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49 results on '"Chakraborty, Srija"'

1. Global urban activity changes from COVID-19 physical distancing restrictions

Author

Chakraborty, Srija, Stokes, Eleanor, and Alexander, Olivia

Subjects
Physics - Physics and Society
Abstract

During the COVID-19 pandemic changes in human activity became widespread through official policies and organically in response to the virus's transmission, which in turn, impacted the environment and the economy. The pandemic has been described as a natural experiment that tested how social and economic disruptions impacted different components of the global Earth System. To move this beyond hypotheses, locally-resolved, globally-available measures of how, where, and when human activity changed are critically needed. Here we use satellite-derived nighttime lights to quantify and map daily changes in human activity that are atypical for each urban area globally for two years after the onset of the pandemic using machine learning anomaly detectors. Metrics characterizing changes in lights from pre-COVID baseline in human settlements and quality assurance measures are reported. This dataset, TRacking Anomalous COVID-19 induced changEs in NTL (TRACE-NTL), is the first to resolve COVID-19 disruptions for all metropolitan regions globally, daily. It is suitable to support a variety of post-pandemic studies that assess how changes in human activity impact environmental systems.

Published
2024

2. Towards A Comprehensive Assessment of AI's Environmental Impact

Author

Chakraborty, Srija

Subjects
Computer Science - Computers and Society
Abstract

Artificial Intelligence, machine learning (AI/ML) has allowed exploring solutions for a variety of environmental and climate questions ranging from natural disasters, greenhouse gas emission, monitoring biodiversity, agriculture, to weather and climate modeling, enabling progress towards climate change mitigation. However, the intersection of AI/ML and environment is not always positive. The recent surge of interest in ML, made possible by processing very large volumes of data, fueled by access to massive compute power, has sparked a trend towards large-scale adoption of AI/ML. This interest places tremendous pressure on natural resources, that are often overlooked and under-reported. There is a need for a framework that monitors the environmental impact and degradation from AI/ML throughout its lifecycle for informing policymakers, stakeholders to adequately implement standards and policies and track the policy outcome over time. For these policies to be effective, AI's environmental impact needs to be monitored in a spatially-disaggregated, timely manner across the globe at the key activity sites. This study proposes a methodology to track environmental variables relating to the multifaceted impact of AI around datacenters using openly available energy data and globally acquired satellite observations. We present a case study around Northern Virginia, United States that hosts a growing number of datacenters and observe changes in multiple satellite-based environmental metrics. We then discuss the steps to expand this methodology for comprehensive assessment of AI's environmental impact across the planet. We also identify data gaps and formulate recommendations for improving the understanding and monitoring AI-induced changes to the environment and climate.

Published
2024

3. Is GN-z11 powered by a super-Eddington massive black hole?

Author

Bhatt, Maulik, Gallerani, Simona, Ferrara, Andrea, Mazzucchelli, Chiara, D'Odorico, Valentina, Valentini, Milena, Zana, Tommaso, Farina, Emanuele Paolo, and Chakraborty, Srija

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Observations of $z \sim 6$ quasars powered by supermassive black holes (SMBHs; $M_{\rm BH} \sim 10^{8-10}\, M_\odot$) challenge our current understanding of early black hole (BH) formation and evolution. The advent of the James Webb Space Telescope (JWST) has enabled the study of massive BHs (MBHs; $M_{\rm BH}\sim 10^{6-7} \ \mathrm{M}_\odot$) up to $z\sim 11$, thus bridging the properties of $z\sim 6$ quasars to their ancestors. The JWST spectroscopic observations of GN-z11, a well-known $z=10.6$ star-forming galaxy, have been interpreted with the presence of a super-Eddington (Eddington ratio $\equiv \,\lambda_{\rm Edd}\sim 5.5$) accreting MBH. To test this hypothesis, we used a zoom-in cosmological simulation of galaxy formation and BH co-evolution. We first tested the simulation results against the observed probability distribution function (PDF) of $\lambda_{\rm Edd}$ found in $z\sim 6$ quasars. Then, in the simulation we selected the BHs that satisfy the following criteria: (a) $10 < z < 11 $, (b) $M_{\rm BH} > 10^6 \ \mathrm{M}_\odot$. Next, we apply the extreme value statistics to the PDF of $\lambda_{\rm Edd}$ resulting from the simulation and we find that the probability of observing a $z\sim 10-11$ MBH accreting with $\lambda_{\rm Edd} \sim 5.5$ in the volume surveyed by JWST is very low ($<0.2\%$). We compared our predictions with those in the literature, and discuss the main limitations of our work. Our simulation cannot explain the JWST observations of GN-z11. This might be due to (i) poor resolution and statistics in simulations, (ii) simplistic sub-grid models (e.g. BH accretion and seeding), (iii) uncertainties in the data analysis and interpretation., Comment: 8 pages, 2 figures; accepted for publication in A&A

Published
2024
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4. Adaptive Modeling of Satellite-Derived Nighttime Lights Time-Series for Tracking Urban Change Processes Using Machine Learning

Author

Chakraborty, Srija and Stokes, Eleanor C.

Subjects
Computer Science - Machine Learning
Abstract

Remotely sensed nighttime lights (NTL) uniquely capture urban change processes that are important to human and ecological well-being, such as urbanization, socio-political conflicts and displacement, impacts from disasters, holidays, and changes in daily human patterns of movement. Though several NTL products are global in extent, intrinsic city-specific factors that affect lighting, such as development levels, and social, economic, and cultural characteristics, are unique to each city, making the urban processes embedded in NTL signatures difficult to characterize, and limiting the scalability of urban change analyses. In this study, we propose a data-driven approach to detect urban changes from daily satellite-derived NTL data records that is adaptive across cities and effective at learning city-specific temporal patterns. The proposed method learns to forecast NTL signatures from past data records using neural networks and allows the use of large volumes of unlabeled data, eliminating annotation effort. Urban changes are detected based on deviations of observed NTL from model forecasts using an anomaly detection approach. Comparing model forecasts with observed NTL also allows identifying the direction of change (positive or negative) and monitoring change severity for tracking recovery. In operationalizing the model, we consider ten urban areas from diverse geographic regions with dynamic NTL time-series and demonstrate the generalizability of the approach for detecting the change processes with different drivers and rates occurring within these urban areas based on NTL deviation. This scalable approach for monitoring changes from daily remote sensing observations efficiently utilizes large data volumes to support continuous monitoring and decision making.

