Article
Astronomy & Astrophysics
Timothy Lingard, Karen L. Masters, Coleman Krawczyk, Chris Lintott, Sandor Kruk, Brooke Simmons, William Keel, Robert C. Nichol, Elisabeth Baeten
Summary: The study presents a hierarchical Bayesian approach to galaxy pitch angle determination, finds no correlation between bulge and bar strength and pitch angle, and tests a model for spiral arm winding which suggests most winding spirals disappear at pitch angles larger than 10 degrees.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2021)
Article
Astronomy & Astrophysics
Aritra Ghosh, C. Megan Urry, Amrit Rau, Laurence Perreault-Levasseur, Miles Cranmer, Kevin Schawinski, Dominic Stark, Chuan Tian, Ryan Ofman, Tonima Tasnim Ananna, Connor Auge, Nico Cappelluti, David B. Sanders, Ezequiel Treister
Summary: The study introduces a machine-learning framework GaMPEN for estimating the Bayesian posteriors of morphological parameters of galaxies, demonstrating its accuracy and stability through training and testing on simulated data.
ASTROPHYSICAL JOURNAL
(2022)
Article
Astronomy & Astrophysics
Kaili Cao, David J. Barnes, Mark Vogelsberger
Summary: The study found reasonable agreement between observed and simulated criteria distributions for relaxed galaxy clusters, but the effectiveness of a single relaxation threshold value is limited by factors such as redshift, cluster mass, numerical resolution, and subgrid physics. There is a positive correlation between different criteria, but the strength of the correlation is sensitive to redshift, mass, and numerical choices, leading to relatively poor consistency of relaxed subsets defined by different metrics. The use of relaxed cluster subsets introduces significant selection effects that are non-trivial to resolve.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2021)
Article
Multidisciplinary Sciences
Zhanwu Lv, Xinyi Cao, Xinyi Jin, Shuangqing Xu, Huangling Deng
Summary: Accurate identification and classification of bone marrow nucleated cells are crucial for hematological disease diagnosis. We developed Morphogo, a convolutional neural network-based system, to address the time-consuming and subjective nature of manual identification by pathologists. Morphogo achieved a sensitivity of 80.95%, specificity of 99.48%, positive predictive value of 76.49%, negative predictive value of 99.44%, and an overall accuracy of 99.01% in identifying over 25 different types of bone marrow nucleated cells. The system showed high correlation with pathologists' proofreading in various cell types, validating its practical applicability in clinical practice.
SCIENTIFIC REPORTS
(2023)
Article
Astronomy & Astrophysics
Rebecca J. Smethurst, Karen L. Masters, Brooke D. Simmons, Izzy L. Garland, Tobias Geron, Boris Haeussler, Sandor Kruk, Chris J. Lintott, David O'Ryan, Mike Walmsley
Summary: The galaxy population is bimodal in both colour and morphology, with most blue galaxies being late-types and most red galaxies being early-types. The use of colour as a proxy for morphology results in impure and incomplete samples. This paper utilizes morphological labels to measure the incompleteness and impurity of such samples and finds that even with the addition of near-ultraviolet bands, a sample of early-types with high purity cannot be constructed. Therefore, the use of colour-morphology proxy selections is largely unnecessary, and the implications of sample incompleteness and impurity should be carefully considered in future studies.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2022)
Article
Astronomy & Astrophysics
Emir Uzeirbegovic, Garreth Martin, Sugata Kaviraj
Summary: We introduce an empirical methodology to study the relationship between the spectral energy distribution (SED) and galaxy morphology and apply it to around 8000 galaxies. We find that the SED can constrain morphology and present a method to quantify their link. Galaxies with similar SEDs are more likely to have similar morphologies, particularly for massive red elliptical galaxies. We also explore the limitations of using color for morphological selection and find that it is relatively ineffective, even with the use of multiple colors.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2022)
Article
Astronomy & Astrophysics
A. Marasco, B. M. Poggianti, J. Fritz, A. Werle, B. Vulcani, A. Moretti, M. Gullieuszik, A. Kulier
Summary: Research finds that, even without considering dynamic processes, the suppression of star formation in galaxies due to the harsh environment of a cluster can significantly impact the morphological evolution of the galaxy population over the course of a few billion years.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2023)
Article
Multidisciplinary Sciences
Jeonghyuk Park, Yul Ri Chung, Seo Taek Kong, Yeong Won Kim, Hyunho Park, Kyungdoc Kim, Dong-Il Kim, Kyu-Hwan Jung
Summary: Efforts have been made to diagnose cancer using deep learning on digital pathology images. Specialized neural network models for specific cohorts can achieve higher performance, but constructing annotated datasets and maintaining multiple cohort-specific models can be time-consuming and challenging.
