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Journal articles on the topic 'Transition probability'

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Published: 4 June 2021

Last updated: 28 January 2023

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1

BĂLUŢĂ, Alexandra, Diana ROTARU, Mihaela ILIE, Dragoş FĂLIE, and Eugen VASILE. "TRANSITION PROBABILITY MODELING FOR QUANTUM OPTICS." SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 19, no. 1 (July 31, 2017): 345–56. http://dx.doi.org/10.19062/2247-3173.2017.19.1.42.

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2

Pulmannová, Sylvia. "Transition probability spaces." Journal of Mathematical Physics 27, no. 7 (July 1986): 1791–95. http://dx.doi.org/10.1063/1.527045.

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3

Grahn, T., H. Watkins, D. T. Joss, R. D. Page, R. J. Carroll, A. Dewald, P. T. Greenlees, et al. "Transition probability studies in175Au." Journal of Physics: Conference Series 420 (March 25, 2013): 012047. http://dx.doi.org/10.1088/1742-6596/420/1/012047.

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4

Dixon, Robbie J., Maki Matsuka, Roger D. Braddock, Josh M. Whitcombe, and Igor E. Agranovski. "FCCU transition-probability model." Mathematical and Computer Modelling 45, no. 3-4 (February 2007): 241–51. http://dx.doi.org/10.1016/j.mcm.2006.03.019.

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5

Cacelli, I., V. Carravetta, R. Moccia, and A. Rizzo. "Two-photon transition probability calculations: electronic transitions in methane." Chemical Physics 109, no. 2-3 (November 1986): 227–35. http://dx.doi.org/10.1016/0301-0104(86)87054-9.

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6

Perilioglu, Ahmet, and Sukriye Tuysuz. "Conditional Sovereign Transition Probability Matrices." Procedia Economics and Finance 30 (2015): 643–55. http://dx.doi.org/10.1016/s2212-5671(15)01283-6.

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7

Carle, Steven F., and Graham E. Fogg. "Transition probability-based indicator geostatistics." Mathematical Geology 28, no. 4 (May 1996): 453–76. http://dx.doi.org/10.1007/bf02083656.

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8

Huang, Zheng-Hai, and Liqun Qi. "Stationary Probability Vectors of Higher-Order Two-Dimensional Symmetric Transition Probability Tensors." Asia-Pacific Journal of Operational Research 37, no. 04 (July 24, 2020): 2040019. http://dx.doi.org/10.1142/s0217595920400199.

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In this paper, we investigate stationary probability vectors of higher-order two-dimensional symmetric transition probability tensors. We show that there are two special symmetric transition probability tensors of order [Formula: see text] dimension 2, which have and only have two stationary probability vectors; and any other symmetric transition probability tensor of order [Formula: see text] dimension 2 has a unique stationary probability vector. As a byproduct, we obtain that any symmetric transition probability tensor of order [Formula: see text] dimension 2 has a unique positive stationary probability vector, and that any symmetric irreducible transition probability tensor of order [Formula: see text] dimension 2 has a unique stationary probability vector.

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9

Hasegawa, Shigeaki F., and Takenori Takada. "Probability of Deriving a Yearly Transition Probability Matrix for Land-Use Dynamics." Sustainability 11, no. 22 (November 12, 2019): 6355. http://dx.doi.org/10.3390/su11226355.

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Takada’s group developed a method for estimating the yearly transition matrix by calculating the mth power roots of a transition matrix with an interval of m years. However, the probability of obtaining a yearly transition matrix with real and positive elements is unknown. In this study, empirical verification based on transition matrices from previous land-use studies and Monte-Carlo simulations were conducted to estimate the probability of obtaining an appropriate yearly transition probability matrix. In 62 transition probability matrices of previous land-use studies, 54 (87%) could provide a positive or small-negative solution. For randomly generated matrices with differing sizes or power roots, the probability of obtaining a positive or small-negative solution is low. However, the probability is relatively large for matrices with large diagonal elements, exceeding 90% in most cases. These results indicate that Takada et al.’s method is a powerful tool for analyzing land-use dynamics.

