Survival exponents for fractional Brownian motion with multivariate time

Size: px
Start display at page:

Download "Survival exponents for fractional Brownian motion with multivariate time"

Transcription

1 Survival exponents for fractional Brownian motion with multivariate time G Molchan Institute of Earthquae Preiction heory an Mathematical Geophysics Russian Acaemy of Science 84/3 Profsoyuznaya st 7997 Moscow Russian Feeration aress: molchan@mitpru Abstract Fractional Brownian motion -FBM of inex 0 with -imensional time is consiere in a spherical omain that contains 0 at its bounary he main result : the logasymptotics of probability that -FBM oes not excee a fixe positive level is -log+o >> is raius of the omain ey wors Fractional Brownian motion; One-sie exit problem; Survival exponent Introuction Fractional Brownian motion -FBM of inex 0 with multivariate time centere Gaussian ranom process w t with correlation function Ew t w s / t s t s -FBM is -self-similar -ss isotropic an has stationary increments si ie { w 0 0 t t R is a t t w t } { w } hols in the sense of the equality of finite-imensional istributions for any fixe t 0 0 an rotation aroun 0 he one-sie exit problem for a ranom process t an its characteristics the so-calle survival exponents: lim log P t t are the subject of intensive analysis in applications ere / is an increasing sequence of omains of size an is a suitable slowly varying function typically log for ss-processes he greatest progress in this area has been achieve for processes with oneimensional time See surveys by Bray et al 03 in the physics literature an by Aurzaa an Simon 05 in the mathematical one

2 -FBM was one of the first non-trivial examples of non-marovian processes for which the survival exponents have been foun exactly Molchan999 Namely for log the survival exponents are 0 an w w Recently Aurzaa et al 06 consierably refine the asymptotics of probability p P w t t 0 3 an showe that the exponent is universal for a broa class of -ss processes with stationary increments he ieas of this wor have prove useful in analysis of the conjunction that for w t in w ] [ 0 ] [ Molchan 0 he case 0 correspons to the right part of he case is supporte by the result which we iscuss below: for fractional Brownian motion in is w a unit ball that contains 0 at its bounary o estimate w we moify the famous result by Aurzaa et al 06 which says that for a broa class of si-processes: t 0 0 with iscrete time t Z P t t \ {0} E max t t 4 [ 0 ] an For -ss processes with continuous time the right part of 4 is proportional to an therefore the exponent for 3 is owever the result by Aurzaa et al 06 essentially uses the -D nature of time Consiering as the volume of relation 4 is foun to be in formal agreement with the conjunction for but not for ; in aition 4 is very crue for 0 see 3 his means that the analysis of the cases nees in aitional ieas he lower boun Proposition Let t 0 0 t R be a centere isotropic ranom process with stationary increments hen P t t t c E max t t 5 is a ball of raius that contains 0 at its bounary

3 3 Consequence If t is fractional Brownian motion of inex 0 exponent has the lower boun w in then the survival Remar Proposition hols for [0 ] [ ] as well Proof Let { x n ; } be a subset of ball B of raius in of N points such that R ; consists x r x xm N C r r 6 Consier the following increasing sequence of subsets of : x x : x r } { i i Fix { t : t e } e 00 Let O be a rotation transferring x in x r e Setting O one has B x \ {0} \ herefore using the notation M A sup t t A we get p 7 : P t t \ B P M x \ {0} 8 By the si-property of t we can continue P M \ x x P M x 9 he last equality hols because t is rotation invariant he event { M x } is measurable relative to the sequence x x ; x 0 n x n an means that x is a recor which excees the previous one by at least Let be the number of such recors in 0 hen by 89 N p P M x E E M x { x } n x n x Finally by 6 p E M / N c Esup{ t t Suppose that t is fractional Brownian motion of inex 0 in By the stanar proceure we can compare p with

4 p Pw t t \ B For this purpose we can fin a continuous function t such that 4 t t const 3 is the norm of the ilbert space with the reproucing ernel Ew t w s t s see for this fact Molchan999 or Appenixhen h p Pw t t t \ B Accoring to Aurzaa&Dereich 00 ln / p ln/ p Т / 4 From the self-similarity of -FBM an one has Combining 3-5 one has p с EM 5 w [ln/ P w t t ] / / ln O/ ln 6 ie w 3 he upper boun Below we use notation M A sup w t t A an A #{ t : t A} Proposition Let w t be -FBM in R the is a boune omain an 0 Consier a finite -net of ie a subset { x N 0} } { such that N N an B xr B x is unite ball with center x hen for 0 an 0 q P M c ln qp M 0 7

