The Experts below are selected from a list of 279 Experts worldwide ranked by ideXlab platform
Niccolò Torri - One of the best experts on this subject based on the ideXlab platform.
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Scaling limit of the uniform prudent walk
Electronic Journal of Probability, 2017Co-Authors: Nicolas Pétrélis, Rongfeng Sun, Niccolò TorriAbstract:We study the 2-dimensional uniform prudent self-avoiding walk, which assigns Equal Probability to all nearest-neighbor self-avoiding paths of a fixed length that respect the prudent condition, namely, the path cannot take any step in the direction of a previously visited site. The uniform prudent walk has been investigated with combinatorial techniques in [Bousquet-Melou, 2010], while another variant, the kinetic prudent walk has been analyzed in detail in [Beffara, Friedli and Velenik, 2010]. In this paper, we prove that the 2-dimensional uniform prudent walk is ballistic and follows one of the 4 diagonals with Equal Probability. We also establish a functional central limit theorem for the fluctuations of the path around the diagonal.
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Scaling limit of the uniform prudent walk
Electronic Journal of Probability, 2017Co-Authors: Nicolas Pétrélis, Rongfeng Sun, Niccolò TorriAbstract:International audienceWe study the 2-dimensional uniform prudent self-avoiding walk, which assigns Equal Probability to all nearest-neighbor self-avoiding paths of a fixed length that respect the prudent condition, namely, the path cannot take any step in the direction of a previously visited site. The uniform prudent walk has been investigated with combinatorial techniques in [Bousquet-Mélou, 2010], while another variant, the kinetic prudent walk has been analyzed in detail in [Beffara, Friedli and Velenik, 2010]. In this paper, we prove that the 2-dimensional uniform prudent walk is ballistic and follows one of the 4 diagonals with Equal Probability. We also establish a functional central limit theorem for the fluctuations of the path around the diagonal
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Scaling limit of the uniform prudent walk
Electronic Journal of Probability, 2017Co-Authors: Nicolas Pétrélis, Rongfeng Sun, Niccolò TorriAbstract:We study the 2-dimensional uniform prudent self-avoiding walk, which assigns Equal Probability to all nearest-neighbor self-avoiding paths of a fixed length that respect the prudent condition, namely, the path cannot take any step in the direction of a previously visited site. The uniform prudent walk has been investigated with combinatorial techniques in [Bousquet-Mélou, 2010], while another variant, the kinetic prudent walk has been analyzed in detail in [Beffara, Friedli and Velenik, 2010]. In this paper, we prove that the 2-dimensional uniform prudent walk is ballistic and follows one of the 4 diagonals with Equal Probability. We also establish a functional central limit theorem for the fluctuations of the path around the diagonal.
Nicolas Pétrélis - One of the best experts on this subject based on the ideXlab platform.
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Scaling limit of the uniform prudent walk
Electronic Journal of Probability, 2017Co-Authors: Nicolas Pétrélis, Rongfeng Sun, Niccolò TorriAbstract:We study the 2-dimensional uniform prudent self-avoiding walk, which assigns Equal Probability to all nearest-neighbor self-avoiding paths of a fixed length that respect the prudent condition, namely, the path cannot take any step in the direction of a previously visited site. The uniform prudent walk has been investigated with combinatorial techniques in [Bousquet-Melou, 2010], while another variant, the kinetic prudent walk has been analyzed in detail in [Beffara, Friedli and Velenik, 2010]. In this paper, we prove that the 2-dimensional uniform prudent walk is ballistic and follows one of the 4 diagonals with Equal Probability. We also establish a functional central limit theorem for the fluctuations of the path around the diagonal.
