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Journal of the Operations Research Society of Japan

 Short Title: J. Oper. Res. Soc. Japan Publisher: Operations Research Society of Japan, Tokyo ISSN: 0453-4514 Online: http://www.orsj.or.jp/~archive/menu/01_10.html Comments: Indexed cover-to-cover
 Documents Indexed: 1,160 Publications (since 1965)
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Latest Issues

 64, No. 2 (2021) 64, No. 1 (2021) 63, No. 4 (2020) 63, No. 3 (2020) 63, No. 2 (2020) 63, No. 1 (2020) 62, No. 4 (2019) 62, No. 3 (2019) 62, No. 2 (2019) 62, No. 1 (2019) 61, No. 4 (2018) 61, No. 2 (2018) 61, No. 1 (2018) 60, No. 4 (2017) 60, No. 3 (2017) 60, No. 2 (2017) 60, No. 1 (2017) 59, No. 4 (2016) 59, No. 3 (2016) 59, No. 2 (2016) 59, No. 1 (2016) 58, No. 4 (2015) 58, No. 3 (2015) 58, No. 2 (2015) 58, No. 1 (2015) 57, No. 3-4 (2014) 57, No. 2 (2014) 57, No. 1 (2014) 56, No. 4 (2013) 56, No. 3 (2013) 56, No. 2 (2013) 56, No. 1 (2013) 55, No. 4 (2012) 55, No. 3 (2012) 55, No. 2 (2012) 55, No. 1 (2012) 54, No. 4 (2011) 54, No. 2-3 (2011) 54, No. 1 (2011) 53, No. 4 (2010) 53, No. 3 (2010) 53, No. 2 (2010) 53, No. 1 (2010) 52, No. 4 (2009) 52, No. 3 (2009) 52, No. 2 (2009) 52, No. 1 (2009) 51, No. 4 (2008) 51, No. 3 (2008) 51, No. 2 (2008) 51, No. 1 (2008) 50, No. 4 (2007) 50, No. 3 (2007) 50, No. 2 (2007) 50, No. 1 (2007) 49, No. 4 (2006) 49, No. 3 (2006) 49, No. 2 (2006) 49, No. 1 (2006) 48, No. 4 (2005) 48, No. 3 (2005) 48, No. 2 (2005) 48, No. 1 (2005) 47, No. 4 (2004) 47, No. 3 (2004) 47, No. 2 (2004) 47, No. 1 (2004) 46, No. 4 (2003) 46, No. 3 (2003) 46, No. 2 (2003) 46, No. 1 (2003) 45, No. 4 (2002) 45, No. 3 (2002) 45, No. 2 (2002) 45, No. 1 (2002) 44, No. 4 (2001) 44, No. 3 (2001) 44, No. 2 (2001) 44, No. 1 (2001) 43, No. 4 (2000) 43, No. 3 (2000) 43, No. 2 (2000) 43, No. 1 (2000) 42, No. 4 (1999) 42, No. 3 (1999) 42, No. 2 (1999) 42, No. 1 (1999) 41, No. 4 (1998) 41, No. 3 (1998) 41, No. 2 (1998) 41, No. 1 (1998) 40, No. 4 (1997) 40, No. 3 (1997) 40, No. 2 (1997) 40, No. 1 (1997) 39, No. 4 (1996) 39, No. 3 (1996) 39, No. 2 (1996) 39, No. 1 (1996) 38, No. 4 (1995) ...and 58 more Volumes
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Authors

 35 Nishida, Toshio 30 Ishii, Hiroaki 27 Hohzaki, Ryusuke 20 Fujishige, Satoru 17 Ibaraki, Toshihide 17 Iida, Koji 17 Mizuno, Shinji 16 Fukushima, Masao 16 Sumita, Ushio 16 Yamamoto, Yoshitsugu 15 Konno, Hiroshi 15 Mori, Masao 14 Mine, Hisashi 14 Nakagawa, Toshio 14 Takahashi, Yukio 14 Takine, Tetsuya 12 Ichimori, Tetsuo 12 Takagi, Hideaki 11 Hasegawa, Toshiharu 11 Kijima, Masaaki 11 Sawaki, Katsushige 11 Shioura, Akiyoshi 10 Dohi, Tadashi 10 Kojima, Masakazu 10 Kubo, Mikio 10 Murota, Kazuo 10 Ohno, Katsuhisa 10 Takahashi, Iwaro 10 Takahashi, Yutaka 10 Tamura, Akihisa 9 Imai, Hideki 9 Kikuta, Kensaku 9 Machihara, Fumiaki 9 Masuyama, Hiroyuki 9 Nishimura, Shoichi 9 Sakaguchi, Minoru 9 Suzuki, Atsuo 8 Ando, Kazutoshi 8 Baba, Yutaka 8 Kurano, Masami 8 Sekitani, Kazuyuki 8 Sung, Chang Sup 8 Takahashi, Yoshitaka 8 Tone, Kaoru 8 Yabe, Hiroshi 7 Karuno, Yoshiyuki 7 Kise, Hiroshi 7 Miyazawa, Masakiyo 7 Nakayama, Akira 7 Ohi, Fumio 7 Osaki, Shunji 7 Sandoh, Hiroaki 7 Taguchi, Azuma 6 Hamada, Toshio 6 Hibiki, Norio 6 Iri, Masao 6 Iwamoto, Seiichi 6 Kasahara, Shoji 6 Kasugai, Hiroshi 6 Kawai, Hajime 6 Kimura, Toshikazu 6 Kurisu, Tadashi 6 Matsui, Tomomi 6 Nagamochi, Hiroshi 6 Shioda, Shigeo 6 Sueyoshi, Toshiyuki 6 Sunaga, Teruo 6 Tabata, Yoshio 6 Tanaka, Hideo 5 Fujisawa, Katsuki 5 Hirabayashi, Ryuichi 5 Hirai, Hiroshi 5 Kaji, Ikuo 5 Kino, Issei 5 Komiya, Toru 5 Kusaka, Yasuo 5 Lin, Yi-Kuei 5 Masuda, Yasushi 5 Moriguti, Sigeiti 5 Muramatsu, Masakazu 5 Muto, Shigeo 5 Nakagami, Junichi 5 Nakai, Teruhisa 5 Nakata, Kazuhide 5 Nishino, Hisakazu 5 Nishizawa, Kazutomo 5 Ohuchi, Azuma 5 Oyama, Tatsuo 5 Sasaki, Mihiro 5 Sato, Kimitoshi 5 Shanthikumar, Jeyaveerasingam George 5 Sugiyama, Manabu 5 Suzuki, Hisatoshi 5 Tokinaga, Shozo 5 Yagiura, Mutsunori 5 Yamada, Yoshiyasu 5 Yamaki, Naokazu 4 Adachi, Kouichi 4 Fujita, Toshiharu 4 Fukuta, Jiro ...and 931 more Authors
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Fields

 949 Operations research, mathematical programming (90-XX) 237 Game theory, economics, finance, and other social and behavioral sciences (91-XX) 234 Probability theory and stochastic processes (60-XX) 98 Numerical analysis (65-XX) 62 Computer science (68-XX) 54 Statistics (62-XX) 51 Combinatorics (05-XX) 23 Calculus of variations and optimal control; optimization (49-XX) 20 Systems theory; control (93-XX) 14 Convex and discrete geometry (52-XX) 9 Mathematical logic and foundations (03-XX) 7 General and overarching topics; collections (00-XX) 6 Information and communication theory, circuits (94-XX) 5 Order, lattices, ordered algebraic structures (06-XX) 4 Linear and multilinear algebra; matrix theory (15-XX) 3 General topology (54-XX) 3 Global analysis, analysis on manifolds (58-XX) 3 Biology and other natural sciences (92-XX) 2 Number theory (11-XX) 2 Integral transforms, operational calculus (44-XX) 2 Manifolds and cell complexes (57-XX) 2 Classical thermodynamics, heat transfer (80-XX) 1 Measure and integration (28-XX) 1 Ordinary differential equations (34-XX) 1 Approximations and expansions (41-XX) 1 Harmonic analysis on Euclidean spaces (42-XX) 1 Operator theory (47-XX) 1 Mechanics of particles and systems (70-XX) 1 Mechanics of deformable solids (74-XX)

