Bisecting Sparse Random Graphs

Size: px
Start display at page:

Download "Bisecting Sparse Random Graphs"

Transcription

1 Bisecting Sparse Ranom Graphs Malwina J. Luczak,, Colin McDiarmi Mathematical Institute, University of Oxfor, Oxfor OX 3LB, Unite Kingom; Department of Statistics, University of Oxfor, Oxfor OX 3TG, Unite Kingom; Receie 3 September 999; accepte June 000 ABSTRACT: Consier partitions of the vertex set of a graph G into two sets with sizes iffering by at most : the bisection with of G is the minimum over all such partitions of the number of cross eges between the parts. We are intereste in sparse ranom graphs G with ege probability cn. We show that, if cln 4, then the bisection with is Ž n. n, c n with high probability; while if cln 4, then it is equal to 0 with high probability. There are corresponing threshol results for partitioning into any fixe number of parts. 00 John Wiley & Sons, Inc. Ranom Struct. Alg., 8, 338, 00. INTRODUCTION A leel -partition of a set V is a partition of V into sets with sizes iffering by at most. Given a partition of the vertex set of a graph G, the cross eges are the eges between the parts. The -section with w Ž G. is the minimum number of cross eges over all level -partitions of the vertex set V. When we refer to the bisection with, which has receive much attention, partly because of its relation to very large scale integrate circuit Ž VLSI. esign, 5, 7, 9, 0, 6. For general results on the -section with see 4. It is ifficult Ž NP-har. to etermine the -section with of a graph for any fixe Ž8,., an thus there has been interest in consiering its behavior for Corresponence to: C. McDiarmi. * Supporte by a British Telecommunications stuentship. 00 John Wiley & Sons, Inc. 3

2 3 LUCZAK AND MCDIARMID ranom graphs. We consier the stanar ranom graph G ž/, with vertices n, p,,..., n, an where the n possible eges appear inepenently with probability p. We shall be intereste in the sparse case, where ppž ncn. for some constant c0. This case has been investigate by MacGregor 4, Golberg an Lynch, an Alous. For each constant c, a value fž c. 0 is known such that a.s. the bisection with is at least fž c. n, so that for each c there is a linear lower boun on the bisection with. We use a.s. to mean with probability tening to as n. There are also upper bouns known for the bisection with. In particular, in it is shown that, if 0cln 4 then a.s. the bisection with is on. This follows from the result that, when cln 4, the maximum size of a component in G is about n. Golberg an Lynch n, c n further propose a conjecture which woul imply that the upper boun extens to cover all c, so that if 0c then a.s. the bisection with is on. In this paper we strengthen some of the above results, an isprove the conjecture of Golberg an Lynch: the threshol for linear bisection with is at cln 4, not at c. Our main theorem is as follows. Given an integer, let c ln. Note that c ln 4 an that c ecreases to as. We say that the events A Ž n hol with high probability if there exists 0 such that PA o e.. n Theorem. Let be an integer, an consier the -section with w. For any cc, there exists a constant 0 such that an for any 0cc, w G n with high probability, n, c n w G 0 with high probability. n, c n When pcn the giant component of the ranom graph Gn, p has size about n. Ž We iscuss the giant component in Section.. A main step in proving Theorem is the following result, which is perhaps of inepenent interest. Given, 0, a Ž,. -cut of a graph GŽ V, E. is a partition of V into two sets both of size at least V such that there are at most V cross eges. Lemma. Let c. For any 0, there exists 0 such that, with high probability, the giant component of G has no Ž,. -cut. n, c n n. PROOF Let L Ž G. j enote the jth largest orer of a component of a graph G. Recall the following result concerning the components of ranom graphs ŽEros an Renyi 6, see. 3.

3 BISECTING SPARSE RANDOM GRAPHS 33 Ž. ct Lemma 3. a For c, the equation te 0 has a unique positie solution Ž c., an Ž c. gies a continuous strictly increasing function from Ž,. to Ž 0,.. Ž b. Let c be a constant, an let pcn. Let Ž n. as n. Then the largest orer of a component satisfies L Gn, p c n n n a.s. an the secon largest orer of a component satisfies where cln c. L G Ž. ln n a.s. n, p By the results above, when c the ranom graph Gn, c n a.s. has a unique component of largest orer, which is much larger than all the other components. We efine the giant component of a ranom graph Gn, c n to be the lexicographi- cally first component of largest orer. In fact, there is a unique component of maximum orer with high probability. We nee a lemma on concentration, which follows irectly from Theorem 3.9 of 3. Ž. Lemma 4. Consier a graph inariant f such that f G f G b wheneer the graphs G an G iffer in only one ege. Let c0 an let pcn. Then for any 0 n, p n, p ž / bcž 3. b ž / ž / P f G E f G n exp n. Lemma 5. Let c0, let pcn, an let k be a positie integer. For any 0, the number Z Z Ž G. of components of orer k satisfies k k n, p Z EZ n with high probability. In particular, the number Z with high probability. k c Z e n n k of isolate ertices satisfies Proof. Apply Lemma 4 with fgz G an b. k Lemma 6. Let c an let pcn. Let Ž c. be as in Lemma 3. For any 0, both L G Ž c. n n an with high probability. n, p LŽ Gn, p. n Proof. The first part is from O Connell 5. For the secon part, we use two results from 3. First, for each k,,..., the number Z Z Ž G. of compok k n, p

4 34 LUCZAK AND MCDIARMID nents that are trees of orer k satisfies as n; an secon, k kc ke Zk n kc e k! k kc Ž c. Ý Ž kc. e k!. k These results together imply that for any 0 there exists k 0 such that k 0 kež Z. Ž Ž c.. n Ý k for all n sufficiently large. Now use the first part an Lemma 5. k Lemma 7. For any 0, there exist an n0 such that the following hols. For all nn 0, an for all connecte graphs G with n ertices, there are at most Ž. n bipartitions of G with at most 0 n cross eges. Proof. Let T be an arbitrary spanning tree of G. Any -partition S, S of T is etermine uniquely by the corresponing set of cross eges, together with the specification for each cross ege of which of its enpoints is in S. For as T is connecte, the cross eges specify a nonempty subset S of S, an then S is the set of vertices such that there is a path from to one of the vertices in S where this path oes not use any of the cross eges. ŽIf S then no path from to S can avoi the cross eges, an if S then any shortest path from to S avois the cross eges.. Hence, since T has n eges, the number of -partitions of T Ž an hence also of G. with at most n cross eges is no more than ž / n n j n Ý j ž Ž. / j n O n, assuming. Now let 0. As 0, ŽŽ... Hence, for sufficiently small an n sufficiently large, there are at most Ž. n partitions with at most n cross eges. Proof of Lemma. Let pcn. The iea of the proof is to construct the ranom graph Gn, p as the union of two new ranom graphs, such that the giant component U of the first new ranom graph Gn, p is close to the giant component of the original ranom graph, there are not too many -partitions of U in Gn, p with few cross eges, an the secon new ranom graph Gn, p puts many eges into each of these -partitions. Let 0. Let c c be such that Ž c. Ž. Ž c., an let ccc. Let pcn, an let ž / pp c p O. p n n