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Scaling limit of the uniform prudent walk
Electronic Journal of Probability, 2017Co-Authors: Nicolas Pétrélis, Rongfeng Sun, Niccolò TorriAbstract:International audienceWe study the 2-dimensional uniform prudent self-avoiding walk, which assigns Equal Probability to all nearest-neighbor self-avoiding paths of a fixed length that respect the prudent condition, namely, the path cannot take any step in the direction of a previously visited site. The uniform prudent walk has been investigated with combinatorial techniques in [Bousquet-Mélou, 2010], while another variant, the kinetic prudent walk has been analyzed in detail in [Beffara, Friedli and Velenik, 2010]. In this paper, we prove that the 2-dimensional uniform prudent walk is ballistic and follows one of the 4 diagonals with Equal Probability. We also establish a functional central limit theorem for the fluctuations of the path around the diagonal
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Scaling limit of the uniform prudent walk
Electronic Journal of Probability, 2017Co-Authors: Nicolas Pétrélis, Rongfeng Sun, Niccolò TorriAbstract:We study the 2-dimensional uniform prudent self-avoiding walk, which assigns Equal Probability to all nearest-neighbor self-avoiding paths of a fixed length that respect the prudent condition, namely, the path cannot take any step in the direction of a previously visited site. The uniform prudent walk has been investigated with combinatorial techniques in [Bousquet-Mélou, 2010], while another variant, the kinetic prudent walk has been analyzed in detail in [Beffara, Friedli and Velenik, 2010]. In this paper, we prove that the 2-dimensional uniform prudent walk is ballistic and follows one of the 4 diagonals with Equal Probability. We also establish a functional central limit theorem for the fluctuations of the path around the diagonal.
Rongfeng Sun - One of the best experts on this subject based on the ideXlab platform.
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Scaling limit of the uniform prudent walk
Electronic Journal of Probability, 2017Co-Authors: Nicolas Pétrélis, Rongfeng Sun, Niccolò TorriAbstract:We study the 2-dimensional uniform prudent self-avoiding walk, which assigns Equal Probability to all nearest-neighbor self-avoiding paths of a fixed length that respect the prudent condition, namely, the path cannot take any step in the direction of a previously visited site. The uniform prudent walk has been investigated with combinatorial techniques in [Bousquet-Melou, 2010], while another variant, the kinetic prudent walk has been analyzed in detail in [Beffara, Friedli and Velenik, 2010]. In this paper, we prove that the 2-dimensional uniform prudent walk is ballistic and follows one of the 4 diagonals with Equal Probability. We also establish a functional central limit theorem for the fluctuations of the path around the diagonal.
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Scaling limit of the uniform prudent walk
Electronic Journal of Probability, 2017Co-Authors: Nicolas Pétrélis, Rongfeng Sun, Niccolò TorriAbstract:International audienceWe study the 2-dimensional uniform prudent self-avoiding walk, which assigns Equal Probability to all nearest-neighbor self-avoiding paths of a fixed length that respect the prudent condition, namely, the path cannot take any step in the direction of a previously visited site. The uniform prudent walk has been investigated with combinatorial techniques in [Bousquet-Mélou, 2010], while another variant, the kinetic prudent walk has been analyzed in detail in [Beffara, Friedli and Velenik, 2010]. In this paper, we prove that the 2-dimensional uniform prudent walk is ballistic and follows one of the 4 diagonals with Equal Probability. We also establish a functional central limit theorem for the fluctuations of the path around the diagonal
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Scaling limit of the uniform prudent walk
Electronic Journal of Probability, 2017Co-Authors: Nicolas Pétrélis, Rongfeng Sun, Niccolò TorriAbstract:We study the 2-dimensional uniform prudent self-avoiding walk, which assigns Equal Probability to all nearest-neighbor self-avoiding paths of a fixed length that respect the prudent condition, namely, the path cannot take any step in the direction of a previously visited site. The uniform prudent walk has been investigated with combinatorial techniques in [Bousquet-Mélou, 2010], while another variant, the kinetic prudent walk has been analyzed in detail in [Beffara, Friedli and Velenik, 2010]. In this paper, we prove that the 2-dimensional uniform prudent walk is ballistic and follows one of the 4 diagonals with Equal Probability. We also establish a functional central limit theorem for the fluctuations of the path around the diagonal.
Yonina C. Eldar - One of the best experts on this subject based on the ideXlab platform.
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unambiguous quantum state discrimination and the Equal Probability measurement
International Symposium on Information Theory, 2003Co-Authors: Yonina C. EldarAbstract:This paper proposes a simple suboptimal measurement for unambiguous quantum state discrimination known as the Equal-Probability measurement (EPM) in a quantum detection problem where a transmitter conveys classical information to a receiver using a quantum-mechanical channel.
