On Asymptotic Quantum Statistical Inference
Autor: | Gill, R.D., Guta, M.I., Banerjee, M., Bunea, F., Huang, J., Koltchinskii, V., Maathuis, M.H. |
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Přispěvatelé: | Banerjee, M., Bunea, F., Huang, J., Koltchinskii, V., Maathuis, M.H. |
Jazyk: | angličtina |
Rok vydání: | 2011 |
Předmět: |
Quantum Physics
Local asymptotic normality quantum local asymptotic normality FOS: Physical sciences Mathematics - Statistics Theory Statistics Theory (math.ST) State (functional analysis) 62P35 Asymptotically optimal algorithm van Trees inequality FOS: Mathematics Statistical inference Applied mathematics local asymptotic normality 62F12 Quantum Physics (quant-ph) Quantum quantum Cramér-Rao bound Mathematics |
Zdroj: | Banerjee, M., Bunea, F., Huang, J., Koltchinskii, V., and Maathuis, M. H., eds., From Probability to Statistics and Back: High-Dimensional Models and Processes--A Festschrift in Honor of Jon A. Wellner, (Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2013), 105-127 Institute of Mathematical Statistics collections, 105-127. Beachwood, Ohio, USA: Institute of Mathematical Statistics STARTPAGE=105;ENDPAGE=127;TITLE=Institute of Mathematical Statistics collections |
Popis: | We study asymptotically optimal statistical inference concerning the unknown state of $N$ identical quantum systems, using two complementary approaches: a "poor man's approach" based on the van Trees inequality, and a rather more sophisticated approach using the recently developed quantum form of LeCam's theory of Local Asymptotic Normality. 34 pages. to appear in `From Probability to Statistics and Back: High-Dimensional Models and Processes'. A Festschrift in Honor of Jon Wellner. Edited by Banerjee, M., Bunea, F., Huang, J., Maathuis, M. and Koltchinskii, V. extension of a previous paper arXiv:math/0512443 |
Databáze: | OpenAIRE |
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