A MIGHTEE Investigation of radio quiet AGN
- Authors: Namane, Neo
- Date: 2024-04-04
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/435367 , vital:73151
- Description: This study is aimed at being an overview and investigation of the behaviour and morphology of radio quiet (RQ) active galactic nuclei (AGN) in the radio and optical/near-infrared (NIR) bands. It is hoped that a concise description of the relation that exists between accretion activity and star formation (SF) will be achieved through utilization of multiwavelength astronomy analysis. This analysis includes the processing of data acquired from the MeerKAT International GHz Tiered Extragalactic Exploration survey (MIGHTEE), the Southern African Large Telescope (SALT), the Hyper Suprime Camera (HSC) mounted on the Subaru telescope and the VISTA telescope. In this thesis, several targets were observed using SALT spectroscopy, but a redshift of only one of them was obtained. Lastly, it was established that for the sample of RQ AGN studied, the AGN contribute a large fraction of the radio emission observed. , Thesis (MSc) -- Faculty of Science, Physics and Electronics, 2024
- Full Text:
- Date Issued: 2024-04-04
- Authors: Namane, Neo
- Date: 2024-04-04
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/435367 , vital:73151
- Description: This study is aimed at being an overview and investigation of the behaviour and morphology of radio quiet (RQ) active galactic nuclei (AGN) in the radio and optical/near-infrared (NIR) bands. It is hoped that a concise description of the relation that exists between accretion activity and star formation (SF) will be achieved through utilization of multiwavelength astronomy analysis. This analysis includes the processing of data acquired from the MeerKAT International GHz Tiered Extragalactic Exploration survey (MIGHTEE), the Southern African Large Telescope (SALT), the Hyper Suprime Camera (HSC) mounted on the Subaru telescope and the VISTA telescope. In this thesis, several targets were observed using SALT spectroscopy, but a redshift of only one of them was obtained. Lastly, it was established that for the sample of RQ AGN studied, the AGN contribute a large fraction of the radio emission observed. , Thesis (MSc) -- Faculty of Science, Physics and Electronics, 2024
- Full Text:
- Date Issued: 2024-04-04
MeerKAT observations of the Abell 141 galaxy cluster
- Authors: Stanbury, Savannah Mae
- Date: 2024-04-04
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/435378 , vital:73152
- Description: This study is aimed at being an overview and investigation of the behaviour and morphology of radio quiet (RQ) active galactic nuclei (AGN) in the radio and optical/near-infrared (NIR) bands. It is hoped that a concise description of the relation that exists between accretion activity and star formation (SF) will be achieved through utilization of multiwavelength astronomy analysis. This analysis includes the processing of data acquired from the MeerKAT International GHz Tiered Extragalactic Exploration survey (MIGHTEE), the Southern African Large Telescope (SALT), the Hyper Suprime Camera (HSC) mounted on the Subaru telescope and the VISTA telescope. In this thesis, several targets were observed using SALT spectroscopy, but a redshift of only one of them was obtained. Lastly, it was established that for the sample of RQ AGN studied, the AGN contribute a large fraction of the radio emission observed. , Thesis (MSc) -- Faculty of Science, Physics and Electronics, 2024
- Full Text:
- Date Issued: 2024-04-04
- Authors: Stanbury, Savannah Mae
- Date: 2024-04-04
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/435378 , vital:73152
- Description: This study is aimed at being an overview and investigation of the behaviour and morphology of radio quiet (RQ) active galactic nuclei (AGN) in the radio and optical/near-infrared (NIR) bands. It is hoped that a concise description of the relation that exists between accretion activity and star formation (SF) will be achieved through utilization of multiwavelength astronomy analysis. This analysis includes the processing of data acquired from the MeerKAT International GHz Tiered Extragalactic Exploration survey (MIGHTEE), the Southern African Large Telescope (SALT), the Hyper Suprime Camera (HSC) mounted on the Subaru telescope and the VISTA telescope. In this thesis, several targets were observed using SALT spectroscopy, but a redshift of only one of them was obtained. Lastly, it was established that for the sample of RQ AGN studied, the AGN contribute a large fraction of the radio emission observed. , Thesis (MSc) -- Faculty of Science, Physics and Electronics, 2024
- Full Text:
