astrophysics at the Universities of Bonn and Cologne; Joint Princeton/Flatiron and Joint Columbia/Flatiron Postdoctoral Fellowships, research at the Flatiron Institute is supported by the Simons Foundation; the Japanese Government (Monbukagakusho: MEXT) Scholarship; the Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for JSPS Research Fellowship (JP17J08829); the Key Research Program of Frontier Sciences, Chinese Academy of Sciences (CAS, grants QYZDJ-SSW-SLH057, QYZDJSSW-SYS008, ZDBS-LY-SLH011); the Leverhulme Trust Early Career Research Fellowship; the Max-Planck-Gesellschaft (MPG); the Max Planck Partner Group of the MPG and the CAS; the MEXT/JSPS KAKENHI (grants 18KK0090, JP18K13594, JP18K03656, JP18H03721, 18K03709, 18H01245, 25120007); the Malaysian Fundamental Research Grant Scheme (FRGS) FRGS/1/2019/STG02/UM/02/6; the MIT International Science and Technology Initiatives (MISTI) Funds; the Ministry of Science and Technology (MOST) of Taiwan (105-2112-M-001-025-MY3, 106-2112-M-001-011, 106-2119-M-001-027, 107-2119-M-001-017, 107-2119-M-001-020, 107-2119-M-110-005, 108-2112-M-001-048, and 109-2124-M-001-005); the National Aeronautics and Space Administration (NASA, Fermi Guest Investigator grant 80NSSC20K1567, NASA Astrophysics Theory Program grant 80NSSC20K0527, NASA NuSTAR award 80NSSC20K0645); the National Institute of Natural Sciences (NINS) of Japan; the National Key Research and Development Program of China (grant 2016YFA0400704, 2016YFA0400702); the National Science Foundation (NSF, grants AST-0096454, AST-0352953, AST-0521233, AST-0705062, AST-0905844, AST-0922984, AST-1126433, AST-1140030, DGE-1144085, AST-1207704, AST-1207730, AST-1207752, MRI-1228509, OPP-1248097, AST-1310896, AST-1555365, AST-1615796, AST-1715061, AST-1716327, AST-1903847, AST-2034306); the Natural Science Foundation of China (grants 11573051, 11633006, 11650110427, 10625314, 11721303, 11725312, 11933007, 11991052, 11991053); a fellowship of China Postdoctoral Science Foundation (2020M671266); the Natural Sciences and Engineering Research Council of Canada (NSERC, including a Discovery Grant and the NSERC Alexander Graham Bell Canada Graduate Scholarships-Doc-toral Program); the National Youth Thousand Talents Program of China; the National Research Foundation of Korea (the Global PhD Fellowship Grant: grants NRF-2015H1A2A1033752, 2015-R1D1A1A01056807, the Korea Research Fellowship Program: NRF-2015H1D3A1066561,
Basic Research Support Grant 2019R1F1A1059721); the Netherlands Organization for Scientific Research (NWO) VICI award (grant 639.043.513) and Spinoza Prize SPI 78-409; the New Scientific Frontiers with Precision Radio Interferometry Fellowship awarded by the South African Radio Astronomy Observatory (SARAO), which is a facility of the National Research Foundation (NRF), an agency of the Department of Science and Technology (DST) of South Africa; the Onsala Space Observatory (OSO) national infrastructure, for the provisioning of its facilities/observational support (OSO receives funding through the Swedish Research Council under grant 2017-00648) the Perimeter Institute for Theoretical Physics (research at Perimeter Institute is supported by the Government of Canada through the Department of Innovation, Science and Economic Development and by the Province of Ontario through the Ministry of Research, Innovation and Science); the Spanish Ministerio de Economía y Competitividad (grants PGC2018-098915-B-C21, AYA2016-80889-P, PID2019-108995GB-C21); the State Agency for Research of the Spanish MCIU through the “Center of Excellence Severo Ochoa” award for the Instituto de Astrofísica de Andalucía (SEV-2017-0709); the Toray Science Foundation; the Consejería de Economía, Conocimiento, Empresas y Universidad of the Junta de Andalucía (grant P18-FR-1769), the Consejo Superior de Investigaciones Científicas (grant 2019AEP112); the US Department of Energy (USDOE) through the Los Alamos National Laboratory (operated by Triad National Security, LLC, for the National Nuclear Security Administration of the USDOE (Contract 89233218CNA000001); the European Union’s Horizon 2020 research and innovation program under grant agreement No 730562 RadioNet; ALMA North America Development Fund; the Academia Sinica; Chandra DD7-18089X and TM6-17006X; the GenT Program (Generalitat Valenciana) Project CIDEGENT/2018/021. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant ACI-1548562, and CyVerse, supported by NSF grants DBI-0735191, DBI-1265383, and DBI-1743442. XSEDE Stampede2 resource at TACC was allocated through TG-AST170024 and TG-AST080026N. XSEDE JetStream resource at PTI and TACC was allocated through AST170028. The simulations were performed in part on the SuperMUC cluster at the LRZ in Garching, on the LOEWE cluster in CSC in Frankfurt, and on the HazelHen cluster at the HLRS in Stuttgart. This research was enabled in part by support provided by Compute Ontario (http://computeontario.ca), Calcul Quebec (http://www.calculquebec.ca) and Compute Canada (http://www.computecanada.ca). We thank the staff at the participating observatories, correlation centers, and institutions for their enthusiastic support. This paper makes use of the following ALMA data: ADS/JAO.ALMA#2016.1.01154.V and ADS/JAO.ALMA2016.1.00413.V. ALMA is a partnership of the European Southern Observatory (ESO; Europe, representing its member states), NSF, and National Institutes of Natural Sciences of Japan, together with National Research Council (Canada), Ministry of Science and Technology (MOST; Taiwan), Academia Sinica Institute of Astronomy and Astrophysics (ASIAA; Taiwan), and Korea Astronomy and Space Science Institute (KASI; Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, Associated Universities, Inc. (AUI)/NRAO, and the National Astronomical Observatory of Japan (NAOJ). The NRAO is a facility of the NSF operated under cooperative