5 5 c v v is the Fernique constant In aition EM EM o EM o 8 Proof One has c P M 0 P M 0 A P A 9 A {max maxt w t w x t B x b } We can continue the previous inequality P M b Pmax w t w x t B x b 0 P M b N P M B b : p p Applying the Fernique 975 result to w t we have u / P M B r c c e u r r / 4 From here settingb 4 ln c one has p C / ln C / ln o show p o p note that B D is iameter of D herefore p P M b P M B b P M B D D/ 3 / b By Molchan 999 P M B o Due to 3 we have p / p / / Oln =o 4 Relations 9 0 an 4 imply 7 o prove relation 8 note that

6 M M max max w t w x t B x : M 5 t 6 As above using the event A {max maxt w t w x t B x b } one has E b E b N EM B [ M B b ] 6 A b 4 ln c an N C herefore the - term in 6 is o By 5 6 we obtain 8 because EM EM E EM с ln o EM с ln o Proposition 3 Let w t t be -FBM 0 hen R is a unite ball an P M c ln ie the survival exponent for -FBM in has the upper boun w Consequence Due to Propositions 3 the survival exponent for -FBM in exists an is equal to Proof As in proof of Proposition we consier again the subset { x n ; } elements of are numerate in such way that of ball B R : { 0} In aition to the properties 6 we suppose that the x B x an x B x n 7 As before x x : x r } : 0 { ; i i { t : t e } e 00 ; O is a rotation transferring x in x r e Setting O one has B x \ {0} \ Due to 7 x is -net in herefore by 7 for 0 P M ln c qp M x \ {0} 0

7 qp M w x 0 qp M w x 7 As a result n n P M c ln q P M w 8 x [ ] an [ ] Similarly to the proof of Proposition we conclue that the right part of 8 is equal to E is a number of recors in the following sequences: M w x w x n ; w x w x n Let be the maximum increment between ajacent elements of the sequence w x w x w x n ; w x w x n n hen M M Т b R 9 R \ Т [ b ] Due to 7 ER t \ max Ew t[ w t b ] Setting b n ln an we obtain ER с n c n 30 By 9 E EM ER EM b accoring to 8 Setting n EM EM o one has

8 8 E с n ln с o 3 Now we can continue 8 as follows: qe n P M c ln 3 Due to ss-propery of -FBM P M c ln P M / / c ln an therefore the probability term ecreases as function of ence 3 implies qe \ P M c ln C P M 33 / /c ln or ln / c o Finally by 3 an P M c ln Appenix Example from Proposition Consier -FBM in omains 0 ; then a suitable function t t can be chosen as follows: t f t / f t f x x R is a finite smooth function such that t f for x / an f t 0 for x ere is the iameter of his can be seen as follows Molchan 999 Due to the spectral representation of -FBM the ilbert space with the reproucing ernel Ew t wh s t s Aronszajn 950 is closure of smooth functions t 0 0 relative to the norm inf с ˆ Where t is a finite function such that t t t ; ˆ R is the Fourier transform of t Obviously we have 0 0 for t \ B an f f t / f t f t / f f

9 9 References Aronszajn N heory of reproucing ernels ransamer Math Soc Aurzaa F an Dereich S niversality of the asymptotics of the one-sie exit problem for integrate processes Ann Inst Poincar é Probab Statist 49: Aurzaa FGuillotin-Plantar N Pene F Persistence probabilities for stationary increment processes Preprint https: arxiv: Aurzaa F; Simon Persistence probabilities an exponents L évy matters V p 83- Lecture Notes in Math 49 Springer 05 Bray A J; Majumar S N; an Schehr G Persistence an first-passage properties in nonequilibrium systems Avances in Physics 63: FerniqueX Regularite es trajectories es functions aleatoires gaussiannes Lecture Notes in Mathematics 480 Berlin-eielberg-New Yor : Springer Verlag975 Molchan G Maximum of fractional Brownian motion: probabilities of small values Comm Math Phys05: Molchan G nilateral small eviations of processes relate to the fractional Brownian motion Stoch Proc Appl Molchan G Survival exponents for some Gaussian processes IntJ of Stochastic Analysis 0 Article ID 377 inawi Publishing Corporationoi:055/0/377