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10

Li, Wen, and Michael K. Ng. "On the limiting probability distribution of a transition probability tensor." Linear and Multilinear Algebra 62, no. 3 (March 19, 2013): 362–85. http://dx.doi.org/10.1080/03081087.2013.777436.

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11

Fang, Yun Mei, and Jun Tao Fei. "Transition Probability Analysis for Piezoceramic Materials." Advanced Materials Research 452-453 (January 2012): 1286–90. http://dx.doi.org/10.4028/scientific5/amr.452-453.1286.

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12

Fang, Yun Mei, and Jun Tao Fei. "Transition Probability Analysis for Piezoceramic Materials." Advanced Materials Research 452-453 (January 2012): 1286–90. http://dx.doi.org/10.4028/www.scientific.net/amr.452-453.1286.

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In this paper, transition probability analysis for piezoceramic actuators is presented. Nonlinear constitutive equations and resulting system models quantifying the non-linear and hysteretic field-displacement relations inherent to piezoceramic elements are developed. In the model development, lattice-level energy relations are combined with stochastic homogenization techniques to construct non-linear constitutive relations which accommodate the piezoceramic hysteresis. Simulation results demonstrated the effectiveness of the theoretical model development using transition probability analysis.

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13

Yong, Li, Liu wenyul, Rao Jianguo, and Li Baiwen. "Calculation of Microwave Multiphoton Transition Probability." Communications in Theoretical Physics 30, no. 1 (July 30, 1998): 1–6. http://dx.doi.org/10.1088/0253-6102/30/1/1.

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14

Kawasaki, Mitsuhiro, Atsushi Furuya, Masatoshi Yagi, Kimitaka Itoh, and Sanae-I. Itoh. "Transition probability to turbulent transport regime." Plasma Physics and Controlled Fusion 44, no. 5A (April 30, 2002): A473—A478. http://dx.doi.org/10.1088/0741-3335/44/5a/352.

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15

Landsman, N. P. "Poisson Spaces with a Transition Probability." Reviews in Mathematical Physics 09, no. 01 (January 1997): 29–57. http://dx.doi.org/10.1142/s0129055x97000038.

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The common structure of the space of pure states ℘ of a classical or a quantum mechanical system is that of a Poisson space with a transition probability. This is a topological space equipped with a Poisson structure, as well as with a function p:℘×℘→[0,1], with certain properties. The Poisson structure is connected with the transition probabilities through unitarity (in a specific formulation intrinsic to the given context). In classical mechanics, where p(ρ,σ)=δρσ, unitarity poses no restriction on the Poisson structure. Quantum mechanics is characterized by a specific (complex Hilbert space) form of p, and by the property that the irreducible components of ℘ as a transition probability space coincide with the symplectic leaves of ℘ as a Poisson space. In conjunction, these stipulations determine the Poisson structure of quantum mechanics up to a multiplicative constant (identified with Planck's constant). Motivated by E. M. Alfsen, H. Hanche-Olsen and F. W. Shultz (Acta Math.144 (1980) 267–305) and F.W. Shultz (Commun. Math. Phys.82 (1982) 497–509), we give axioms guaranteeing that ℘ is the space of pure states of a unital C*-algebra. We give an explicit construction of this algebra from ℘.

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16

Shen Xiao-Zhi, Yuan Ping, Wang Jie, Guo Yi-Xiao, Qiao Hong-Zhen, and Zhao Xue-Yan. "Fit parameter to calculate transition probability." Acta Physica Sinica 57, no. 7 (2008): 4066. http://dx.doi.org/10.7498/aps.57.4066.

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17

Xie, Yu Quan. "Some new results on transition probability." Acta Mathematica Sinica, English Series 24, no. 12 (November 5, 2008): 1965–84. http://dx.doi.org/10.1007/s10114-008-6054-2.