Published
2023
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5. Probing $z \gtrsim 6$ massive black holes with gravitational waves

Author

Chakraborty, Srija, Gallerani, Simona, Zana, Tommaso, Sesana, Alberto, Valentini, Milena, Izquierdo-Villalba, David, Di Mascia, Fabio, Vito, Fabio, and Barai, Paramita

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We investigate the coalescence of massive black hole ($M_{\rm BH}\gtrsim 10^{6}~\rm M_{\odot}$) binaries (MBHBs) at $63 \sigma$) overdense regions ($M_h\sim 10^{12}~\rm M_{\odot}$ dark matter halos at $z = 6$) of the Universe. We first analyse the impact of different resolutions and AGN feedback prescriptions on the merger rate, assuming instantaneous mergers. Then, we compute the halo bias correction factor due to the overdense simulated region. Our simulations predict merger rates that range between 3 - 15 $\rm yr^{-1}$ at $z\sim 6$, depending on the run considered, and after correcting for a bias factor of $\sim 20-30$. For our fiducial model, we further consider the effect of delay in the MBHB coalescence due to dynamical friction. We find that 83 per cent of MBHBs will merge within the Hubble time, and 21 per cent within 1 Gyr, namely the age of the Universe at $z > 6$. We finally compute the expected properties of the gravitational wave (GW) signals and find the fraction of LISA detectable events with high signal-to-noise ratio (SNR $>$ 5) to range between 66-69 per cent. However, identifying the electro-magnetic counterpart of these events remains challenging due to the poor LISA sky localization that, for the loudest signals ($\mathcal M_c\sim 10^6~\rm M_{\odot}$ at $z=6$), is around 10 $\rm deg^2$., Comment: 17 pages, 11 figures, 3 tables. Accepted for publication in MNRAS

Published
2023
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7. Astrophysics with the Laser Interferometer Space Antenna

Author

Seoane, Pau Amaro, Andrews, Jeff, Sedda, Manuel Arca, Askar, Abbas, Baghi, Quentin, Balasov, Razvan, Bartos, Imre, Bavera, Simone S., Bellovary, Jillian, Berry, Christopher P. L., Berti, Emanuele, Bianchi, Stefano, Blecha, Laura, Blondin, Stephane, Bogdanović, Tamara, Boissier, Samuel, Bonetti, Matteo, Bonoli, Silvia, Bortolas, Elisa, Breivik, Katelyn, Capelo, Pedro R., Caramete, Laurentiu, Cattorini, Federico, Charisi, Maria, Chaty, Sylvain, Chen, Xian, Chruślińska, Martyna, Chua, Alvin J. K., Church, Ross, Colpi, Monica, D'Orazio, Daniel, Danielski, Camilla, Davies, Melvyn B., Dayal, Pratika, De Rosa, Alessandra, Derdzinski, Andrea, Destounis, Kyriakos, Dotti, Massimo, Duţan, Ioana, Dvorkin, Irina, Fabj, Gaia, Foglizzo, Thierry, Ford, Saavik, Fouvry, Jean-Baptiste, Franchini, Alessia, Fragos, Tassos, Fryer, Chris, Gaspari, Massimo, Gerosa, Davide, Graziani, Luca, Groot, Paul, Habouzit, Melanie, Haggard, Daryl, Haiman, Zoltan, Han, Wen-Biao, Istrate, Alina, Johansson, Peter H., Khan, Fazeel Mahmood, Kimpson, Tomas, Kokkotas, Kostas, Kong, Albert, Korol, Valeriya, Kremer, Kyle, Kupfer, Thomas, Lamberts, Astrid, Larson, Shane, Lau, Mike, Liu, Dongliang, Lloyd-Ronning, Nicole, Lodato, Giuseppe, Lupi, Alessandro, Ma, Chung-Pei, Maccarone, Tomas, Mandel, Ilya, Mangiagli, Alberto, Mapelli, Michela, Mathis, Steéphane, Mayer, Lucio, McGee, Sean, McKernan, Berry, Miller, M. Coleman, Mota, David F., Mumpower, Matthew, Nasim, Syeda S, Nelemans, Gijs, Noble, Scott, Pacucci, Fabio, Panessa, Francesca, Paschalidis, Vasileio, Pfister, Hugo, Porquet, Delphine, Quenby, John, Ricarte, Angelo, Röpke, Friedrich K., Regan, John, Rosswog, Stephan, Ruiter, Ashley, Ruiz, Milton, Runnoe, Jessie, Schneider, Raffaella, Schnittman, Jeremy, Secunda, Amy, Sesana, Alberto, Seto, Naoki, Shao, Lijing, Shapiro, Stuart, Sopuerta, Carlos, Stone, Nicholas C., Suvorov, Arthur, Tamanini, Nicola, Tamfal, Tomas, Tauris, Thomas, Temmink, Karel, Tomsick, John, Toonen, Silvia, Torres-Orjuela, Alejandro, Toscani, Martina, Tsokaros, Antonios, Unal, Caner, Vázquez-Aceves, Verónica, Valiante, Rosa, van Putten, Maurice, van Roestel, Jan, Vignali, Christian, Volonteri, Marta, Wu, Kinwah, Younsi, Ziri, Yu, Shenghua, Zane, Silvia, Zwick, Lorenz, Antonini, Fabio, Baibhav, Vishal, Barausse, Enrico, Rivera, Alexander Bonilla, Branchesi, Marica, Branduardi-Raymont, Graziella, Burdge, Kevin, Chakraborty, Srija, Cuadra, Jorge, Dage, Kristen, Davis, Benjamin, de Mink, Selma E., Decarli, Roberto, Doneva, Daniela, Escoffier, Stephanie, Fragione, Giacomo, Gandhi, Poshak, Haardt, Francesco, Lousto, Carlos O., Nissanke, Samaya, Nordhaus, Jason, O'Shaughnessy, Richard, Zwart, Simon Portegies, Pound, Adam, Schussler, Fabian, Sergijenko, Olga, Spallicci, Alessandro, Vernieri, Daniele, and Vigna-Gómez, Alejandro

Subjects
General Relativity and Quantum Cosmology, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract

The Laser Interferometer Space Antenna (LISA) will be a transformative experiment for gravitational wave astronomy, and, as such, it will offer unique opportunities to address many key astrophysical questions in a completely novel way. The synergy with ground-based and space-born instruments in the electromagnetic domain, by enabling multi-messenger observations, will add further to the discovery potential of LISA. The next decade is crucial to prepare the astrophysical community for LISA's first observations. This review outlines the extensive landscape of astrophysical theory, numerical simulations, and astronomical observations that are instrumental for modeling and interpreting the upcoming LISA datastream. To this aim, the current knowledge in three main source classes for LISA is reviewed; ultracompact stellar-mass binaries, massive black hole binaries, and extreme or intermediate mass ratio inspirals. The relevant astrophysical processes and the established modeling techniques are summarized. Likewise, open issues and gaps in our understanding of these sources are highlighted, along with an indication of how LISA could help making progress in the different areas. New research avenues that LISA itself, or its joint exploitation with upcoming studies in the electromagnetic domain, will enable, are also illustrated. Improvements in modeling and analysis approaches, such as the combination of numerical simulations and modern data science techniques, are discussed. This review is intended to be a starting point for using LISA as a new discovery tool for understanding our Universe.