A LIMIT THEOREM FOR RANDOM FIELDS WITH A SINGULARITY IN THE SPECTRUM

A LIMIT THEOREM FOR RANDOM FIELDS WITH A SINGULARITY IN THE SPECTRUM Teor Imov r. ta Matem. Statist. Theor. Probability an Math. Statist. Vip. 81, 1 No. 81, 1, Pages 147 158 S 94-911)816- Article electronically publishe on January, 11 UDC 519.1 A LIMIT THEOREM FOR RANDOM

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

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

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

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

On the number of isolated eigenvalues of a pair of particles in a quantum wire

On the number of isolated eigenvalues of a pair of particles in a quantum wire On the number of isolate eigenvalues of a pair of particles in a quantum wire arxiv:1812.11804v1 [math-ph] 31 Dec 2018 Joachim Kerner 1 Department of Mathematics an Computer Science FernUniversität in

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

Generalized Tractability for Multivariate Problems

Generalized Tractability for Multivariate Problems Generalize Tractability for Multivariate Problems Part II: Linear Tensor Prouct Problems, Linear Information, an Unrestricte Tractability Michael Gnewuch Department of Computer Science, University of Kiel,

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

Tractability results for weighted Banach spaces of smooth functions

Tractability results for weighted Banach spaces of smooth functions Tractability results for weighte Banach spaces of smooth functions Markus Weimar Mathematisches Institut, Universität Jena Ernst-Abbe-Platz 2, 07740 Jena, Germany email: markus.weimar@uni-jena.e March

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

WELL-POSEDNESS OF A POROUS MEDIUM FLOW WITH FRACTIONAL PRESSURE IN SOBOLEV SPACES

WELL-POSEDNESS OF A POROUS MEDIUM FLOW WITH FRACTIONAL PRESSURE IN SOBOLEV SPACES Electronic Journal of Differential Equations, Vol. 017 (017), No. 38, pp. 1 7. ISSN: 107-6691. URL: http://eje.math.txstate.eu or http://eje.math.unt.eu WELL-POSEDNESS OF A POROUS MEDIUM FLOW WITH FRACTIONAL

More information

Discrete Operators in Canonical Domains

Discrete Operators in Canonical Domains Discrete Operators in Canonical Domains VLADIMIR VASILYEV Belgoro National Research University Chair of Differential Equations Stuencheskaya 14/1, 308007 Belgoro RUSSIA vlaimir.b.vasilyev@gmail.com Abstract:

More information

Markov Chains in Continuous Time

Markov Chains in Continuous Time Chapter 23 Markov Chains in Continuous Time Previously we looke at Markov chains, where the transitions betweenstatesoccurreatspecifietime- steps. That it, we mae time (a continuous variable) avance in

More information

ELECTRON DIFFRACTION

ELECTRON DIFFRACTION ELECTRON DIFFRACTION Electrons : wave or quanta? Measurement of wavelength an momentum of electrons. Introuction Electrons isplay both wave an particle properties. What is the relationship between the

More information

Lower Tail Probabilities and Related Problems

Lower Tail Probabilities and Related Problems Lower Tail Probabilities and Related Problems Qi-Man Shao National University of Singapore and University of Oregon qmshao@darkwing.uoregon.edu . Lower Tail Probabilities Let {X t, t T } be a real valued

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

arxiv: v2 [cond-mat.stat-mech] 11 Nov 2016

arxiv: v2 [cond-mat.stat-mech] 11 Nov 2016 Noname manuscript No. (will be inserte by the eitor) Scaling properties of the number of ranom sequential asorption iterations neee to generate saturate ranom packing arxiv:607.06668v2 [con-mat.stat-mech]

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

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

Some Examples. Uniform motion. Poisson processes on the real line

Some Examples. Uniform motion. Poisson processes on the real line Some Examples Our immeiate goal is to see some examples of Lévy processes, an/or infinitely-ivisible laws on. Uniform motion Choose an fix a nonranom an efine X := for all (1) Then, {X } is a [nonranom]

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

Modelling and simulation of dependence structures in nonlife insurance with Bernstein copulas

Modelling and simulation of dependence structures in nonlife insurance with Bernstein copulas Moelling an simulation of epenence structures in nonlife insurance with Bernstein copulas Prof. Dr. Dietmar Pfeifer Dept. of Mathematics, University of Olenburg an AON Benfiel, Hamburg Dr. Doreen Straßburger