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18

Pulmannová, Sylvia. "Functional properties of transition probability spaces." Reports on Mathematical Physics 24, no. 1 (August 1986): 81–86. http://dx.doi.org/10.1016/0034-4877(86)90042-x.

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19

Uhlmann, Armin. "Transition Probability (Fidelity) and Its Relatives." Foundations of Physics 41, no. 3 (January 22, 2010): 288–98. http://dx.doi.org/10.1007/s10701-009-9381-y.

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20

Moccia, R., and A. Rizzo. "Two-photon transition probability calculations: electronic transitions in the water molecule." Journal of Physics B: Atomic and Molecular Physics 18, no. 16 (August 28, 1985): 3319–37. http://dx.doi.org/10.1088/0022-3700/18/16/017.

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21

Djenize, Stevan, Aleksandar Sreckovic, and Srdjan Bukvic. "Transition probability ratios in the Mg I 3p-4s transition." Serbian Astronomical Journal, no. 168 (2004): 45–48. http://dx.doi.org/10.2298/saj0468045d.

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Using the relative line intensity I ratios of the astrophysically important 518.360 nm, 517.268 nm and 516.732 nm neutral magnesium (Mg I) lines in the 3p 3Po 0,1,2 - 4s 3S1 transition we have obtained the ratios of corresponding transition probability values (Einstein's A values). They represent the first experimental data based on the analysis of the emission spectral lines. The linear, low-pressure, pulsed arc was used as a plasma source operated in the helium with magnesium atoms introduced as impurities from discharge electrodes, providing there is no self-absorption within the investigated range of Mg I spectrum. We have found excellent agreement with theoretical transition probability ratios tabulated by NIST (2003).

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22

Rigney, D. R. "Multiple-Transition Cell Cycle Models That Exhibit Transition Probability Kinetics." Cell Proliferation 19, no. 1 (January 1986): 23–37. http://dx.doi.org/10.1111/j.1365-2184.1986.tb00712.x.

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23

WAN, ANDY T. S., M. H. S. AMIN, and SHANNON X. WANG. "LANDAU-ZENER TRANSITIONS IN THE PRESENCE OF SPIN ENVIRONMENT." International Journal of Quantum Information 07, no. 04 (June 2009): 725–37. http://dx.doi.org/10.1142/s0219749909005353.

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We study the effect of an environment consisting of noninteracting two level systems on Landau-Zener transitions with an interest on the performance of an adiabatic quantum computer. We show that if the environment is initially at zero temperature, it does not affect the transition probability. An excited environment, however, will always increase the probability of making a transition out of the ground state. For the case of equal intermediate gaps, we find an analytical upper bound for the transition probability in the limit of large number of environmental spins. We show that such an environment will only suppress the probability of success for adiabatic quantum computation by at most a factor close to 1/2.

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24

Eastman, J. Ronald, and Jiena He. "A Regression-Based Procedure for Markov Transition Probability Estimation in Land Change Modeling." Land 9, no. 11 (October 25, 2020): 407. http://dx.doi.org/10.3390/land9110407.

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Land change models commonly model the expected quantity of change as a Markov chain. Markov transition probabilities can be estimated by tabulating the relative frequency of change for all transitions between two dates. To estimate the appropriate transition probability matrix for any future date requires the determination of an annualized matrix through eigendecomposition followed by matrix powering. However, the technique yields multiple solutions, commonly with imaginary parts and negative transitions, and possibly with no non-negative real stochastic matrix solution. In addition, the computational burden of the procedure makes it infeasible for practical use with large problems. This paper describes a Regression-Based Markov (RBM) approximation technique based on quadratic regression of individual transitions that is shown to always yield stochastic matrices, with very low error characteristics. Using land cover data for the 48 conterminous US states, median errors in probability for the five states with the highest rates of transition were found to be less than 0.00001 and the maximum error of 0.006 was of the same order of magnitude experienced by the commonly used compromise of forcing small negative transitions estimated by eigendecomposition to 0. Additionally, the technique can solve land change modeling problems of any size with extremely high computational efficiency.