Published
2022
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10. Application of Machine Learning in understanding plant virus pathogenesis: Trends and perspectives on emergence, diagnosis, host-virus interplay and management

Author

Ghosh, Dibyendu, Chakraborty, Srija, Kodamana, Hariprasad, and Chakraborty, Supriya

Subjects
Computer Science - Machine Learning
Abstract

Inclusion of high throughput technologies in the field of biology has generated massive amounts of biological data in the recent years. Now, transforming these huge volumes of data into knowledge is the primary challenge in computational biology. The traditional methods of data analysis have failed to carry out the task. Hence, researchers are turning to machine learning based approaches for the analysis of high-dimensional big data. In machine learning, once a model is trained with a training dataset, it can be applied on a testing dataset which is independent. In current times, deep learning algorithms further promote the application of machine learning in several field of biology including plant virology. Considering a significant progress in the application of machine learning in understanding plant virology, this review highlights an introductory note on machine learning and comprehensively discusses the trends and prospects of machine learning in diagnosis of viral diseases, understanding host-virus interplay and emergence of plant viruses.

Published
2021

12. Astrophysics with the Laser Interferometer Space Antenna

Author

Amaro-Seoane, Pau, Andrews, Jeff, Arca Sedda, Manuel, Askar, Abbas, Baghi, Quentin, Balasov, Razvan, Bartos, Imre, Bavera, Simone S., Bellovary, Jillian, Berry, Christopher P. L., Berti, Emanuele, Bianchi, Stefano, Blecha, Laura, Blondin, Stéphane, Bogdanović, Tamara, Boissier, Samuel, Bonetti, Matteo, Bonoli, Silvia, Bortolas, Elisa, Breivik, Katelyn, Capelo, Pedro R., Caramete, Laurentiu, Cattorini, Federico, Charisi, Maria, Chaty, Sylvain, Chen, Xian, Chruślińska, Martyna, Chua, Alvin J. K., Church, Ross, Colpi, Monica, D’Orazio, Daniel, Danielski, Camilla, Davies, Melvyn B., Dayal, Pratika, De Rosa, Alessandra, Derdzinski, Andrea, Destounis, Kyriakos, Dotti, Massimo, Duţan, Ioana, Dvorkin, Irina, Fabj, Gaia, Foglizzo, Thierry, Ford, Saavik, Fouvry, Jean-Baptiste, Franchini, Alessia, Fragos, Tassos, Fryer, Chris, Gaspari, Massimo, Gerosa, Davide, Graziani, Luca, Groot, Paul, Habouzit, Melanie, Haggard, Daryl, Haiman, Zoltan, Han, Wen-Biao, Istrate, Alina, Johansson, Peter H., Khan, Fazeel Mahmood, Kimpson, Tomas, Kokkotas, Kostas, Kong, Albert, Korol, Valeriya, Kremer, Kyle, Kupfer, Thomas, Lamberts, Astrid, Larson, Shane, Lau, Mike, Liu, Dongliang, Lloyd-Ronning, Nicole, Lodato, Giuseppe, Lupi, Alessandro, Ma, Chung-Pei, Maccarone, Tomas, Mandel, Ilya, Mangiagli, Alberto, Mapelli, Michela, Mathis, Stéphane, Mayer, Lucio, McGee, Sean, McKernan, Berry, Miller, M. Coleman, Mota, David F., Mumpower, Matthew, Nasim, Syeda S., Nelemans, Gijs, Noble, Scott, Pacucci, Fabio, Panessa, Francesca, Paschalidis, Vasileios, Pfister, Hugo, Porquet, Delphine, Quenby, John, Ricarte, Angelo, Röpke, Friedrich K., Regan, John, Rosswog, Stephan, Ruiter, Ashley, Ruiz, Milton, Runnoe, Jessie, Schneider, Raffaella, Schnittman, Jeremy, Secunda, Amy, Sesana, Alberto, Seto, Naoki, Shao, Lijing, Shapiro, Stuart, Sopuerta, Carlos, Stone, Nicholas C., Suvorov, Arthur, Tamanini, Nicola, Tamfal, Tomas, Tauris, Thomas, Temmink, Karel, Tomsick, John, Toonen, Silvia, Torres-Orjuela, Alejandro, Toscani, Martina, Tsokaros, Antonios, Unal, Caner, Vázquez-Aceves, Verónica, Valiante, Rosa, van Putten, Maurice, van Roestel, Jan, Vignali, Christian, Volonteri, Marta, Wu, Kinwah, Younsi, Ziri, Yu, Shenghua, Zane, Silvia, Zwick, Lorenz, Antonini, Fabio, Baibhav, Vishal, Barausse, Enrico, Bonilla Rivera, Alexander, Branchesi, Marica, Branduardi-Raymont, Graziella, Burdge, Kevin, Chakraborty, Srija, Cuadra, Jorge, Dage, Kristen, Davis, Benjamin, de Mink, Selma E., Decarli, Roberto, Doneva, Daniela, Escoffier, Stephanie, Gandhi, Poshak, Haardt, Francesco, Lousto, Carlos O., Nissanke, Samaya, Nordhaus, Jason, O’Shaughnessy, Richard, Portegies Zwart, Simon, Pound, Adam, Schussler, Fabian, Sergijenko, Olga, Spallicci, Alessandro, Vernieri, Daniele, and Vigna-Gómez, Alejandro

Published
2023
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13. Tomatidine targets ATF4-dependent signaling and induces ferroptosis to limit pancreatic cancer progression

Author

Mukherjee, Debasmita, Chakraborty, Srija, Bercz, Lena, D’Alesio, Liliana, Wedig, Jessica, Torok, Molly A., Pfau, Timothy, Lathrop, Hannah, Jasani, Shrina, Guenther, Abigail, McGue, Jake, Adu-Ampratwum, Daniel, Fuchs, James R., Frankel, Timothy L., Pietrzak, Maciej, Culp, Stacey, Strohecker, Anne M., Skardal, Aleksander, and Mace, Thomas A.