5 BISECTING SPARSE RANDOM GRAPHS 35 We may form the ranom graph Gn, p as the union of two inepenent ranom graphs as follows. We generate inepenent ranom graphs Gn, p an G n, p, an form a thir ranom graph on the same vertex set,...,n4 with ege set the union of the ege sets of these two graphs. This thir graph has exactly the istribution of G, since pž p.ž p. n, p. Let U an U enote the giant components of the ranom graphs Gn, p an G n, p, respectively. It is convenient an shoul cause no confusion to use these symbols to enote also the corresponing vertex sets. We next efine four events A,..., A involving U an U, an efine three Ž small. 4 positive constants,, an. Let A A Ž n. U Ž. Ž c. n, an let 4 4 A A Ž n. U U an U Ž. U. Then by Lemma 6, both the events A an A let 0 satisfy ž / Ž c. c, expž 8., 3 hol with high probability. Let an let 0 be the minimum of an Ž from Lemma 7.. Let an A A Ž n. U has a Ž, n. -cut in G, n, p 4 A A Ž n. U has a Ž,. -cut in G. 4 4 n, p We aim to show that the complementary event A3 hols with high probability. We claim that AA3A 4. Ž. To show this, suppose that A hols an that U has a Ž,. -cut into BC. Let B BU an C CU. Then U has a partition into B C, both B an C are at least U U U U, an the number of cross eges is at most U U. Thus the event A4 hols, an we have prove the claim Ž.. It follows that PŽ A. PŽ A. PŽ A Our remaining task is to show that A4 hols with high probability. By Lemma 7 an our choice of, there are at most Ž. n Ž,. -cuts of U in G n, p. Consier any one such cut, partitioning U into BC say. Conitional on A, in the inepenent ranom graph G, the number of possible eges n, p

6 36 LUCZAK AND MCDIARMID between B an C is ž / ž / 3 B C U c n. Thus, conitional on A, the number X of eges in Gn, p between B an C has a binomial istribution with mean B C p nn. But if Y has a binomial istribution with mean m then PYm expž m8. see, for example Theorem A3, or 3 Theorem.3Ž. c. Hence an so PŽ X na. expž 8. expž n8. Ž., / PŽ A4A. ž. Finally, PŽ A. PŽ A A. PŽ A. 4 4, an it follows that A4 hols with high probability, as require. We nee two more lemmas in orer to complete the proof of the theorem. Lemma 8. Let be an integer, let GŽ V, E. be a graph with n ertices, an let UV be such that U n n, where 0Ž.. Suppose that there is a leel -partition of G with at most x cross eges. Then there is a bipartition of G with at most x cross eges, such that both parts contain at least n ertices in U. Proof. Let S,...,S be a -partition of V such that t S U n for each i,..., an t t. Now t t U t n. i i Thus, if t n then we may partition V into S an S S. So we may suppose that t n. Let j,...,4 be such that Note that tj t n, an so t t nt t. j j / ž / t tj ž n n n. Hence we may partition V into S Sj an Sj S. Lemma 9. Gien a list of positie integers aa ak summing to n, if a n an the number z of inices i such that ai is at least Ž.Ž a., then there is a partition of a,...,ak into sets, with sums iffering by at most. n n

7 BISECTING SPARSE RANDOM GRAPHS 37 Proof. First we put a into the ith set for i,...,. Ž If k we are one.. i We then a the remaining ai one by one to the sets arbitrarily, so that the sum of the numbers in each set is at most n. This can never fail, since when we try to a a number x, the total resiual capacity, namely n less the sum allocate, is at least zxž x.. Finally, we a the s. Proof of Theorem. First consier the case cc. For some 0Ž., L Ž G. n n, p n with high probability, by Lemma 6, an so the esire result follows from Lemmas an 8. Now let cc. Then by Lemmas 5 an 6, each of the events L Ž G. n, p n, c c L Gn, p e n, an Z e n hol with high probability, an the esire result follows from Lemma 9. Theorem above establishes the first-orer behavior of the -section with of G n, c n, which is what is important for algorithmic implications. The finer behavior exactly on the threshol is not aresse above. Let us simply make the following observations here. Fix an integer, an let pc n. Then, by 4 Ž. P w Gn, p 0 as n. Also, by Lemma 3, if n as n, then ' w G n n a.s. 3 n, p Perhaps this last inequality can be strengthene? ACKNOWLEDGMENT We woul like to thank the referees for helpful comments. REFERENCES D. Alous, The harmonic mean formula for probabilities of unions: applications to sparse ranom graphs, Discrete Math 76 Ž 989., N. Alon an J. Spencer, The probabilistic metho, Wiley, New York, B. Bollobas, Ranom graphs, Acaemic Press, New York, D. Barraez, S. Boucheron, an W. Fernanez e la Vega, The giant component is normal, Combin Probab Comput Ž to appear.. 5 T.N. Biu, S. Chauhuri, F.T. Leighton, an M. Sipser, Graph bisection algorithms with goo average case behaviour, Combinatorica 7 Ž 987., P. Eros an A. Renyi, On the evolution of ranom graphs, Publ Math Inst Hungar Aca Sci 5 Ž 960., A. Frieze an M. Jerrum, Improve approximation algorithms for MAX k-cut an MAX BISECTION, Algorithmica 8 Ž 997., 677.