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25

Frič, Roman, Peter Eliaš, and Martin Papčo. "Divisible extension of probability." Mathematica Slovaca 70, no. 6 (December 16, 2020): 1445–56. http://dx.doi.org/10.1515/ms-2017-0441.

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AbstractWe outline the transition from classical probability space (Ω, A, p) to its "divisible" extension, where (as proposed by L. A. Zadeh) the σ-field A of Boolean random events is extended to the class 𝓜(A) of all measurable functions into [0,1] and the σ-additive probability measure p on A is extended to the probability integral ∫(·) dp on 𝓜(A). The resulting extension of (Ω, A,p) can be described as an epireflection reflecting A to 𝓜(A) and p to ∫(·) dp.The transition from A to 𝓜(A), resembling the transition from whole numbers to real numbers, is characterized by the extension of two-valued Boolean logic on A to multivalued Łukasiewicz logic on 𝓜(A) and the divisibility of random events: for each random event u ∈ 𝓜(A) and each positive natural number n we have u/n ∈ 𝓜(A) and ∫(u/n) dp = (1/n) ∫u dp.From the viewpoint of category theory, objects are of the form 𝓜(A), morphisms are observables from one object into another one and serve as channels through which stochastic information is conveyed.We study joint random experiments and asymmetrical stochastic dependence/independence of one constituent experiment on the other one. We present a canonical construction of conditional probability so that observables can be viewed as conditional probabilities.In the present paper we utilize various published results related to "quantum and fuzzy" generalizations of the classical theory, but our ultimate goal is to stress mathematical (categorical) aspects of the transition from classical to what we call divisible probability.

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26

M�ller, G., E. Tr�bert, V. Lodwig, C. Wagner, P. H. Heckmann, J. H. Blanke, A. E. Livingston, and P. H. Mokler. "Experimental transition probability for theE1 intercombination transition in Be-like Xe50+." Zeitschrift f�r Physik D Atoms, Molecules and Clusters 11, no. 4 (December 1989): 333–34. http://dx.doi.org/10.1007/bf01438508.

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27

Cygan, Wojciech, and Stjepan Šebek. "Transition probability estimates for subordinate random walks." Mathematische Nachrichten 294, no. 3 (January 21, 2021): 518–58. http://dx.doi.org/10.1002/mana.201900065.

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28

Yuting Hu, Rong Xie, and Wenjun Zhang. "Transition Probability Matrix Based Tourists Flow Prediction." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 5, no. 1 (January 15, 2013): 194–201. http://dx.doi.org/10.4156/aiss.vol5.issue1.24.

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29

Watanabe, Takuya. "Adiabatic transition probability for a tangential crossing." Hiroshima Mathematical Journal 36, no. 3 (November 2006): 443–68. http://dx.doi.org/10.32917/hmj/1171377083.

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30

NAGAYAMA, Haruya. "TRANSITION PROBABILITY OF A CERTAIN STOCHASTIC PROCESS." Memoirs of the Faculty of Science, Kyusyu University. Series A, Mathematics 47, no. 2 (1993): 213–26. http://dx.doi.org/10.2206/kyushumfs.47.213.

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31

Kawabata, T., and K. Nishikawa. "Protein structure comparison using transition probability matrix." Seibutsu Butsuri 39, supplement (1999): S116. http://dx.doi.org/10.2142/biophys.39.s116_3.

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32

Chen, Yu Ying, and Jimin Ye. "Community leader and transition probability based LPA." International Journal of Modern Physics B 34, no. 27 (October 6, 2020): 2050253. http://dx.doi.org/10.1142/s0217979220502537.