SCIENTIFIC REPORTS
(2021)
Article
Astronomy & Astrophysics
Simon P. Driver, Sabine Bellstedt, Aaron S. G. Robotham, Ivan K. Baldry, Luke J. Davies, Jochen Liske, Danail Obreschkow, Edward N. Taylor, Angus H. Wright, Mehmet Alpaslan, Steven P. Bamford, Amanda E. Bauer, Joss Bland-Hawthorn, Maciej Bilicki, Matias Bravo, Sarah Brough, Sarah Casura, Michelle E. Cluver, Matthew Colless, Christopher J. Conselice, Scott M. Croom, Jelte de Jong, Franceso D'Eugenio, Roberto De Propris, Burak Dogruel, Michael J. Drinkwater, Andrej Dvornik, Daniel J. Farrow, Carlos S. Frenk, Benjamin Giblin, Alister W. Graham, Meiert W. Grootes, Madusha L. P. Gunawardhana, Abdolhosein Hashemizadeh, Boris Haeussler, Catherine Heymans, Hendrik Hildebrandt, Benne W. Holwerda, Andrew M. Hopkins, Tom H. Jarrett, D. Heath Jones, Lee S. Kelvin, Soheil Koushan, Konrad Kuijken, Maritza A. Lara-Lopez, Rebecca Lange, Angel R. Lopez-Sanchez, Jon Loveday, Smriti Mahajan, Martin Meyer, Amanda J. Moffett, Nicola R. Napolitano, Peder Norberg, Matt S. Owers, Mario Radovich, Mojtaba Raouf, John A. Peacock, Steven Phillipps, Kevin A. Pimbblet, Cristina Popescu, Khaled Said, Anne E. Sansom, Mark Seibert, Will J. Sutherland, Jessica E. Thorne, Richard J. Tuffs, Ryan Turner, Arjen van der Wel, Eelco van Kampen, Steve M. Wilkins
Summary: In the Galaxy And Mass Assembly Data Release 4 (GAMA DR4), a full spectroscopic redshift sample is provided, which includes 248,682 galaxy spectra and a total of 330,542 redshifts. This data set has the highest redshift density and high completeness, making it suitable for studying galaxy mergers, galaxy groups, and low redshift galaxy population. The release also includes additional measured and derived data products. The analysis of the data reveals the total galaxy stellar mass function and its subdivision by morphological class.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2022)
Article
Astronomy & Astrophysics
Yu-Ting Wu, Alfonso Trejo, Daniel Espada, Yusuke Miyamoto
Summary: This study utilized ALMA CO (2-1) data to investigate the double-barred galaxy NGC3504, revealing an inner molecular gas bar, a nuclear ring, and inner spiral arm-like structures. The CO emission in the outer bar region is aligned with the dust lanes, and the total molecular gas mass is estimated to be 17% of the stellar mass in the observed region.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2021)
Article
Astronomy & Astrophysics
Jonathan J. Davies, Robert A. Crain, Andrew Pontzen
Summary: The evolution of a simulated similar to L* galaxy is significantly influenced by the dark matter halo assembly history. Different assembly timings lead to systematic changes in the galaxy's present-day star formation rate, with delayed assembly resulting in higher star formation rates and accelerated assembly leading to quenching and spheroidal formation. The close coupling of central black hole growth and halo assembly drives these changes, with earlier assembly fostering more massive black hole formation and enhanced gas expulsion from the circumgalactic medium.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2021)
Article
Astronomy & Astrophysics
B. W. Holwerda, S. Phillipps, S. Weerasooriya, M. S. Bovill, S. Brough, M. J. Brown, C. Robertson, K. Cook
Summary: Groups of galaxies are important environments for the evolution of galaxies. This study combines the GAMA group catalogue with the xSAGA catalogue to investigate the satellite content of GAMA galaxy groups. Interesting results are found.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2023)
Article
Astronomy & Astrophysics
Hong Wang, Sreevarsha Sreejith, Ande Slosar, Yuewei Lin, Shinjae Yoo
Summary: This paper presents a new approach for deblending galaxy images in astronomical data using residual dense neural network (RDN) architecture. The approach utilizes two distinct neural networks to isolate individual galaxies and count the remaining number of galaxies, allowing for assessment of the deblending quality. The approach is compared to the industry standard and possible future extensions are discussed.