Published
2023
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17. Abstract B097: Tomatidine inhibits ATF4 activity and induces ferroptosis to limit pancreatic cancer progression

Author

Mukherjee, Debasmita, primary, Chakraborty, Srija, additional, Bercz, Lena, additional, D’Alesio, Liliana, additional, Wedig, Jessica, additional, Torok, Molly A., additional, Pfau, Timothy, additional, Lathrop, Hannah, additional, Jasani, Shrina, additional, Guenther, Abigail, additional, McGue, Jake, additional, Adu-Ampratwum, Daniel, additional, Fuchs, James R., additional, Frankel, Timothy L., additional, Pietrzak, Maciej, additional, Culp, Stacey, additional, Strohecker, Anne M., additional, Skardal, Aleksander, additional, and Mace, Thomas A., additional

Published
2024
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18. Flower Pollination Algorithm-Based FIR Filter Design for Image Denoising

Author

Dhabal, Supriya, Chakraborty, Srija, Sikdar, Prosenjit, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Mandal, Jyotsna Kumar, editor, and Bhattacharya, Debika, editor

Published
2020
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22. Astrophysics with the Laser Interferometer Space Antenna

Author

Seoane, Pau Amaro, Andrews, Jeff, Sedda, Manuel Arca, Askar, Abbas, Baghi, Quentin, Balasov, Razvan, Bartos, Imre, Bavera, Simone S., Bellovary, Jillian, Berry, Christopher P. L., Berti, Emanuele, Bianchi, Stefano, Blecha, Laura, Blondin, Stephane, Bogdanović, Tamara, Boissier, Samuel, Bonetti, Matteo, Bonoli, Silvia, Bortolas, Elisa, Breivik, Katelyn, Capelo, Pedro R., Caramete, Laurentiu, Cattorini, Federico, Charisi, Maria, Chaty, Sylvain, Chen, Xian, Chruślińska, Martyna, Chua, Alvin J. K., Church, Ross, Colpi, Monica, D'Orazio, Daniel, Danielski, Camilla, Davies, Melvyn B., Dayal, Pratika, De Rosa, Alessandra, Derdzinski, Andrea, Destounis, Kyriakos, Dotti, Massimo, Duţan, Ioana, Dvorkin, Irina, Fabj, Gaia, Foglizzo, Thierry, Ford, Saavik, Fouvry, Jean-Baptiste, Franchini, Alessia, Fragos, Tassos, Fryer, Chris, Gaspari, Massimo, Gerosa, Davide, Graziani, Luca, Groot, Paul, Habouzit, Melanie, Haggard, Daryl, Haiman, Zoltan, Han, Wen-Biao, Istrate, Alina, Johansson, Peter H., Khan, Fazeel Mahmood, Kimpson, Tomas, Kokkotas, Kostas, Kong, Albert, Korol, Valeriya, Kremer, Kyle, Kupfer, Thomas, Lamberts, Astrid, Larson, Shane, Lau, Mike, Liu, Dongliang, Lloyd-Ronning, Nicole, Lodato, Giuseppe, Lupi, Alessandro, Ma, Chung-Pei, Maccarone, Tomas, Mandel, Ilya, Mangiagli, Alberto, Mapelli, Michela, Mathis, Steéphane, Mayer, Lucio, McGee, Sean, McKernan, Berry, Miller, M. Coleman, Mota, David F., Mumpower, Matthew, Nasim, Syeda S, Nelemans, Gijs, Noble, Scott, Pacucci, Fabio, Panessa, Francesca, Paschalidis, Vasileio, Pfister, Hugo, Porquet, Delphine, Quenby, John, Ricarte, Angelo, Röpke, Friedrich K., Regan, John, Rosswog, Stephan, Ruiter, Ashley, Ruiz, Milton, Runnoe, Jessie, Schneider, Raffaella, Schnittman, Jeremy, Secunda, Amy, Sesana, Alberto, Seto, Naoki, Shao, Lijing, Shapiro, Stuart, Sopuerta, Carlos, Stone, Nicholas C., Suvorov, Arthur, Tamanini, Nicola, Tamfal, Tomas, Tauris, Thomas, Temmink, Karel, Tomsick, John, Toonen, Silvia, Torres-Orjuela, Alejandro, Toscani, Martina, Tsokaros, Antonios, Unal, Caner, Vázquez-Aceves, Verónica, Valiante, Rosa, van Putten, Maurice, van Roestel, Jan, Vignali, Christian, Volonteri, Marta, Wu, Kinwah, Younsi, Ziri, Yu, Shenghua, Zane, Silvia, Zwick, Lorenz, Antonini, Fabio, Baibhav, Vishal, Barausse, Enrico, Rivera, Alexander Bonilla, Branchesi, Marica, Branduardi-Raymont, Graziella, Burdge, Kevin, Chakraborty, Srija, Cuadra, Jorge, Dage, Kristen, Davis, Benjamin, de Mink, Selma E., Decarli, Roberto, Doneva, Daniela, Escoffier, Stephanie, Fragione, Giacomo, Gandhi, Poshak, Haardt, Francesco, Lousto, Carlos O., Nissanke, Samaya, Nordhaus, Jason, O'Shaughnessy, Richard, Zwart, Simon Portegies, Pound, Adam, Schussler, Fabian, Sergijenko, Olga, Spallicci, Alessandro, Vernieri, Daniele, Vigna-Gómez, Alejandro, Amaro-Seoane, Pau, Andrews, Jeff, Arca Sedda, Manuel, Askar, Abba, Baghi, Quentin, Balasov, Razvan, Bartos, Imre, Bavera, Simone S., Bellovary, Jillian, Berry, Christopher P. L., Berti, Emanuele, Bianchi, Stefano, Blecha, Laura, Blondin, Stéphane, Bogdanović, Tamara, Boissier, Samuel, Bonetti, Matteo, Bonoli, Silvia, Bortolas, Elisa, Breivik, Katelyn, Capelo, Pedro R., Caramete, Laurentiu, Cattorini, Federico, Charisi, Maria, Chaty, Sylvain, Chen, Xian, Chruślińska, Martyna, Chua, Alvin J. K., Church, Ro, Colpi, Monica, D’Orazio, Daniel, Danielski, Camilla, Davies, Melvyn