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Many practice problems can be transformed into complex networks, and complex network community discovery has become a hot research topic in various fields. The classic label propagation algorithm (LPA) can give community partition very quickly, but stability of the algorithm is poor due to random label propagation. To solve this problem, community leader principle is built and transition probability is introduced, a label propagation algorithm based on community leader and transition probability (CTLPA) is proposed. CTLPA selects threatened leaders and their communities according to the community leader principle, and uses the transition probability and the degree of the leader to jointly control the order for community merger, so that the threatened leader continuously devours the communities that threaten him, until a preliminary community partition is formed. To further reduce the number of community, in CTLPA, based on the characteristic of the community structure: close relationship within the community and sparse relationship outside the community, the closest communities are merged, until the final community partition is obtained. The CTLPA is compared with other five classic algorithms on LFR artificially generated networks and several real data sets. The experimental results show that CTLPA is robust in community partition, it always gives the same community partition, while the LPA will give different results from multiple independent runs. The number of community partition and the normalized mutual information (NMI) of the CTLPA are the best in most cases.

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33

Tong, Ming, C. F. Fischer, and L. Sturesson. "Systematic transition probability studies for neutral nitrogen." Journal of Physics B: Atomic, Molecular and Optical Physics 27, no. 20 (October 28, 1994): 4819–28. http://dx.doi.org/10.1088/0953-4075/27/20/003.

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34

Guo, Xiao-Kan. "Transition probability spaces in loop quantum gravity." Journal of Mathematical Physics 59, no. 3 (March 2018): 032302. http://dx.doi.org/10.1063/1.5022662.

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35

Wang, M. S. "Transition probability and interference in stochastic mechanics." Physical Review A 38, no. 10 (November 1, 1988): 5401–3. http://dx.doi.org/10.1103/physreva.38.5401.

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36

Val, J. A. del, J. A. Aparicio, V. R. González, and S. Mar. "Transition probability measurement of several OIIspectral lines." Journal of Physics B: Atomic, Molecular and Optical Physics 34, no. 22 (November 13, 2001): 4531–38. http://dx.doi.org/10.1088/0953-4075/34/22/319.

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37

Fu-Sui, Liu, and Chen Wan-Fang. "Necessity of Exact Calculation for Transition Probability." Communications in Theoretical Physics 39, no. 2 (February 15, 2003): 209–11. http://dx.doi.org/10.1088/0253-6102/39/2/209.

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38

Rumbos, B. "Noncommutativity and transition probability in quantum mechanics." International Journal of Theoretical Physics 32, no. 6 (June 1993): 927–31. http://dx.doi.org/10.1007/bf01215299.

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39

Telcs, Andras. "Transition Probability Estimates for Reversible Markov Chains." Electronic Communications in Probability 5 (2000): 29–37. http://dx.doi.org/10.1214/ecp.v5-1015.

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40

Semmes, P. B., R. A. Braga, J. C. Griffin, and R. W. Fink. "L2-L3Coster-Kronig transition probability forZ=54." Physical Review C 35, no. 2 (February 1, 1987): 749–51. http://dx.doi.org/10.1103/physrevc.35.749.

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41

Spears, William M. "A Compression Algorithm for Probability Transition Matrices." SIAM Journal on Matrix Analysis and Applications 20, no. 1 (January 1998): 60–77. http://dx.doi.org/10.1137/s0895479897316916.

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42

Plane, David A. "Requiem for the Fixed-Transition-Probability Migrant." Geographical Analysis 25, no. 3 (September 3, 2010): 211–23. http://dx.doi.org/10.1111/j.1538-4632.1993.tb00292.x.

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43

Denton, Frank T., Byron G. Spencer, and Deborah A. Welland. "Lifetime smoking patterns: A transition probability analysis." Socio-Economic Planning Sciences 27, no. 3 (September 1993): 181–98. http://dx.doi.org/10.1016/0038-0121(93)90003-2.

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44

Uhlmann, A. "The Transition Probability for States of *-Algebras." Annalen der Physik 497, no. 4-6 (1985): 524–32. http://dx.doi.org/10.1002/andp.19854970419.