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

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

Optimal Control of Spatially Distributed Systems

Optimal Control of Spatially Distributed Systems Optimal Control of Spatially Distribute Systems Naer Motee an Ali Jababaie Abstract In this paper, we stuy the structural properties of optimal control of spatially istribute systems. Such systems consist

More information

Algorithms and matching lower bounds for approximately-convex optimization

Algorithms and matching lower bounds for approximately-convex optimization Algorithms an matching lower bouns for approximately-convex optimization Yuanzhi Li Department of Computer Science Princeton University Princeton, NJ, 08450 yuanzhil@cs.princeton.eu Anrej Risteski Department

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

1 Math 285 Homework Problem List for S2016

1 Math 285 Homework Problem List for S2016 1 Math 85 Homework Problem List for S016 Note: solutions to Lawler Problems will appear after all of the Lecture Note Solutions. 1.1 Homework 1. Due Friay, April 8, 016 Look at from lecture note exercises:

More information

arxiv: v1 [math.pr] 4 Feb 2016

arxiv: v1 [math.pr] 4 Feb 2016 Mittag-Leffler Lévy Processes Arun Kumar an N. S. Upahye *Inian Statistical Institute, Chennai Center, Taramani, Chennai-636, Inia an **Department of Mathematics, Inian Institute of Technology Maras, Chennai

More information

Lyapunov Functions. V. J. Venkataramanan and Xiaojun Lin. Center for Wireless Systems and Applications. School of Electrical and Computer Engineering,

Lyapunov Functions. V. J. Venkataramanan and Xiaojun Lin. Center for Wireless Systems and Applications. School of Electrical and Computer Engineering, On the Queue-Overflow Probability of Wireless Systems : A New Approach Combining Large Deviations with Lyapunov Functions V. J. Venkataramanan an Xiaojun Lin Center for Wireless Systems an Applications

More information

An Optimal Algorithm for Bandit and Zero-Order Convex Optimization with Two-Point Feedback

An Optimal Algorithm for Bandit and Zero-Order Convex Optimization with Two-Point Feedback Journal of Machine Learning Research 8 07) - Submitte /6; Publishe 5/7 An Optimal Algorithm for Banit an Zero-Orer Convex Optimization with wo-point Feeback Oha Shamir Department of Computer Science an

More information

On a limit theorem for non-stationary branching processes.

On a limit theorem for non-stationary branching processes. On a limit theorem for non-stationary branching processes. TETSUYA HATTORI an HIROSHI WATANABE 0. Introuction. The purpose of this paper is to give a limit theorem for a certain class of iscrete-time multi-type

More information

Research Article Survival Exponents for Some Gaussian Processes

Research Article Survival Exponents for Some Gaussian Processes International Journal of Stochastic Analysis Volume 01, Article ID 13771, 0 pages doi:10.1155/01/13771 Research Article Survival Exponents for Some Gaussian Processes G. Molchan Institute of Earthquake

More information

Schrödinger s equation.

Schrödinger s equation. Physics 342 Lecture 5 Schröinger s Equation Lecture 5 Physics 342 Quantum Mechanics I Wenesay, February 3r, 2010 Toay we iscuss Schröinger s equation an show that it supports the basic interpretation of

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

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

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

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

arxiv: v1 [hep-lat] 19 Nov 2013

arxiv: v1 [hep-lat] 19 Nov 2013 HU-EP-13/69 SFB/CPP-13-98 DESY 13-225 Applicability of Quasi-Monte Carlo for lattice systems arxiv:1311.4726v1 [hep-lat] 19 ov 2013, a,b Tobias Hartung, c Karl Jansen, b Hernan Leovey, Anreas Griewank

More information

MARKO NEDELJKOV, DANIJELA RAJTER-ĆIRIĆ

MARKO NEDELJKOV, DANIJELA RAJTER-ĆIRIĆ GENERALIZED UNIFORMLY CONTINUOUS SEMIGROUPS AND SEMILINEAR HYPERBOLIC SYSTEMS WITH REGULARIZED DERIVATIVES MARKO NEDELJKOV, DANIJELA RAJTER-ĆIRIĆ Abstract. We aopt the theory of uniformly continuous operator