Article
Astronomy & Astrophysics
Rosie Y. Talbot, Martin A. Bourne, Debora Sijacki
Summary: Jets launched by active galactic nuclei have a significant impact on the properties of galaxies, especially in high-pressure environments. The efficiency of jet thermalization and the retention of momentum flux are influenced by the presence of recollimation shocks and instabilities. This novel AGN feedback model effectively regulates jet power evolution through black hole self-regulation and drives large-scale outflows in galaxies.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2021)
Article
Astronomy & Astrophysics
L. E. Garduno, M. A. Lara-Lopez, O. Lopez-Cruz, A. M. Hopkins, M. S. Owers, K. A. Pimbblet, B. W. Holwerda
Summary: The study of 4636 galaxy pairs reveals significant SFR enhancements compared to single pairs, while the impact of Z is minimal. Both major and minor pairs show considerable SFR enhancements, with the pair separation affecting the variation in Z. High-velocity dispersion and high multiplicity are factors leading to Z enhancements in minor pairs.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2021)
Article
Astronomy & Astrophysics
Ting-Yun Cheng, Christopher J. Conselice, Alfonso Aragon-Salamanca, Nan Li, Asa F. L. Bluck, Will G. Hartley, James Annis, David Brooks, Peter Doel, Juan Garcia-Bellido, David J. James, Kyler Kuehn, Nikolay Kuropatkin, Mathew Smith, Flavia Sobreira, Gregory Tarle
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2020)
Article
Astronomy & Astrophysics
Ting-Yun Cheng, Nan Li, Christopher J. Conselice, Alfonso Aragon-Salamanca, Simon Dye, Robert B. Metcalf
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2020)
Article
Astronomy & Astrophysics
Bela Abolfathi, David Alonso, Robert Armstrong, Eric Aubourg, Humna Awan, Yadu N. Babuji, Franz Erik Bauer, Rachel Bean, George Beckett, Rahul Biswas, Joanne R. Bogart, Dominique Boutigny, Kyle Chard, James Chiang, Chuck F. Claver, Johann Cohen-Tanugi, Celine Combet, Andrew J. Connolly, Scott F. Daniel, Seth W. Digel, Alex Drlica-Wagner, Richard Dubois, Emmanuel Gangler, Eric Gawiser, Thomas Glanzman, Phillipe Gris, Salman Habib, Andrew P. Hearin, Katrin Heitmann, Fabio Hernandez, Renee Hlozek, Joseph Hollowed, Mustapha Ishak, Zeljko Ivezic, Mike Jarvis, Saurabh W. Jha, Steven M. Kahn, J. Bryce Kalmbach, Heather M. Kelly, Eve Kovacs, Danila Korytov, K. Simon Krughoff, Craig S. Lage, Francois Lanusse, Patricia Larsen, Laurent Le Guillou, Nan Li, Emily Phillips Longley, Robert H. Lupton, Rachel Mandelbaum, Yao-Yuan Mao, Phil Marshall, Joshua E. Meyers, Marc Moniez, Christopher B. Morrison, Andrei Nomerotski, Paul O'Connor, HyeYun Park, Ji Won Park, Julien Peloton, Daniel Perrefort, James Perry, Stephane Plaszczynski, Adrian Pope, Andrew Rasmussen, Kevin Reil, Aaron J. Roodman, Eli S. Rykoff, F. Javier Sanchez, Samuel J. Schmidt, Daniel Scolnic, Christopher W. Stubbs, J. Anthony Tyson, Thomas D. Uram, Antonio Villarreal, Christopher W. Walter, Matthew P. Wiesner, W. Michael Wood-Vasey, Joe Zuntz
Summary: The simulated sky survey for the second data challenge (DC2) serves as preparation for the analysis of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) by the LSST Dark Energy Science Collaboration (LSST DESC). This modeling effort emphasizes interconnectivity across multiple science domains in a way that has not been tried before, covering a wide range of aspects from N-body simulation to image processing with LSST-like observations. The DC2 sky survey allows LSST DESC to develop analysis pipelines, test image processing software, and explore new scientific ideas in both static and time domain cosmology.
ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES
(2021)
Article
Astronomy & Astrophysics
Jacob Maresca, Simon Dye, Nan Li
Summary: This study examines a method using a Convolutional Neural Network to analyze lens modeling and source reconstruction, showcasing a significant reduction in unphysical source reconstructions by reinitializing the models based on CNN predictions.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2021)
Article
Astronomy & Astrophysics
J. D. Remolina Gonzalez, K. Sharon, N. Li, G. Mahler, L. E. Bleem, M. Gladders, A. Niemiec
Summary: The study evaluated the use of a single-halo model as an efficient method to estimate the strong lensing cluster core mass, finding that the projected core mass estimated with this method has a small scatter and bias compared to the true mass. Excluding models that fail visual inspection test can reduce the bias and scatter, while excluding single giant arc configurations can improve the accuracy of the model predictions. When the source redshift is unknown, the model-predicted redshifts are overestimated, underlining the importance of securing spectroscopic redshifts of background sources.