Citations contained in zbMATH Open

600 Publications have been cited 2,458 times in 2,089 Documents Cited by Year
Extension of Newton and quasi-Newton methods to systems of $$PC^ 1$$ equations. Zbl 0611.65032
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1986
Bond portfolio optimization by bilinear fractional programming. Zbl 0675.90011
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A revision of Minty’s algorithm for finding a maximum weight stable set of a claw-free graph. Zbl 1128.05318
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2001
A mean-variance-skewness portfolio optimization model. Zbl 0839.90012
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Bond portfolio optimization problems and their applications to index tracking: A partial optimization approach. Zbl 0873.90009
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1996
On an extension of the maximum-flow minimum-cut theorem to multicommodity flows. Zbl 0223.90010
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1971
An overview of some stochastic stability methods. Zbl 1134.93412
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2004
Piecewise linear risk function and portfolio optimization. Zbl 0706.90005
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1990
The mean-variance approach to portfolio optimization subject to transaction costs. Zbl 0851.90014
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1996
Improvements of the incremental method for the Voronoi diagram with computational comparison of various algorithms. Zbl 0556.68039
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1984
Smoothing methods for complementarity problems and their applications: A survey. Zbl 0998.90078
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2000
Algorithms for solving the independent-flow problems. Zbl 0388.05007
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Properties of a positive reciprocal matrix and their application to AHP. Zbl 1003.15019
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1998
An algorithm for single constraint maximum collection problem. Zbl 0665.90092
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1988
A survey of algorithms for calculating power indices of weighted majority games. Zbl 1028.91511
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2000
A simple characterization of returns to scale in DEA. Zbl 0874.90006
Tone, Kaoru
1996
A summary of periodic replacement with minimal repair at failure. Zbl 0471.90055
Nakagawa, Toshio
1981
An algorithm for finding an optimal ”independent assignment”. Zbl 0346.90062
Iri, Masao; Tomizawa, Nobuaki
1976
A numerical method for the steady-state probabilities of a G1/G/C queueing system in a general class. Zbl 0348.60127
Takahashi, Yukio; Takami, Yoshinori
1976
Performance analysis of six approximation algorithms for the one-machine maximum lateness scheduling problem with ready times. Zbl 0427.90049
Kise, Hiroshi; Ibaraki, Toshihide; Mine, Hisashi
1979
Iterative methods for approximation of fixed points and their applications. Zbl 1004.65069
Takahashi, Wataru
2000
$$MAP/G/1$$ queues under $$N$$-policy with and without vacations. Zbl 0870.90062
Kasahara, Shoji; Takine, Tetsuya; Takahashi, Yutaka; Hasegawa, Toshiharu
1996
Models and measures for efficiency dominance in DEA. I: Additive models and MED measures. Zbl 0873.90001
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1996
On some preventive maintenance policies for IFR. Zbl 0205.48401
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1970
A note on submodular functions on distributive lattices. Zbl 0532.06008
Fujishige, Satoru; Tomizawa, Nobuaki
1983
The multiple-choice knapsack problem. Zbl 0379.90076
Ibaraki, Toshihide; Hasegawa, Toshiharu; Teranaka, Katsumi; Iwase, Jiro
1978
Comparative analyses of expected shortfall and value-at-risk. Zbl 1080.91047
Yamai, Yasuhiro; Yoshiba, Toshinao
2002
Linear complementarity and oriented matroids. Zbl 0773.90077
Fukuda, Komei; Terlaky, Tamás
1992
On an automated two-machine flowshop scheduling problem with infinite buffer. Zbl 0747.90048
Kise, Hiroshi
1991
A fast algorithm for solving large scale mean-variance models by compact factorization of covariance matrices. Zbl 0763.90004
Konno, Hiroshi; Suzuki, Ken-ichi
1992
Gross substitutes condition and discrete concavity for multi-unit valuations: a survey. Zbl 1367.91114
Shioura, Akiyoshi; Tamura, Akihisa
2015
Discrete-time Markovian decision processes with an unknown parameter. Average return criterion. Zbl 0238.90006
Kurano, Masami
1972
Mean-absolute deviation portfolio optimization model under transaction costs. Zbl 1028.91549
Konno, Hiroshi; Wijayanayake, Annista
1999
Relaxation heuristics for the set covering problem. Zbl 1142.90479
Umetani, Shunji; Yagiura, Mutsunori
2007
Generalized models for determining optimal number of minimal repairs before replacement. Zbl 0475.90038
Nakagawa, Toshio
1981
A survey of numerical methods for nonlinear semidefinite programming. Zbl 1367.65092
Yamashita, Hiroshi; Yabe, Hiroshi
2015
Flowshop schedules with sequence dependent setup times. Zbl 0625.90042
Gupta, Jatinder N. D.
1986
Analysis for minimizing weighted mean flow-time in flow-shop scheduling. Zbl 0451.90074
Miyazaki, Shigeji; Nishiyama, Noriyuki
1980
Search games: literature and survey. Zbl 1352.90044
Hohzaki, Ryusuke
2016
A discrete Bass model and its parameter estimation. Zbl 1107.90385
Satoh, Daisuke
2001
Stackelberg hub location problem. Zbl 1027.90054
Sasaki, Mihiro; Fukushima, Masao
2001
Optimal replacement policy for minimal repair model. Zbl 0322.90023
Tahara, Akihiko; Nishida, Toshio
1975
On G/G/1 queues with LIFO-P service discipline. Zbl 0609.60096
Shanthikumar, J. George; Sumita, Ushio
1986
A dual algorithm for finding the minimum-norm point in a polytope. Zbl 0712.90055
Fujishige, Satoru; Zhan, Ping
1990
Network-flow algorithms for lower-truncated transversal polymatroids. Zbl 0524.05025
Imai, Hiroshi
1983
A nonpreemptive priority $$MAP/G/1$$ queue with two classes of customers. Zbl 0870.90063
Takine, Tetsuya
1996
Two-machine scheduling under required precedence among jobs. Zbl 0328.90036
1976
$$L$$-convexity on graph structures. Zbl 1391.90475
Hirai, Hiroshi
2018
Least distance based inefficiency measures on the Pareto-efficient frontier in DEA. Zbl 1278.90257
Ando, Kazutoshi; Kai, Atsuhiko; Maeda, Yasunobu; Sekitani, Kazuyuki
2012
Nonlinear fractional programming. Zbl 0257.90043
Mangasarian, O. L.
1969
Ordering of convex fuzzy sets – a brief survey and new results. Zbl 0999.03512
Kurano, Masami; Yasuda, Masami; Nakagami, Jun-ichi; Yoshida, Yuji
2000
Efficiency-measuring DEA model for production system with $$k$$ independent subsystems. Zbl 0998.90032
Yang, Yinsheng; Ma, Benjiang; Koike, Masayuki
2000
A general framework for convex relaxation of polynomial optimization problems over cones. Zbl 1049.90052
Kojima, Masakazu; Kim, Sunyoung; Waki, Hayato
2003
One machine scheduling problem with dual criteria. Zbl 0453.90045
Miyazaki, Shigeji
1981
Application of principal component analysis for parsimonious summarization of DEA inputs and/or outputs. Zbl 0905.90002
Ueda, Tohru; Hoshiai, Yoko
1997
Best subset selection for eliminating multicollinearity. Zbl 1382.90068
Tamura, Ryuta; Kobayashi, Ken; Takano, Yuichi; Miyashiro, Ryuhei; Nakata, Kazuhide; Matsui, Tomomi
2017
A dichotomous search. Zbl 0273.90034
Murakami, Satoru
1971
Optimal stopping problem with uncertain recall. Zbl 0645.60050
Ikuta, Seizo
1988
Infinite-series representations of Laplace transforms of probability density functions for numerical inversion. Zbl 1002.60016
Abate, Joseph; Whitt, Ward
1999
Chance constrained bottleneck spanning tree problem with fuzzy random edge costs. Zbl 0998.90092
Katagiri, Hideki; Ishii, Hiroaki
2000
On the hub-and-spoke model with arc capacity constraints. Zbl 1137.90590
Sasaki, Mihiro; Fukushima, Masao
2003
On equivalent-job for job-block in 2xn sequencing problem with transportation-times. Zbl 0459.90033
Maggu, Parkash Lal; Das, Ghanshiam; Kumar, Ravinder
1981
Algorithms for quadratic fractional programming problems. Zbl 0349.90073
Ibaraki, Toshihide; Ishii, Hiroaki; Iwase, Jiro; Hasegawa, Toshiharu; Mine, Hisashi
1976
A dual algorithm for finding a nearest pair of points in two polytopes. Zbl 0778.90062
Fujishige, Satoru; Zhan, Ping
1992
An $$\varepsilon$$-free DEA and a new measure of efficiency. Zbl 0798.90004
Tone, Kaoru
1993
The generalized linear search problem. Existence of optimal search paths. Zbl 0642.90061
Balkhi, Zaid T.
1987
Markov modulated fluid queues with batch fluid arrivals. Zbl 1027.90018
2001
A minimax distribution free procedure for stochastic inventory models with a random backorder rate. Zbl 1138.90326
Ouyang, Liang-Yuh; Chuang, Bor-Ren
1999
Characteristics on stochastic DEA efficiency—reliability and probability being efficient. Zbl 0998.90059
Morita, Hiroshi; Seiford, Lawrence M.
1999
A search game with traveling cost on a tree. Zbl 0839.90064
Kikuta, Kensaku
1995
Optimal tool module design problem for NC machine tools. Zbl 0552.90066
Hirabayashi, Ryuichi; Suzuki, Hisatoshi; Tsuchiya, Noboru
1984
Local convergence properties of new methods in linear programming. Zbl 0714.90059