8 38 LUCZAK AND MCDIARMID 8 M.R. Garey, D.S. Johnson, an L. Stockmeyer, Some simplifie NP-complete graph problems, Theoret Comput Sci Ž 976., O. Golschmit an D.S. Hochbaum, Asymptotically optimal linear algorithm for the minimum k-cut in a ranom graph, SIAM J Discrete Math 3 Ž 980., M.K. Golberg an R. Garner, On the minimal cut problem, Proceeings of the Silver Jubilee Conference on Combinatorics, Waterloo, 98. M.K. Golberg an J.F. Lynch, Lower an upper bouns for the bisection with of a ranom graph, Congr Numer 49 Ž 985., 95. M.J. Luczak an S.D. Noble, Optimal arrangement of ata in a tree irectory, Discrete Appl Math Ž to appear.. 3 C. McDiarmi, Concentration, in probabilistic methos for algorithmic iscrete mathematics, M. Habib, C. McDiarmi, J. Ramirez, an B. Ree Ž Eitors., Springer-Verlag, Berlin, R.M. MacGregor, On partitioning a graph: a theoretical an empirical stuy, Ph.D. thesis, Stanfor University, N. O Connell, Some large eviation results for sparse ranom graphs, Probab Theory Relate Fiels 0 Ž 998., V. Rao an Y. Saab, On the graph bisection problem, IEEE Trans Circuits Systems- Fun Theory Appl 39 Ž 99.,

Ramsey numbers of some bipartite graphs versus complete graphs

Ramsey numbers of some bipartite graphs versus complete graphs Ramsey numbers of some bipartite graphs versus complete graphs Tao Jiang, Michael Salerno Miami University, Oxfor, OH 45056, USA Abstract. The Ramsey number r(h, K n ) is the smallest positive integer

More information

The chromatic number of graph powers

The chromatic number of graph powers Combinatorics, Probability an Computing (19XX) 00, 000 000. c 19XX Cambrige University Press Printe in the Unite Kingom The chromatic number of graph powers N O G A A L O N 1 an B O J A N M O H A R 1 Department

More information

Lecture 5. Symmetric Shearer s Lemma

Lecture 5. Symmetric Shearer s Lemma Stanfor University Spring 208 Math 233: Non-constructive methos in combinatorics Instructor: Jan Vonrák Lecture ate: January 23, 208 Original scribe: Erik Bates Lecture 5 Symmetric Shearer s Lemma Here

More information

Sharp Thresholds. Zachary Hamaker. March 15, 2010

Sharp Thresholds. Zachary Hamaker. March 15, 2010 Sharp Threshols Zachary Hamaker March 15, 2010 Abstract The Kolmogorov Zero-One law states that for tail events on infinite-imensional probability spaces, the probability must be either zero or one. Behavior

More information

A new proof of the sharpness of the phase transition for Bernoulli percolation on Z d

A new proof of the sharpness of the phase transition for Bernoulli percolation on Z d A new proof of the sharpness of the phase transition for Bernoulli percolation on Z Hugo Duminil-Copin an Vincent Tassion October 8, 205 Abstract We provie a new proof of the sharpness of the phase transition

More information

Survey Sampling. 1 Design-based Inference. Kosuke Imai Department of Politics, Princeton University. February 19, 2013

Survey Sampling. 1 Design-based Inference. Kosuke Imai Department of Politics, Princeton University. February 19, 2013 Survey Sampling Kosuke Imai Department of Politics, Princeton University February 19, 2013 Survey sampling is one of the most commonly use ata collection methos for social scientists. We begin by escribing

More information

Topic 7: Convergence of Random Variables

Topic 7: Convergence of Random Variables Topic 7: Convergence of Ranom Variables Course 003, 2016 Page 0 The Inference Problem So far, our starting point has been a given probability space (S, F, P). We now look at how to generate information

More information

On colour-blind distinguishing colour pallets in regular graphs

On colour-blind distinguishing colour pallets in regular graphs J Comb Optim (2014 28:348 357 DOI 10.1007/s10878-012-9556-x On colour-blin istinguishing colour pallets in regular graphs Jakub Przybyło Publishe online: 25 October 2012 The Author(s 2012. This article

More information

JUST THE MATHS UNIT NUMBER DIFFERENTIATION 2 (Rates of change) A.J.Hobson

JUST THE MATHS UNIT NUMBER DIFFERENTIATION 2 (Rates of change) A.J.Hobson JUST THE MATHS UNIT NUMBER 10.2 DIFFERENTIATION 2 (Rates of change) by A.J.Hobson 10.2.1 Introuction 10.2.2 Average rates of change 10.2.3 Instantaneous rates of change 10.2.4 Derivatives 10.2.5 Exercises

More information

Acute sets in Euclidean spaces

Acute sets in Euclidean spaces Acute sets in Eucliean spaces Viktor Harangi April, 011 Abstract A finite set H in R is calle an acute set if any angle etermine by three points of H is acute. We examine the maximal carinality α() of

More information

TOEPLITZ AND POSITIVE SEMIDEFINITE COMPLETION PROBLEM FOR CYCLE GRAPH

TOEPLITZ AND POSITIVE SEMIDEFINITE COMPLETION PROBLEM FOR CYCLE GRAPH English NUMERICAL MATHEMATICS Vol14, No1 Series A Journal of Chinese Universities Feb 2005 TOEPLITZ AND POSITIVE SEMIDEFINITE COMPLETION PROBLEM FOR CYCLE GRAPH He Ming( Λ) Michael K Ng(Ξ ) Abstract We

More information

Discrete Mathematics

Discrete Mathematics Discrete Mathematics 309 (009) 86 869 Contents lists available at ScienceDirect Discrete Mathematics journal homepage: wwwelseviercom/locate/isc Profile vectors in the lattice of subspaces Dániel Gerbner

More information

Least-Squares Regression on Sparse Spaces

Least-Squares Regression on Sparse Spaces Least-Squares Regression on Sparse Spaces Yuri Grinberg, Mahi Milani Far, Joelle Pineau School of Computer Science McGill University Montreal, Canaa {ygrinb,mmilan1,jpineau}@cs.mcgill.ca 1 Introuction

More information

Chromatic number for a generalization of Cartesian product graphs

Chromatic number for a generalization of Cartesian product graphs Chromatic number for a generalization of Cartesian prouct graphs Daniel Král Douglas B. West Abstract Let G be a class of graphs. The -fol gri over G, enote G, is the family of graphs obtaine from -imensional

More information

u!i = a T u = 0. Then S satisfies

u!i = a T u = 0. Then S satisfies Deterministic Conitions for Subspace Ientifiability from Incomplete Sampling Daniel L Pimentel-Alarcón, Nigel Boston, Robert D Nowak University of Wisconsin-Maison Abstract Consier an r-imensional subspace

