A Logarithmic Bayesian Approach to Quantum Error Detection

Kavli Affiliate: K. Birgitta Whaley | First 5 Authors: Ian Convy, K. Birgitta Whaley, , , | Summary: We consider the problem of continuous quantum error correction from a Bayesian perspective, proposing a pair of digital filters using logarithmic probabilities that are able to achieve near-optimal performance on a three-qubit bit-flip code while still being […]


Continue.. A Logarithmic Bayesian Approach to Quantum Error Detection

Deep Realistic Extragalactic Model (DREaM) Galaxy Catalogs: Predictions for a Roman Ultra-Deep Field

Kavli Affiliate: Risa H. Wechsler | First 5 Authors: Nicole E. Drakos, Bruno Villasenor, Brant E. Robertson, Ryan Hausen, Mark E. Dickinson | Summary: In the next decade, deep galaxy surveys from telescopes such as the James Webb Space Telescope and Roman Space Telescope will provide transformational data sets that will greatly enhance the understanding […]


Continue.. Deep Realistic Extragalactic Model (DREaM) Galaxy Catalogs: Predictions for a Roman Ultra-Deep Field

Kilonova and Optical Afterglow from Binary Neutron Star Mergers. II. Optimal Search Strategy for Serendipitous Observations and Target-of-opportunity Observations of Gravitational-wave Triggers

Kavli Affiliate: Lijing Shao | First 5 Authors: Jin-Ping Zhu, Shichao Wu, Yuan-Pei Yang, Chang Liu, Bing Zhang | Summary: In the second work of this series, we explore the optimal search strategy for serendipitous and gravitational-wave-triggered target-of-opportunity (ToO) observations of kilonovae and optical short-duration gamma-ray burst (sGRB) afterglows from binary neutron star (BNS) mergers, […]


Continue.. Kilonova and Optical Afterglow from Binary Neutron Star Mergers. II. Optimal Search Strategy for Serendipitous Observations and Target-of-opportunity Observations of Gravitational-wave Triggers

Machine Learning for Continuous Quantum Error Correction on Superconducting Qubits

Kavli Affiliate: K. Birgitta Whaley | First 5 Authors: Ian Convy, Haoran Liao, Song Zhang, Sahil Patel, William P. Livingston | Summary: We propose a machine learning algorithm for continuous quantum error correction that is based on the use of a recurrent neural network to identity bit-flip errors from continuous noisy syndrome measurements. The algorithm […]


Continue.. Machine Learning for Continuous Quantum Error Correction on Superconducting Qubits