agreement by AUI. APEX is a collaboration between the Max-Planck-Institut für Radioastronomie (Germany), ESO, and the Onsala Space Observatory (Sweden). The SMA is a joint project between the SAO and ASIAA and is funded by the Smithsonian Institution and the Academia Sinica. The JCMT is operated by the East Asian Observatory on behalf of the NAOJ, ASIAA, and KASI, as well as the Ministry of Finance of China, Chinese Academy of Sciences, and the National Key R&D Program (No. 2017YFA0402700) of China. Additional funding support for the JCMT is provided by the Science and Technologies Facility Council (UK) and participating universities in the UK and Canada. The LMT is a project operated by the Instituto Nacional de Astrófísica, Óptica, y Electrónica (Mexico) and the University of Massachusetts at Amherst (USA). The IRAM 30 m telescope on Pico Veleta, Spain is operated by IRAM and supported by CNRS (Centre National de la Recherche Scientifique, France), MPG (Max-Planck- Gesellschaft, Germany) and IGN (Instituto Geográfico Nacional, Spain). The SMT is operated by the Arizona Radio Observatory, a part of the Steward Observatory of the University of Arizona, with financial support of operations from the State of Arizona and financial support for instrumentation development from the NSF. Support for SPT participation in the EHT is provided by the National Science Foundation through award OPP-1852617 to the University of Chicago. Partial support is also provided by the Kavli Institute of Cosmological Physics at the University of Chicago. The SPT hydrogen maser was provided on loan from the GLT, courtesy of ASIAA. The EHTC has received generous donations of FPGA chips from Xilinx Inc., under the Xilinx University Program. The EHTC has benefited from technology shared under open-source license by the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER). The EHT project is grateful to T4Science and Microsemi for their assistance with Hydrogen Masers. This research has made use of NASA’s Astrophysics Data System. We gratefully acknowledge the support provided by the extended staff of the ALMA, both from the inception of the ALMA Phasing Project through the observational campaigns of 2017 and 2018. We would like to thank A. Deller and W. Brisken for EHT-specific support with the use of DiFX. We acknowledge the significance that Maunakea, where the SMA and JCMT EHT stations are located, has for the indigenous Hawaiian people.

