An improved robust ADMM algorithm for quantum state tomography
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Publication:332021
DOI10.1007/s11128-016-1288-xzbMath1348.81170OpenAlexW2299087967MaRDI QIDQ332021
Fangfang Meng, Kezhi Li, Shuang Cong, Sen Kuang, Hui Zhang
Publication date: 27 October 2016
Published in: Quantum Information Processing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11128-016-1288-x
Quantum computation (81P68) Quantum state estimation, approximate cloning (81P50) Quantum algorithms and complexity in the theory of computing (68Q12)
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Cites Work
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- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Self-protected quantum algorithms based on quantum state tomography
- Quantum error correction via convex optimization
- Alternating direction method with self-adaptive penalty parameters for monotone variational inequalities
- Quantum tomography under prior information
- Partial standard quantum process tomography
- Quantitative robust uncertainty principles and optimally sparse decompositions
- Robust principal component analysis?
- Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
- Using SeDuMi 1.02, A Matlab toolbox for optimization over symmetric cones
- Compressive Sensing Reconstruction With Prior Information by Iteratively Reweighted Least-Squares
- Compressive principal component pursuit
- Quantum tomography via compressed sensing: error bounds, sample complexity and efficient estimators
- Generating random density matrices
- Recovering Low-Rank Matrices From Few Coefficients in Any Basis
- Sparsity and incoherence in compressive sampling
- Compressed sensing
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