Tsuchiya, Takashi; Tanabe, Kunio
1990
An $$O(n^ 3L)$$ algorithm using a sequence for a linear complementarity problem. Zbl 0715.90091
Mizuno, Shinji
1990
The secretary problem in a competitive situation. Zbl 0482.90090
Fushimi, Masanori
1981
Optimal schedule in a GT-type flow-shop under series-parallel precedence constraints. Zbl 0524.90049
Sekiguchi, Yasuki
1983
Stochastic decision-making in a fuzzy environment. Zbl 0849.90122
Iwamoto, Seiichi; Fujita, Toshiharu
1995
Efficiently scanning all spanning trees of an undirected graph. Zbl 0862.90124
Shioura, Akiyoshi; Tamura, Akihisa
1995
Models and measures for efficiency dominance in DEA. II: Free disposal hull (FDH) and Russell measure (RM) approaches. Zbl 0873.90002
Bardhan, I.; Bowlin, W. F.; Cooper, W. W.; Sueyoshi, T.
1996
Vehicle scheduling on a tree to minimize maximum lateness. Zbl 0873.90051
Karuno, Yoshiyuki; Nagamochi, Hiroshi; Ibaraki, Toshihide
1996
$$Q$$-superlinear convergence of primal-dual interior point quasi-Newton methods for constrained optimization. Zbl 0914.90246
Yabe, Hiroshi; Yamashita, Hiroshi
1997
A primal approach to the independent assignment problem. Zbl 0364.90102
Fujishige, Satoru
1977
Locating a single facility in the plane in the presence of a bounded region and different norms. Zbl 1274.90192
Brimberg, Jack; Kakhki, Hossein Taghizadeh; Wesolowsky, George Orest
2005
A polling model with retrial customers. Zbl 0905.90067
Langaris, Christos
1997
An EOQ model for deterioration items under trade credit policy in a supply chain system. Zbl 1177.90017
Liao, Jui-Jung; Chung, Kun-Jen
2009
A structural geometrical analysis of weakly infeasible SDPS. Zbl 1357.90113
Lourenço, Bruno F.; Muramatsu, Masakazu; Tsuchiya, Takashi
2016
Approximate algorithms for the multiple-choice continuous knapsack problems. Zbl 0426.90059
Ibaraki, Toshihide
1980
Two machine open shop scheduling problem with controllable machine speeds. Zbl 0611.90059
Ishii, Hiroaki; Nishida, Toshio
1986
Performance analysis of a two-queue model with an $$(M,N)$$-threshold service schedule. Zbl 1038.90019
2001
Solving large scale mean variance models with dense non-factorable covariance matrices. Zbl 1052.90046
2001
Asymptotic properties of stationary distributions in two-stage tandem queueing systems. Zbl 1001.60100
Fujimoto, Kou; Takahashi, Yukio; Makimoto, Naoki
1998
On the reliability of Gaver’s parallel system sustained by a cold standby unit and attended by two repairmen. Zbl 0998.90029
Vanderperre, Edmond J.
1998
A characterization of faces of the base polyhedron associated with a submodular system. Zbl 0543.52008
Fujishige, Satoru
1984
Practical polynomial time algorithms for linear complementarity problems. Zbl 0708.90050
Mizuno, Shinji; Yoshise, Akiko; Kikuchi, Takeshi
1989
SDPA project: solving large-scale semidefinite programs. Zbl 1142.90465
Fujisawa, Katsuki; Nakata, Kazuhide; Yamashita, Makoto; Fukuda, Mituhiro
2007
On the joint distribution of the departure intervals in an $$M/G/1/N$$ queue. Zbl 0754.60111
Ishikawa, Akihiko
1991
Multi-variate stopping problem with a majority rule. Zbl 0439.90105
Kurano, Masami; Yasuda, Masami; Nakagami, Junichi
1980
Analysis of the control of queues with shortest processing time service discipline. Zbl 0448.60065
Shanthikumar, Jeyaveerasingam George
1980
Multi-variate stopping problems with a monotone rule. Zbl 0511.60040
Yasuda, Masami; Nakagami, Junichi; Kurano, Masami
1982
Application of the graph coloring algorithm to the frequency assignment problem. Zbl 0863.90131
Park, Taehoon; Lee, Chae Y.
1996
Analysis and optimization of a U-shaped production line. Zbl 0889.90079
1997
On fundamental operations for multimodular functions. Zbl 1426.90081
Moriguchi, Satoko; Murota, Kazuo
2019
$$L$$-convexity on graph structures. Zbl 1391.90475
Hirai, Hiroshi
2018
Real options and signaling in strategic investment games. Zbl 1395.91313
Watanabe, Takahiro
2018
A mixed integer programming approach for the minimum maximal flow. Zbl 1415.90014
Lu, Kuan; Mizuno, Shinji; Shi, Jianming
2018
On equivalence of $$M^\natural$$-concavity of a set function and submodularity of its conjugate. Zbl 1397.90334
Murota, Kazuo; Shioura, Akiyoshi
2018
A straightforward approach for solving fully fuzzy linear programming problem with LR-type fuzzy numbers. Zbl 1397.90263
Gong, Zengtai; Zhao, Wencui; Liu, Kun
2018
Corrigendum: “Error bounds for last-column-block-augmented-truncations of block-structured Markov chains”. Zbl 1406.90027
Masuyama, Hiroyuki
2018
A memoryless symmetric rank-one method with sufficient descent property for unconstrained optimization. Zbl 1391.90493
Nakayama, Shummin; Narushima, Yasushi; Yabe, Hiroshi
2018
Efficient overlap detection and construction algorithms for the bitmap shape packing problem. Zbl 1394.90092
Hu, Yannan; Fukatsu, Sho; Hashimoto, Hideki; Imahori, Shinji; Yagiura, Mutsunori
2018
Best subset selection for eliminating multicollinearity. Zbl 1382.90068
Tamura, Ryuta; Kobayashi, Ken; Takano, Yuichi; Miyashiro, Ryuhei; Nakata, Kazuhide; Matsui, Tomomi
2017
Algorithms for L-convex functions minimization: connection between discrete convex analysis and other research fields. Zbl 1382.90078
Shioura, Akiyoshi
2017
Error bounds for last-column-block-augmented truncations of block-structured Markov chains. Zbl 1387.90069
Masuyama, Hiroyuki
2017
Piecewise-linear approximation for feature subset selection in a sequential logit model. Zbl 1371.90068
Sato, Toshiki; Takano, Yuichi; Miyashiro, Ryuhei
2017
Search games on a broken wheel with traveling and search costs. Zbl 1382.91017
Baston, Vic; Kikuta, Kensaku
2017
A 2-approximation algorithm for the minimum knapsack problem with a forcing graph. Zbl 1371.90028
Takazawa, Yotaro; Mizuno, Shinji
2017
Optimal multiple pairs trading strategy using derivative free optimization under actual investment management conditions. Zbl 1386.91131
Yamamoto, Rei; Hibiki, Norio
2017
A note on the squared slack variables technique for nonlinear optimization. Zbl 1382.90103
Fukuda, Ellen H.; Fukushima, Masao
2017
Effects of a player’s awareness of information acquisition and ability to change strategy in attrition games. Zbl 1382.91008
Hohzaki, Ryusuke; Tanaka, Makoto
2017
A cutting plane algorithm for modularity maximization problem. Zbl 1371.90033
Izunaga, Yoichi; Yamamoto, Yoshitsugu
2017
Search games: literature and survey. Zbl 1352.90044
Hohzaki, Ryusuke
2016
A structural geometrical analysis of weakly infeasible SDPS. Zbl 1357.90113
Lourenço, Bruno F.; Muramatsu, Masakazu; Tsuchiya, Takashi
2016
Two-sided matching with externalities: a survey. Zbl 1349.91197
Bando, Keisuke; Kawasaki, Ryo; Muto, Shigeo
2016
PH fitting algorithm and its application to reliability engineering. Zbl 1349.90261
2016
Gross substitutes condition and discrete concavity for multi-unit valuations: a survey. Zbl 1367.91114
Shioura, Akiyoshi; Tamura, Akihisa
2015
A survey of numerical methods for nonlinear semidefinite programming. Zbl 1367.65092
Yamashita, Hiroshi; Yabe, Hiroshi
2015
Multi-leader-follower games: models, methods and applications. Zbl 1367.91045
Hu, Ming; Fukushima, Masao
2015
Diffusion approximation for stationary analysis of queues and their networks: a review. Zbl 1367.90042
Miyazawa, Masakiyo
2015
Parallel optimization algorithm for smooth convex optimization over fixed point sets of quasi-nonexpansive mappings. Zbl 1338.90080
Iiduka, Hideaki
2015
Routing algorithms under mutual interference constraints. Zbl 1339.90088
Ishihara, Kota; Kobayashi, Yusuke
2015
Stochastic marksmanship contest games with random termination – survey and applications. Zbl 1336.91027
2015
Stability in supply chain networks: an approach by discrete convex analysis. Zbl 1339.90056
Ikebe, Yoshiko T.; Tamura, Akihisa
2015
Enumerating bottom-left stable positions for rectangle placements with overlap. Zbl 1300.90037
Imahori, Shinji; Chien, Yuyao; Tanaka, Yuma; Yagiura, Mutsunori
2014
A two-step primal-dual interior point method for nonlinear semidefinite programming problems and its superlinear convergence. Zbl 1344.90048
Yamakawa, Yuya; Yamashita, Nobuo
2014
An alternative proof of Lovász’s cathedral theorem. Zbl 1301.05264
Kita, Nanao
2014
On half-integrality of network synthesis problem. Zbl 1302.90180
Hau, Than Nguyen; Hirai, Hiroshi; Tsuchimura, Nobuyuki
2014
An optimal control model for uncertain systems with time-delay. Zbl 1295.49019
Chen, Rong; Zhu, Yuanguo
2013
Tail asymptotics for cumulative processes sampled at heavy-tailed random times with applications to queueing models in Markovian environments. Zbl 1302.90049
Masuyama, Hiroyuki
2013
Comparisons of replacement policies with constant and random times. Zbl 1288.90018
Nakagawa, Toshio; Zhao, Xufeng
2013
Matroid intersection with priority constraints. Zbl 1288.90077
Kamiyama, Naoyuki
2013
Rebalance schedule optimization of a large scale portfolio under transaction cost. Zbl 1288.91180
Yamamoto, Rei; Konno, Hiroshi
2013
Protection strategies for critical retail facilities: applying interdiction median and maximal covering problems with fortification. Zbl 1288.90041
Choi, Yuran; Suzuki, Tsutomu
2013
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text:
# 3rd International Turkey-Iran Joint Conference on LHC Physics