We also thank Alexandra Elbakyan for her contributions to the open science initiative. This research has made use of data obtained with the Global Millimeter VLBI Array (GMVA), coordinated by the VLBI group at the Max-Planck-Institut für Radioastronomie (MPIfR). The GMVA consists of telescopes operated by MPIfR, IRAM, Onsala, Metsahovi, Yebes, the Korean VLBI Network, the Green Bank Observatory, and the Very Long Baseline Array (VLBA). The VLBA and the GBT are facilities of the National Science Foundation under cooperative agreement by Associated Universities, Inc. The data were correlated at the DiFX correlator of the MPIfR in Bonn, Germany. We thank the National Science Foundation (awards OISE-1743747, AST-1816420, AST-1716536, AST-1440254, AST-1935980) and the Gordon and Betty Moore Foundation (GBMF-5278) for financial support of this work. Support for this work was also provided by the NASA Hubble Fellowship grant HST-HF2-51431.001-A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS5-26555.
# Appendix A
## Data Reduction Pipelines Comparison

In Figure 14 we compare the Stokes *I* (total intensity) 230 GHz images obtained from the two data reduction pipelines: EHT-HOPS (Blackburn et al. 2019), and CASA-based rPICARD (Janssen et al. 2019). All images presented in Figure 14 were obtained using an identical eht-imaging script (Chael et al. 2016). The images correspond to a direct fit to the observations, with no blurring or restoring beam applied.

multisource fit (EHTC et al. 2021a; Martí-Vidal et al. 2021). For the remaining sites the leakage terms need to be modeled simultaneously with the source structure and the problem becomes degenerate. The values presented in Table 1 are representative values based on the analysis spanning multiple epochs and different image reconstruction algorithms (EHTC et al. 2021a). These values were used for the linear-polarization imaging with eht-imaging, and only SPT D-terms were solved for in this framework. For imaging with DMC, leakage terms were fitted within the software, providing a consistency

<figure><img src="image_17.png" /><figcaption>**Figure 14.** Total-intensity images of J1924–2914 for the four EHT observing epochs in April 2017, for two independent data calibration pipelines EHT-HOPS (upper panels) and CASA-rPICARD (bottom panels). The color scale is the same for all images, with a peak value corresponding to 10 mJy/µas². Contours correspond to 15, 30, 45, 60, 75, 90% of the peak flux density. There is a high level of consistency between the two calibration methods.</figcaption></figure>

# Appendix B
## Leakage Terms Consistency

Leakage coefficients can be estimated robustly for the telescopes with an intra-site station (ALMA, APEX, SMA, JCMT), where a point source model can be employed for a

test with the assumed values (see Figure 15). Systematic differences between days are seen for the DMC fits. As D-terms are unlikely to significantly vary in time for stations other than ALMA (Goddi et al. 2019), this highlights the importance of using multiepoch fits to constrain the leakage coefficients. SPT

<figure><img src="image_18.png" /><figcaption>**Figure 15.** Leakage terms estimated with DMC for J1924–2914 data for 2017 April 6, 7, and 11, shown with $1\sigma$ error bars. The matching symbols without error bars correspond to the assumed leakage terms given in Table 1. Filled and open symbols denote right and left circular polarization D-terms, respectively. In case of the SPT, markers correspond to leakage terms estimated by eht-imaging, separately for each observing day.</figcaption></figure>
leakage calibration is particularly challenging given the limited parallactic coverage and the relevant D-terms have not been estimated in EHTC et al. (2021a) because M87* is not observable from the south pole. Our fits to J1924-2914 data indicate that the magnitude of the SPT D-terms does not exceed 5%. Overall the D-terms have an acceptable degree of consistency and the residual uncertainties related to imperfect leakage calibration do not influence the overall morphology of the linear-polarization images (see Section 3.2).

## ORCID iDs

Sara Issaoun https://orcid.org/0000-0002-5297-921X

Maciek Wielgus https://orcid.org/0000-0002-8635-4242

Svetlana Jorstad https://orcid.org/0000-0001-6158-1708

Thomas P. Krichbaum https://orcid.org/0000-0002-4892-9586

Lindy Blackburn https://orcid.org/0000-0002-9030-642X

Michael Janssen https://orcid.org/0000-0001-8685-6544

Chi-kwan Chan https://orcid.org/0000-0001-6337-6126

Dominic W. Pesce https://orcid.org/0000-0002-5278-9221

José L. Gómez https://orcid.org/0000-0003-4190-7613

Kazunori Akiyama https://orcid.org/0000-0002-9475-4254

Monika Mościbrodzka https://orcid.org/0000-0002-4661-6332

Iván Martí-Vidal https://orcid.org/0000-0003-3708-9611

Andrew Chael https://orcid.org/0000-0003-2966-6220

Rocco Lico https://orcid.org/0000-0001-7361-2460

Jun Liu (刘俊) https://orcid.org/0000-0002-7615-7499

Venkatessh Ramakrishnan https://orcid.org/0000-0002-9248-086X

Mikhail Lisakov https://orcid.org/0000-0001-6088-3819

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Roberto García https://orcid.org/0000-0002-6584-7443