More information

arxiv: v4 [math.pr] 27 Jul 2016

arxiv: v4 [math.pr] 27 Jul 2016 The Asymptotic Distribution of the Determinant of a Ranom Correlation Matrix arxiv:309768v4 mathpr] 7 Jul 06 AM Hanea a, & GF Nane b a Centre of xcellence for Biosecurity Risk Analysis, University of Melbourne,

More information

ON THE OPTIMAL CONVERGENCE RATE OF UNIVERSAL AND NON-UNIVERSAL ALGORITHMS FOR MULTIVARIATE INTEGRATION AND APPROXIMATION

ON THE OPTIMAL CONVERGENCE RATE OF UNIVERSAL AND NON-UNIVERSAL ALGORITHMS FOR MULTIVARIATE INTEGRATION AND APPROXIMATION ON THE OPTIMAL CONVERGENCE RATE OF UNIVERSAL AN NON-UNIVERSAL ALGORITHMS FOR MULTIVARIATE INTEGRATION AN APPROXIMATION MICHAEL GRIEBEL AN HENRYK WOŹNIAKOWSKI Abstract. We stuy the optimal rate of convergence

More information

Function Spaces. 1 Hilbert Spaces

Function Spaces. 1 Hilbert Spaces Function Spaces A function space is a set of functions F that has some structure. Often a nonparametric regression function or classifier is chosen to lie in some function space, where the assume structure

More information

Lecture 6: Calculus. In Song Kim. September 7, 2011

Lecture 6: Calculus. In Song Kim. September 7, 2011 Lecture 6: Calculus In Song Kim September 7, 20 Introuction to Differential Calculus In our previous lecture we came up with several ways to analyze functions. We saw previously that the slope of a linear

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

FURTHER BOUNDS FOR THE ESTIMATION ERROR VARIANCE OF A CONTINUOUS STREAM WITH STATIONARY VARIOGRAM

FURTHER BOUNDS FOR THE ESTIMATION ERROR VARIANCE OF A CONTINUOUS STREAM WITH STATIONARY VARIOGRAM FURTHER BOUNDS FOR THE ESTIMATION ERROR VARIANCE OF A CONTINUOUS STREAM WITH STATIONARY VARIOGRAM N. S. BARNETT, S. S. DRAGOMIR, AND I. S. GOMM Abstract. In this paper we establish an upper boun for the

More information

arxiv: v1 [math.dg] 1 Nov 2015

arxiv: v1 [math.dg] 1 Nov 2015 DARBOUX-WEINSTEIN THEOREM FOR LOCALLY CONFORMALLY SYMPLECTIC MANIFOLDS arxiv:1511.00227v1 [math.dg] 1 Nov 2015 ALEXANDRA OTIMAN AND MIRON STANCIU Abstract. A locally conformally symplectic (LCS) form is

More information

SELBERG S ORTHOGONALITY CONJECTURE FOR AUTOMORPHIC L-FUNCTIONS

SELBERG S ORTHOGONALITY CONJECTURE FOR AUTOMORPHIC L-FUNCTIONS SELBERG S ORTHOGONALITY CONJECTURE FOR AUTOMORPHIC L-FUNCTIONS JIANYA LIU 1 AND YANGBO YE 2 Abstract. Let π an π be automorphic irreucible unitary cuspial representations of GL m (Q A ) an GL m (Q A ),

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

Exponential asymptotic property of a parallel repairable system with warm standby under common-cause failure

Exponential asymptotic property of a parallel repairable system with warm standby under common-cause failure J. Math. Anal. Appl. 341 (28) 457 466 www.elsevier.com/locate/jmaa Exponential asymptotic property of a parallel repairable system with warm stanby uner common-cause failure Zifei Shen, Xiaoxiao Hu, Weifeng

More information

GLOBAL DYNAMICS OF THE SYSTEM OF TWO EXPONENTIAL DIFFERENCE EQUATIONS

GLOBAL DYNAMICS OF THE SYSTEM OF TWO EXPONENTIAL DIFFERENCE EQUATIONS Electronic Journal of Mathematical Analysis an Applications Vol. 7(2) July 209, pp. 256-266 ISSN: 2090-729X(online) http://math-frac.org/journals/ejmaa/ GLOBAL DYNAMICS OF THE SYSTEM OF TWO EXPONENTIAL