More information

CONTAINMENT GAME PLAYED ON RANDOM GRAPHS: ANOTHER ZIG-ZAG THEOREM

CONTAINMENT GAME PLAYED ON RANDOM GRAPHS: ANOTHER ZIG-ZAG THEOREM CONTAINMENT GAME PLAYED ON RANDOM GRAPHS: ANOTHER ZIG-ZAG THEOREM PAWE L PRA LAT Abstract. We consier a variant of the game of Cops an Robbers, calle Containment, in which cops move from ege to ajacent

More information

Iterated Point-Line Configurations Grow Doubly-Exponentially

Iterated Point-Line Configurations Grow Doubly-Exponentially Iterate Point-Line Configurations Grow Doubly-Exponentially Joshua Cooper an Mark Walters July 9, 008 Abstract Begin with a set of four points in the real plane in general position. A to this collection

More information

Computing Exact Confidence Coefficients of Simultaneous Confidence Intervals for Multinomial Proportions and their Functions

Computing Exact Confidence Coefficients of Simultaneous Confidence Intervals for Multinomial Proportions and their Functions Working Paper 2013:5 Department of Statistics Computing Exact Confience Coefficients of Simultaneous Confience Intervals for Multinomial Proportions an their Functions Shaobo Jin Working Paper 2013:5

More information

Lower bounds on Locality Sensitive Hashing

Lower bounds on Locality Sensitive Hashing Lower bouns on Locality Sensitive Hashing Rajeev Motwani Assaf Naor Rina Panigrahy Abstract Given a metric space (X, X ), c 1, r > 0, an p, q [0, 1], a istribution over mappings H : X N is calle a (r,

More information

Combinatorica 9(1)(1989) A New Lower Bound for Snake-in-the-Box Codes. Jerzy Wojciechowski. AMS subject classification 1980: 05 C 35, 94 B 25

Combinatorica 9(1)(1989) A New Lower Bound for Snake-in-the-Box Codes. Jerzy Wojciechowski. AMS subject classification 1980: 05 C 35, 94 B 25 Combinatorica 9(1)(1989)91 99 A New Lower Boun for Snake-in-the-Box Coes Jerzy Wojciechowski Department of Pure Mathematics an Mathematical Statistics, University of Cambrige, 16 Mill Lane, Cambrige, CB2

More information

Linear First-Order Equations

Linear First-Order Equations 5 Linear First-Orer Equations Linear first-orer ifferential equations make up another important class of ifferential equations that commonly arise in applications an are relatively easy to solve (in theory)

More information

Diophantine Approximations: Examining the Farey Process and its Method on Producing Best Approximations

Diophantine Approximations: Examining the Farey Process and its Method on Producing Best Approximations Diophantine Approximations: Examining the Farey Process an its Metho on Proucing Best Approximations Kelly Bowen Introuction When a person hears the phrase irrational number, one oes not think of anything

More information

PDE Notes, Lecture #11

PDE Notes, Lecture #11 PDE Notes, Lecture # from Professor Jalal Shatah s Lectures Febuary 9th, 2009 Sobolev Spaces Recall that for u L loc we can efine the weak erivative Du by Du, φ := udφ φ C0 If v L loc such that Du, φ =

More information

A note on network reliability

A note on network reliability A note on network reliability Noga Alon Institute for Advanced Study, Princeton, NJ 08540 and Department of Mathematics Tel Aviv University, Tel Aviv, Israel Let G = (V, E) be a loopless undirected multigraph,

More information

Final Exam Study Guide and Practice Problems Solutions

Final Exam Study Guide and Practice Problems Solutions Final Exam Stuy Guie an Practice Problems Solutions Note: These problems are just some of the types of problems that might appear on the exam. However, to fully prepare for the exam, in aition to making

More information

LECTURE NOTES ON DVORETZKY S THEOREM

LECTURE NOTES ON DVORETZKY S THEOREM LECTURE NOTES ON DVORETZKY S THEOREM STEVEN HEILMAN Abstract. We present the first half of the paper [S]. In particular, the results below, unless otherwise state, shoul be attribute to G. Schechtman.

More information

d-dimensional Arrangement Revisited

d-dimensional Arrangement Revisited -Dimensional Arrangement Revisite Daniel Rotter Jens Vygen Research Institute for Discrete Mathematics University of Bonn Revise version: April 5, 013 Abstract We revisit the -imensional arrangement problem

More information

List coloring hypergraphs

List coloring hypergraphs List coloring hypergraphs Penny Haxell Jacques Verstraete Department of Combinatorics and Optimization University of Waterloo Waterloo, Ontario, Canada pehaxell@uwaterloo.ca Department of Mathematics University

More information

Leaving Randomness to Nature: d-dimensional Product Codes through the lens of Generalized-LDPC codes

Leaving Randomness to Nature: d-dimensional Product Codes through the lens of Generalized-LDPC codes Leaving Ranomness to Nature: -Dimensional Prouct Coes through the lens of Generalize-LDPC coes Tavor Baharav, Kannan Ramchanran Dept. of Electrical Engineering an Computer Sciences, U.C. Berkeley {tavorb,

More information

Mathcad Lecture #5 In-class Worksheet Plotting and Calculus

Mathcad Lecture #5 In-class Worksheet Plotting and Calculus Mathca Lecture #5 In-class Worksheet Plotting an Calculus At the en of this lecture, you shoul be able to: graph expressions, functions, an matrices of ata format graphs with titles, legens, log scales,

More information

A Weak First Digit Law for a Class of Sequences

A Weak First Digit Law for a Class of Sequences International Mathematical Forum, Vol. 11, 2016, no. 15, 67-702 HIKARI Lt, www.m-hikari.com http://x.oi.org/10.1288/imf.2016.6562 A Weak First Digit Law for a Class of Sequences M. A. Nyblom School of

More information

On the enumeration of partitions with summands in arithmetic progression

On the enumeration of partitions with summands in arithmetic progression AUSTRALASIAN JOURNAL OF COMBINATORICS Volume 8 (003), Pages 149 159 On the enumeration of partitions with summans in arithmetic progression M. A. Nyblom C. Evans Department of Mathematics an Statistics

More information

Convergence of Random Walks

Convergence of Random Walks Chapter 16 Convergence of Ranom Walks This lecture examines the convergence of ranom walks to the Wiener process. This is very important both physically an statistically, an illustrates the utility of

More information

Robust Forward Algorithms via PAC-Bayes and Laplace Distributions. ω Q. Pr (y(ω x) < 0) = Pr A k

Robust Forward Algorithms via PAC-Bayes and Laplace Distributions. ω Q. Pr (y(ω x) < 0) = Pr A k A Proof of Lemma 2 B Proof of Lemma 3 Proof: Since the support of LL istributions is R, two such istributions are equivalent absolutely continuous with respect to each other an the ivergence is well-efine

More information

Applications of the Wronskian to ordinary linear differential equations

Applications of the Wronskian to ordinary linear differential equations Physics 116C Fall 2011 Applications of the Wronskian to orinary linear ifferential equations Consier a of n continuous functions y i (x) [i = 1,2,3,...,n], each of which is ifferentiable at least n times.