B., Dayal, Pratika, De Rosa, Alessandra, Derdzinski, Andrea, Destounis, Kyriako, Dotti, Massimo, Duţan, Ioana, Dvorkin, Irina, Fabj, Gaia, Foglizzo, Thierry, Ford, Saavik, Fouvry, Jean-Baptiste, Franchini, Alessia, Fragos, Tasso, Fryer, Chri, Gaspari, Massimo, Gerosa, Davide, Graziani, Luca, Groot, Paul, Habouzit, Melanie, Haggard, Daryl, Haiman, Zoltan, Han, Wen-Biao, Istrate, Alina, Johansson, Peter H., Khan, Fazeel Mahmood, Kimpson, Toma, Kokkotas, Kosta, Kong, Albert, Korol, Valeriya, Kremer, Kyle, Kupfer, Thoma, Lamberts, Astrid, Larson, Shane, Lau, Mike, Liu, Dongliang, Lloyd-Ronning, Nicole, Lodato, Giuseppe, Lupi, Alessandro, Ma, Chung-Pei, Maccarone, Toma, Mandel, Ilya, Mangiagli, Alberto, Mapelli, Michela, Mathis, Stéphane, Mayer, Lucio, Mcgee, Sean, Mckernan, Berry, Miller, M. Coleman, Mota, David F., Mumpower, Matthew, Nasim, Syeda S., Nelemans, Gij, Noble, Scott, Pacucci, Fabio, Panessa, Francesca, Paschalidis, Vasileio, Pfister, Hugo, Porquet, Delphine, Quenby, John, Ricarte, Angelo, Röpke, Friedrich K., Regan, John, Rosswog, Stephan, Ruiter, Ashley, Ruiz, Milton, Runnoe, Jessie, Schneider, Raffaella, Schnittman, Jeremy, Secunda, Amy, Sesana, Alberto, Seto, Naoki, Shao, Lijing, Shapiro, Stuart, Sopuerta, Carlo, Stone, Nicholas C., Suvorov, Arthur, Tamanini, Nicola, Tamfal, Toma, Tauris, Thoma, Temmink, Karel, Tomsick, John, Toonen, Silvia, Torres-Orjuela, Alejandro, Toscani, Martina, Tsokaros, Antonio, Unal, Caner, Vázquez-Aceves, Verónica, Valiante, Rosa, van Putten, Maurice, van Roestel, Jan, Vignali, Christian, Volonteri, Marta, Wu, Kinwah, Younsi, Ziri, Yu, Shenghua, Zane, Silvia, Zwick, Lorenz, Antonini, Fabio, Baibhav, Vishal, Barausse, Enrico, Bonilla Rivera, Alexander, Branchesi, Marica, Branduardi-Raymont, Graziella, Burdge, Kevin, Chakraborty, Srija, Cuadra, Jorge, Dage, Kristen, Davis, Benjamin, de Mink, Selma E., Decarli, Roberto, Doneva, Daniela, Escoffier, Stephanie, Gandhi, Poshak, Haardt, Francesco, Lousto, Carlos O., Nissanke, Samaya, Nordhaus, Jason, O’Shaughnessy, Richard, Portegies Zwart, Simon, Pound, Adam, Schussler, Fabian, Sergijenko, Olga, Spallicci, Alessandro, Vernieri, Daniele, Vigna-Gómez, Alejandro, Max Planck Institute for Gravitational Physics (Albert Einstein Institute) (AEI), Max-Planck-Gesellschaft, Institut de Ciencies de l'Espai [Barcelona] (ICE-CSIC), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Department of Physics, Columbia University, Columbia University [New York], Department of Physics and Astronomy [Nashville], Vanderbilt University [Nashville], Fisk University, Laboratoire d'Astrophysique de Marseille (LAM), Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Observatoire de la Côte d'Azur (OCA), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des deux Infinis de Toulouse (L2IT), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Institut d'Astrophysique de Paris (IAP), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre de Physique des Particules de Marseille (CPPM), Aix Marseille Université (AMU)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherches sur les lois Fondamentales de l'Univers (IRFU), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Amaro-Seoane, P, Andrews, J, Arca Sedda, M, Askar, A, Baghi, Q, Balasov, R, Bartos, I, Bavera, S, Bellovary, J, Berry, C, Berti, E, Bianchi, S, Blecha, L, Blondin, S, Bogdanović, T, Boissier, S, Bonetti, M, Bonoli, S, Bortolas, E, Breivik, K, Capelo, P, Caramete, L, Cattorini, F, Charisi, M, Chaty, S, Chen, X, Chruślińska, M, Chua, A, Church, R, Colpi, M, D’Orazio, D, Danielski, C, Davies, M, Dayal, P, De Rosa, A, Derdzinski, A, Destounis, K, Dotti, M, Duţan, I, Dvorkin, I, Fabj, G, Foglizzo, T, Ford, S, Fouvry, J, Franchini, A, Fragos, T, Fryer, C, Gaspari, M, Gerosa, D, Graziani, L, Groot, P, Habouzit, M, Haggard, D, Haiman, Z, Han, W, Istrate, A, Johansson, P, Khan, F, Kimpson, T, Kokkotas, K, Kong, A, Korol, V, Kremer, K, Kupfer, T, Lamberts, A, Larson, S, Lau, M, Liu, D, Lloyd-Ronning, N, Lodato, G, Lupi, A, Ma, C, Maccarone, T, Mandel, I, Mangiagli, A, Mapelli, M, Mathis, S, Mayer, L, Mcgee, S, Mckernan, B, Miller, M, Mota, D, Mumpower, M, Nasim, S, Nelemans, G, Noble, S, Pacucci, F, Panessa, F, Paschalidis, V, Pfister, H, Porquet, D, Quenby, J, Ricarte, A, Röpke, F, Regan, J, Rosswog, S, Ruiter, A, Ruiz, M, Runnoe, J, Schneider, R, Ministerio de Ciencia e Innovación (España), European Research Council, European Commission, Istituto Nazionale di Astrofisica, Agenzia Spaziale Italiana, and National Aeronautics and Space Administration (US)

