Evolutionary Optimization for Safe Navigation of an Autonomous Robot in Cluttered Dynamic Unknown Environments

We present a path planning approach based on probabilistic methods for a robot to navigate in a cluttered, dynamic, unknown environment. There are dynamic obstacles moving around and static obstacles located in the map. The robot does not have any prior information about them but should be able to navigate through the map beginning from a known starting point and safely ending at a known target point. The only information the robot has is the location of the starting point and the target point and it uses sensory information to collect information about its surroundings. Our method is compared to the D* Lite algorithm and results are presented. In the last section, the parameters of the robot are optimized using biogeography-based optimization (BBO). This is an efficient multivariable optimizer and it is shown that the results of optimization achieve significant improvement in robot navigation performance. In this thesis, we show that using evolutionary optimization methods like BBO can reduce the risk of collision and the navigation time by about 25% each. The resulting risk of collision indicates safe navigation by the robot which leads to the conclusion that this is a feasible method for real-world robots

Evolutionary Optimization for Safe Navigation of an Autonomous Robot in Cluttered Dynamic Unknown Environments

We present a path planning approach based on probabilistic methods for a robot to navigate in a cluttered, dynamic, unknown environment. There are dynamic obstacles moving around and static obstacles located in the map. The robot does not have any prior information about them but should be able to navigate through the map beginning from a known starting point and safely ending at a known target point. The only information the robot has is the location of the starting point and the target point and it uses sensory information to collect information about its surroundings. Our method is compared to the D* Lite algorithm and results are presented. In the last section, the parameters of the robot are optimized using biogeography-based optimization (BBO). This is an efficient multivariable optimizer and it is shown that the results of optimization achieve significant improvement in robot navigation performance. In this thesis, we show that using evolutionary optimization methods like BBO can reduce the risk of collision and the navigation time by about 25% each. The resulting risk of collision indicates safe navigation by the robot which leads to the conclusion that this is a feasible method for real-world robots

School Logo Cleveland State University Logo Title Evolutionary Optimization for Safe Navigation of an Autonomous Robot in Cluttered Dynamic Unknown Environments

We present a path planning approach based on probabilistic methods for a robot to navigate in a cluttered, dynamic, unknown environment. There are dynamic obstacles moving around and static obstacles located in the map. The robot does not have any prior information about them but should be able to navigate through the map beginning from a known starting point and safely ending at a known target point. The only information the robot has is the location of the starting point and the target point and it uses sensory information to collect information about its surroundings. Our method is compared to the D* Lite algorithm and results are presented. In the last section, the parameters of the robot are optimized using biogeography-based optimization (BBO). This is an efficient multivariable optimizer and it is shown that the results of optimization achieve significant improvement in robot navigation performance. In this thesis, we show that using evolutionary optimization methods like BBO can reduce the risk of collision and the navigation time by about 25% each. The resulting risk of collision indicates safe navigation by the robot which leads to the conclusion that this is a feasible method for real-world robots

School Logo Cleveland State University Logo Title Evolutionary Optimization for Safe Navigation of an Autonomous Robot in Cluttered Dynamic Unknown Environments

We present a path planning approach based on probabilistic methods for a robot to navigate in a cluttered, dynamic, unknown environment. There are dynamic obstacles moving around and static obstacles located in the map. The robot does not have any prior information about them but should be able to navigate through the map beginning from a known starting point and safely ending at a known target point. The only information the robot has is the location of the starting point and the target point and it uses sensory information to collect information about its surroundings. Our method is compared to the D* Lite algorithm and results are presented. In the last section, the parameters of the robot are optimized using biogeography-based optimization (BBO). This is an efficient multivariable optimizer and it is shown that the results of optimization achieve significant improvement in robot navigation performance. In this thesis, we show that using evolutionary optimization methods like BBO can reduce the risk of collision and the navigation time by about 25% each. The resulting risk of collision indicates safe navigation by the robot which leads to the conclusion that this is a feasible method for real-world robots