More information

. ISSN (print), (online) International Journal of Nonlinear Science Vol.6(2008) No.3,pp

. ISSN (print), (online) International Journal of Nonlinear Science Vol.6(2008) No.3,pp . ISSN 1749-3889 (print), 1749-3897 (online) International Journal of Nonlinear Science Vol.6(8) No.3,pp.195-1 A Bouneness Criterion for Fourth Orer Nonlinear Orinary Differential Equations with Delay

More information

arxiv: v1 [math.co] 13 Dec 2017

arxiv: v1 [math.co] 13 Dec 2017 The List Linear Arboricity of Graphs arxiv:7.05006v [math.co] 3 Dec 07 Ringi Kim Department of Mathematical Sciences KAIST Daejeon South Korea 344 an Luke Postle Department of Combinatorics an Optimization

More information

Thermal conductivity of graded composites: Numerical simulations and an effective medium approximation

Thermal conductivity of graded composites: Numerical simulations and an effective medium approximation JOURNAL OF MATERIALS SCIENCE 34 (999)5497 5503 Thermal conuctivity of grae composites: Numerical simulations an an effective meium approximation P. M. HUI Department of Physics, The Chinese University

More information

Online Appendix for Trade Policy under Monopolistic Competition with Firm Selection

Online Appendix for Trade Policy under Monopolistic Competition with Firm Selection Online Appenix for Trae Policy uner Monopolistic Competition with Firm Selection Kyle Bagwell Stanfor University an NBER Seung Hoon Lee Georgia Institute of Technology September 6, 2018 In this Online

More information

A simple branching process approach to the phase transition in G n,p

A simple branching process approach to the phase transition in G n,p A simple branching process approach to the phase transition in G n,p Béla Bollobás Department of Pure Mathematics and Mathematical Statistics Wilberforce Road, Cambridge CB3 0WB, UK b.bollobas@dpmms.cam.ac.uk

More information

Calculus and optimization

Calculus and optimization Calculus an optimization These notes essentially correspon to mathematical appenix 2 in the text. 1 Functions of a single variable Now that we have e ne functions we turn our attention to calculus. A function

More information

6 General properties of an autonomous system of two first order ODE

6 General properties of an autonomous system of two first order ODE 6 General properties of an autonomous system of two first orer ODE Here we embark on stuying the autonomous system of two first orer ifferential equations of the form ẋ 1 = f 1 (, x 2 ), ẋ 2 = f 2 (, x

More information

arxiv: v1 [math.mg] 10 Apr 2018

arxiv: v1 [math.mg] 10 Apr 2018 ON THE VOLUME BOUND IN THE DVORETZKY ROGERS LEMMA FERENC FODOR, MÁRTON NASZÓDI, AND TAMÁS ZARNÓCZ arxiv:1804.03444v1 [math.mg] 10 Apr 2018 Abstract. The classical Dvoretzky Rogers lemma provies a eterministic

More information

Evolutionary Stability of Pure-Strategy Equilibria in Finite Games

Evolutionary Stability of Pure-Strategy Equilibria in Finite Games GAMES AND ECONOMIC BEHAVIOR 2, 253265 997 ARTICLE NO GA970533 Evolutionary Stability of Pure-Strategy Equilibria in Finite Games E Somanathan* Emory Uniersity, Department of Economics, Atlanta, Georgia

More information

Role of parameters in the stochastic dynamics of a stick-slip oscillator

Role of parameters in the stochastic dynamics of a stick-slip oscillator Proceeing Series of the Brazilian Society of Applie an Computational Mathematics, v. 6, n. 1, 218. Trabalho apresentao no XXXVII CNMAC, S.J. os Campos - SP, 217. Proceeing Series of the Brazilian Society

More information

1. Aufgabenblatt zur Vorlesung Probability Theory

1. Aufgabenblatt zur Vorlesung Probability Theory 24.10.17 1. Aufgabenblatt zur Vorlesung By (Ω, A, P ) we always enote the unerlying probability space, unless state otherwise. 1. Let r > 0, an efine f(x) = 1 [0, [ (x) exp( r x), x R. a) Show that p f

More information

A nonlinear inverse problem of the Korteweg-de Vries equation

A nonlinear inverse problem of the Korteweg-de Vries equation Bull. Math. Sci. https://oi.org/0.007/s3373-08-025- A nonlinear inverse problem of the Korteweg-e Vries equation Shengqi Lu Miaochao Chen 2 Qilin Liu 3 Receive: 0 March 207 / Revise: 30 April 208 / Accepte:

More information

FLUCTUATIONS IN THE NUMBER OF POINTS ON SMOOTH PLANE CURVES OVER FINITE FIELDS. 1. Introduction

FLUCTUATIONS IN THE NUMBER OF POINTS ON SMOOTH PLANE CURVES OVER FINITE FIELDS. 1. Introduction FLUCTUATIONS IN THE NUMBER OF POINTS ON SMOOTH PLANE CURVES OVER FINITE FIELDS ALINA BUCUR, CHANTAL DAVID, BROOKE FEIGON, MATILDE LALÍN 1 Introuction In this note, we stuy the fluctuations in the number

More information

APPPHYS 217 Thursday 8 April 2010

APPPHYS 217 Thursday 8 April 2010 APPPHYS 7 Thursay 8 April A&M example 6: The ouble integrator Consier the motion of a point particle in D with the applie force as a control input This is simply Newton s equation F ma with F u : t q q

More information

Qubit channels that achieve capacity with two states

Qubit channels that achieve capacity with two states Qubit channels that achieve capacity with two states Dominic W. Berry Department of Physics, The University of Queenslan, Brisbane, Queenslan 4072, Australia Receive 22 December 2004; publishe 22 March

More information

Lower Bounds for the Smoothed Number of Pareto optimal Solutions

Lower Bounds for the Smoothed Number of Pareto optimal Solutions Lower Bouns for the Smoothe Number of Pareto optimal Solutions Tobias Brunsch an Heiko Röglin Department of Computer Science, University of Bonn, Germany brunsch@cs.uni-bonn.e, heiko@roeglin.org Abstract.