Boris Georgiev https://orcid.org/0000-0002-3586-6424

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Arturo I. Gómez-Ruiz https://orcid.org/0000-0001-9395-1670

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Kazuhiro Hada https://orcid.org/0000-0001-6906-772X

Daryl Haggard https://orcid.org/0000-0001-6803-2138
Michael H. Hecht https://orcid.org/0000-0002-4114-4583

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(何子山) https://orcid.org/0000-0001-6947-5846

Mareki Honma https://orcid.org/0000-0003-4058-9000

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Wu Jiang (江悟) https://orcid.org/0000-0001-7369-3539

Alejandra Jimenez-Rosales https://orcid.org/0000-0002-2662-3754

Michael D. Johnson https://orcid.org/0000-0002-4120-3029

Abhishek V. Joshi https://orcid.org/0000-0002-2514-5965

Taehyun Jung https://orcid.org/0000-0001-7003-8643

Mansour Karami https://orcid.org/0000-0001-7387-9333

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Tomohisa Kawashima https://orcid.org/0000-0001-8527-0496

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Michael Kramer https://orcid.org/0000-0002-4175-2271

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Noemi La Bella https://orcid.org/0000-0002-8116-9427

Tod R. Lauer https://orcid.org/0000-0003-3234-7247

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Po Kin Leung https://orcid.org/0000-0002-8802-8256

Aviad Levis https://orcid.org/0000-0001-7307-632X

Zhiyuan Li (李志远) https://orcid.org/0000-0003-0355-6437

Rocco Lico https://orcid.org/0000-0001-7361-2460

Greg Lindahl https://orcid.org/0000-0002-6100-4772

Michael Lindqvist https://orcid.org/0000-0002-3669-0715

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Jirong Mao (毛基荣) https://orcid.org/0000-0002-7077-7195

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James M. Moran https://orcid.org/0000-0002-3882-4414

Cornelia Müller https://orcid.org/0000-0002-2739-2994

Alejandro Mus https://orcid.org/0000-0003-0329-6874

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Ioannis Myserlis https://orcid.org/0000-0003-3025-9497

Andrew Nadolski https://orcid.org/0000-0001-9479-9957

Hiroshi Nagai https://orcid.org/0000-0003-0292-3645

Neil M. Nagar https://orcid.org/0000-0001-6920-662X

Masanori Nakamura https://orcid.org/0000-0001-6081-2420

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Gopal Narayanan https://orcid.org/0000-0002-4723-6569

Iniyan Natarajan https://orcid.org/0000-0001-8242-4373

Joey Neilsen https://orcid.org/0000-0002-8247-786X

Roberto Neri https://orcid.org/0000-0002-7176-4046

Chunchong Ni https://orcid.org/0000-0003-1361-5699

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Michael A. Nowak https://orcid.org/0000-0001-6923-1315