An Extensive Set of Kinematic and Kinetic Data for Individuals with Intact Limbs and Transfemoral Prosthesis Users

This paper introduces an extensive human motion data set for typical activities of daily living. These data are crucial for the design and control of prosthetic devices for transfemoral prosthesis users. This data set was collected from seven individuals, including five individuals with intact limbs and two transfemoral prosthesis users. These data include the following types of movements: (1) walking at three different speeds; (2) walking up and down a 5-degree ramp; (3) stepping up and down; (4) sitting down and standing up. We provide full-body marker trajectories and ground reaction forces (GRFs) as well as joint angles, joint velocities, joint torques, and joint powers. This data set is publicly available at the website referenced in this paper. Data from flexion and extension of the hip, knee, and ankle are presented in this paper. However, the data accompanying this paper (available on the internet) include 46 distinct measurements and can be useful for validating or generating mathematical models to simulate the gait of both transfemoral prosthesis users and individuals with intact legs

First M87 Event Horizon Telescope Results. IV. Imaging the Central Supermassive Black Hole

We present the first Event Horizon Telescope (EHT) images of M87, using observations from April 2017 at 1.3 mm wavelength. These images show a prominent ring with a diameter of similar to 40 mu as, consistent with the size and shape of the lensed photon orbit encircling the "shadow" of a supermassive black hole. The ring is persistent across four observing nights and shows enhanced brightness in the south. To assess the reliability of these results, we implemented a two-stage imaging procedure. In the first stage, four teams, each blind to the others' work, produced images of M87 using both an established method (CLEAN) and a newer technique (regularized maximum likelihood). This stage allowed us to avoid shared human bias and to assess common features among independent reconstructions. In the second stage, we reconstructed synthetic data from a large survey of imaging parameters and then compared the results with the corresponding ground truth images. This stage allowed us to select parameters objectively to use when reconstructing images of M87. Across all tests in both stages, the ring diameter and asymmetry remained stable, insensitive to the choice of imaging technique. We describe the EHT imaging procedures, the primary image features in M87, and the dependence of these features on imaging assumptions.Academy of Finland [274477, 284495, 312496]; European Commission Framework Programme Horizon 2020 Research and Innovation action [731016]; Black Hole Initiative at Harvard University through John Templeton Foundation [60477]; Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT, Chile) [PIA ACT172033, Fondecyt 1171506, BASAL AFB-170002, ALMA-conicyt 31140007]; Consejo Nacional de Ciencia y Tecnologia (CONACYT, Mexico) [104497, 275201, 279006, 281692]; Direccion General de Asuntos del Personal Academico-Universidad Nacional Autonoma de Mexico (DGAPA-UNAM) [IN112417]; European Research Council Synergy Grant "BlackHoleCam: Imaging the