Jun 10 – 15, 2019
Marmara University Sultanahmet Campus
Europe/Istanbul timezone

## Search for large extra dimensions and contact interactions in the dilepton mass spectra from proton-proton collisions at the center of mass energy of 13 TeV

Jun 11, 2019, 11:10 AM
40m
Marmara University Sultanahmet Campus

İstanbul

### Speaker

Mojtaba MOHAMMADI NAJAFABADI (IPM)

### Description

We present a search for nonresonant excesses in the invariant mass spectra of electron and muon pairs. The results are based on the data from proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the CMS experiment in 2016, corresponding to a total integrated luminosity of 36/fb. No significant deviation from the standard model is observed and limits are set at 95% confidence level on energy scales for large extra dimensions and contact interaction models

format: plain


text:
시간 제한 메모리 제한 제출 정답 맞은 사람 정답 비율
5 초 512 MB 5 3 3 60.000%

## 문제

In a parallel universe, people are crazy about using numbers that are powers of two, and they have defined an exciting sorting strategy for permutations of the numbers from 1 to 2N. They have defined a swapping operation in the following way:

• A range of numbers to be swapped is valid if and only if it is a range of adjacent numbers of size 2k, and its starting position (position of the first element in the range) is a multiple of 2k (where positions are 0-indexed).
• A valid swap operation of size-k is defined by swapping two distinct, valid ranges of numbers, each of size 2k.

To sort the given permutation, you are allowed to use at most one swap operation of each size k, for k in [0, N). Also, note that swapping a range with itself is not allowed.

For example, given the permutation [3, 6, 1, 2, 7, 8, 5, 4] (a permutation of the numbers from 1 to 23), the permutation can be sorted as follows:

• [3, 6, 1, 2, 7, 8, 5, 4]: make a size-2 swap of the ranges [3, 6, 1, 2] and [7, 8, 5, 4].
• [7, 8, 5, 4, 3, 6, 1, 2]: make a size-0 swap of [5] and [3].
• [7, 8, 3, 4, 5, 6, 1, 2]: make a size-1 swap of [7, 8] and [1, 2].
• [1, 2, 3, 4, 5, 6, 7, 8]: done.

The previous steps used every swap size (0, 1, and 2) at most once. Also, notice that all the swaps were valid because both ranges for each size k started at indices that were multiples of 2k.

Count how many ways there are to sort the given permutation by using the rules above. A way is an ordered sequence of swaps, and two ways are the same only if the sequences are identical.

## 입력

The first line of the input gives the number of test cases, T. T test cases follow. The first line of each test case contains a single integer N. The following line contains 2N space-separated integers: a permutation of the numbers 1, 2, ..., 2N.

Limits

• 1 ≤ T ≤ 200.
• 1 ≤ N ≤ 12.

## 출력

For each test case, output one line containing "Case #x: y", where x is the test case number (starting from 1) and y is the number of ways to sort the given permutation using the rules above.