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45

Gao, Y., and J. Culberson. "An Analysis of Phase Transition in NK Landscapes." Journal of Artificial Intelligence Research 17 (October 1, 2002): 309–32. http://dx.doi.org/10.1613/jair.1081.

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In this paper, we analyze the decision version of the NK landscape model from the perspective of threshold phenomena and phase transitions under two random distributions, the uniform probability model and the fixed ratio model. For the uniform probability model, we prove that the phase transition is easy in the sense that there is a polynomial algorithm that can solve a random instance of the problem with the probability asymptotic to 1 as the problem size tends to infinity. For the fixed ratio model, we establish several upper bounds for the solubility threshold, and prove that random instances with parameters above these upper bounds can be solved polynomially. This, together with our empirical study for random instances generated below and in the phase transition region, suggests that the phase transition of the fixed ratio model is also easy.

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46

Shenk, Mary K., Ryan O. Begley, David A. Nolin, and Andrew Swiatek. "When does matriliny fail? The frequencies and causes of transitions to and from matriliny estimated from a de novo coding of a cross-cultural sample." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1780 (July 15, 2019): 20190006. http://dx.doi.org/10.1098/rstb.2019.0006.

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The question of when and why societies have transitioned away from matriliny to other types of kinship systems—and when and why they transition towards matriliny—has a long history in anthropology, one that is heavily engaged with both evolutionary theory and cross-cultural research methods. This article presents tabulations from a new coding of ethnographic documents from the Standard Cross-Cultural Sample (SCCS), tallying claims of transitions in kinship systems both away from and to matriliny using various levels of stringency. We then use our counts as the outcome variables in a set of Bayesian analyses that simultaneously estimate the probability of a transition occurring given societal covariates alongside the conditional probability of detecting a transition given the volume of ethnographic data available to code. Our goal is to estimate the cross-cultural and comparative frequency of transitions away from and to matriliny, as well as to explore potential causes underlying these patterns. We find that transitions away from matriliny have been significantly more common than ‘reverse transitions' to matriliny. Our evidence suggests that both rates may be, in part, an artefact of the colonial and globalizing period during which the data comprising much of the current ethnographic record were recorded. Analyses of the correlates of transitions away from matriliny are consistent with several of the key causal arguments made by anthropologists over the past century, especially with respect to subsistence transition (to pastoralism, intensive agriculture and market economies), social complexity and colonialism, highlighting the importance of ecological factors in such transitions. This article is part of the theme issue ‘The evolution of female-biased kinship in humans and other mammals’.

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47

Lei Xiao and Xiaodai Dong. "The exact transition probability and bit error probability of two-dimensional signaling." IEEE Transactions on Wireless Communications 4, no. 5 (September 2005): 2600–2609. http://dx.doi.org/10.1109/twc.2005.853821.

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48

Bidabad, Bijan, and Behrouz Bidabad. "Complex Probability and Markov Stochastic Process." Indian Journal of Finance and Banking 3, no. 1 (June 4, 2019): 13–22. http://dx.doi.org/10.46281/ijfb.v3i1.290.

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This note discusses the existence of "complex probability" in the real world sensible problems. By defining a measure more general than the conventional definition of probability, the transition probability matrix of discrete Markov chain is broken to the periods shorter than a complete step of the transition. In this regard, the complex probability is implied.

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49

Takikawa, Hirofumi, Ryuichi Miyano, and Tateki Sakakibara. "Glow to Arc Transition Accompanying Pressure Increase and Transition Probability-Pressure Characteristics." IEEJ Transactions on Fundamentals and Materials 115, no. 11 (1995): 1057–61. http://dx.doi.org/10.1541/ieejfms1990.115.11_1057.

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50

Labar, J. L. "Relative transition probability of the M5-N3radiative transitions for the rare earth elements." Journal of Physics D: Applied Physics 26, no. 6 (June 14, 1993): 972–78. http://dx.doi.org/10.1088/0022-3727/26/6/014.

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