- Date Issued: 2024-04-04
Performance evaluation of baseline-dependent window functions with several weighing functions
- Authors: Vanqa, Kamvulethu
- Date: 2024-04-04
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/435850 , vital:73206
- Description: Radio interferometric data volume is exponentially increasing with the potential to cause slow processing and data storage issues for radio observations recorded at high time and frequency resolutions. This necessitates that a sort of data compression is imposed. The conventional method to compress the data is averaging across time and frequency. However, this results in amplitude loss and source distortion at the edges of the field of view. To reduce amplitude loss and source distortion, baseline-dependent window functions (BDWFs) are proposed in theliterature. BDWFs are visibility data compression methods using window functions to retainthe signals within a field of interest (FoI) and to suppress signals outside this FoI. However,BDWFs are used with window functions as discussed in the signal processing field without any optimisation. This thesis evaluates the performance of BDWFs and then proposes to use machine learning with gradient descent to optimize the window functions employed in BDWFs. Results show that the convergence of the objective function is limited due to the band-limited nature of the window functions in the Fourier space. BDWFs performance is also investigated and discussed using several weighting schemes. Results show that there exists an optimal parameter tuning (not necessarily unique) that suggests an optimal combination of BDWFs and density sampling. With this, ∼ 4 % smearing is observed within the FoI, and ∼ 80 % source suppression is achieved outside the FoI using the MeerKAT telescope at 1.4 GHz, sampled at 1 s and 184.3 kHz then averaged with BDWFs to achieve a compression factor of 4 in time and 3 in frequency. , Thesis (MA) -- Faculty of Science, Mathematics, 2024
- Full Text:
- Date Issued: 2024-04-04
- Authors: Vanqa, Kamvulethu
- Date: 2024-04-04
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/435850 , vital:73206
- Description: Radio interferometric data volume is exponentially increasing with the potential to cause slow processing and data storage issues for radio observations recorded at high time and frequency resolutions. This necessitates that a sort of data compression is imposed. The conventional method to compress the data is averaging across time and frequency. However, this results in amplitude loss and source distortion at the edges of the field of view. To reduce amplitude loss and source distortion, baseline-dependent window functions (BDWFs) are proposed in theliterature. BDWFs are visibility data compression methods using window functions to retainthe signals within a field of interest (FoI) and to suppress signals outside this FoI. However,BDWFs are used with window functions as discussed in the signal processing field without any optimisation. This thesis evaluates the performance of BDWFs and then proposes to use machine learning with gradient descent to optimize the window functions employed in BDWFs. Results show that the convergence of the objective function is limited due to the band-limited nature of the window functions in the Fourier space. BDWFs performance is also investigated and discussed using several weighting schemes. Results show that there exists an optimal parameter tuning (not necessarily unique) that suggests an optimal combination of BDWFs and density sampling. With this, ∼ 4 % smearing is observed within the FoI, and ∼ 80 % source suppression is achieved outside the FoI using the MeerKAT telescope at 1.4 GHz, sampled at 1 s and 184.3 kHz then averaged with BDWFs to achieve a compression factor of 4 in time and 3 in frequency. , Thesis (MA) -- Faculty of Science, Mathematics, 2024
- Full Text:
- Date Issued: 2024-04-04
Discovery and classification of compact radio sources in the MeerKAT Galactic Centre data
- Authors: Rammala, Isabella Dineo
- Date: 2023-10-13
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/432218 , vital:72852
- Description: Access restricted. Expected release date in 2025. , Thesis (PhD) -- Faculty of Science, Physics and Electronics, 2023
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- Date Issued: 2023-10-13
- Authors: Rammala, Isabella Dineo
- Date: 2023-10-13
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/432218 , vital:72852
- Description: Access restricted. Expected release date in 2025. , Thesis (PhD) -- Faculty of Science, Physics and Electronics, 2023
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- Date Issued: 2023-10-13
