Constraints on charged black holes from merger-ringdown signals in GWTC-3 and prospects for the Einstein Telescope

Kavli Affiliate: Lijing Shao | First 5 Authors: Hua-Peng Gu, Hai-Tian Wang, Lijing Shao, , | Summary: Whether astrophysical black holes (BHs) can have charge is a question to be addressed by observations. In the era of gravitational wave (GW) astronomy, one can constrain the charge of a merged BH remnant using the merger-ringdown signal […]


Continue.. Constraints on charged black holes from merger-ringdown signals in GWTC-3 and prospects for the Einstein Telescope

Till the core collapses: the evolution and properties of self-interacting dark matter subhalos

Zhichao Carton Zeng, Annika H. G. Peter, Xiaolong Du, Shengqi Yang, Andrew Benson | Summary: [[{“value”:”One of the hottest questions in the cosmology of self-interacting dark matter (SIDM) is whether scatterings can induce detectable core-collapse in halos by the present day. Because gravitational tides can accelerate core-collapse, the most promising targets to observe core-collapse are […]


Continue.. Till the core collapses: the evolution and properties of self-interacting dark matter subhalos

Till the core collapses: the evolution and properties of self-interacting dark matter subhalos

Zhichao Carton Zeng, Annika H. G. Peter, Xiaolong Du, Shengqi Yang, Andrew Benson | Summary: [[{“value”:”One of the hottest questions in the cosmology of self-interacting dark matter (SIDM) is whether scatterings can induce detectable core-collapse in halos by the present day. Because gravitational tides can accelerate core-collapse, the most promising targets to observe core-collapse are […]


Continue.. Till the core collapses: the evolution and properties of self-interacting dark matter subhalos

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

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

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

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

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

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 […]


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

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

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