JWST-TST High Contrast: Achieving direct spectroscopy of faint substellar companions next to bright stars with the NIRSpec IFU

Posted by dbos MIT

Kavli Affiliate: Sara Seager | First 5 Authors: Jean-Baptiste Ruffio, Marshall D. Perrin, Kielan K. W. Hoch, Jens Kammerer, Quinn M. Konopacky | Summary: The JWST NIRSpec integral field unit (IFU) presents a unique opportunity to observe directly imaged exoplanets from 3-5um at moderate spectral resolution (R~2,700) and thereby better constrain the composition, disequilibrium chemistry, […]


Continue.. JWST-TST High Contrast: Achieving direct spectroscopy of faint substellar companions next to bright stars with the NIRSpec IFU

JWST-TST High Contrast: Achieving direct spectroscopy of faint substellar companions next to bright stars with the NIRSpec IFU

Posted by dbos MIT

Kavli Affiliate: Sara Seager | First 5 Authors: Jean-Baptiste Ruffio, Marshall D. Perrin, Kielan K. W. Hoch, Jens Kammerer, Quinn M. Konopacky | Summary: The JWST NIRSpec integral field unit (IFU) presents a unique opportunity to observe directly imaged exoplanets from 3-5 um at moderate spectral resolution (R~2,700) and thereby better constrain the composition, disequilibrium […]


Continue.. JWST-TST High Contrast: Achieving direct spectroscopy of faint substellar companions next to bright stars with the NIRSpec IFU

Federated Multi-Objective Learning

Posted by dbos Tokyo

Kavli Affiliate: Jia Liu | First 5 Authors: Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma | Summary: In recent years, multi-objective optimization (MOO) emerges as a foundational problem underpinning many multi-agent multi-task learning applications. However, existing algorithms in MOO literature remain limited to centralized learning settings, which do not satisfy the distributed […]


Continue.. Federated Multi-Objective Learning

Federated Multi-Objective Learning

Posted by dbos Tokyo

Kavli Affiliate: Jia Liu | First 5 Authors: Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma | Summary: In recent years, multi-objective optimization (MOO) emerges as a foundational problem underpinning many multi-agent multi-task learning applications. However, existing algorithms in MOO literature remain limited to centralized learning settings, which do not satisfy the distributed […]


Continue.. Federated Multi-Objective Learning

Federated Multi-Objective Learning

Posted by dbos Tokyo

Kavli Affiliate: Jia Liu | First 5 Authors: Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma | Summary: In recent years, multi-objective optimization (MOO) emerges as a foundational problem underpinning many multi-agent multi-task learning applications. However, existing algorithms in MOO literature remain limited to centralized learning settings, which do not satisfy the distributed […]


Continue.. Federated Multi-Objective Learning

Exploring the Dependence of Gas Cooling and Heating Functions on the Incident Radiation Field with Machine Learning

Posted by Chicago

Kavli Affiliate: Nickolay Y. Gnedin | First 5 Authors: David Robinson, Camille Avestruz, Nickolay Y. Gnedin, , | Summary: Gas cooling and heating functions play a crucial role in galaxy formation. But, it is computationally expensive to exactly compute these functions in the presence of an incident radiation field. These computations can be greatly sped […]


Continue.. Exploring the Dependence of Gas Cooling and Heating Functions on the Incident Radiation Field with Machine Learning

Unraveling emission line galaxy conformity at z~1 with DESI early data

Posted by dbos Stanford

Kavli Affiliate: Risa H. Wechsler | First 5 Authors: Sihan Yuan, Risa H. Wechsler, Yunchong Wang, Mithi A. C. de los Reyes, Justin Myles | Summary: Emission line galaxies (ELGs) are now the preeminent tracers of large-scale structure at z>0.8 due to their high density and strong emission lines, which enable accurate redshift measurements. However, […]


Continue.. Unraveling emission line galaxy conformity at z~1 with DESI early data

Exploring the Dependence of Gas Cooling and Heating Functions on the Incident Radiation Field with Machine Learning

Posted by Chicago

Kavli Affiliate: Nickolay Y. Gnedin | First 5 Authors: David Robinson, Camille Avestruz, Nickolay Y. Gnedin, , | Summary: Gas cooling and heating functions play a crucial role in galaxy formation. But, it is computationally expensive to exactly compute these functions in the presence of an incident radiation field. These computations can be greatly sped […]


Continue.. Exploring the Dependence of Gas Cooling and Heating Functions on the Incident Radiation Field with Machine Learning

TOI-5126: A hot super-Neptune and warm Neptune pair discovered by $textit{TESS}$ and $textit{CHEOPS}$

Posted by dbos MIT

Kavli Affiliate: Sara Seager | First 5 Authors: Tyler R. Fairnington, Emma Nabbie, Chelsea X. Huang, George Zhou, Orion Foo | Summary: We present the confirmation of a hot super-Neptune with an exterior Neptune companion orbiting a bright (V = 10.1 mag) F-dwarf identified by the $textit{Transiting Exoplanet Survey Satellite}$ ($textit{TESS}$). The two planets, observed […]


Continue.. TOI-5126: A hot super-Neptune and warm Neptune pair discovered by $textit{TESS}$ and $textit{CHEOPS}$