## 예제 입력

4
1
2 1
2
1 4 3 2
3
7 8 5 6 1 2 4 3
2
4 3 2 1

## 예제 출력

Case #1: 1
Case #2: 3
Case #3: 6
Case #4: 0


text:
# clf3 dipole moment value

Vydáno 11.12.2020 - 07:05h. 0 Komentářů

For example, a molecule with two bond pairs and two lone pairs would have this notation: AX2E2. Polar "In chemistry, polarity is a separation of electric charge leading to a molecule or its chemical groups having an electric dipole or multipole moment. �pb�}������t[���a���>�D7�"k1fp�Q��:]���*n���wK̉b�ɽP�~�|Zz��ST'���{a�T��׫jӕ�{t��L��ɉԾǬ'Uշ�(��K�~ʌ�O�4 �֓�4߶t��ѡ|L!���r��>9Θ�h���]���s��X�o*�Њ���TUo�����X To determine the shapes of molecules, we must become acquainted with the Lewis electron dot structure. Favorite Answer. We need to determine if there are any lone pairs because we only looked at bonds. Therefore, the linear orientation minimizes the repulsion forces. The shape of a molecule is determined by the location of the nuclei and its electrons. When the electron groups are all bond pairs, they are named exactly like the electron-group geometry. BCl3 (trigonal planar) The molecular geometry of the SF2 molecule is _____.-tetrahedral ... Would the molecule have a nonzero dipole moment? Now, we are ready to apply EN to determine whether or not molecules are polar. Whereas the molecules like Chlorine gas (Cl2) and oxygen gas (O2) are nonpolar and exhibit 0 D dipole moment. Hence, we have 4 tetrahedrals. There are three ways to go about determining whether a molecule is polar or not. 2. Yes, it does. ), Chapter 4: Mass Relationships in Chemical Reactions, Valence-Shell Electron-Pair Repulsion Theory, Molecules with More than One Central Atom, Steps Used to Find the Shape of the Molecule, valence-shell electron-pair repulsion (VSPER) theory, http://en.wikipedia.org/wiki/File:Butane-2D-flat.png, http://en.wikipedia.org/wiki/File:Butane-3D-balls.png, http://www.green-planet-solar-energy.com/images/PT-small-electroneg.gif, http://en.wikipedia.org/wiki/Molecular_geometry, http://www.youtube.com/watch?v=QwpH0fEwwmo, http://library.thinkquest.org/10429/low/geometry/geometry.htm, http://www.youtube.com/watch?v=P79WCZIZXwk, information contact us at info@libretexts.org, status page at https://status.libretexts.org. OF2. One negative person is bad enough, but if you have two put together...that's just horrible. Res. NF3. So, they will be far away from each other. Try drawing the Lewis Structure for this molecule. The Lewis structure helps us identify the bond pairs and the lone pairs. We need to comprehend electronegativity which is abbreviated EN. The equation for dipole moment is as follows. Relevance. Draw CH3CH2CH2CH2Br. If it is linear or square planar, then it is non-polar. Electron-group geometry is determined by the number of electron groups. However, we live in a 3-D world. The shape is linear and the EN arrows point towards Oxygen. Due to the presence of extremely electronegative fluorines (3.98) the impact of the lone pairs of electrons is dented and therefore the dipole moment is weaker than in a comparable molecule such as ClH3. As a result ClF3 has a melting point of -76˚C and a boiling point of 12˚C. An electron group can be an electron pair, a lone pair, a single unpaired electron, a double bond or a triple bond on the center atom. When two electrical charges, of opposite sign and equal magnitude, are separated by a distance, an electric dipole is established. It is calculated as the product of the charge on atoms and the difference between them. Using the example above, we would add that H2O has a bond angle of 109.5° and CO2 would have a bond angle of 180°. Molecular geometry, also known as the molecular structure, is the three-dimensional structure or arrangement of atoms in a molecule. Name the electron-group geometry. Let's create an analogy. 3. , a nonpolar molecule), which is not consistent with the observation that the ClF 3 molecule does have a dipole moment. Thus, it has a symmetrical structure and zero dipole moment. Lewis structure-----F. F---S**---F-----F ** represent nonbonding electron pair on S atom. Join Our Performance Improvement Batch. Well, we want to optimize the bond angle of each central atom attached to each other. The hybridisation of Xe in XeF2 is sp3d i.e the geometry is trigonal pyramidal with 3 lone pair and 2 bond pair. Thus, the molecule's shape reflects its equilibrium state in which it has the lowest possible energy in the system. UV Tri-planar Project VOP node. If it has different terminal atoms, then it is polar. nonpolar. ... ClF3. Thus, electron pairs will spread themselves as far from each other as possible to minimize repulsion. h�bbdb�"/��� �AD2i�H�)�\��Z0�'�L ���y����s����^\$q��@������40��� ��׃E�H�`�o0�"Y��T��2.��a�o��?��sؒ����� �=�4!�30�|0 wd"� Answer Save. Dipole moment is equal to the product of the partial charge and the distance. The three fluorine atoms lie at the corners of an equilateral triangle with boron at the centre. e) Two of the given answers do not have a dipole moment. nonzero dipole moment. Dipole moment measurements help to distinguish between o-, m- and p-isomers because the dipole moment of p-isomer is zero and that of o-isomers is more than that of m-isomer. ClF3 XeF2 In these molecules the 2nd and 3rd lone pairs still prefer to occupy the equatorial sites In this way, the lone pairs are arranged farther apart from each other T-shaped Linear All bond angles are 90° IF5 XeF4 Square Pyramidal Square Planar The 1st lone pair can occupy any site The 2nd lone pair is arranged opposite to the 1st * * Bond dipole moments are commonly measured in debyes, represented by the symbol D. Molecules with only two atoms contain only one (single or multiple) bond, so the bond dipole moment is the molecular dipole moment. Refer back to the Lewis dot diagram of CO2. Red regions are nucleophilic (electron rich) and blue regions are electrophilic (electron poor) Ask Question + 100. This is examplified in the picture above. Remember that electron groups include lone pairs! We take in account the geometric distribution of the terminal atoms around each central atom. PCl 3 Br 2 dipole moment not =0 while that of PCl 2 Br 3 dipole moment =0,why??? Let's start with the leftmost side. Anonymous. Then, with the Lewis structure, we apply the valence-shell electron-pair repulsion (VSPER) theory to determine the molecular geometry and the electron-group geometry. Dip ole moment is measured in Debye units, which is equal to the distance between the charges multiplied by the charge (1 Debye eq uals $$3.34 \times 10^{-30}\; C\, m$$). To visualize this, think about movies. Explain which bonds are polar, indicate dipole moment, if one exist. The most electronegative element is Flourine with 4.0. Two negatives don't attract. The valence-shell electron-pair repulsion (VSEPR) theory states that electron pairs repel each other whether or not they are in bond pairs or in lone pairs. Dipole moment is equal to the product of the partial charge and the distance. The LibreTexts libraries are Powered by MindTouch® and are supported by the Department of Education Open Textbook Pilot Project, the UC Davis Office of the Provost, the UC Davis Library, the California State University Affordable Learning Solutions Program, and Merlot. The more electronegative end of the molecule is the negative end and the less electronegative end is the positive end. Each piece will form a particular shape. If it has different terminal atoms, then it is polar. a) CO 2 (linear) b) SO 2 (bent) c) BF 3 (trigonal planar) d) CF 4 (tetrahedral) Learn this topic by watching Molecular vs Electron Geometry Concept Videos. Each player represent an element and the ball represents the electron. For the final description, we combine the separate description of each atom. Have questions or comments? On the cross-base arrow, the cross represents the positive charge and the arrow represents the negative charge. Then, the angle between the atoms is used to find the net dipole moment. Luckily, there is a trend in the periodic table for EN. Since both arrows point toward Oxygen, we can say that there is a net EN. XeF 4 Xenon Tetrafluoride, ClF 3 Chlorine Trifluoride and CCl 3 Br Bromotrichloromethane. %%EOF p → \overrightarrow{p} p - electric dipole moment of the whole system, r i → \overrightarrow{r_i} r i - a vector pointing to the i-th electric charge, q i q_i q i - value of i-th charge, n n n - number of charges in the system. Formula where the Hydrogens ( not shown ) are implied to have single bonds to 2 and... Lewis structure -- -- -F. F -- -S * * represent nonbonding electron pair on s atom moment. And shape of the electrons and the distance will be far away from each other through... Contribute to the top, EN is how much an element and the EN arrows point towards Oxygen expected have... Charges and electrostatic potential mapped onto the surface of each other as possible to minimize and... With the Carbon it 's molecular shape is linear and the arrow represents the positive end other! Whenever a molecule is known to be near each other and have the same EN difference with... As bad or mean and you do n't want to optimize the angles. With single bonds attached to each other meter ( C x m ) there are no pairs... Arrow towards Oxygen people will be far away from each other c-c-c-c the... On how they are named exactly like the electron-group geometry Definition, Detailed explanation and Formula dipole clf3 dipole moment value... Be near each other are polar, it means that it has a net EN @ libretexts.org or out. Will increase molecules must contain polar bonds due to the product of polarity! Problems molecular vs electron geometry Practice Problems molecular vs electron geometry Practice Problems molecular vs electron geometry Problems. Both compounds are sp3d2 hybridised but in pcl3br2 the 2 lone pairs. ) it it. Of 0 D dipole moment with the observation that the ClF 3 Chlorine and! We need to determine the molecular geometry a 2-D plane, then the molecule ( )!, is the value of the charge and will repel each other is abbreviated EN lines bonds! To find the net dipole moment point to Oxygen and we end with... Otherwise noted, LibreTexts content is licensed by CC BY-NC-SA 3.0 geometry Practice Problems vs. Below for more information contact us at info @ libretexts.org or check out our page. The terminal atoms around each central atom and sigma - would be on the hydrogen and gas! Which results in having a dipole moment is equal to the electrons and the bond moment of the nuclei into! Not determine the shapes of molecules, we have no net charge and the molecule is polar two electron and... It overrules it because it has a melting point of -76˚C and boiling... Trend, we have two arrows because Oxygen is bonded to which compound would expected. Are implied to have single bonds attached to hydrogen and the less electronegative of! Zero dipole moment ( \ ( \mu\ ) ) and determine whether they are named exactly the! Only on electron groups so it overrules it because it has a symmetrical molecule is non-polar 2 by the of... Off by drawing the Lewis theory does not determine the polarity and whether not..., what are we going to do with 4 tetrahedrals, the shape of CO2 SOCl2 and Prdict the and. Simplified structural Formula where the Hydrogens ( not shown ) are implied to have same... A tetrahedral where Carbon binds with one Carbon and 3 Hydrogens occupy the equitor Behind. Bonds are polar, it is polar: //en.wikipedia.org/wiki/File: Butane-3D-balls.png content is licensed by CC 3.0. Are the 2 Br occupy the equitor Falling Behind in Studies -S *. And you do n't want to optimize the bond angle ) ( tetrahedral )... bond polarity is the of! Step in predicting shapes of molecules because it helps us identify the valence electron pairs are in! A boiling point of 12˚C bonds to 2 Carbons and 2 single bonds to and! And name the shape and determine whether they are clf3 dipole moment value depending on the center atom, then it is or... Electrons = 6 + ( 4x7 ) = 34 an equilateral triangle with boron at positions... In a tetrahedral where Carbon binds with one Carbon and 3 Hydrogens arrow towards.. Named exactly like the electron-group geometry are the angles between adjacent lines representing bonds must contain polar due... Same when there are any lone pairs of electron groups contribute to the product the... Binds with one Carbon and 3 Hydrogens equilibrium State in which it has the lowest possible energy the. On how they are polar, indicate dipole moment not =0 while that of 2... Atoms is used to find the net dipole at Butane provided by the number of electron groups all. Angle around central atom around 2.6×10 −30Cm because there are no lone pairs present in the EN! Is how much an element really wants an clf3 dipole moment value all Chemistry Practice Problems that the... Pairs and the arrow represents the electron groups are all bond pairs and the 2 lone pairs one. Molecule is polar non-polar C. there are any lone pairs. ) have bonds! The hybridisation of Xe in XeF2 is sp3d i.e the geometry is determined by the difference in electronegativity between hydrogen... In consideration of the molecule have a tetrahedral clf3 dipole moment value Carbon binds with one Carbon and 3 Hydrogens an important constants! Planar, tetraheral, trigonal-bipyramidal, and Approximate bond angle can help differentiate between,! To other ones the two negative people will be mean towards each other arrows because Oxygen is bonded to pieces... Central atoms, all Carbon top, EN is how much an element and ball! Structural Formula where the Hydrogens ( not shown ) are nonpolar and exhibit 0 D dipole moment have two together!. ) it had a net dipole moment - Definition, Detailed explanation and Formula dipole.. Known to be near each other going to do with 4 tetrahedrals likely to repel each other structure arrangement!, each bond is -1.5D and electrostatic potential mapped onto the surface of each molecule electrons are alike charge! ( O2 ) are nonpolar and exhibit 0 D have 4 electron groups and no lone pairs present the! Degrees does not work since electronegative difference between C and F is canceled due to a difference in electronegativity the! Example, a negative person dioxide is therefore linear in electron-group geometry geometry is determined by the number lone! Other and have the same EN difference \mu\ ) ) theory does not determine the molecular shape is and... The given answers do not have a dipole moment nonpolar and exhibit D! Central atom are the angles that demonstrate the maximum angle where it would minimize repulsion maximize... The ClF 3 molecule has dipole moment, if we draw out a tetrahedral would the molecule is polar non-polar... Not have a bond angle can help differentiate between linear, trigonal-planar,,. Answer = ClF3 ( Chlorine Trifluoride and CCl 3 Br Bromotrichloromethane end up with a new bigger... Is C4H10 step in predicting shapes of molecules, we move on to the Lewis does... Are ready to apply the VSEPR theory provided by the number of lone there. Negative charges which results in having a dipole moment value of the molecules like Chlorine gas Cl2! A '' represents the positive charge and the difference between them is known! Oxygen atoms by the difference between them Foundation support under grant numbers 1246120, 1525057, and.! A link that has all the choices habe one atom then three another! Molecules and break it down into pieces: //status.libretexts.org the net dipole, then it is calculated by multiplying distance. Broke the molecule the seventh group of the SF2 molecule is 1.03 D originating towards direction. Exhibit 0 D when there are lone pairs and two lone pairs it 's bonded to and... Carbon, we have a dipole moment around central atom angle around central and! Do with 4 tetrahedrals, the linear orientation minimizes the repulsion forces if the molecule has dipole... Carbon has 2 single bonds to 2 Carbons and 2 because it has a symmetrical and. The molecules melting point of 12˚C: AX2E2 of Iodinewill be in the centre 1 0! The maximum angle where it would minimize repulsion and maximize attraction a difference in their charge left on the and! Into two categories, the electron-group geometry is trigonal pyramidal with 3 lone and. = 6 + ( 4x7 ) = 34 question Next question get more help from Chegg the screen that. Also, Iodine is in the centre Carbon and 3 Hydrogens Tetrafluoride, ClF 3 molecule does a... Trigonal-Bipyramidal, or octahedral ( \mu\ ) ) away from each other is through angles,. Of Iodinewill be in the molecule electron groups are the 2 lone pairs affecting the orientation of the bond! If there are lone pairs of Oxygen clf3 dipole moment value d\ ] with continuing this trend, can! Has three single bonds attached to each other nuclei settle into positions that minimize repulsion of equilateral. 'S just horrible for more information contact us at info @ libretexts.org check... Four simple steps to apply the VSEPR theory predicts the distribution of the molecules and arrangement of atoms a... Negative charges go about determining whether a molecule is polar or non-polar and F is canceled due to its moment... Can say that there is a ball hog is more important. ) you have two put together that! 2-D plane, then it is the first step in predicting shapes of molecules because it non-polar... One negative person is seen as bad or mean and you do n't want to optimize the angle. Atoms, then it is polar when the electrons, the linear orientation the. Status page at https: //status.libretexts.org electrons in its outer orbit not =0 while that of 2. One negative person is bad enough, but also lone pairs affecting the orientation of the molecule... Other atomic nuclei around the central determine the polarity of any compound depends on geometry. Is called the dipole moment ( trigonal planar ) the molecular geometry molecular vs electron geometry Problems...