Event Horizon of Black Holes" [610058]; Generalitat Valenciana postdoctoral grant [APOSTD/2018/177]; Gordon and Betty Moore Foundation [GBMF 947, GBMF-3561, GBMF-5278]; Japanese Government (Monbukagakusho: MEXT) Scholarship; Japan Society for the Promotion of Science (JSPS) [JP17J08829]; JSPS Overseas Research Fellowships; Key Research Program of Frontier Sciences, Chinese Academy of Sciences (CAS) [QYZDJ-SSW-SLH057, QYZDJ-SSW-SYS008]; Leverhulme Trust Early Career Research Fellowship; MEXT/JSPS KAKENHI [18KK0090, JP18K13594, JP18K03656, JP18H03721, 18K03709, 18H01245, 25120007]; MIT International Science and Technology Initiatives (MISTI) Funds; 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]; National Aeronautics and Space Administration (NASA) [80NSSC17K0649]; National Key Research and Development Program of China [2016YFA0400704, 2016YFA0400702]; National Science Foundation (NSF) [AST-0096454, AST-0352953, AST-0521233, AST-0705062, AST-0905844, AST-0922984, AST-1126433, AST-1140030, DGE-1144085]; Natural Science Foundation of China [11573051, 11633006, 11650110427, 10625314, 11721303, 11725312, 11873028, 11873073, U1531245, 11473010]; Natural Sciences and Engineering Research Council of Canada (NSERC); National Research Foundation of Korea [2015-R1D1A1A01056807, NRF-2015H1A2A1033752, NRF-2015H1D3A1066561]; Netherlands Organization for Scientific Research (NWO) VICI award [639.043.513]; Spinoza Prize [SPI 78-409]; Swedish Research Council [2017-00648]; Government of Canada through the Department of Innovation, Science and Economic Development Canada; Province of Ontario through the Ministry of Economic Development, Job Creation and Trade; Russian Science Foundation [17-12-01029]; Spanish Ministerio de Economia y Competitividad [AYA2015-63939-C2-1-P, AYA2016-80889-P]; US Department of Energy (USDOE) through the Los Alamos National Laboratory [89233218CNA000001]; Italian Ministero dell'Istruzione Universita e Ricerca through the grant Progetti Premiali 2012-iALMA [CUP C52I13000140001]; ALMA North America Development Fund; NSF [DBI-0735191, DBI-1265383, DBI-1743442, ACI-1548562]; Smithsonian Institution; Academia Sinica; National Key R&D Program of China [2017YFA0402700]; Science and Technologies Facility Council (UK); CNRS (Centre National de la Recherche Scientifique, France); MPG (Max-Planck-Gesellschaft, Germany); State of Arizona; NSF Physics Frontier Center award [PHY-0114422]; Kavli Foundation; National Science Foundation [PLR-1248097]; NSF Physics Frontier Center [PHY-1125897]; KREONET (Korea Research Environment Open NETwork); Jansky Fellowship program of the National Radio Astronomy Observatory (NRAO); 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; State Agency for Research of the Spanish MCIU through the "Center of Excellence Severo Ochoa" award [SEV-2017-0709]; Compute Ontario; Calcul Quebec; Compute Canada; IGN (Instituto Geografico Nacional, Spain); NSF; GBMF [GBMF-947]; CyVerse; [Chandra TM6-17006X]; [MM07B]; [AST-1207704]; [AST-1207730]; [AST-1207752]; [MRI-1228509]; [OPP-1248097]; [AST-1310896]; [AST-1312651]; [AST-1337663]; [AST-1440254]; [AST-1555365]; [AST-1715061]; [AST-1614868]; [AST-1615796]; [AST-1716327]; [OISE-1743747]; [AST-1816420]This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