More information

WUCHEN LI AND STANLEY OSHER

WUCHEN LI AND STANLEY OSHER CONSTRAINED DYNAMICAL OPTIMAL TRANSPORT AND ITS LAGRANGIAN FORMULATION WUCHEN LI AND STANLEY OSHER Abstract. We propose ynamical optimal transport (OT) problems constraine in a parameterize probability

More information

A Unified Theorem on SDP Rank Reduction

A Unified Theorem on SDP Rank Reduction A Unifie heorem on SDP Ran Reuction Anthony Man Cho So, Yinyu Ye, Jiawei Zhang November 9, 006 Abstract We consier the problem of fining a low ran approximate solution to a system of linear equations in

More information

A study on ant colony systems with fuzzy pheromone dispersion

A study on ant colony systems with fuzzy pheromone dispersion A stuy on ant colony systems with fuzzy pheromone ispersion Louis Gacogne LIP6 104, Av. Kenney, 75016 Paris, France gacogne@lip6.fr Sanra Sanri IIIA/CSIC Campus UAB, 08193 Bellaterra, Spain sanri@iiia.csic.es

More information

A simple tranformation of copulas

A simple tranformation of copulas A simple tranformation of copulas V. Durrleman, A. Nikeghbali & T. Roncalli Groupe e Recherche Opérationnelle Créit Lyonnais France July 31, 2000 Abstract We stuy how copulas properties are moifie after

More information

Parameter estimation: A new approach to weighting a priori information

Parameter estimation: A new approach to weighting a priori information Parameter estimation: A new approach to weighting a priori information J.L. Mea Department of Mathematics, Boise State University, Boise, ID 83725-555 E-mail: jmea@boisestate.eu Abstract. We propose a

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

OPTIMAL CONTROL PROBLEM FOR PROCESSES REPRESENTED BY STOCHASTIC SEQUENTIAL MACHINE

OPTIMAL CONTROL PROBLEM FOR PROCESSES REPRESENTED BY STOCHASTIC SEQUENTIAL MACHINE OPTIMA CONTRO PROBEM FOR PROCESSES REPRESENTED BY STOCHASTIC SEQUENTIA MACHINE Yaup H. HACI an Muhammet CANDAN Department of Mathematics, Canaale Onseiz Mart University, Canaale, Turey ABSTRACT In this

More information

A Spectral Method for the Biharmonic Equation

A Spectral Method for the Biharmonic Equation A Spectral Metho for the Biharmonic Equation Kenall Atkinson, Davi Chien, an Olaf Hansen Abstract Let Ω be an open, simply connecte, an boune region in Ê,, with a smooth bounary Ω that is homeomorphic

More information

S10.G.1. Fluid Flow Around the Brownian Particle

S10.G.1. Fluid Flow Around the Brownian Particle Rea Reichl s introuction. Tables & proofs for vector calculus formulas can be foun in the stanar textbooks G.Arfken s Mathematical Methos for Physicists an J.D.Jackson s Classical Electroynamics. S0.G..

More information

Convergence rates of moment-sum-of-squares hierarchies for optimal control problems

Convergence rates of moment-sum-of-squares hierarchies for optimal control problems Convergence rates of moment-sum-of-squares hierarchies for optimal control problems Milan Kora 1, Diier Henrion 2,3,4, Colin N. Jones 1 Draft of September 8, 2016 Abstract We stuy the convergence rate

More information

Separation of Variables

Separation of Variables Physics 342 Lecture 1 Separation of Variables Lecture 1 Physics 342 Quantum Mechanics I Monay, January 25th, 2010 There are three basic mathematical tools we nee, an then we can begin working on the physical

More information

arxiv: v2 [math.dg] 16 Dec 2014

arxiv: v2 [math.dg] 16 Dec 2014 A ONOTONICITY FORULA AND TYPE-II SINGULARITIES FOR THE EAN CURVATURE FLOW arxiv:1312.4775v2 [math.dg] 16 Dec 2014 YONGBING ZHANG Abstract. In this paper, we introuce a monotonicity formula for the mean

More information

4. Important theorems in quantum mechanics

4. Important theorems in quantum mechanics TFY4215 Kjemisk fysikk og kvantemekanikk - Tillegg 4 1 TILLEGG 4 4. Important theorems in quantum mechanics Before attacking three-imensional potentials in the next chapter, we shall in chapter 4 of this

More information

The Renormalization of Self Intersection Local Times of Fractional Brownian Motion

The Renormalization of Self Intersection Local Times of Fractional Brownian Motion International Mathematical Forum, 2, 27, no. 44, 26-278 The Renormalization of Self Intersection Local Times of Fractional Brownian Motion Anis Rezgui Mathematics epartement INSAT centre urbain nor B.P.