text:
## anonymous 5 years ago Find Function represented by

1. anonymous

$\sum_{0}^{\infty}n x^n$

2. anonymous

$\sum_{1}^{\infty}nx^n$

3. anonymous

f(x)=x,2x^2,3x^3...nx^n

4. anonymous

Thank you for answering but this is just the series, not a function


text:
# find eigenvalues of 3x3 matrix symbolab

is lambda plus 1. easy to factor. 1 coefficient out here. The calculator will find the eigenvalues and eigenvectors (eigenspace) of the given square matrix, with steps shown. non-zero vector v is equal to lambda times that non-zero matrix for any lambda. And so it's usually In general, you can skip the multiplication sign, so 5x is equivalent to 5*x. Lambda squared times that. there is no real trivial-- there is no quadratic. out the eigenvalues for a 3 by 3 matrix. with integer solutions. is minus 9 lambda plus 27. Plus 16. And now the rule of Sarrus I Thus it can find eigenvalues of a square matrix up to 4th degree. If $\mathbf{I}$ is the identity matrix of $\mathbf{A}$ and $\lambda$ is the unknown eigenvalue (represent the unknown eigenvalues), then the characteristic equation is \begin{equation*} \det(\mathbf{A}-\lambda \mathbf{I})=0. That’s generally not too bad provided we keep $$n$$ small. you get a 0. Here, you already know that the matrix is rank deficient, since one column is zero. Likewise this fact also tells us that for an $$n \times n$$ matrix, $$A$$, we will have $$n$$ eigenvalues if we include all repeated eigenvalues. We’ll be using the latter to find the inverse of matrices of order 3x3 or larger. The Matrixâ ¦ Symbolab Version. And then I can take this For this matrix, the eigenvalues are complex: lambda = -3.0710 -2.4645+17.6008i -2.4645-17.6008i The real part of each of the eigenvalues is negative, so e λ t approaches zero as t increases. And so lambda minus Please Find The Eigenvalues Of 2B+3I In Terms Of λ, Where I Is The Identity Matrix. And these roots, we already 0 minus 2 is minus 2. Problems in Mathematics. this diagonal. to remember the formula. Find the characteristic function, eigenvalues, and eigenvectors of the rotation matrix. So I'll just write This scalar is called an eigenvalue of A . that in a different color. times minus 2. Step 1: Rewrite the first two columns of the matrix. The eigenvalues are immediately found, and finding eigenvectors for these matrices then becomes much easier. But let's apply it now to The determinant of a triangular matrix is easy to find - it is simply the product of the diagonal elements. Step 2: Estimate the matrix A – λ I A – \lambda I A – λ I, where λ \lambda λ is a scalar quantity. you might recognize it. It's been some time (school/uni) since I've worked with eigenvalues etc but I took a look at some of the articles I found when googled. So this is the characteristic by 3 identity matrix. Let D= Diagonal( 0; 1; 2) be the diagonal matrix whose diagonal entries are the eigenvalues. More than just an online eigenvalue calculator. matrix times A. The Matrixâ ¦ Symbolab Version. So that's 24 minus 1. We can thus find two linearly independent eigenvectors (say <-2,1> and <3,-2>) one for each eigenvalue. just take this product plus this product plus this product We will see how to find them (if they can be found) soon, but first let us see one in action: this up a little bit. To embed this widget in a post, install the Wolfram|Alpha Widget Shortcode Plugin and copy and paste the shortcode above into the HTML source. Minus 9 times 3, which sides, rewrote v as the identity matrix times v. Well this is only true if and Or another way to think about it And which one to use would really be up to yourself based on your actual needs. Khan Academy is a 501(c)(3) nonprofit organization. Lambda squared times minus 3 lambda minus 3. Calculating eigenvalues and eigenvectors for age- and stage-structured populations is made very simple by computers. from the right-hand side of both of these guys, and You can also explore eigenvectors, characteristic polynomials, invertible matrices, diagonalization and many other matrix-related topics. Let me finish up the diagonal. one and multiply it times that guy. going to be-- times the 3 by 3 identity matrix is just I divide it into this guy up here, into lambda cubed minus So it went in very nicely. The matrix has two eigenvalues (1 and 1) but they are obviously not distinct. For real eigenvalue λ3 = 6.6162, the eigenvector is: v3 = [ 6.3373, 14.282, 1] T. NOTE 1: The eigenvector output you see here may not be the same as what you obtain on paper. minus 9 times. It does so only for matrices 2x2, 3x3, and 4x4, using Solution of quadratic equation, Cubic equation and Quartic equation solution calculators. Since doing so results in a determinant of a matrix with a zero column, $\det A=0$. We have a minus 9 lambda and It Has 3 Eigenvalues λ1, λ2, And λ3. Let Abe a 3 3 symmetric matrix of real numbers. The values of λ that satisfy the equation are the generalized eigenvalues. So these two cancel out. Thanks In Advance. The first thing we need to do is to define the transition matrix. For a square matrix A, an Eigenvector and Eigenvalue make this equation true:. To embed this widget in a post on your WordPress blog, copy and paste the shortcode below into the HTML source: To add a widget to a MediaWiki site, the wiki must have the. $\endgroup$ – P. Lawrence Feb 13 at 13:49 To find eigenvalues of a matrix all we need to do is solve a polynomial. determinate. It is quite easy to notice that if X is a vector which satisfies , then the vector Y = c X (for any arbitrary number c) satisfies the same equation, i.e. minus 9 here. So if I take lambda minus 3 and So that is plus 4 again. Ae = e. for some scalar . And then let me simplify Now solve the systems [A - aI | 0], [A - bI | 0], [A - cI | 0]. becomes a little hairier. SOLUTION: • In such problems, we ﬁrst ﬁnd the eigenvalues of the matrix. And the easiest way, at least The algebraic multiplicity of an eigenvalue is the number of times it appears as a root of the characteristic polynomial (i.e., the polynomial whose roots are the eigenvalues of a matrix). 9 lambda plus 27. And then we do minus this column Let me repeat the definition of eigenvectors and eigenvalues from the Eigenvalue calculator. Wolfram|Alpha is a great resource for finding the eigenvalues of matrices. Get the free "Eigenvalues Calculator 3x3" widget for your website, blog, Wordpress, Blogger, or iGoogle. FINDING EIGENVALUES AND EIGENVECTORS EXAMPLE 1: Find the eigenvalues and eigenvectors of the matrix A = 1 −3 3 3 −5 3 6 −6 4 . The determinant of a triangular matrix is easy to find - it is simply the product of the diagonal elements. matrix minus A is going to be equal to-- it's actually pretty straightforward to find. Those are the two values that I just subtracted Av from both lambda squared times. to this guy, but I think you get the idea. The picture is more complicated, but as in the 2 by 2 case, our best insights come from finding the matrix's eigenvectors : that is, those vectors whose direction the transformation leaves unchanged. I have a plus lambda squared Beware, however, that row-reducing to row-echelon form and obtaining a triangular matrix does not give you the eigenvalues, as row-reduction changes the eigenvalues of the matrix … So this is true if and only if-- other root is. Here I show how to calculate the eigenvalues and eigenvectors for the right whale population example from class. \\) (enter a data after click each cell … Calculate eigenvalues and eigenvectors. Find the eigenvalues of A. I have solved a similar problem with a 2x2 matrix by using the properties of trace and determinant (trace = a + d and det = ad-bc). So I have minus 9 lambda. Minus 3 times 3 squared \\) (enter a data after click each cell … Calculate eigenvalues and eigenvectors. And then I have-- let's see. lambda minus 2. So we can just try them out. This is the final calculator devoted to the eigenvectors and eigenvalues. Plus 23. So if we try a 1, it's 1 minus So we say minus 2 then we have a-- let's see. Finding the inverse matrix of a 3x3 matrix or 4x4 matrix is a lot more complex and requires more complex mathematics including elementary row operations, etc. Home | Example: Find Eigenvalues and Eigenvectors of a 2x2 Matrix. And of course, we're going to right here is equal to 0. And now of course, we have There are two methods to find the inverse of a matrix: using minors or using elementary row operations (also called the Gauss-Jordan method), both methods are equally tedious. is minus 3 lambda squared. [V,D] = eig(A) returns matrices V and D.The columns of V present eigenvectors of A.The diagonal matrix D contains eigenvalues. And we said that this has to be And if you are dealing with A simple example is that an eigenvector does not change direction in a transformation:. And that was our takeaway. The basis of the solution sets of these systems are the eigenvectors. Everything along the diagonal is times this product. Ae= I e. and in turn as. there-- this matrix A right there-- the possible eigenvalues Use this tool to easily calculate the eigenvalues and eigenvectors of 3x3 matrices. Introduction to eigenvalues and eigenvectors, Proof of formula for determining eigenvalues, Example solving for the eigenvalues of a 2x2 matrix, Finding eigenvectors and eigenspaces example, Eigenvectors and eigenspaces for a 3x3 matrix, Showing that an eigenbasis makes for good coordinate systems. This is true if and only if-- This is the final calculator devoted to the eigenvectors and eigenvalues. The Mathematics Of It. This page explains how to calculate the determinant of 4 x 4 matrix. This is the final calculator devoted to the eigenvectors and eigenvalues. And that says, any value, lambda, that satisfies this equation for v is a non-zero vector. 3X3 Eigenvalue Calculator. Let's do this one. 3 4 1 2 5 −2 −1 6 −3 times this column. Matrix, the one with numbers, arranged with rows and columns, is extremely useful in most scientific fields. For a square matrix A, an Eigenvector and Eigenvalue make this equation true:. minus 9 lambda. This may be rewritten. So we're going to have to do That does equal 0. is it's not invertible, or it has a determinant of 0. We're going to use the 3 So all these are potential About & Contact | Input the components of a square matrix separating the numbers with spaces. If non-zero e is an eigenvector of the 3 by 3 matrix A, then. It is very unlikely that you have square matrix of higher degree in math problems, because, according to Abel–Ruffini theorem, a general polynomial equation of degree 5 or higher has no solution in radicals, thus, it can be solved only by numerical methods. let's see, these guys right here become an 8 and then And then we have minus 2 times So lambda times the identity The eigenvalues are not necessarily distinct. determinant of lambda times the identity matrix minus roots. 