Junghwan Oh https://orcid.org/0000-0002-4991-9638

Hiroki Okino https://orcid.org/0000-0003-3779-2016

Héctor Olivares https://orcid.org/0000-0001-6833-7580

Gisela N. Ortiz-León https://orcid.org/0000-0002-2863-676X

Tomoaki Oyama https://orcid.org/0000-0003-4046-2923

Feryal Özel https://orcid.org/0000-0003-4413-1523

Daniel C. M. Palumbo https://orcid.org/0000-0002-7179-3816

Georgios Filippos Paraschos https://orcid.org/0000-0001-6757-3098

Jongho Park https://orcid.org/0000-0001-6558-9053

Harriet Parsons https://orcid.org/0000-0002-6327-3423

Nimesh Patel https://orcid.org/0000-0002-6021-9421

Ue-Li Pen https://orcid.org/0000-0003-2155-9578

Richard Plambeck https://orcid.org/0000-0001-6765-9609

Oliver Porth https://orcid.org/0000-0002-4584-2557

Felix M. Pötzl https://orcid.org/0000-0002-6579-8311

Ben Prather https://orcid.org/0000-0002-0393-7734

Jorge A. Preciado-López https://orcid.org/0000-0002-4146-0113

Dimitrios Psaltis https://orcid.org/0000-0003-1035-3240

Hung-Yi Pu https://orcid.org/0000-0001-9270-8812

Ramprasad Rao https://orcid.org/0000-0002-1407-7944

Mark G. Rawlings https://orcid.org/0000-0002-6529-202X

Alexander W. Raymond https://orcid.org/0000-0002-5779-4767

Luciano Rezzolla https://orcid.org/0000-0002-1330-7103

Angelo Ricarte https://orcid.org/0000-0001-5287-0452

Bart Ripperda https://orcid.org/0000-0002-7301-3908

Freek Roelofs https://orcid.org/0000-0001-5461-3687

Alan Rogers https://orcid.org/0000-0003-1941-7458

Eduardo Ros https://orcid.org/0000-0001-9503-4892

Cristina Romero-Canizales https://orcid.org/0000-0001-6301-9073

Arash Roshanineshat https://orcid.org/0000-0002-8280-9238
Alan L. Roy https://orcid.org/0000-0002-1931-0135

Ignacio Ruiz https://orcid.org/0000-0002-0965-5463

Chet Ruszczyk https://orcid.org/0000-0001-7278-9707

Kazi L. J. Rygl https://orcid.org/0000-0003-4146-9043

Salvador Sánchez https://orcid.org/0000-0002-8042-5951

David Sánchez-Arguelles https://orcid.org/0000-0002-7344-9920

Miguel Sanchez-Portal https://orcid.org/0000-0003-0981-9664

Mahito Sasada https://orcid.org/0000-0001-5946-9960

Kaushik Satapathy https://orcid.org/0000-0003-0433-3585

Tuomas Savolainen https://orcid.org/0000-0001-6214-1085

Karl-Friedrich Schuster https://orcid.org/0000-0003-2890-9454

Lijing Shao https://orcid.org/0000-0002-1334-8853

Zhiqiang Shen (沈志强) https://orcid.org/0000-0003-3540-8746

Des Small https://orcid.org/0000-0003-3723-5404

Bong Won Sohn https://orcid.org/0000-0002-4148-8378

Jason SooHoo https://orcid.org/0000-0003-1938-0720

Kamal Souccar https://orcid.org/0000-0001-7915-5272

He Sun (孙赫) https://orcid.org/0000-0003-1526-6787

Fumie Tazaki https://orcid.org/0000-0003-0236-0600

Alexandra J. Tetarenko https://orcid.org/0000-0003-3906-4354

Paul Tiede https://orcid.org/0000-0003-3826-5648

Remo P. J. Tilanus https://orcid.org/0000-0002-6514-553X

Michael Titus https://orcid.org/0000-0002-3423-4505

Pablo Torne https://orcid.org/0000-0001-8700-6058

Sascha Trippe https://orcid.org/0000-0003-0465-1559

Ilse van Bemmel https://orcid.org/0000-0001-5473-2950

Huib Jan van Langevelde https://orcid.org/0000-0002-0230-5946

Daniel R. van Rossum https://orcid.org/0000-0001-7772-6131

Jesse Vos https://orcid.org/0000-0003-3349-7394

Jan Wagner https://orcid.org/0000-0003-1105-6109

Derek Ward-Thompson https://orcid.org/0000-0003-1140-2761

John Wardle https://orcid.org/0000-0002-8960-2942

Jonathan Weintroub https://orcid.org/0000-0002-4603-5204

Norbert Wex https://orcid.org/0000-0003-4058-2837

Robert Wharton https://orcid.org/0000-0002-7416-5209

Kaj Wiik https://orcid.org/0000-0002-0862-3398

Gunther Witzel https://orcid.org/0000-0003-2618-797X

Michael Wondrak https://orcid.org/0000-0002-6894-1072

George N. Wong https://orcid.org/0000-0001-6952-2147

Qingwen Wu (吴庆文) https://orcid.org/0000-0003-4773-4987

Paul Yamaguchi https://orcid.org/0000-0002-6017-8199

Doosoo Yoon https://orcid.org/0000-0001-8694-8166

André Young https://orcid.org/0000-0003-0000-2682

Ken Young https://orcid.org/0000-0002-3666-4920

Ziri Younsi https://orcid.org/0000-0001-9283-1191

Feng Yuan (袁峰) https://orcid.org/0000-0003-3564-6437

Ye-Fei Yuan (袁业飞) https://orcid.org/0000-0002-7330-4756

J. Anton Zensus https://orcid.org/0000-0001-7470-3321

Shuo Zhang https://orcid.org/0000-0002-2967-790X

Shan-Shan Zhao https://orcid.org/0000-0002-9774-3606

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