Maximum a posteriori probability estimates for quantum tomography
نویسندگان
چکیده
منابع مشابه
Maximum a posteriori probability tree models
The context-tree weighting method (Willems, Shtarkov, and Tjalkens [1995]) can be used to compress sequences generated by tree sources. Its redundancy behavior is optimal in the sense that Rissanen’s lower bound [1984] is achieved. Here we study some questions related to the context-tree weighting method. First we stress again that the a priori distribution over all tree models that is mainly c...
متن کاملGlobally convergent algorithms for maximum a posteriori transmission tomography
This paper reviews and compares three maximum likelihood algorithms for transmission tomography. One of these algorithms is the EM algorithm, one is based on a convexity argument devised by De Pierro (see IEEE Trans. Med. Imaging, vol.12, p.328-333, 1993) in the context of emission tomography, and one is an ad hoc gradient algorithm. The algorithms enjoy desirable local and global convergence p...
متن کاملA (simplified) Bluetooth Maximum a Posteriori Probability (map) Receiver
In our software-defined radio project we aim at combining two standards: Bluetooth and HiperLAN/2. The HiperLAN/2 receiver requires the most computation power in comparison with Bluetooth. We choose to use this computational power also for Bluetooth and look for more advanced demodulation algorithms such as a Maximum A posteriori Probability (MAP) receiver. This paper discusses a simplified MAP...
متن کاملMaximum-likelihood Algorithm for Quantum Tomography
Several years after the first demonstration [1], optical homodyne tomography has become a well established tool for measuring quantum statistical properties of optical radiation. What is particularly fascinating, this technique provides practical means to visualise the measured quantum state in the form of the Wigner function. This success is a result of combining a complete quantum mechanical ...
متن کاملMaximum a Posteriori Parameter
An iterative stochastic algorithm to perform maximum a posteriori parameter estimation of hidden Markov models is proposed. It makes the most of the statistical model by introducing an artiicial probability model based on an increasing number of the unobserved Markov chain at each iteration. Under minor regularity assumptions, we provide suucient conditions to ensure global convergence of this ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Physical Review A
سال: 2019
ISSN: 2469-9926,2469-9934
DOI: 10.1103/physreva.99.012342