M3: Mining Mini-Halos with MeerKAT
- Authors: Trehaeven, Keegan Somerset
- Date: 2023-10-13
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/424754 , vital:72181
- Description: This work aims to showcase the MeerKAT telescope’s capabilities and related calibration and imaging software in studying the emission of radio mini-halos. These diffuse radio synchrotron sources surround a Brightest Cluster Galaxy (BCG) in relatively relaxed clusters out to a few 100 kpc in size. They are difficult to image because of their relatively low surface brightness and small angular size. Hence, they could not be studied in great detail by previous generations of radio telescopes and much about their nature, particularly the exact production mechanism, is not yet fully understood. Thus, for the first time, MeerKAT observed a sample of five galaxy clusters to investigate the central radio mini-halo in each. Studying these sources requires the deepest images generated from the data and the effective subtraction of any projected sources obscuring or contaminating the underlying diffuse emission. Therefore, I describe the data reduction used to create third-generation calibrated, primary beam corrected, point source subtracted Stokes I L-band continuum images of these clusters. For first- and second-generation calibration, I use the CARACal pipeline, which implements software optimised explicitly for MeerKAT data. For third-generation calibration, I use the faceted approach of killMS and DDFacet, and then I perform visibility-plane point source subtraction to disentangle the compact and diffuse emissions. I then measured the size, flux density, in-band spectral properties, and radio power of the central mini-halos. I present the first new mini-halo detection by MeerKAT (MACS J2140.2-2339, Trehaeven et al. accepted), the first spectral index maps of these mini-halos, which show very interesting distributions, and a ∼100 kpc II southern extension to the ACO 3444 mini-halo previously unseen in archival VLA data. Thereafter, I present a multi-wavelength case study for two complementary mini-halos from our sample and show via a radio-to-X-ray spatial correlation test that they might be caused by different particle (re)-acceleration mechanisms. Through these initial science results, I have shown that future observations of radio mini-halos with MeerKAT are an exciting prospect that can lead to a better understanding of the fundamental physics behind these sources. , Thesis (MSc) -- Faculty of Science, Physics and Electronics, 2023
- Full Text:
- Date Issued: 2023-10-13
- Authors: Trehaeven, Keegan Somerset
- Date: 2023-10-13
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/424754 , vital:72181
- Description: This work aims to showcase the MeerKAT telescope’s capabilities and related calibration and imaging software in studying the emission of radio mini-halos. These diffuse radio synchrotron sources surround a Brightest Cluster Galaxy (BCG) in relatively relaxed clusters out to a few 100 kpc in size. They are difficult to image because of their relatively low surface brightness and small angular size. Hence, they could not be studied in great detail by previous generations of radio telescopes and much about their nature, particularly the exact production mechanism, is not yet fully understood. Thus, for the first time, MeerKAT observed a sample of five galaxy clusters to investigate the central radio mini-halo in each. Studying these sources requires the deepest images generated from the data and the effective subtraction of any projected sources obscuring or contaminating the underlying diffuse emission. Therefore, I describe the data reduction used to create third-generation calibrated, primary beam corrected, point source subtracted Stokes I L-band continuum images of these clusters. For first- and second-generation calibration, I use the CARACal pipeline, which implements software optimised explicitly for MeerKAT data. For third-generation calibration, I use the faceted approach of killMS and DDFacet, and then I perform visibility-plane point source subtraction to disentangle the compact and diffuse emissions. I then measured the size, flux density, in-band spectral properties, and radio power of the central mini-halos. I present the first new mini-halo detection by MeerKAT (MACS J2140.2-2339, Trehaeven et al. accepted), the first spectral index maps of these mini-halos, which show very interesting distributions, and a ∼100 kpc II southern extension to the ACO 3444 mini-halo previously unseen in archival VLA data. Thereafter, I present a multi-wavelength case study for two complementary mini-halos from our sample and show via a radio-to-X-ray spatial correlation test that they might be caused by different particle (re)-acceleration mechanisms. Through these initial science results, I have shown that future observations of radio mini-halos with MeerKAT are an exciting prospect that can lead to a better understanding of the fundamental physics behind these sources. , Thesis (MSc) -- Faculty of Science, Physics and Electronics, 2023