More information

Energy behaviour of the Boris method for charged-particle dynamics

Energy behaviour of the Boris method for charged-particle dynamics Version of 25 April 218 Energy behaviour of the Boris metho for charge-particle ynamics Ernst Hairer 1, Christian Lubich 2 Abstract The Boris algorithm is a wiely use numerical integrator for the motion

More information

Equilibrium Glauber dynamics of continuous particle systems as a scaling limit of Kawasaki dynamics

Equilibrium Glauber dynamics of continuous particle systems as a scaling limit of Kawasaki dynamics Equilibrium Glauber ynamics of continuous particle systems as a scaling limit of Kawasaki ynamics Dmitri L. Finkelshtein Institute of Mathematics, National Acaemy of Sciences of Ukraine, 3 Tereshchenkivska

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

Physics 505 Electricity and Magnetism Fall 2003 Prof. G. Raithel. Problem Set 3. 2 (x x ) 2 + (y y ) 2 + (z + z ) 2

Physics 505 Electricity and Magnetism Fall 2003 Prof. G. Raithel. Problem Set 3. 2 (x x ) 2 + (y y ) 2 + (z + z ) 2 Physics 505 Electricity an Magnetism Fall 003 Prof. G. Raithel Problem Set 3 Problem.7 5 Points a): Green s function: Using cartesian coorinates x = (x, y, z), it is G(x, x ) = 1 (x x ) + (y y ) + (z z

More information

The effect of dissipation on solutions of the complex KdV equation

The effect of dissipation on solutions of the complex KdV equation Mathematics an Computers in Simulation 69 (25) 589 599 The effect of issipation on solutions of the complex KV equation Jiahong Wu a,, Juan-Ming Yuan a,b a Department of Mathematics, Oklahoma State University,

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

PETER L. BARTLETT AND MARTEN H. WEGKAMP

PETER L. BARTLETT AND MARTEN H. WEGKAMP CLASSIFICATION WITH A REJECT OPTION USING A HINGE LOSS PETER L. BARTLETT AND MARTEN H. WEGKAMP Abstract. We consier the problem of binary classification where the classifier can, for a particular cost,

More information

INVERSE PROBLEM OF A HYPERBOLIC EQUATION WITH AN INTEGRAL OVERDETERMINATION CONDITION

INVERSE PROBLEM OF A HYPERBOLIC EQUATION WITH AN INTEGRAL OVERDETERMINATION CONDITION Electronic Journal of Differential Equations, Vol. 216 (216), No. 138, pp. 1 7. ISSN: 172-6691. URL: http://eje.math.txstate.eu or http://eje.math.unt.eu INVERSE PROBLEM OF A HYPERBOLIC EQUATION WITH AN

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

REVERSIBILITY FOR DIFFUSIONS VIA QUASI-INVARIANCE. 1. Introduction We look at the problem of reversibility for operators of the form

REVERSIBILITY FOR DIFFUSIONS VIA QUASI-INVARIANCE. 1. Introduction We look at the problem of reversibility for operators of the form REVERSIBILITY FOR DIFFUSIONS VIA QUASI-INVARIANCE OMAR RIVASPLATA, JAN RYCHTÁŘ, AND BYRON SCHMULAND Abstract. Why is the rift coefficient b associate with a reversible iffusion on R given by a graient?

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

Structural Risk Minimization over Data-Dependent Hierarchies

Structural Risk Minimization over Data-Dependent Hierarchies Structural Risk Minimization over Data-Depenent Hierarchies John Shawe-Taylor Department of Computer Science Royal Holloway an Befor New College University of Lonon Egham, TW20 0EX, UK jst@cs.rhbnc.ac.uk

More information

Math 342 Partial Differential Equations «Viktor Grigoryan

Math 342 Partial Differential Equations «Viktor Grigoryan Math 342 Partial Differential Equations «Viktor Grigoryan 6 Wave equation: solution In this lecture we will solve the wave equation on the entire real line x R. This correspons to a string of infinite

More information

Slovak University of Technology in Bratislava Institute of Information Engineering, Automation, and Mathematics PROCEEDINGS