0 plus or minus minus 1 is If you're seeing this message, it means we're having trouble loading external resources on our website. find the eigenvalues and eigenvectors of matrices 3x3 The 3x3 matrix is similar to a matrix with diagonal elements 1,4,4 reading down the main diagonal and a 1 on the super-diagonal, i.e. Active 5 days ago. Suppose that t r ( A) = − 1 and d e t ( A) = 45. rows right there. So that's the identity So 1 is not a root. And unlucky or lucky for us, Plus 4. Step 2: Estimate the matrix A – λ I A – \lambda I A … You can find the reduced row echelon form of a matrix to find the solutions to a system of equations. is that its columns are not linearly independent. The solutions x are your eigenvalues. And then plus, let's see, And we're just left with matrix minus A times v. I just factored the vector v out minus 2 lambda. Every eigenvector makes up a one-dimensional eigenspace. It can also be termed as characteristic roots, characteristic values, proper values, or latent roots.The eigen value and eigen vector of a given matrix A, satisfies the equation Ax = λx , … The next step is finding the roots/eigenvalues of the characteristic polynomial. That's one. plus 8 here. of A. across here, so that's the only thing that becomes I'll write it like this. Consider the 2 by 2 rotation matrix given by cosine and sine functions. is lambda cubed. We know that 3 is a root and And let's see if we that's going to be minus 3 lambda squared. A, if and only if, each of these steps are true. I just take those two rows. I'm just left with some matrix times v. Well this is only true-- let to be equal to 0 for some non-zero vector v. That means that the null space 0 plus 1, which is 1. . Keywords: eigenvalues, symmetric matrix, Jacobi’s method, RPN, programmable calculator, HP-41C, HP42S 1. what the eigenvalues are. So it's going to be 4 times algebra class generally-- it doesn't even have to be in the https://www.khanacademy.org/.../v/linear-algebra-eigenvalues-of-a-3x3-matrix for some non-zero vector v. In the next video, we'll So now you have minus Lambda minus minus 1-- I'll Talk about over my head - whoosh!!! Consider the 2 by 2 rotation matrix given by cosine and sine functions. From linear algebra, we know that Ahas all real-valued eigenvalues and a full basis of eigenvectors. matrix-eigenvalues-calculator. Let's say that a, b, c are your eignevalues. polynomial and this represents the determinant for I have a 3x3 real symmetric matrix, from which I need to find the eigenvalues. me rewrite this over here, this equation just in a form We have a 23 and we do this one. these terms right here. if-- for some at non-zero vector, if and only if, the everything really. Eigenvalues and eigenvectors calculator. Find the determinant of | 3 4 1 25 − −1 6 −3 |. abelian group augmented matrix basis basis for a vector space characteristic polynomial commutative ring determinant determinant of a matrix diagonalization diagonal matrix eigenvalue eigenvector elementary row operations exam finite group group group homomorphism group theory homomorphism ideal inverse matrix invertible matrix kernel linear algebra linear combination linearly … The generalized eigenvalue problem is to determine the solution to the equation Av = λBv, where A and B are n-by-n matrices, v is a column vector of length n, and λ is a scalar. EXAMPLE 1: Find the eigenvalues and eigenvectors of the matrix A = 1 −3 3 3 −5 3 6 −6 4 . this 3 by 3 matrix A. JACOBI is a program written in 1980 for the HP-41C programmable calculator to find all eigenvalues of a real NxN symmetric matrix using Jacobi’s method. So it's going to be lambda cubed has simplified to lambda minus 3 times lambda squared Eigenvalues and Eigenvectors Calculator for a 3 X 3 Real Matrix This page contains a routine that numerically finds the eigenvalues and eigenvectors of a 3 X 3 Real Matrix. I have a minus 1, I have an 8 and I have an 8. The geometric multiplicity of an eigenvalue is the dimension of the linear space of its associated eigenvectors (i.e., its eigenspace). have to set this equal to 0 if lambda is truly an eigenvalue 3 lambda squared minus 9 lambda plus 27, what do I get? This calculator allows you to enter any square matrix from 2x2, 3x3, 4x4 all the way up to 9x9 size. So this product is lambda plus and the two eigenvalues are . actually solve for the eigenvectors, now that we know Learn the steps on how to find the eigenvalues of a 3x3 matrix. Let be a basis for of generalized eigenvectors of . our matrix A, our 3 by 3 matrix A that we had way up ... Related Symbolab blog posts. integer solutions, then your roots are going to be factors Matrices are the foundation of Linear Algebra; which has gained more and more importance in science, physics and eningineering. Thus it can find eigenvalues of a square matrix up to 4th degree. This is just some matrix. And then I have this That's plus 4. and then I subtract out this product times this product You get 0. , where is some scalar number. of this matrix has got to be nontrivial. vector v. Let we write that for 0 minus minus 1. First, we will create a square matrix of order 3X3 using numpy library. and the two eigenvalues are . 0 minus 2 is minus 2. EigenValues is a special set of scalar values, associated with a linear system of matrix equations. to be x minus 3 times something else. put them right there. context of eigenvalues, you probably will be dealing Specifically a tri-diagonal matrix with real entries, but with complex values in the top right and bottom left corners. I want you to just remember the squared terms? this leads to-- I'll write it like this. They have many uses! And then, what are my lambda Let me write this. B is a 3x3 matrix. Minus 2 lambda and then There are vectors for which matrix transformation produces the vector that is parallel to the original vector. Well lambda minus 3 goes And now I have to simplify equal to minus 3. need to have in order for lambda to be an eigenvalue of a If and only if A times some Times lambda minus 2. Eigenvalues[{m, a}] gives the generalized eigenvalues of m with respect to a . I have a minus 4 lambda. times v is just v. Minus Av. 1 cubed is 1 minus 3. some non-zero v. Now this is true if and only if, Find more Mathematics widgets in Wolfram|Alpha. lambda minus 2. First one was the Characteristic polynomial calculator, which produces characteristic equation suitable for further processing. Especially if you have a Eigenvalues[m, k] gives the first k eigenvalues of m . would make our characteristic polynomial or the determinant So first I can take lambda and kind of the art of factoring a quadratic polynomial. $\begingroup$ @Morten The transformation-invariance is pretty clear if you understand a matrix … Step 3: Find the determinant of matrix A – λ I A – \lambda I A – λ I and equate it to zero. It is the union of zero vector and set of all eigenvector corresponding to the eigenvalue. this equal to 0. I think it was two videos Finding of eigenvalues and eigenvectors. You can also calculate a 4x4 determinant on the input form. into 9 lambda. So let's see what the So I just rewrite these The constant terms, I have an 8, We could put it down minus lambda minus 1 minus 4 lambda plus 8. 0 minus 2 is minus 2. That's that one there. lambda minus 2 and we're subtracting. So we're going to have So lambda is an eigenvalue minus 4 lambda squared plus 4 lambda. Fact Get the free "Eigenvalue and Eigenvector for a 3x3 Matrix " widget for your website, blog, Wordpress, Blogger, or iGoogle. So that means that this is going Times-- if I multiply these two So let me try 1. SOLUTION: â ¢ In such problems, we ï¬ rst ï¬ nd the eigenvalues of the matrix. Also, if you can guess the eigenvector (up to a constant) by looking at the structure of $(A-\lambda I)$, you can find the corresponding eigenvalue. Eigenvalues and Eigenvectors of a 3 by 3 matrix Just as 2 by 2 matrices can represent transformations of the plane, 3 by 3 matrices can represent transformations of 3D space. Minus 2 times minus Or another way to think about it Related Symbolab blog posts. Let me just multiply That does not equal 0. If the resulting V has the same size as A, the matrix A has a full set of linearly independent eigenvectors that satisfy A*V = V*D. So you get to 0. SOLUTION: â ¢ In such problems, we ï¬ rst ï¬ nd the eigenvalues of the matrix. And this is very 9 is minus 11. with-- lambda times the identity matrix is just As in the 2 by 2 case, the matrix A− I must be singular. So we have a 27. 3 goes into this. So we're going to set The calculator will find the eigenvalues and eigenvectors (eigenspace) of the given square matrix, with steps shown. So plus lambda squared. Eigenvector and Eigenvalue. going to be-- this is, let me write this. So minus lambda plus 1. ago or three videos ago. only if the 0 vector is equal to lambda times the identity I could call it eigenvector v, paste them really. lambda plus 1. And then you have Show Instructions. The Matrix… Symbolab Version. know one of them. Steps to Find Eigenvalues of a Matrix. The Matrix… Symbolab Version. The eigenvalue is the factor which the matrix is expanded. is minus 27. Lambda minus minus 1 because when you do this 10 years from now, I don't want you And then the lambda terms [V,D,W] = eig(A,B) also returns full matrix W whose columns are the corresponding left eigenvectors, so that W'*A = D*W'*B. but diagonal really. And this is true if and only So minus 4 lambda. By definition, if and only if-- You can also explore eigenvectors, characteristic polynomials, invertible matrices, diagonalization and many other matrix-related topics. , a } ] gives the first two columns of the art of factoring a quadratic.. Let Abe a 3 3 symmetric matrix, a to do this, we 're going to have to it. Well, we ï¬ rst ï¬ nd the eigenvalues, not the and. Diagonal ( 0 ; 1 ; 2 ) be the diagonal is going to be x minus 3 times,! Still be an eigenvector the one with numbers, arranged with rows and columns is. Then becomes much easier the eigenvector, and λ3 the multiplication sign, . Sine functions or lucky for us, on our Second try we were able to find the eigenvalues are found! Of its associated eigenvectors ( eigenspace ) so lambda is an eigenvector and eigenvalue make this equation if is. With numbers, arranged with rows and columns, is to define the transition.. And actually, but with complex values in the last video we set out to find the eigenvalues of... If find eigenvalues of 3x3 matrix symbolab multiply these two guys out, lambda, that right there λ1... 1 and d e t ( a ) = − 1 and.! – Practice page 3 of 4 3 importance in science, physics eningineering. Our matrix of how we got to it symmetric matrix of real numbers the equation are the generalized eigenvalues a... Any square matrix a, then often find the space generated by the eigen vectors of a 2x2.. Minus 1 minus 4 lambda squared minus 9 lambda plus 27 0 or! The last video we set out to find - it is simply the product of the characteristic function eigenvalues... 4 x 4 matrix be a basis for of generalized eigenvectors of the of. 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text:
# If an atom has 34 protons and 40 neutrons, what is its atomic number?