ASTROPHYSICAL JOURNAL
(2021)
Article
Astronomy & Astrophysics
Nan Li, Christoph Becker, Simon Dye
Summary: This paper investigates the impact of line-of-sight structures on time-delay measurements in strong lensing systems and concludes that lens modelling must incorporate multiple-lens planes to accurately infer H-0.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2021)
Article
Astronomy & Astrophysics
James Pearson, Jacob Maresca, Nan Li, Simon Dye
Summary: The study trains a CNN to predict mass profile parameters of galaxy-galaxy gravitational lenses, with significantly lower errors compared to traditional methods, especially when incorporating uncertainties predicted by the CNN. Combining neural networks with conventional techniques can greatly improve accuracy and speed in automated modelling.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2021)
Article
Astronomy & Astrophysics
J. D. Remolina Gonzalez, K. Sharon, G. Mahler, C. Fox, C. A. Garcia Diaz, K. Napier, L. E. Bleem, M. D. Gladders, N. Li, A. Niemiec
Summary: The core mass of galaxy clusters plays a crucial role in studying their structure formation. Efficient methods for estimating core mass are essential with the discovery of numerous strong lensing galaxy clusters. Advancements in observational techniques have improved the accuracy and depth of research on core mass in these clusters.
ASTROPHYSICAL JOURNAL
(2021)
Article
Astronomy & Astrophysics
Yang Han, Zhiqiang Zou, Nan Li, Yanli Chen
Summary: Studying astronomical outliers is crucial for discovering previously unknown knowledge. However, mining rare and unexpected targets from vast amounts of data is a significant challenge. In this study, unsupervised machine learning approaches were used to identify outliers in galaxy image data, leading to promising results.
RESEARCH IN ASTRONOMY AND ASTROPHYSICS
(2022)
Article
Astronomy & Astrophysics
Zizhao He, Nan Li
Summary: This study uses a machine learning algorithm to create a catalog of quasar candidates based on photometric data, providing priors for further object classification with spectroscopic data in the future. The catalog significantly reduces the workload for confirming quasars while maintaining high completeness.
RESEARCH IN ASTRONOMY AND ASTROPHYSICS
(2022)
Article
Astronomy & Astrophysics
Peng Jia, Ruiqi Sun, Nan Li, Yu Song, Runyu Ning, Hongyan Wei, Rui Luo
Summary: Strong lensing in galaxy clusters allows us to study dense cores of dark matter halos, explore the distant universe, and test cosmological models. We propose a framework using a transformer-based detection algorithm and image simulation to detect cluster-scale strongly lensed arcs. Our approach achieves high accuracy, recall, and precision rates in simulated images and can detect most strongly lensed arcs in real observation images. We plan to apply our approach to available observations and simulated data from upcoming large-scale sky surveys for further testing and validation.
ASTRONOMICAL JOURNAL
(2023)
Article
Astronomy & Astrophysics
Shoulin Wei, Yadi Li, Wei Lu, Nan Li, Bo Liang, Wei Dai, Zhijian Zhang
Summary: This paper proposes an approach based on contrastive learning to learn the visual representation of galaxy morphology using unlabeled data. By combining vision transformers and convolutional networks for feature extraction and fusion, rich semantic representation is provided. Experimental results show high accuracy in galaxy morphology classification and transferability and generalization ability of the proposed method.
PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC
(2022)
Article
Astronomy & Astrophysics
Zizhao He, Nan Li, Xiaoyue Cao, Rui Li, Hu Zou, Simon Dye
Summary: To better understand the origin of the Hubble tension, independent techniques like strong lensing time delays are needed. This study identified 620 new candidate multiply imaged lensed quasars within the DESI dataset, which will be further validated using spectroscopic and photometric data.
ASTRONOMY & ASTROPHYSICS
(2023)
Article
Astronomy & Astrophysics
J. D. Remolina Gonzalez, K. Sharon, B. Reed, N. Li, G. Mahler, L. E. Bleem, M. Gladders, A. Niemiec, A. Acebron, H. Child
ASTROPHYSICAL JOURNAL
(2020)