Slovak University of Technology in Bratislava Institute of Information Engineering, Automation, and Mathematics PROCEEDINGS lovak University of echnology in Bratislava Institute of Information Engineering, Automation, an athematics PROCEEDING 7 th International Conference on Process Control 009 Hotel Baník, Štrbské Pleso, lovakia,

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

QF101: Quantitative Finance September 5, Week 3: Derivatives. Facilitator: Christopher Ting AY 2017/2018. f ( x + ) f(x) f(x) = lim

QF101: Quantitative Finance September 5, Week 3: Derivatives. Facilitator: Christopher Ting AY 2017/2018. f ( x + ) f(x) f(x) = lim QF101: Quantitative Finance September 5, 2017 Week 3: Derivatives Facilitator: Christopher Ting AY 2017/2018 I recoil with ismay an horror at this lamentable plague of functions which o not have erivatives.

More information

26.1 Metropolis method

26.1 Metropolis method CS880: Approximations Algorithms Scribe: Dave Anrzejewski Lecturer: Shuchi Chawla Topic: Metropolis metho, volume estimation Date: 4/26/07 The previous lecture iscusse they some of the key concepts of

More information

Monotonicity for excited random walk in high dimensions

Monotonicity for excited random walk in high dimensions Monotonicity for excite ranom walk in high imensions Remco van er Hofsta Mark Holmes March, 2009 Abstract We prove that the rift θ, β) for excite ranom walk in imension is monotone in the excitement parameter

More information

On the Aloha throughput-fairness tradeoff

On the Aloha throughput-fairness tradeoff On the Aloha throughput-fairness traeoff 1 Nan Xie, Member, IEEE, an Steven Weber, Senior Member, IEEE Abstract arxiv:1605.01557v1 [cs.it] 5 May 2016 A well-known inner boun of the stability region of

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

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

Probabilistic Analysis of Power Assignments

Probabilistic Analysis of Power Assignments Probabilistic Analysis of Power Assignments Maurits e Graaf 1,2 an Boo Manthey 1 1 University of Twente, Department of Applie Mathematics, Enschee, Netherlans m.egraaf/b.manthey@utwente.nl 2 Thales Neerlan

More information

On combinatorial approaches to compressed sensing

On combinatorial approaches to compressed sensing On combinatorial approaches to compresse sensing Abolreza Abolhosseini Moghaam an Hayer Raha Department of Electrical an Computer Engineering, Michigan State University, East Lansing, MI, U.S. Emails:{abolhos,raha}@msu.eu

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

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

LATTICE-BASED D-OPTIMUM DESIGN FOR FOURIER REGRESSION

LATTICE-BASED D-OPTIMUM DESIGN FOR FOURIER REGRESSION The Annals of Statistics 1997, Vol. 25, No. 6, 2313 2327 LATTICE-BASED D-OPTIMUM DESIGN FOR FOURIER REGRESSION By Eva Riccomagno, 1 Rainer Schwabe 2 an Henry P. Wynn 1 University of Warwick, Technische

More information

Chapter 6: Energy-Momentum Tensors

Chapter 6: Energy-Momentum Tensors 49 Chapter 6: Energy-Momentum Tensors This chapter outlines the general theory of energy an momentum conservation in terms of energy-momentum tensors, then applies these ieas to the case of Bohm's moel.

More information

The Press-Schechter mass function

The Press-Schechter mass function The Press-Schechter mass function To state the obvious: It is important to relate our theories to what we can observe. We have looke at linear perturbation theory, an we have consiere a simple moel for

More information

Multi-View Clustering via Canonical Correlation Analysis

Multi-View Clustering via Canonical Correlation Analysis Keywors: multi-view learning, clustering, canonical correlation analysis Abstract Clustering ata in high-imensions is believe to be a har problem in general. A number of efficient clustering algorithms

More information

A Randomized Approximate Nearest Neighbors Algorithm - a short version

A Randomized Approximate Nearest Neighbors Algorithm - a short version We present a ranomize algorithm for the approximate nearest neighbor problem in - imensional Eucliean space. Given N points {x } in R, the algorithm attempts to fin k nearest neighbors for each of x, where

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

Solutions to MATH 271 Test #3H

Solutions to MATH 271 Test #3H Solutions to MATH 71 Test #3H This is the :4 class s version of the test. See pages 4 7 for the 4:4 class s. (1) (5 points) Let a k = ( 1)k. Is a k increasing? Decreasing? Boune above? Boune k below? Convergant

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