First M87 Event Horizon Telescope Results. V. Physical Origin of the Asymmetric Ring

The Event Horizon Telescope (EHT) has mapped the central compact radio source of the elliptical galaxy M87 at 1.3 mm with unprecedented angular resolution. Here we consider the physical implications of the asymmetric ring seen in the 2017 EHT data. To this end, we construct a large library of models based on general relativistic magnetohydrodynamic (GRMHD) simulations and synthetic images produced by general relativistic ray tracing. We compare the observed visibilities with this library and confirm that the asymmetric ring is consistent with earlier predictions of strong gravitational lensing of synchrotron emission from a hot plasma orbiting near the black hole event horizon. The ring radius and ring asymmetry depend on black hole mass and spin, respectively, and both are therefore expected to be stable when observed in future EHT campaigns. Overall, the observed image is consistent with expectations for the shadow of a spinning Kerr black hole as predicted by general relativity. If the black hole spin and M87's large scale jet are aligned, then the black hole spin vector is pointed away from Earth. Models in our library of non-spinning black holes are inconsistent with the observations as they do not produce sufficiently powerful jets. At the same time, in those models that produce a sufficiently powerful jet, the latter is powered by extraction of black hole spin energy through mechanisms akin to the Blandford-Znajek process. We briefly consider alternatives to a black hole for the central compact object. Analysis of existing EHT polarization data and data taken simultaneously at other wavelengths will soon enable new tests of the GRMHD models, as will future EHT campaigns at 230 and 345 GHz.Academy of Finland [274477, 284495, 312496]; European Commission Framework Programme Horizon 2020 Research and Innovation action [731016]; Black Hole Initiative at Harvard University through John Templeton Foundation [60477]; Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT, Chile) [PIA ACT172033, Fondecyt 1171506, BASAL AFB-170002, ALMA-conicyt 31140007]; Consejo Nacional de Ciencia y Tecnologica (CONACYT, Mexico) [104497, 275201, 279006, 281692]; Direccion General de Asuntos del Personal Academico-Universidad Nacional Autonoma de Mexico (DGAPA-UNAM) [IN112417]; European Research Council Synergy Grant "BlackHoleCam: Imaging the Event Horizon of Black Holes" [610058]; Generalitat Valenciana postdoctoral grant [APOSTD/2018/177]; Gordon and Betty Moore Foundation [GBMF-947, GBMF-3561, GBMF-5278]; Japanese Government (Monbukagakusho: MEXT) Scholarship; Japan Society for the Promotion of Science (JSPS) [JP17J08829]; JSPS Overseas Research Fellowships; Key Research Program of Frontier Sciences, Chinese Academy of Sciences (CAS) [QYZDJ-SSW-SLH057, QYZDJ-SSW-SYS008]; Leverhulme Trust Early Career Research Fellowship; MEXT/JSPS KAKENHI [18KK0090, JP18K13594, JP18K03656, JP18H03721, 18K03709, 18H01245, 25120007]; MIT International Science and Technology Initiatives (MISTI) Funds; 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-0 01-017, 107-2119-M-001-020, 107-2119-M-110-005]; National Aeronautics and Space Administration (NASA) [80NSSC17K0649]; National Key Research and Development Program of China [2016YFA0400704, 2016YFA0400702]; National Science Foundation (NSF) [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]; Natural Science Foundation of China [11573051, 11633006, 11650110427, 10625314, 11721303, 11725312, 11873028, 11873073, U1531245, 11473010]; Natural Sciences and Engineering Research Council of Canada (NSERC); National Research Foundation of Korea [NRF-2015H1A2A1033752, 2015-R1D1A1A01056807, NRF-2015H1D3A1066561]; Netherlands Organization for Scientific Research (NWO) VICI award [639.043.513]; Spinoza Prize [SPI 78-409]; Swedish Research Council [2017-00648]; Government of Canada through the Department of Innovation, Science and Economic Development Canada; Province of Ontario through the Ministry of Economic Development, Job Creation and Trade; Russian Science Foundation [17-12-01029]; Spanish Ministerio de Economia y Competitividad [AYA2015-63939-C2-1-P, AYA2016-80889-P]; US Department of Energy (USDOE) through the Los Alamos National Laboratory [89233218CNA000001]; Italian Ministero dell'Istruzione Universita e Ricerca through the grant Progetti Premiali 2012-iALMA [CUP C52I13000140001]; ALMA North America Development Fund; Sprows Family VURF Fellowship; NSERC Discovery Grant; NINS program of Promoting Research by Networking among Institutions [01421701]; NSF [ACI-1548562, DBI-0735191, DBI-1265383, DBI-1743442]; Compute Ontario; Calcul Quebec; Compute Canada; Smithsonian Institution; Academia Sinica; National Key R&D Program of China [2017YFA0402700]; Science and Technologies Facility Council (UK); CNRS (Centre National de la Recherche Scientifique, France); MPG (Max-Planck-Gesellschaft, Germany); IGN (Instituto Geografico Nacional, Spain); State of Arizona; NSF; NSF Physics Frontier Center award [PHY-0114422]; Kavli Foundation; GBMF [GBMF-947]; National Science Foundation [PLR-1248097]; NSF Physics Frontier Center grant [PHY-1125897]; 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; CyVerse; [Chandra TM6-17006X]; [DD7-18089X]; [AST-1310896]; [AST-1312651]; [AST-1337663]; [AST-1440254]; [AST-1555365]; [AST-1715061]; [AST-1615796]; [AST-1716327]; [OISE-1743747]; [AST-1816420]; [AST-1614868]This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

