Single electron Sensitive Readout (SiSeRO) X-ray detectors: Technological progress and characterization

Kavli Affiliate: Richard Foster | First 5 Authors: Tanmoy Chattopadhyay, Sven Herrmann, Peter Orel, R. G. Morris, Daniel R. Wilkins | Summary: Single electron Sensitive Read Out (SiSeRO) is a novel on-chip charge detector output stage for charge-coupled device (CCD) image sensors. Developed at MIT Lincoln Laboratory, this technology uses a p-MOSFET transistor with a […]


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2022 Upgrade and Improved Low Frequency Camera Sensitivity for CMB Observation at the South Pole

Kavli Affiliate: Chao-Lin Kuo | First 5 Authors: A. Soliman, P. A. R. Ade, Z. Ahmed, M. Amiri, D. Barkats | Summary: Constraining the Galactic foregrounds with multi-frequency Cosmic Microwave Background (CMB) observations is an essential step towards ultimately reaching the sensitivity to measure primordial gravitational waves (PGWs), the sign of inflation after the Big-Bang […]


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Robust Clustering of the Local Milky Way Stellar Kinematic Substructures with Gaia eDR3

Kavli Affiliate: Anna Frebel | First 5 Authors: Xiaowei Ou, Lina Necib, Anna Frebel, , | Summary: We apply the clustering algorithm HDBSCAN on the Gaia early third data release astrometry combined with the Gaia second data release radial velocity measurements of almost 5.5 million stars to identify the local stellar kinematic substructures in the […]


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Composable Text Control Operations in Latent Space with Ordinary Differential Equations

Kavli Affiliate: Feng Yuan | First 5 Authors: Guangyi Liu, Zeyu Feng, Yuan Gao, Zichao Yang, Xiaodan Liang | Summary: Real-world text applications often involve composing a wide range of text control operations, such as editing the text w.r.t. an attribute, manipulating keywords and structure, and generating new text of desired properties. Prior work typically […]


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Composable Text Controls in Latent Space with ODEs

Kavli Affiliate: Feng Yuan | First 5 Authors: Guangyi Liu, Zeyu Feng, Yuan Gao, Zichao Yang, Xiaodan Liang | Summary: Real-world text applications often involve composing a wide range of text control operations, such as editing the text w.r.t. an attribute, manipulating keywords and structure, and generating new text of desired properties. Prior work typically […]


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Newly discovered $zsim5$ quasars based on deep learning and Bayesian information criterion

Kavli Affiliate: Linhua Jiang | First 5 Authors: Suhyun Shin, Myungshin Im, Yongjung Kim, Linhua Jiang, | Summary: We report the discovery of four quasars with $M_{1450} gtrsim -25.0$ mag at $zsim5$ and supermassive black hole mass measurement for one of the quasars. They were selected as promising high-redshift quasar candidates via deep learning and […]


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Conserved charges in the quantum simulation of integrable spin chains

Kavli Affiliate: Masahito Yamazaki | First 5 Authors: Kazunobu Maruyoshi, Takuya Okuda, Juan William Pedersen, Ryo Suzuki, Masahito Yamazaki | Summary: When simulating the time evolution of quantum many-body systems on a digital quantum computer, one faces the challenges of quantum noise and of the Trotter error due to time discretization. The Trotter error in […]


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Estimating Cosmological Constraints from Galaxy Cluster Abundance using Simulation-Based Inference

Kavli Affiliate: Brian Nord | First 5 Authors: Moonzarin Reza, Yuanyuan Zhang, Brian Nord, Jason Poh, Aleksandra Ciprijanovic | Summary: Inferring the values and uncertainties of cosmological parameters in a cosmology model is of paramount importance for modern cosmic observations. In this paper, we use the simulation-based inference (SBI) approach to estimate cosmological constraints from […]


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Testing the key role of the stellar mass-halo mass relation in galaxy merger rates and morphologies via DECODE, a novel Discrete statistical sEmi-empiriCal mODEl

| First 5 authors: [#feed_custom_author[1]], [#feed_custom_author[2]], [#feed_custom_author[3]], [#feed_custom_author[4]], [#feed_custom_author[5]] | Summary: The relative roles of mergers and star formation in regulating galaxy growth are still a matter of intense debate. We here present our DECODE, a new Discrete statistical sEmi-empiriCal mODEl specifically designed to predict rapidly and efficiently, in a full cosmological context, galaxy assembly […]


Continue.. Testing the key role of the stellar mass-halo mass relation in galaxy merger rates and morphologies via DECODE, a novel Discrete statistical sEmi-empiriCal mODEl