Subjects
Astrofísica, ACTIVE GALACTIC NUCLEI, Cosmology and Nongalactic Astrophysics (astro-ph.CO), Physics and Astronomy (miscellaneous), Black hole, Astronomy, Stellar remnant, FOS: Physical sciences, General Relativity and Quantum Cosmology (gr-qc), TIDAL DISRUPTION EVENTS, General Relativity and Quantum Cosmology, Gravitational waves, MOCCA-SURVEY DATABASE, Settore FIS/05 - Astronomia e Astrofisica, Stellar remnants, Software Science, Multi-messenger, GRAVITATIONAL-WAVE SOURCES, Instrumentation and Methods for Astrophysics (astro-ph.IM), Extreme mass ratio in-spirals, Solar and Stellar Astrophysics (astro-ph.SR), High Energy Astrophysical Phenomena (astro-ph.HE), Black holes, Data Science, Astrophysics::Instrumentation and Methods for Astrophysics, Extreme mass ratio in-spiral, AM-CVN STARS, Astrophysics - Astrophysics of Galaxies, WHITE-DWARF BINARIES, DOUBLE NEUTRON-STARS, Astrophysics - Solar and Stellar Astrophysics, [SDU]Sciences of the Universe [physics], Astrophysics of Galaxies (astro-ph.GA), Astronomia, MASSIVE BLACK-HOLE, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics, X-RAY BINARIES, COMMON-ENVELOPE EVOLUTION, Gravitational wave, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Full list of authors: Amaro-Seoane, Pau; Andrews, Jeff; Sedda, Manuel Arca; Askar, Abbas.; Baghi, Quentin; Balasov, Razvan; Bartos, Imre; Bavera, Simone S.; Bellovary, Jillian; Berry, Christopher P. L.; Berti, Emanuele; Bianchi, Stefano; Blecha, Laura; Blondin, Stephane; Bogdanovic, Tamara; Boissier, Samuel; Bonetti, Matteo; Bonoli, Silvia; Bortolas, Elisa; Breivik, Katelyn; Capelo, Pedro R.; Caramete, Laurentiu; Cattorini, Federico; Charisi, Maria; Chaty, Sylvain; Chen, Xian; Chruslinska, Martyna; Chua, Alvin J. K.; Church, Ross; Colpi, Monica; D'Orazio, Daniel; Danielski, Camilla; Davies, Melvyn B.; Dayal, Pratika; De Rosa, Alessandra; Derdzinski, Andrea; Destounis, Kyriakos; Dotti, Massimo; Dutan, Ioana; Dvorkin, Irina; Fabj, Gaia; Foglizzo, Thierry; Ford, Saavik; Fouvry, Jean-Baptiste; Franchini, Alessia; Fragos, Tassos; Fryer, Chris; Gaspari, Massimo; Gerosa, Davide; Graziani, Luca; Groot, Paul; Habouzit, Melanie; Haggard, Daryl; Haiman, Zoltan; Han, Wen-Biao; Istrate, Alina; Johansson, Peter H.; Khan, Fazeel Mahmood; Kimpson, Tomas; Kokkotas, Kostas; Kong, Albert; Korol, Valeriya; Kremer, Kyle; Kupfer, Thomas; Lamberts, Astrid; Larson, Shane; Lau, Mike; Liu, Dongliang; Lloyd-Ronning, Nicole; Lodato, Giuseppe; Lupi, Alessandro; Ma, Chung-Pei; Maccarone, Tomas; Mandel, Ilya; Mangiagli, Alberto; Mapelli, Michela; Mathis, Stephane; Mayer, Lucio; McGee, Sean; McKernan, Berry; Miller, M. Coleman; Mota, David F.; Mumpower, Matthew; Nasim, Syeda S.; Nelemans, Gijs; Noble, Scott; Pacucci, Fabio; Panessa, Francesca; Paschalidis, Vasileios; Pfister, Hugo; Porquet, Delphine; Quenby, John; Ricarte, Angelo; Roepke, Friedrich K.; Regan, John; Rosswog, Stephan; Ruiter, Ashley; Ruiz, Milton; Runnoe, Jessie; Schneider, Raffaella; Schnittman, Jeremy; Secunda, Amy; Sesana, Alberto; Seto, Naoki; Shao, Lijing; Shapiro, Stuart; Sopuerta, Carlos; Stone, Nicholas C.; Suvorov, Arthur; Tamanini, Nicola; Tamfal, Tomas; Tauris, Thomas; Temmink, Karel; Tomsick, John; Toonen, Silvia; Torres-Orjuela, Alejandro; Toscani, Martina; Tsokaros, Antonios; Unal, Caner; Vazquez-Aceves, Veronica; Valiante, Rosa; van Putten, Maurice; van Roestel, Jan; Vignali, Christian; Volonteri, Marta; Wu, Kinwah; Younsi, Ziri; Yu, Shenghua; Zane, Silvia; Zwick, Lorenz; Antonini, Fabio; Baibhav, Vishal; Barausse, Enrico; Bonilla Rivera, Alexander; Branchesi, Marica; Branduardi-Raymont, Graziella; Burdge, Kevin; Chakraborty, Srija; Cuadra, Jorge; Dage, Kristen; Davis, Benjamin; de Mink, Selma E.; Decarli, Roberto; Doneva, Daniela; Escoffier, Stephanie; Gandhi, Poshak; Haardt, Francesco; Lousto, Carlos O.; Nissanke, Samaya; Nordhaus, Jason; O'Shaughnessy, Richard; Portegies Zwart, Simon; Pound, Adam; Schussler, Fabian; Sergijenko, Olga; Spallicci, Alessandro; Vernieri, Daniele; Vigna-Gomez, Alejandro.-- This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/., The Laser Interferometer Space Antenna (LISA) will be a transformative experiment for gravitational wave astronomy, and, as such, it will offer unique opportunities to address many key astrophysical questions in a completely novel way. The synergy with ground-based and space-born instruments in the electromagnetic domain, by enabling multi-messenger observations, will add further to the discovery potential of LISA. The next decade is crucial to prepare the astrophysical community for LISA’s first observations. This review outlines the extensive landscape of astrophysical theory, numerical simulations, and astronomical observations that are instrumental for modeling and interpreting the upcoming LISA datastream. To this aim, the current knowledge in three main source classes for LISA is reviewed; ultra-compact stellar-mass binaries, massive black hole binaries, and extreme or interme-diate mass ratio inspirals. The relevant astrophysical processes and the established modeling techniques are summarized. Likewise, open issues and gaps in our understanding of these sources are highlighted, along with an indication of how LISA could help making progress in the different areas. New research avenues that LISA itself, or its joint exploitation with upcoming studies in the electromagnetic domain, will enable, are also illustrated. Improvements in modeling and analysis approaches, such as the combination of numerical simulations and modern data science techniques, are discussed. This review is intended to be a starting point for using LISA as a new discovery tool for understanding our Universe. © The Author(s) 2023, corrected publication 2023., P. Dayal acknowledges support from the European Research council (ERC-717001) and from the Netherlands Research Council NWO (016.VIDI.189.162). P.H. Johansson acknowledges the support from the European Research Council (ERC-818930). S. Toonen acknowledges support from the Netherlands Research Council NWO (VENI 639.041.645 Grants) C. Unal is supported by European Structural and Investment Funds and the Czech Ministry of Education, Youth and Sports (Project CoGraDS - CZ.02.1.01/0.0/0.0/15_003/0000437). S. Chaty acknowledges the LabEx UnivEarthS for the funding of Interface project I10 “From binary evolution towards merging of compact objects”. A. De Rosa acknowledges financial contribution from the agreement ASI-INAF n.2017-14-H.O E. Berti is supported by NSF Grants No. PHY-1912550 and AST-2006538, NASA ATP Grants No. 17-ATP17-0225 and 19-ATP19-0051, NSF-XSEDE Grant No. PHY-090003, and NSF Grant PHY-20043. D. Gerosa is supported by European Union’s H2020 ERC Starting Grant No. 945155–GWmining, Leverhulme Trust Grant No. RPG-2019-350 and Royal Society Grant No. RGS-R2-202004. T. Bogdanovic acknowledges support by the NASA award No. 80NSSC19K0319 and by the NSF award AST-1908042. D. Porquet acknowledges funding support from CNES. C. Danielski acknowledges financial support from the State Agency for Research of the Spanish MCIU through the “Center of Excellence Severo Ochoa” award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709) B.L. Davis acknowledges support from Tamkeen under the NYU Abu Dhabi Research Institute Grant CAP3. F. Pacucci acknowledges support from a Clay Fellowship by the SAO and from the Black Hole Initiative, which is funded by grants from the John Templeton Foundation and the Gordon and Betty Moore Foundation. A.J. Ruiter acknowledges support from the Australian Research Council Future Fellowship Grant FT170100243. V. Paschalidis is supported by NSF Grant PHY-1912619 and NASA Grant 80NSSC20K1542 to the University of Arizona, and NSF-XSEDE Grant TG-PHY190020. D. Haggard acknowledges support from the NSERC Discovery Grant and Canada Research Chairs programs, and the Bob Wares Science Innovation Prospectors Fund. M. Toscani acknowledges European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant Agreement No. 823823 (RISE DUSTBUSTERS project) and COST Action CA16104 - Gravitational waves, black holes and fundamental physics, supported by COST (European Cooperation in Science and Technology). M. Chruslinska, A. Istrate and G. Nelemans acknowledge support from Netherlands Research Council NWO. T. Fragos and S. Bavera acknowledge support from a Swiss National Science Foundation Professorship Grant (project numbers PP00P2_176868 and PP00P2_211006)., With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).