First M87 Event Horizon Telescope Results. VI. The Shadow and Mass of the Central Black Hole

We present measurements of the properties of the central radio source in M87 using Event Horizon Telescope data obtained during the 2017 campaign. We develop and fit geometric crescent models (asymmetric rings with interior brightness depressions) using two independent sampling algorithms that consider distinct representations of the visibility data. We show that the crescent family of models is statistically preferred over other comparably complex geometric models that we explore. We calibrate the geometric model parameters using general relativistic magnetohydrodynamic (GRMHD) models of the emission region and estimate physical properties of the source. We further fit images generated from GRMHD models directly to the data. We compare the derived emission region and black hole parameters from these analyses with those recovered from reconstructed images. There is a remarkable consistency among all methods and data sets. We find that >50% of the total flux at arcsecond scales comes from near the horizon, and that the emission is dramatically suppressed interior to this region by a factor >10, providing direct evidence of the predicted shadow of a black hole. Across all methods, we measure a crescent diameter of 42 +/- 3 mu as and constrain its fractional width to be <0.5. Associating the crescent feature with the emission surrounding the black hole shadow, we infer an angular gravitational radius of GM/Dc(2) = 3.8 +/- 0.4 mu as. Folding in a distance measurement of 16.8(-0.7)(+0.8) gives a black hole mass of M = 6.5. 0.2 vertical bar(stat) +/- 0.7 vertical bar(sys) x 10(9) M-circle dot. This measurement from lensed emission near the event horizon is consistent with the presence of a central Kerr black hole, as predicted by the general theory of relativity.Academy of Finland [274477, 284495, 312496]; European Commission Framework Programme Horizon 2020 Research and Innovation action [731016]; Black Hole Initiative at Harvard University through John Templeton Foundation [60477]; Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT, Chile) [PIA ACT172033, Fondecyt 1171506, BASAL AFB-170002, ALMA-conicyt 31140007]; Consejo Nacional de Ciencia y Tecnologia (CONACYT, Mexico) [104497, 275201, 279006, 281692]; Direccion General de Asuntos del Personal Academico-Universidad Nacional Autonoma de Mexico (DGAPA-UNAM) [IN112417]; European Research Council Synergy Grant "BlackHoleCam: Imaging the Event Horizon of Black Holes" [610058]; Generalitat Valenciana postdoctoral grant [APOSTD/2018/177]; Gordon and Betty Moore Foundation [GBMF 947, GBMF-3561, GBMF-5278]; Japanese Government (Monbukagakusho: MEXT) Scholarship; Japan Society for the Promotion of Science (JSPS) [JP17J08829]; JSPS Overseas Research Fellowships; Key Research Program of Frontier Sciences, Chinese Academy of Sciences (CAS) [QYZDJ-SSW-SLH057, QYZDJ-SSW-SYS008]; Leverhulme Trust Early Career Research Fellowship; MEXT/JSPS KAKENHI [18KK0090, JP18K13594, JP18K03656, JP18H03721, 18K03709, 18H01245, 25120007]; MIT International Science and Technology Initiatives (MISTI) Funds; 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]; National Aeronautics and Space Administration (NASA) [80NSSC17K0649]; National Key Research and Development Program of China [2016YFA0400704, 2016YFA0400702]; National Science Foundation (NSF) [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]; Natural Science Foundation of China [11573051, 11633006, 11650110427, 10625314, 11721303, 11725312, 11873028, 11873073, U1531245, 11473010]; Natural Sciences and Engineering Research Council of Canada (NSERC); National Research Foundation of Korea [2015-R1D1A1A01056807, NRF-2015H1A2A1033752, NRF-2015H1D3A1066561]; Netherlands Organization for Scientific Research (NWO) VICI award [639.043.513]; Spinoza Prize [SPI 78-409]; Swedish Research Council [2017-00648]; Government of Canada through the Department of Innovation, Science and Economic Development Canada; Province of Ontario through the Ministry of Economic Development, Job Creation and Trade; Russian Science Foundation [17-12-01029]; Spanish Ministerio de Economia y Competitividad [AYA2015-63939-C2-1-P, AYA2016-80889-P]; US Department of Energy (USDOE) through the Los Alamos National Laboratory [89233218CNA000001]; Italian Ministero dell'Istruzione Universita e Ricerca through the grant Progetti Premiali 2012-iALMA [CUP C52I13000140001]; ALMA North America Development Fund; NSF [DBI-0735191, DBI-1265383, DBI-1743442, ACI-1548562]; Smithsonian Institution; Academia Sinica; National Key R&D Program of China [2017YFA0402700]; Science and Technologies Facility Council (UK); CNRS (Centre National de la Recherche Scientifique, France); MPG (Max-Planck-Gesellschaft, Germany); IGN (Instituto Geografico Nacional, Spain); State of Arizona; NSF Physics Frontier Center award [PHY-0114422]; Kavli Foundation; National Science Foundation [PLR-1248097]; NSF Physics Frontier Center [PHY-1125897]; 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; Compute Ontario; Calcul Quebec; Compute Canada; NSF; GBMF [GBMF-947]; CyVerse; [OPP-1248097]; [AST-1310896]; [AST-1312651]; [AST-1337663]; [AST-1440254]; [AST-1555365]; [AST-1715061]; [AST-1614868]; [AST-1615796]; [AST-1716327]; [OISE-1743747]; [AST-1816420]This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