More information

IPA Derivatives for Make-to-Stock Production-Inventory Systems With Backorders Under the (R,r) Policy

IPA Derivatives for Make-to-Stock Production-Inventory Systems With Backorders Under the (R,r) Policy IPA Derivatives for Make-to-Stock Prouction-Inventory Systems With Backorers Uner the (Rr) Policy Yihong Fan a Benamin Melame b Yao Zhao c Yorai Wari Abstract This paper aresses Infinitesimal Perturbation

More information

A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks

A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks A PAC-Bayesian Approach to Spectrally-Normalize Margin Bouns for Neural Networks Behnam Neyshabur, Srinah Bhojanapalli, Davi McAllester, Nathan Srebro Toyota Technological Institute at Chicago {bneyshabur,

More information

On decomposing graphs of large minimum degree into locally irregular subgraphs

On decomposing graphs of large minimum degree into locally irregular subgraphs On decomposing graphs of large minimum degree into locally irregular subgraphs Jakub Przyby lo AGH University of Science and Technology al. A. Mickiewicza 0 0-059 Krakow, Poland jakubprz@agh.edu.pl Submitted:

More information

Adding random edges to create the square of a Hamilton cycle

Adding random edges to create the square of a Hamilton cycle Adding random edges to create the square of a Hamilton cycle Patrick Bennett Andrzej Dudek Alan Frieze October 7, 2017 Abstract We consider how many random edges need to be added to a graph of order n

More information

Linear and quadratic approximation

Linear and quadratic approximation Linear an quaratic approximation November 11, 2013 Definition: Suppose f is a function that is ifferentiable on an interval I containing the point a. The linear approximation to f at a is the linear function

More information

Time-of-Arrival Estimation in Non-Line-Of-Sight Environments

Time-of-Arrival Estimation in Non-Line-Of-Sight Environments 2 Conference on Information Sciences an Systems, The Johns Hopkins University, March 2, 2 Time-of-Arrival Estimation in Non-Line-Of-Sight Environments Sinan Gezici, Hisashi Kobayashi an H. Vincent Poor

More information

REAL ANALYSIS I HOMEWORK 5

REAL ANALYSIS I HOMEWORK 5 REAL ANALYSIS I HOMEWORK 5 CİHAN BAHRAN The questions are from Stein an Shakarchi s text, Chapter 3. 1. Suppose ϕ is an integrable function on R with R ϕ(x)x = 1. Let K δ(x) = δ ϕ(x/δ), δ > 0. (a) Prove

More information

International Journal of Pure and Applied Mathematics Volume 35 No , ON PYTHAGOREAN QUADRUPLES Edray Goins 1, Alain Togbé 2

International Journal of Pure and Applied Mathematics Volume 35 No , ON PYTHAGOREAN QUADRUPLES Edray Goins 1, Alain Togbé 2 International Journal of Pure an Applie Mathematics Volume 35 No. 3 007, 365-374 ON PYTHAGOREAN QUADRUPLES Eray Goins 1, Alain Togbé 1 Department of Mathematics Purue University 150 North University Street,

More information

An alternative proof of the linearity of the size-ramsey number of paths. A. Dudek and P. Pralat

An alternative proof of the linearity of the size-ramsey number of paths. A. Dudek and P. Pralat An alternative proof of the linearity of the size-ramsey number of paths A. Dudek and P. Pralat REPORT No. 14, 2013/2014, spring ISSN 1103-467X ISRN IML-R- -14-13/14- -SE+spring AN ALTERNATIVE PROOF OF

More information

THE MONIC INTEGER TRANSFINITE DIAMETER

THE MONIC INTEGER TRANSFINITE DIAMETER MATHEMATICS OF COMPUTATION Volume 00, Number 0, Pages 000 000 S 005-578(XX)0000-0 THE MONIC INTEGER TRANSFINITE DIAMETER K. G. HARE AND C. J. SMYTH ABSTRACT. We stuy the problem of fining nonconstant monic

More information

Expected Value of Partial Perfect Information

Expected Value of Partial Perfect Information Expecte Value of Partial Perfect Information Mike Giles 1, Takashi Goa 2, Howar Thom 3 Wei Fang 1, Zhenru Wang 1 1 Mathematical Institute, University of Oxfor 2 School of Engineering, University of Tokyo

More information

On the threshold for k-regular subgraphs of random graphs

On the threshold for k-regular subgraphs of random graphs On the threshold for k-regular subgraphs of random graphs Pawe l Pra lat Department of Mathematics and Statistics Dalhousie University Halifax NS, Canada Nicholas Wormald Department of Combinatorics and

More information

arxiv: v1 [math.co] 29 May 2009

arxiv: v1 [math.co] 29 May 2009 arxiv:0905.4913v1 [math.co] 29 May 2009 simple Havel-Hakimi type algorithm to realize graphical egree sequences of irecte graphs Péter L. Erős an István Miklós. Rényi Institute of Mathematics, Hungarian

More information

New Statistical Test for Quality Control in High Dimension Data Set

New Statistical Test for Quality Control in High Dimension Data Set International Journal of Applie Engineering Research ISSN 973-456 Volume, Number 6 (7) pp. 64-649 New Statistical Test for Quality Control in High Dimension Data Set Shamshuritawati Sharif, Suzilah Ismail

More information

19 Eigenvalues, Eigenvectors, Ordinary Differential Equations, and Control

19 Eigenvalues, Eigenvectors, Ordinary Differential Equations, and Control 19 Eigenvalues, Eigenvectors, Orinary Differential Equations, an Control This section introuces eigenvalues an eigenvectors of a matrix, an iscusses the role of the eigenvalues in etermining the behavior

More information

Asymptotic determination of edge-bandwidth of multidimensional grids and Hamming graphs

