Parity-Odd Power Spectra: Concise Statistics for Cosmological Parity Violation

Kavli Affiliate: Eiichiro Komatsu | First 5 Authors: Drew Jamieson, Angelo Caravano, Jiamin Hou, Zachary Slepian, Eiichiro Komatsu | Summary: We introduce the Parity-Odd Power (POP) spectra, a novel set of observables for probing parity violation in cosmological $N$-point statistics. POP spectra are derived from composite fields obtained by applying nonlinear transformations, involving also gradients, […]


Continue.. Parity-Odd Power Spectra: Concise Statistics for Cosmological Parity Violation

Parity-Odd Power Spectra: Concise Statistics for Cosmological Parity Violation

Kavli Affiliate: Eiichiro Komatsu | First 5 Authors: Drew Jamieson, Angelo Caravano, Jiamin Hou, Zachary Slepian, Eiichiro Komatsu | Summary: We introduce the Parity-Odd Power (POP) spectra, a novel set of observables for probing parity violation in cosmological $N$-point statistics. POP spectra are derived from composite fields obtained by applying nonlinear transformations, involving also gradients, […]


Continue.. Parity-Odd Power Spectra: Concise Statistics for Cosmological Parity Violation

The neural correlates of logical-mathematical symbol systems processing resemble that of spatial cognition more than natural language processing

Kavli Affiliate: Jia Liu | First 5 Authors: Yuannan Li, Shan Xu, Jia Liu, , | Summary: The ability to manipulate logical-mathematical symbols (LMS), encompassing tasks such as calculation, reasoning, and programming, is a cognitive skill arguably unique to humans. Considering the relatively recent emergence of this ability in human evolutionary history, it has been […]


Continue.. The neural correlates of logical-mathematical symbol systems processing resemble that of spatial cognition more than natural language processing

Weak-lensing Shear-selected Galaxy Clusters from the Hyper Suprime-Cam Subaru Strategic Program: II. Cosmological Constraints from the Cluster Abundance

Kavli Affiliate: Masahiro Takada | First 5 Authors: I-Non Chiu, Kai-Feng Chen, Masamune Oguri, Markus M. Rau, Hironao Miyatake | Summary: We present cosmological constraints using the abundance of weak-lensing shear-selected galaxy clusters in the Hyper Suprime-Cam (HSC) Subaru Strategic Program. The clusters are selected on the mass maps constructed using the three-year (Y3) weak-lensing […]


Continue.. Weak-lensing Shear-selected Galaxy Clusters from the Hyper Suprime-Cam Subaru Strategic Program: II. Cosmological Constraints from the Cluster Abundance

Weak-Lensing Shear-Selected Galaxy Clusters from the Hyper Suprime-Cam Subaru Strategic Program: II. Cosmological Constraints from the Cluster Abundance

Kavli Affiliate: Masahiro Takada | First 5 Authors: I-Non Chiu, Kai-Feng Chen, Masamune Oguri, Markus M. Rau, Takashi Hamana | Summary: We present cosmological constraints using the abundance of weak-lensing shear-selected galaxy clusters in the Hyper Suprime-Cam (HSC) Subaru Strategic Program. The clusters are selected on the mass maps constructed using the three-year (Y3) weak-lensing […]


Continue.. Weak-Lensing Shear-Selected Galaxy Clusters from the Hyper Suprime-Cam Subaru Strategic Program: II. Cosmological Constraints from the Cluster Abundance

Weak-Lensing Shear-Selected Galaxy Clusters from the Hyper Suprime-Cam Subaru Strategic Program: I. Cluster Catalog, Selection Function and Mass–Observable Relation

Kavli Affiliate: Masahiro Takada | First 5 Authors: Kai-Feng Chen, I-Non Chiu, Masamune Oguri, Yen-Ting Lin, Hironao Miyatake | Summary: We present the first step towards deriving cosmological constraints through the abundances of galaxy clusters selected in a $510,mathrm{deg}^2$ weak-lensing aperture mass map, constructed with the Year-Three shear catalog from the Hyper Suprime-Cam Subaru Strategic […]


Continue.. Weak-Lensing Shear-Selected Galaxy Clusters from the Hyper Suprime-Cam Subaru Strategic Program: I. Cluster Catalog, Selection Function and Mass–Observable Relation

Imperceptible Rhythm Backdoor Attacks: Exploring Rhythm Transformation for Embedding Undetectable Vulnerabilities on Speech Recognition

Kavli Affiliate: Jia Liu | First 5 Authors: Wenhan Yao, Jiangkun Yang, Yongqiang He, Jia Liu, Weiping Wen | Summary: Speech recognition is an essential start ring of human-computer interaction, and recently, deep learning models have achieved excellent success in this task. However, when the model training and private data provider are always separated, some […]


Continue.. Imperceptible Rhythm Backdoor Attacks: Exploring Rhythm Transformation for Embedding Undetectable Vulnerabilities on Speech Recognition

Imperceptible Rhythm Backdoor Attacks: Exploring Rhythm Transformation for Embedding Undetectable Vulnerabilities on Speech Recognition

Kavli Affiliate: Jia Liu | First 5 Authors: Wenhan Yao, Jiangkun Yang, Yongqiang He, Jia Liu, Weiping Wen | Summary: Speech recognition is an essential start ring of human-computer interaction, and recently, deep learning models have achieved excellent success in this task. However, when the model training and private data provider are always separated, some […]


Continue.. Imperceptible Rhythm Backdoor Attacks: Exploring Rhythm Transformation for Embedding Undetectable Vulnerabilities on Speech Recognition

Byzantine-Robust Decentralized Federated Learning

Kavli Affiliate: Jia Liu | First 5 Authors: Minghong Fang, Zifan Zhang, Hairi, Prashant Khanduri, Jia Liu | Summary: Federated learning (FL) enables multiple clients to collaboratively train machine learning models without revealing their private training data. In conventional FL, the system follows the server-assisted architecture (server-assisted FL), where the training process is coordinated by […]


Continue.. Byzantine-Robust Decentralized Federated Learning

Byzantine-Robust Decentralized Federated Learning

Kavli Affiliate: Jia Liu | First 5 Authors: Minghong Fang, Zifan Zhang, Hairi, Prashant Khanduri, Jia Liu | Summary: Federated learning (FL) enables multiple clients to collaboratively train machine learning models without revealing their private training data. In conventional FL, the system follows the server-assisted architecture (server-assisted FL), where the training process is coordinated by […]


Continue.. Byzantine-Robust Decentralized Federated Learning