Published
2023

25. Responsive Onboard Science for Europa Clipper

Author

Doran, Gary, Wagstaff, Kiri L, Davies, Ashley G, Chien, Steve A, Chakraborty, Srija, Cameron, Marissa, Wissler, Steve, Chritensen, Phil, Anwar, Saadat, Piqueux, Sylvain, Daubar, Ingrid, and Cochrane, Corey

Published
2020

26. Responsive Onboard Science for Europa Clipper

Author

Cochrane, Corey, Daubar, Ingrid, Piqueux, Sylvain, Anwar, Saadat, Chritensen, Phil, Wissler, Steve, Cameron, Marissa, Chakraborty, Srija, Chien, Steve A, Davies, Ashley G, Wagstaff, Kiri L, and Doran, Gary

Abstract

UNKNOWN

Published
2020

31. Spectral anomaly detection for the Mapping and Imaging Spectrometer for Europa (MISE)

Author

Doran, Gary, Diniega, Serina, Davies, Ashley, Chien, Steve, Chakraborty, Srija, Blaney, Diana L, and Wagstaff, Kiri L

Abstract

We are exploring software advances that would enable Clipper to collect additional data, analyze it onboard to assign downlink priorities,and potentially increase science return without increasing downlink consumption.

Published
2019

34. Astrophysics with the Laser Interferometer Space Antenna

Author

Amaro-Seoane, Pau, Andrews, Jeff, Sedda, Manuel Arca, Askar, Abbas, Balasov, Razvan, Bartos, Imre, Bavera, Simone S., Bellovary, Jillian, Berry, Christopher P. L., Berti, Emanuele, Bianchi, Stefano, Blecha, Laura, Blondin, Stéphane, Bogdanović, Tamara, Boissier, Samuel, Bonetti, Matteo, Bonoli, Silvia, Bortolas, Elisa, Breivik, Katie, Capelo, Pedro R., Caramete, Laurentiu, Catorini, Federico, Charisi, Maria, Chaty, Sylvain, Chen, Xian, Chruślińska, Martyna, Chua, Alvin J. K., Church, Ross, Colpi, Monica, D'Orazio, Daniela, Danielski, Camilla, Davies, Melvyn B., Dayal, Pratika, De Rosa, Alessandra, Derdzinski, Andrea, Destounis, Kyriakos, Dotti, Massimo, Duţan, Ioana, Dvorkin, Irina, Fabj, Gaia, Foglizzo, Thierry, Ford, Saavik, Fouvry, Jean-Baptiste, Fragkos, Tassos, Fryer, Chris, Gaspari, Massimo, Gerosa, Davide, Graziani, Luca, Groot, Paul J., Habouzit, Melanie, Haggard, Daryl, Haiman, Zoltan, Han, Wen-Biao, Istrate, Alina, Johansson, Peter H., Khan, Fazeel Mahmood, Kimpson, Tomas, Kokkotas, Kostas, Kong, Albert, Korol, Valeriya, Kremer, Kyle, Kupfer, Thomas, Lamberts, Astrid, Larson, Shane, Lau, Mike, Liu, Dongliang, Lloyd-Ronning, Nicole, Lodato, Giuseppe, Lupi, Alessandro, Ma, Chung-Pei, Maccarone, Tomas, Mandel, Ilya, Mangiagli, Alberto, Mapelli, Michela, Mathis, Stefan, Mayer, Lucio, McGee, Sean, McKernan, Berry, Miller, M. Coleman, Mota, David F., Mumpower, Matthew, Nasim, Syeda S., Nelemans, Gijs, Noble, Scott, Pacucci, Fabio, Panessa, Francesca, Paschalidis, Vasileios, Pfister, Hugo, Porquet, Delphine, Quenby, John, Röpke, Fritz, Regan, John, Rosswog, Stephan, Ruiter, Ashley, Ruiz, Milton, Runnoe, Jessie, Schneider, Rafaella, Schnittman, Jeremy, Secunda, Amy, Sesana, Alberto, Seto, Naoki, Shao, Lijing, Shapiro, Stuart, Sopuerta, Carlos, Stone, Nick, Suvorov, Arthur, Tamanini, Nicola, Tamfal, Tomas, Tauris, Thomas, Temmink, Karel, Tomsick, John, Toonen, Silvia, Torres-Orjuela, Alejandro, Toscani, Martina, Tsokaros, Antonios, Unal, Caner, Vázquez-Aceves, Verónica, Valiante, Rosa, van Putten, Maurice, van Roestel, Jan, Vignali, Christian, Volonteri, Marta, Wu, Kinwah, Younsi, Ziri, Yu, Shenghua, Zane, Silvia, Zwick, Lorenz, Antonini, Fabio, Baibhav, Vishal, Barausse, Enrico, Rivera, Alexander Bonilla, Branchesi, Marica, Branduardi-Raymont, Graziella, Burdge, Kevin, Chakraborty, Srija, Cuadra, Jorge, Dage, Kristen, Davis, Benjamin, de Mink, Selma E., Decarli, Roberto, Doneva, Daniela, Escoffier, Stephanie, Gandhi, Poshak, Haardt, Francesco, Lousto, Carlos O., Nissanke, Samaya, Nordhaus, Jason, O'Shaughnessy, Richard, Zwart, Simon Portegies, Pound, Adam, Schussler, Fabian, Sergijenko, Olga, Spallicci, Alessandro, Vernieri, Daniele, Vigna-Gómez, Alejandro, Amaro-Seoane, Pau, Andrews, Jeff, Sedda, Manuel Arca, Askar, Abbas, Balasov, Razvan, Bartos, Imre, Bavera, Simone S., Bellovary, Jillian, Berry, Christopher P. L., Berti, Emanuele, Bianchi, Stefano, Blecha, Laura, Blondin, Stéphane, Bogdanović, Tamara, Boissier, Samuel, Bonetti, Matteo, Bonoli, Silvia, Bortolas, Elisa, Breivik, Katie, Capelo, Pedro R., Caramete, Laurentiu, Catorini, Federico, Charisi, Maria, Chaty, Sylvain, Chen, Xian, Chruślińska, Martyna, Chua, Alvin J. K., Church, Ross, Colpi, Monica, D'Orazio, Daniela, Danielski, Camilla, Davies, Melvyn B., Dayal, Pratika, De Rosa, Alessandra, Derdzinski, Andrea, Destounis, Kyriakos, Dotti, Massimo, Duţan, Ioana, Dvorkin, Irina, Fabj, Gaia, Foglizzo, Thierry, Ford, Saavik, Fouvry, Jean-Baptiste, Fragkos, Tassos, Fryer, Chris, Gaspari, Massimo, Gerosa, Davide, Graziani, Luca, Groot, Paul J., Habouzit, Melanie, Haggard, Daryl, Haiman, Zoltan, Han, Wen-Biao, Istrate, Alina, Johansson, Peter H., Khan, Fazeel Mahmood, Kimpson, Tomas, Kokkotas, Kostas, Kong, Albert, Korol, Valeriya, Kremer, Kyle, Kupfer, Thomas, Lamberts, Astrid, Larson, Shane, Lau, Mike, Liu, Dongliang, Lloyd-Ronning, Nicole, Lodato, Giuseppe, Lupi, Alessandro, Ma, Chung-Pei, Maccarone, Tomas, Mandel, Ilya, Mangiagli, Alberto, Mapelli, Michela, Mathis, Stefan, Mayer, Lucio, McGee, Sean, McKernan, Berry, Miller, M. Coleman, Mota, David F., Mumpower, Matthew, Nasim, Syeda S., Nelemans, Gijs, Noble, Scott, Pacucci, Fabio, Panessa, Francesca, Paschalidis, Vasileios, Pfister, Hugo, Porquet, Delphine, Quenby, John, Röpke, Fritz, Regan, John, Rosswog, Stephan, Ruiter, Ashley, Ruiz, Milton, Runnoe, Jessie, Schneider, Rafaella, Schnittman, Jeremy, Secunda, Amy, Sesana, Alberto, Seto, Naoki, Shao, Lijing, Shapiro, Stuart, Sopuerta, Carlos, Stone, Nick, Suvorov, Arthur, Tamanini, Nicola, Tamfal, Tomas, Tauris, Thomas, Temmink, Karel, Tomsick, John, Toonen, Silvia, Torres-Orjuela, Alejandro, Toscani, Martina, Tsokaros, Antonios, Unal, Caner, Vázquez-Aceves, Verónica, Valiante, Rosa, van Putten, Maurice, van Roestel, Jan, Vignali, Christian, Volonteri, Marta, Wu, Kinwah, Younsi, Ziri, Yu, Shenghua, Zane, Silvia, Zwick, Lorenz, Antonini, Fabio, Baibhav, Vishal, Barausse, Enrico, Rivera, Alexander Bonilla, Branchesi, Marica, Branduardi-Raymont, Graziella, Burdge, Kevin, Chakraborty, Srija, Cuadra, Jorge, Dage, Kristen, Davis, Benjamin, de Mink, Selma E., Decarli, Roberto, Doneva, Daniela, Escoffier, Stephanie, Gandhi, Poshak, Haardt, Francesco, Lousto, Carlos O., Nissanke, Samaya, Nordhaus, Jason, O'Shaughnessy, Richard, Zwart, Simon Portegies, Pound, Adam, Schussler, Fabian, Sergijenko, Olga, Spallicci, Alessandro, Vernieri, Daniele, and Vigna-Gómez, Alejandro