First M87 Event Horizon Telescope Results. III. Data Processing and Calibration

We present the calibration and reduction of Event Horizon Telescope (EHT) 1.3 mm radio wavelength observations of the supermassive black hole candidate at the center of the radio galaxy M87 and the quasar 3C 279, taken during the 2017 April 5-11 observing campaign. These global very long baseline interferometric observations include for the first time the highly sensitive Atacama Large Millimeter/submillimeter Array (ALMA); reaching an angular resolution of 25 mu as, with characteristic sensitivity limits of similar to 1 mJy on baselines to ALMA and similar to 10 mJy on other baselines. The observations present challenges for existing data processing tools, arising from the rapid atmospheric phase fluctuations, wide recording bandwidth, and highly heterogeneous array. In response, we developed three independent pipelines for phase calibration and fringe detection, each tailored to the specific needs of the EHT. The final data products include calibrated total intensity amplitude and phase information. They are validated through a series of quality assurance tests that show consistency across pipelines and set limits on baseline systematic errors of 2% in amplitude and 1 degrees in phase. The M87 data reveal the presence of two nulls in correlated flux density at similar to 3.4 and similar to 8.3 G lambda and temporal evolution in closure quantities, indicating intrinsic variability of compact structure on a. timescale of days, or several light-crossing times for a. few billion solar-mass black hole. These measurements provide the first opportunity to image horizon-scale structure in M87.Academy of Finland [274477, 284495, 312496]; European Commission Framework Programme Horizon 2020 Research and Innovation action [731016]; Black Hole Initiative at Harvard University through John Templeton Foundation [60477]; Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT, Chile) [PIA ACT172033, Fondecyt 1171506, BASAL AFB-170002, ALMA-conicyt 31140007]; Consejo Nacional de Ciencia y Tecnologia (CONACYT, Mexico) [104497, 275201, 279006, 281692]; Direccion General de Asuntos del Personal Academico-Universidad Nacional Autonoma de Mexico (DGAPA-UNAM) [IN112417]; European Research Council Synergy Grant "BlackHoleCam: Imaging the Event Horizon of Black Holes" [610058]; Generalitat Valenciana postdoctoral grant [APOSTD/2018/177]; Gordon and Betty Moore Foundation [GBMF 947, GBMF-3561, GBMF-5278]; Japanese Government (Monbukagakusho: MEXT) Scholarship; Japan Society for the Promotion of Science (JSPS) [JP17J08829]; JSPS Overseas Research Fellowships; Key Research Program of Frontier Sciences, Chinese Academy of Sciences (CAS) [QYZDJ-SSW-SLH057, QYZDJ-SSW-SYS008]; Leverhulme Trust Early Career Research