- Full Text:
- Date Issued: 2023-10-13
Semantic segmentation of astronomical radio images: a computer vision approach
- Authors: Kupa, Ramadimetse Sydil
- Date: 2023-03-29
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/422378 , vital:71937
- Description: The new generation of radio telescopes, such as the MeerKAT, ASKAP (Australian Square Kilometre Array Pathfinder) and the future Square Kilometre Array (SKA), are expected to produce vast amounts of data and images in the petabyte region. Therefore, the amount of incoming data at a specific point in time will overwhelm any current traditional data analysis method being deployed. Deep learning architectures have been applied in many fields, such as, in computer vision, machine vision, natural language processing, social network filtering, speech recognition, machine translation, bioinformatics, medical image analysis, and board game programs. They have produced results which are comparable to human expert performance. Hence, it is appealing to apply it to radio astronomy data. Image segmentation is one such area where deep learning techniques are prominent. The images from the new generation of telescopes have a high density of radio sources, making it difficult to classify the sources in the image. Identifying and segmenting sources from radio images is a pre-processing step that occurs before sources are put into different classes. There is thus a need for automatic segmentation of the sources from the images before they can be classified. This work uses the Unet architecture (originally developed for biomedical image segmentation) to segment radio sources from radio astronomical images with 99.8% accuracy. After segmenting the sources we use OpenCV tools to detect the sources on the mask images, then the detection is translated to the original image where borders are drawn around each detected source. This process automates and simplifies the pre-processing of images for classification tools and any other post-processing tool that requires a specific source as an input. , Thesis (MSc) -- Faculty of Science, Physics and Electronics, 2023
- Full Text:
- Date Issued: 2023-03-29
- Authors: Kupa, Ramadimetse Sydil
- Date: 2023-03-29
- Subjects: Uncatalogued
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/422378 , vital:71937
- Description: The new generation of radio telescopes, such as the MeerKAT, ASKAP (Australian Square Kilometre Array Pathfinder) and the future Square Kilometre Array (SKA), are expected to produce vast amounts of data and images in the petabyte region. Therefore, the amount of incoming data at a specific point in time will overwhelm any current traditional data analysis method being deployed. Deep learning architectures have been applied in many fields, such as, in computer vision, machine vision, natural language processing, social network filtering, speech recognition, machine translation, bioinformatics, medical image analysis, and board game programs. They have produced results which are comparable to human expert performance. Hence, it is appealing to apply it to radio astronomy data. Image segmentation is one such area where deep learning techniques are prominent. The images from the new generation of telescopes have a high density of radio sources, making it difficult to classify the sources in the image. Identifying and segmenting sources from radio images is a pre-processing step that occurs before sources are put into different classes. There is thus a need for automatic segmentation of the sources from the images before they can be classified. This work uses the Unet architecture (originally developed for biomedical image segmentation) to segment radio sources from radio astronomical images with 99.8% accuracy. After segmenting the sources we use OpenCV tools to detect the sources on the mask images, then the detection is translated to the original image where borders are drawn around each detected source. This process automates and simplifies the pre-processing of images for classification tools and any other post-processing tool that requires a specific source as an input. , Thesis (MSc) -- Faculty of Science, Physics and Electronics, 2023
- Full Text:
- Date Issued: 2023-03-29
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