Asymptotic determination of edge-bandwidth of multidimensional grids and Hamming graphs Asymptotic etermination of ege-banwith of multiimensional gris an Hamming graphs Reza Akhtar Tao Jiang Zevi Miller. Revise on May 7, 007 Abstract The ege-banwith B (G) of a graph G is the banwith of the

More information

Lecture Introduction. 2 Examples of Measure Concentration. 3 The Johnson-Lindenstrauss Lemma. CS-621 Theory Gems November 28, 2012

Lecture Introduction. 2 Examples of Measure Concentration. 3 The Johnson-Lindenstrauss Lemma. CS-621 Theory Gems November 28, 2012 CS-6 Theory Gems November 8, 0 Lecture Lecturer: Alesaner Mąry Scribes: Alhussein Fawzi, Dorina Thanou Introuction Toay, we will briefly iscuss an important technique in probability theory measure concentration

More information

A Random Graph Model for Massive Graphs

A Random Graph Model for Massive Graphs A Ranom Graph Moel for Massive Graphs William Aiello AT&T Labs Florham Park, New Jersey aiello@research.att.com Fan Chung University of California, San Diego fan@ucs.eu Linyuan Lu University of Pennsylvania,

More information

The concentration of the chromatic number of random graphs

The concentration of the chromatic number of random graphs The concentration of the chromatic number of random graphs Noga Alon Michael Krivelevich Abstract We prove that for every constant δ > 0 the chromatic number of the random graph G(n, p) with p = n 1/2

More information

All Ramsey numbers for brooms in graphs

All Ramsey numbers for brooms in graphs All Ramsey numbers for brooms in graphs Pei Yu Department of Mathematics Tongji University Shanghai, China yupeizjy@16.com Yusheng Li Department of Mathematics Tongji University Shanghai, China li yusheng@tongji.edu.cn

More information

ON THE NUMBER OF ALTERNATING PATHS IN BIPARTITE COMPLETE GRAPHS

ON THE NUMBER OF ALTERNATING PATHS IN BIPARTITE COMPLETE GRAPHS ON THE NUMBER OF ALTERNATING PATHS IN BIPARTITE COMPLETE GRAPHS PATRICK BENNETT, ANDRZEJ DUDEK, ELLIOT LAFORGE December 1, 016 Abstract. Let C [r] m be a code such that any two words of C have Hamming

More information

Lecture 2: Correlated Topic Model

Lecture 2: Correlated Topic Model Probabilistic Moels for Unsupervise Learning Spring 203 Lecture 2: Correlate Topic Moel Inference for Correlate Topic Moel Yuan Yuan First of all, let us make some claims about the parameters an variables

More information

CUSTOMER REVIEW FEATURE EXTRACTION Heng Ren, Jingye Wang, and Tony Wu

CUSTOMER REVIEW FEATURE EXTRACTION Heng Ren, Jingye Wang, and Tony Wu CUSTOMER REVIEW FEATURE EXTRACTION Heng Ren, Jingye Wang, an Tony Wu Abstract Popular proucts often have thousans of reviews that contain far too much information for customers to igest. Our goal for the

More information

d dx But have you ever seen a derivation of these results? We ll prove the first result below. cos h 1

d dx But have you ever seen a derivation of these results? We ll prove the first result below. cos h 1 Lecture 5 Some ifferentiation rules Trigonometric functions (Relevant section from Stewart, Seventh Eition: Section 3.3) You all know that sin = cos cos = sin. () But have you ever seen a erivation of

More information

The derivative of a function f(x) is another function, defined in terms of a limiting expression: f(x + δx) f(x)

The derivative of a function f(x) is another function, defined in terms of a limiting expression: f(x + δx) f(x) Y. D. Chong (2016) MH2801: Complex Methos for the Sciences 1. Derivatives The erivative of a function f(x) is another function, efine in terms of a limiting expression: f (x) f (x) lim x δx 0 f(x + δx)

More information

Table of Common Derivatives By David Abraham

Table of Common Derivatives By David Abraham Prouct an Quotient Rules: Table of Common Derivatives By Davi Abraham [ f ( g( ] = [ f ( ] g( + f ( [ g( ] f ( = g( [ f ( ] g( g( f ( [ g( ] Trigonometric Functions: sin( = cos( cos( = sin( tan( = sec

More information

Similar Operators and a Functional Calculus for the First-Order Linear Differential Operator

Similar Operators and a Functional Calculus for the First-Order Linear Differential Operator Avances in Applie Mathematics, 9 47 999 Article ID aama.998.067, available online at http: www.iealibrary.com on Similar Operators an a Functional Calculus for the First-Orer Linear Differential Operator

More information

Sliding mode approach to congestion control in connection-oriented communication networks

Sliding mode approach to congestion control in connection-oriented communication networks JOURNAL OF APPLIED COMPUTER SCIENCE Vol. xx. No xx (200x), pp. xx-xx Sliing moe approach to congestion control in connection-oriente communication networks Anrzej Bartoszewicz, Justyna Żuk Technical University

More information

Physics 251 Results for Matrix Exponentials Spring 2017

Physics 251 Results for Matrix Exponentials Spring 2017 Physics 25 Results for Matrix Exponentials Spring 27. Properties of the Matrix Exponential Let A be a real or complex n n matrix. The exponential of A is efine via its Taylor series, e A A n = I + n!,

More information

2Algebraic ONLINE PAGE PROOFS. foundations

2Algebraic ONLINE PAGE PROOFS. foundations Algebraic founations. Kick off with CAS. Algebraic skills.3 Pascal s triangle an binomial expansions.4 The binomial theorem.5 Sets of real numbers.6 Surs.7 Review . Kick off with CAS Playing lotto Using

More information

Stopping-Set Enumerator Approximations for Finite-Length Protograph LDPC Codes

Stopping-Set Enumerator Approximations for Finite-Length Protograph LDPC Codes Stopping-Set Enumerator Approximations for Finite-Length Protograph LDPC Coes Kaiann Fu an Achilleas Anastasopoulos Electrical Engineering an Computer Science Dept. University of Michigan, Ann Arbor, MI

More information

The symmetry in the martingale inequality

The symmetry in the martingale inequality Statistics & Probability Letters 56 2002 83 9 The symmetry in the martingale inequality Sungchul Lee a; ;, Zhonggen Su a;b;2 a Department of Mathematics, Yonsei University, Seoul 20-749, South Korea b

