Murphy Yuezhen Niu

According to our database, Murphy Yuezhen Niu authored at least 12 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Learning high-accuracy error decoding for quantum processors.

Johannes Bausch, Andrew W. Senior, Francisco J. H. Heras, Thomas Edlich, Alex Davies, Michael Newman, Cody Jones, Kevin J. Satzinger, Murphy Yuezhen Niu, Sam Blackwell, George Holland, Dvir Kafri, Juan Atalaya, Craig Gidney, Demis Hassabis, Sergio Boixo, Hartmut Neven, Pushmeet Kohli

Nat., November, 2024

Universal Logical Quantum Photonic Neural Network Processor via Cavity-Assisted Interactions.

Jasvith Raj Basani, Murphy Yuezhen Niu, Edo Waks

CoRR, 2024

Optimal Low-Depth Quantum Signal-Processing Phase Estimation.

Yulong Dong, Jonathan Gross, Murphy Yuezhen Niu

CoRR, 2024

A SAT Scalpel for Lattice Surgery: Representation and Synthesis of Subroutines for Surface-Code Fault-Tolerant Quantum Computing.

Daniel Bochen Tan, Murphy Yuezhen Niu, Craig Gidney

Proceedings of the 51st ACM/IEEE Annual International Symposium on Computer Architecture, 2024

2023

Learning to Decode the Surface Code with a Recurrent, Transformer-Based Neural Network.

Johannes Bausch, Andrew W. Senior, Francisco J. H. Heras, Thomas Edlich, Alex Davies, Michael Newman, Cody Jones, Kevin J. Satzinger, Murphy Yuezhen Niu, Sam Blackwell, George Holland, Dvir Kafri, Juan Atalaya, Craig Gidney, Demis Hassabis, Sergio Boixo, Hartmut Neven, Pushmeet Kohli

CoRR, 2023

2022

Domain-Specific Quantum Architecture Optimization.

Wan-Hsuan Lin, Bochen Tan, Murphy Yuezhen Niu, Jason Kimko, Jason Cong

IEEE J. Emerg. Sel. Topics Circuits Syst., 2022

Beyond Heisenberg Limit Quantum Metrology through Quantum Signal Processing.

Yulong Dong, Jonathan Gross, Murphy Yuezhen Niu

CoRR, 2022

2020

Learnability and Complexity of Quantum Samples.

Murphy Yuezhen Niu, Andrew M. Dai, Li Li, Augustus Odena, Zhengli Zhao, Vadim Smelyanskyi, Hartmut Neven, Sergio Boixo

CoRR, 2020

TensorFlow Quantum: A Software Framework for Quantum Machine Learning.

Michael Broughton, Guillaume Verdon, Trevor McCourt, Antonio J. Martinez, Jae Hyeon Yoo, Sergei V. Isakov, Philip Massey, Murphy Yuezhen Niu, Ramin Halavati, Evan Peters, Martin Leib, Andrea Skolik, Michael Streif, David Von Dollen, Jarrod R. McClean, Sergio Boixo, Dave Bacon, Alan K. Ho, Hartmut Neven, Masoud Mohseni

CoRR, 2020

2019

Learning Non-Markovian Quantum Noise from Moiré-Enhanced Swap Spectroscopy with Deep Evolutionary Algorithm.

Murphy Yuezhen Niu, Vadim Smelyanskyi, Paul Klimov, Sergio Boixo, Rami Barends, Julian Kelly, Yu Chen, Kunal Arya, Brian Burkett, Dave Bacon, Zijun Chen, Benjamin Chiaro, Roberto Collins, Andrew Dunsworth, Brooks Foxen, Austin G. Fowler, Craig Gidney, Marissa Giustina, Rob Graff, Trent Huang, Evan Jeffrey, David Landhuis, Erik Lucero, Anthony Megrant, Josh Mutus, Xiao Mi, Ofer Naaman, Matthew Neeley, Charles J. Neill, Chris Quintana, Pedram Roushan, John M. Martinis, Hartmut Neven

CoRR, 2019

Recurrent Neural Networks in the Eye of Differential Equations.

Murphy Yuezhen Niu, Lior Horesh, Isaac Chuang

CoRR, 2019

2017

Quantum simulation from the bottom up: the case of rebits.

Dax Enshan Koh, Murphy Yuezhen Niu, Theodore J. Yoder

CoRR, 2017