Abstract

Laser Interferometer Space Antenna (LISA) will be a transformative experiment for gravitational wave astronomy as it will offer unique opportunities to address many key astrophysical questions in a completely novel way. The synergy with ground-based and other space-based instruments in the electromagnetic domain, by enabling multi-messenger observations, will add further to the discovery potential of LISA. The next decade is crucial to prepare the astrophysical community for LISA's first observations. This review outlines the extensive landscape of astrophysical theory, numerical simulations, and astronomical observations that are instrumental for modeling and interpreting the upcoming LISA datastream. To this aim, the current knowledge in three main source classes for LISA is reviewed: ultra-compact stellar-mass binaries, massive black hole binaries, and extreme or intermediate mass ratio inspirals. The relevant astrophysical processes and the established modeling techniques are summarized. Likewise, open issues and gaps in our understanding of these sources are highlighted, along with an indication of how LISA could help make progress in the different areas. New research avenues that LISA itself, or its joint exploitation with studies in the electromagnetic domain, will enable, are also illustrated. Improvements in modeling and analysis approaches, such as the combination of numerical simulations and modern data science techniques, are discussed. This review is intended to be a starting point for using LISA as a new discovery tool for understanding our Universe., Comment: submitted to Living Reviews In Relativity

Published
2022

35. Native human collagen type I provides a viable physiologically relevant alternative to xenogeneic sources for tissue engineering applications: A comparative in vitro and in vivo study

Author

Baltazar, Tânia, primary, Kajave, Nilabh S., additional, Rodriguez, Marco, additional, Chakraborty, Srija, additional, Jiang, Bo, additional, Skardal, Aleksander, additional, Kishore, Vipuil, additional, Pober, Jordan S., additional, and Albanna, Mohammad Z., additional

Published
2022
Full Text
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37. Earth and Space Science Informatics Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

Author

Hills, Denise, primary, Damerow, Joan, additional, Ahmmed, Bulbul, additional, Catolico, Nora, additional, Chakraborty, Srija, additional, Coward, Caroline, additional, Crystal-Ornelas, Robert, additional, Duncan, William, additional, Goparaju, Laxmi, additional, Lin, Cindy, additional, Liu, Zhong, additional, Mudunuru, Maruti, additional, Rao, Yuhan, additional, Rovetto, Robert, additional, Sun, Ziheng, additional, Whitehead, Brandon, additional, Wyborn, Lesley, additional, and Yao, Tian, additional

Published
2022
Full Text
View/download PDF

39. Earth and Space Science Informatics Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

Author

Hills, Denise, primary, Damerow, Joan, additional, Ahmmed, Bulbul, additional, Catolico, Nora, additional, Chakraborty, Srija, additional, Coward, Caroline, additional, Crystal-Ornelas, Robert, additional, Duncan, William, additional, Goparaju, Laxmi, additional, Lin, Cindy, additional, Liu, Zhong, additional, Mudunuru, Maruti, additional, Rao, Yuhan, additional, Rovetto, Robert, additional, Sun, Ziheng, additional, Whitehead, Brandon, additional, Wyborn, Lesley, additional, and Yao, Tian, additional

Published
2021
Full Text
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40. US Cities in the Dark

Author

Oda, Tomohiro, primary, Román, Miguel O., additional, Wang, Zhuosen, additional, Stokes, Eleanor C., additional, Sun, Qingsong, additional, Shrestha, Ranjay M., additional, Feng, Sha, additional, Lauvaux, Thomas, additional, Bun, Rostyslav, additional, Maksyutov, Shamil, additional, Chakraborty, Srija, additional, Paynter, Ian, additional, and Kalb, Virginia L., additional

Published
2021
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