Fellowship; MEXT/JSPS KAKENHI [18KK0090, JP18K13594, JP18K03656, JP18H03721, 18K03709, 18H01245, 25120007]; MIT International Science and Technology Initiatives (MISTI) Funds; 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]; National Aeronautics and Space Administration (NASA) [80NSSC17K0649]; National Key Research and Development Program of China [2016YFA0400704, 2016YFA0 400702]; National Science Foundation (NSF) [AST-0096454, AST-0352953, AST-0521233, AST-0705062, AST-0905844, AST-0922984, AST-1126433, AST-1140030, DGE-1144085, AST-1207704, AST-1207730]; Natural Science Foundation of China [11573051, 11633006, 11650110427, 10625314, 11721303, 11725312, 11873028, 11873073, U1531245, 11473010]; Natural Sciences and Engineering Research Council of Canada (NSERC); National Research Foundation of Korea [2015-R1D1A1A01056807, NRF-2015H1A2A1033752, NRF-2015H1D3A1066561]; Netherlands Organization for Scientific Research (NWO) VICI award [639.043.513]; Spinoza Prize [SPI 78-409]; Swedish Research Council [2017-00648]; Government of Canada through the Department of Innovation, Science and Economic Development Canada; Province of Ontario through the Ministry of Economic Development, Job Creation and Trade; Russian Science Foundation [17-12-01029]; Spanish Ministerio de Economia y Competitividad [AYA2015-63939-C2-1-P, AYA2016-80889-P]; US Department of Energy (USDOE) through the Los Alamos National Laboratory [89233218CNA000001]; Italian Ministero dell'Istruzione Universita e Ricerca through the grant Progetti Premiali 2012-iALMA [CUP C52I13000140001]; ALMA North America Development Fund; NSF [ACI-1548562, DBI-0735191, DBI-1265383, DBI-1743442]; Smithsonian Institution; Academia Sinica; National Key R&D Program of China [2017YFA0402700]; Science and Technologies Facility Council (UK); CNRS (Centre National de la Recherche Scientifique, France); MPG(Max-Planck-Gesellschaft, Germany); IGN (Instituto Geografico Nacional, Spain); State of Arizona; NSF Physics Frontier Center award [PHY-0114422]; Kavli Foundation; National Science Foundation [PLR-1248097]; NSF Physics Frontier Center [PHY-1125897]; Jansky Fellowship program of the National Radio Astronomy Observatory (NRAO); 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; State Agency for Research of the Spanish MCIU through the "Center of Excellence Severo Ochoa" award [SEV-2017-0709]; European Union' s Horizon 2020 research and innovation programme [730562 RadioNet]; GBMF [GBMF-947]; Compute Ontario; Calcul Quebec; Compute Canada; NSF; CyVerse; [Chandra TM6-17006X]; [AST-1207752]; [MRI-1228509]; [OPP-1248097]; [AST-1310896]; [AST-1312651]; [AST-1337663]; [AST-1440254]; [AST-1555365]; [AST-1715061]; [AST-1615796]; [AST-1716327]; [OISE-1743747]; [AST-1816420]; [AST-1614868]This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]