More information

Capacity Analysis of MIMO Systems with Unknown Channel State Information

Capacity Analysis of MIMO Systems with Unknown Channel State Information Capacity Analysis of MIMO Systems with Unknown Channel State Information Jun Zheng an Bhaskar D. Rao Dept. of Electrical an Computer Engineering University of California at San Diego e-mail: juzheng@ucs.eu,

More information

Two formulas for the Euler ϕ-function

Two formulas for the Euler ϕ-function Two formulas for the Euler ϕ-function Robert Frieman A multiplication formula for ϕ(n) The first formula we want to prove is the following: Theorem 1. If n 1 an n 2 are relatively prime positive integers,

More information

Closed and Open Loop Optimal Control of Buffer and Energy of a Wireless Device

Closed and Open Loop Optimal Control of Buffer and Energy of a Wireless Device Close an Open Loop Optimal Control of Buffer an Energy of a Wireless Device V. S. Borkar School of Technology an Computer Science TIFR, umbai, Inia. borkar@tifr.res.in A. A. Kherani B. J. Prabhu INRIA

More information

DEGREE DISTRIBUTION OF SHORTEST PATH TREES AND BIAS OF NETWORK SAMPLING ALGORITHMS

DEGREE DISTRIBUTION OF SHORTEST PATH TREES AND BIAS OF NETWORK SAMPLING ALGORITHMS DEGREE DISTRIBUTION OF SHORTEST PATH TREES AND BIAS OF NETWORK SAMPLING ALGORITHMS SHANKAR BHAMIDI 1, JESSE GOODMAN 2, REMCO VAN DER HOFSTAD 3, AND JÚLIA KOMJÁTHY3 Abstract. In this article, we explicitly

More information

Perfect Matchings in Õ(n1.5 ) Time in Regular Bipartite Graphs

Perfect Matchings in Õ(n1.5 ) Time in Regular Bipartite Graphs Perfect Matchings in Õ(n1.5 ) Time in Regular Bipartite Graphs Ashish Goel Michael Kapralov Sanjeev Khanna Abstract We consier the well-stuie problem of fining a perfect matching in -regular bipartite

More information

Math 1271 Solutions for Fall 2005 Final Exam

Math 1271 Solutions for Fall 2005 Final Exam Math 7 Solutions for Fall 5 Final Eam ) Since the equation + y = e y cannot be rearrange algebraically in orer to write y as an eplicit function of, we must instea ifferentiate this relation implicitly

More information

Dissipative numerical methods for the Hunter-Saxton equation

Dissipative numerical methods for the Hunter-Saxton equation Dissipative numerical methos for the Hunter-Saton equation Yan Xu an Chi-Wang Shu Abstract In this paper, we present further evelopment of the local iscontinuous Galerkin (LDG) metho esigne in [] an a

More information

c 2003 Society for Industrial and Applied Mathematics

c 2003 Society for Industrial and Applied Mathematics SIAM J DISCRETE MATH Vol 7, No, pp 7 c 23 Society for Inustrial an Applie Mathematics SOME NEW ASPECTS OF THE COUPON COLLECTOR S PROBLEM AMY N MYERS AND HERBERT S WILF Abstract We exten the classical coupon

More information

On permutation-invariance of limit theorems

On permutation-invariance of limit theorems On permutation-invariance of limit theorems I. Beres an R. Tichy Abstract By a classical principle of probability theory, sufficiently thin subsequences of general sequences of ranom variables behave lie

More information

A FURTHER REFINEMENT OF MORDELL S BOUND ON EXPONENTIAL SUMS

A FURTHER REFINEMENT OF MORDELL S BOUND ON EXPONENTIAL SUMS A FURTHER REFINEMENT OF MORDELL S BOUND ON EXPONENTIAL SUMS TODD COCHRANE, JEREMY COFFELT, AND CHRISTOPHER PINNER 1. Introuction For a prime p, integer Laurent polynomial (1.1) f(x) = a 1 x k 1 + + a r

More information

The average number of spanning trees in sparse graphs with given degrees

The average number of spanning trees in sparse graphs with given degrees The average number of spanning trees in sparse graphs with given egrees Catherine Greenhill School of Mathematics an Statistics UNSW Australia Syney NSW 05, Australia cgreenhill@unsweuau Matthew Kwan Department

More information

Multi-View Clustering via Canonical Correlation Analysis

Multi-View Clustering via Canonical Correlation Analysis Technical Report TTI-TR-2008-5 Multi-View Clustering via Canonical Correlation Analysis Kamalika Chauhuri UC San Diego Sham M. Kakae Toyota Technological Institute at Chicago ABSTRACT Clustering ata in

More information

Logarithmic spurious regressions

Logarithmic spurious regressions Logarithmic spurious regressions Robert M. e Jong Michigan State University February 5, 22 Abstract Spurious regressions, i.e. regressions in which an integrate process is regresse on another integrate

More information

Agmon Kolmogorov Inequalities on l 2 (Z d )

Agmon Kolmogorov Inequalities on l 2 (Z d ) Journal of Mathematics Research; Vol. 6, No. ; 04 ISSN 96-9795 E-ISSN 96-9809 Publishe by Canaian Center of Science an Eucation Agmon Kolmogorov Inequalities on l (Z ) Arman Sahovic Mathematics Department,

More information

SYNCHRONOUS SEQUENTIAL CIRCUITS

SYNCHRONOUS SEQUENTIAL CIRCUITS CHAPTER SYNCHRONOUS SEUENTIAL CIRCUITS Registers an counters, two very common synchronous sequential circuits, are introuce in this chapter. Register is a igital circuit for storing information. Contents

More information

The Wiener Index of Trees with Prescribed Diameter

The Wiener Index of Trees with Prescribed Diameter 011 1 15 4 ± Dec., 011 Operations Research Transactions Vol.15 No.4 The Wiener Inex of Trees with Prescribe Diameter XING Baohua 1 CAI Gaixiang 1 Abstract The Wiener inex W(G) of a graph G is efine as

More information

Sharp threshold functions for random intersection graphs via a coupling method.

Sharp threshold functions for random intersection graphs via a coupling method. Sharp threshold functions for random intersection graphs via a coupling method. Katarzyna Rybarczyk Faculty of Mathematics and Computer Science, Adam Mickiewicz University, 60 769 Poznań, Poland kryba@amu.edu.pl

More information