$\text{Atomic number, } Z = 34$
$Z$ refers to the number of protons, positively charged nuclear particles. This number specifies the identity of the element. So what is the element?


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A. Morning run
time limit per test
2 seconds
memory limit per test
256 megabytes
input
standard input
output
standard output

People like to be fit. That's why many of them are ready to wake up at dawn, go to the stadium and run. In this problem your task is to help a company design a new stadium.

The city of N has a shabby old stadium. Many people like it and every morning thousands of people come out to this stadium to run. The stadium can be represented as a circle, its length is exactly l meters with a marked start line. However, there can't be simultaneous start in the morning, so exactly at 7, each runner goes to his favorite spot on the stadium and starts running from there. Note that not everybody runs in the same manner as everybody else. Some people run in the clockwise direction, some of them run in the counter-clockwise direction. It mostly depends on the runner's mood in the morning, so you can assume that each running direction is equiprobable for each runner in any fixed morning.

The stadium is tiny and is in need of major repair, for right now there only is one running track! You can't get too playful on a single track, that's why all runners keep the same running speed — exactly 1 meter per a time unit. Nevertheless, the runners that choose different directions bump into each other as they meet.

The company wants to design a new stadium, but they first need to know how bad the old one is. For that they need the expectation of the number of bumpings by t time units after the running has begun. Help the company count the required expectation. Note that each runner chooses a direction equiprobably, independently from the others and then all runners start running simultaneously at 7 a.m. Assume that each runner runs for t time units without stopping. Consider the runners to bump at a certain moment if at that moment they found themselves at the same point in the stadium. A pair of runners can bump more than once.

Input

The first line of the input contains three integers n, l, t (1 ≤ n ≤ 106, 1 ≤ l ≤ 109, 1 ≤ t ≤ 109). The next line contains n distinct integers a1, a2, ..., an (0 ≤ a1 < a2 < ... < an < l), here ai is the clockwise distance from the start line to the i-th runner's starting position.

Output

Print a single real number — the answer to the problem with absolute or relative error of at most 10 - 6.

Examples
Input
2 5 10 2
Output
0.2500000000
Input
3 7 30 1 6
Output
1.5000000000
Note

There are two runners in the first example. If the first runner run clockwise direction, then in 1 time unit he will be 1m away from the start line. If the second runner run counter-clockwise direction then in 1 time unit he will be also 1m away from the start line. And it is the only possible way to meet. We assume that each running direction is equiprobable, so the answer for the example is equal to 0.5·0.5 = 0.25.


text:
Prove that f(x) is an odd function?

• June 21st 2009, 01:11 PM
fardeen_gen
Prove that f(x) is an odd function?
Prove that $f(x) = \left\{ \begin{array}{cc}x^4\tan \frac{\pi x}{2}, &\mbox{if}\ |x|<1\\x|x|, &\mbox{if}\ |x|\geq 1\end{array}\right.$ is an odd function.
• June 21st 2009, 02:09 PM
Bruno J.
We want $f(x)=-f(-x) \: \forall x \in \mathbb{R}$.

If $|x|<1, f(-x) = (-x)^4 \tan(-\pi x/2) = x^4 (-\tan (\pi x/2)) = -f(x)$

If $|x|>1, f(-x) = (-x)|(-x)| = \left\{ \begin{array}{cc}-x|-x|, &\mbox{if}\ x<0\\-x|x|, &\mbox{if}\ x>0\end{array}\right.
$

so that in all cases $-f(-x)=f(x)$


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# Unisolvent point set

{{ safesubst:#invoke:Unsubst||$N=Unreferenced |date=__DATE__ |$B= {{#invoke:Message box|ambox}} }} In approximation theory, a finite collection of points ${\displaystyle X\subset R^{n}}$ is often called unisolvent for a space ${\displaystyle W}$ if any element ${\displaystyle w\in W}$ is uniquely determined by its values on ${\displaystyle X}$.
${\displaystyle X}$ is unisolvent for ${\displaystyle \Pi _{n}^{m}}$ (polynomials in n variables of degree at most m) if there exists a unique polynomial in ${\displaystyle \Pi _{n}^{m}}$ of lowest possible degree which interpolates the data ${\displaystyle X}$.
Simple examples in ${\displaystyle R}$ would be the fact that two distinct points determine a line, three points determine a parabola, etc. It is clear that over ${\displaystyle R}$, any collection of k + 1 distinct points will uniquely determine a polynomial of lowest possible degree in ${\displaystyle \Pi ^{k}}$.