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A semidefinite programming approach to optimal unambiguous discrimination of quantum states
IEEE Transactions on Information Theory, 2003Co-Authors: Yonina C. EldarAbstract:We consider the problem of unambiguous discrimination between a set of linearly independent pure quantum states. We show that the design of the optimal measurement that minimizes the Probability of an inconclusive result can be formulated as a semidefinite programming problem. Based on this formulation, we develop a set of necessary and sufficient conditions for an optimal quantum measurement. We show that the optimal measurement can be computed very efficiently in polynomial time by exploiting the many well-known algorithms for solving semidefinite programs, which are guaranteed to converge to the global optimum. Using the general conditions for optimality, we derive necessary and sufficient conditions so that the measurement that results in an Equal Probability of an inconclusive result for each one of the quantum states is optimal. We refer to this measurement as the Equal-Probability measurement (EPM). We then show that for any state set, the prior probabilities of the states can be chosen such that the EPM is optimal. Finally, we consider state sets with strong symmetry properties and Equal prior probabilities for which the EPM is optimal. We first consider geometrically uniform (GU) state sets that are defined over a group of unitary matrices and are generated by a single generating vector. We then consider compound GU state sets which are generated by a group of unitary matrices using multiple generating vectors, where the generating vectors satisfy a certain (weighted) norm constraint.
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a semidefinite programming approach to optimal unambiguous discrimination of quantum states
arXiv: Quantum Physics, 2002Co-Authors: Yonina C. EldarAbstract:In this paper we consider the problem of unambiguous discrimination between a set of linearly independent pure quantum states. We show that the design of the optimal measurement that minimizes the Probability of an inconclusive result can be formulated as a semidefinite programming problem. Based on this formulation, we develop a set of necessary and sufficient conditions for an optimal quantum measurement. We show that the optimal measurement can be computed very efficiently in polynomial time by exploiting the many well-known algorithms for solving semidefinite programs, which are guaranteed to converge to the global optimum. Using the general conditions for optimality, we derive necessary and sufficient conditions so that the measurement that results in an Equal Probability of an inconclusive result for each one of the quantum states is optimal. We refer to this measurement as the Equal-Probability measurement (EPM). We then show that for any state set, the prior probabilities of the states can be chosen such that the EPM is optimal. Finally, we consider state sets with strong symmetry properties and Equal prior probabilities for which the EPM is optimal. We first consider geometrically uniform state sets that are defined over a group of unitary matrices and are generated by a single generating vector. We then consider compound geometrically uniform state sets which are generated by a group of unitary matrices using multiple generating vectors, where the generating vectors satisfy a certain (weighted) norm constraint.
You Zhi - One of the best experts on this subject based on the ideXlab platform.
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quantitative research of validity on subsection sorting algorithm with Equal Probability data segment
Chinese Journal of Computers, 2003Co-Authors: You ZhiAbstract:This paper brings forward a subsection insertion sorting algorithm with Equal Probability data segment. The algorithm combines traditional sorting algorithms with some knowledge and skill of modern statistics to sort data with general distribution. The distribution information of these data is considered sufficiently. The approaches include mainly the following. Firstly, the distribution type of these data is determined experientially. Secondly, distribution parameters of these data are estimated. Thirdly, these data are assigned evenly to different segments on the whole. Finally, the data of different segments is sorted with traditional sorting algorithms. The complexity of this algorithm is limited to O(n) . And this paper uses the theory of non parametric hypothesis test to quantize the number of segments and approximate degree of distribution types and to deduce some factors which effect the number of segments and approximate degree of distribution types. Some important theoretic results are deduced. Let b represents the ratio of the number of data to the number of segments. Main results as follows. For larger number n , the algorithm is time optimal when b is a constant; the more approximate degree of distribution types is different, the value of b is to ensure the time complexity is O(n). This paper experimentalizes about these important results. Experiment results show that the theoretic results are consistent with practice.
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subsection insertion sorting algorithm with Equal Probability data segmentation
Journal of Hunan University, 2001Co-Authors: You ZhiAbstract:A subsection insertion sorting algorithm with Equal Probability data segmentation is presented.The algorithm conbines traditional sorting algorithms with some knowledge and skill of modem statistics to sort data with general distribution.So the complexity of sorting is limited O(n) ,which reaches the lower bound.Experiments show that this algorithm excels others of the same kind.
