Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Yuen-Lam Voronin"'
Autor:
Chi-Kwong Li, Diane Christine Pelejo, Henry Wolkowicz, Dmitriy Drusvyatskiy, Yuen-Lam Voronin
Publikováno v:
Quantum Information Processing. 14:3075-3096
We consider the problem of constructing quantum channels, if they exist, that transform a given set of quantum states $$\{\rho _1, \ldots , \rho _k\}$${?1,?,?k} to another such set $$\{\hat{\rho }_1, \ldots , \hat{\rho }_k\}$${?^1,?,?^k}. In other wo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::99a8c3c822783849249adf2c537aff75
https://doi.org/10.1007/s11128-015-1024-y
https://doi.org/10.1007/s11128-015-1024-y
Publikováno v:
Static Analysis ISBN: 9783662534120
SAS
23rd Static Analysis Symposium (SAS)
23rd Static Analysis Symposium (SAS), Sep 2016, Edinburgh, United Kingdom. ⟨10.1007/978-3-662-53413-7_21⟩
SAS
23rd Static Analysis Symposium (SAS)
23rd Static Analysis Symposium (SAS), Sep 2016, Edinburgh, United Kingdom. ⟨10.1007/978-3-662-53413-7_21⟩
International audience; Semidefinite programming (SDP) solvers are increasingly used as primitives in many program verification tasks to synthesize and verify polynomial invariants for a variety of systems including programs, hybrid systems and stoch
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::674498b9bfb52663d948396f4c2d9ba0
https://doi.org/10.1007/978-3-662-53413-7_21
https://doi.org/10.1007/978-3-662-53413-7_21
Publikováno v:
Tools and Algorithms for the Construction and Analysis of Systems ISBN: 9783662496732
TACAS
TACAS
Martingale theory yields a powerful set of tools that have recently been used to prove quantitative properties of stochastic systems such as stochastic safety and qualitative properties such as almost sure termination. In this paper, we examine proof
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec2ac497e711a0b3afebcafc828cc2d2
https://doi.org/10.1007/978-3-662-49674-9_15
https://doi.org/10.1007/978-3-662-49674-9_15
We present two algorithms for large-scale low-rank Euclidean distance matrix completion problems, based on semidefinite optimization. Our first method works by relating cliques in the graph of the known distances to faces of the positive semidefinite
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47962746e727a2f76662e36257e4704c
http://arxiv.org/abs/1410.6852
http://arxiv.org/abs/1410.6852