A False History of True Concurrency

Size: px
Start display at page:

Download "A False History of True Concurrency"

Transcription

1 A Fals History of Tru Concurrncy Javir Esparza Sofwar Rliability and Scurity Group Institut for Formal Mthods in Computr Scinc Univrsity of Stuttgart.

2 Th arly 6s. 2

3 Abstract Modls of Computation in th arly 6s Lambda calculus (Church 35) Turing machins (Turing 36) Finit automata (Kln 56, Moor 56, Maly 56, Scott and Rabin 59) Pushdown automata (Ottingr 6, Chomsky 62, Evy 63, Schutznbrgr 63). 3

4 Smantics: xcutions Stats: currnt configurations of th machin On or mor initial stats Possibly som distinguishd final stats Transitions: movs btwn configurations Lambda calculus (λx.xx)(λy.y) (λy.y)(λz.z) Turing machin q q 2 Finit automaton q a q 2 Pushdown automaton (q, XYYZ ) a (q 2, XYXYYZ ) Excutions: altrnating squncs of stats and transitions. 4

5 Physics and Computation Abstract machins ar implmntd as physical systms. 5

6 Physics and Computation Abstract machins ar implmntd as can simulat physical systms SIMULA projct (Nygaard and Dahl) startd in

7 Physics and Computation Abstract machins A plan (physical systm) ar implmntd as can simulat physical systms SIMULA projct (Nygaard and Dahl) startd in

8 Physics and Computation Abstract machins A plan (physical systm) ar implmntd as can simulat physical systms SIMULA projct (Nygaard and Dahl) startd in 962 can b simulatd by a plan simulator (abstract machin). 5

9 Physics and Computation Abstract machins A plan (physical systm) ar implmntd as can simulat physical systms SIMULA projct (Nygaard and Dahl) startd in 962 can b simulatd by a plan simulator (abstract machin) which can b implmntd in a vido consol (physical systm). 5

10 Physics and Computation Abstract machins A plan (physical systm) ar implmntd as can simulat physical systms SIMULA projct (Nygaard and Dahl) startd in 962 can b simulatd by a plan simulator (abstract machin) which can b implmntd in a vido consol (physical systm) which can b simulatd by a hardwar simulator (abstract machin). 5

11 Physics and Computation Abstract machins A plan (physical systm) ar implmntd as can simulat physical systms SIMULA projct (Nygaard and Dahl) startd in 962 can b simulatd by a plan simulator (abstract machin) which can b implmntd in a vido consol (physical systm) which can b simulatd by a hardwar simulator (abstract machin) which is implmntd in a PC (physical systm).... 5

12 Ptri s qustion C.A. Ptri points out a discrpancy btwn how Thortical Physics and Thortical Computr Scinc dscribd systms in 962: Thortical Physics dscribs systms as a collction of intracting particls (subsystms), without a notion of global clock or simultanity Thortical Computr Scinc dscribs systms as squntial virtual machins going through a tmporally ordrd squnc of global stats Ptri s qustion: Which kind of abstract machin should b usd to dscrib th physical implmntation of a Turing machin?. 6

13 Ptri Nts A graphical rprsntation of intracting finit automata: s r q a b b c d d s r q. 7

14 Ptri Nts A graphical rprsntation of intracting finit automata: s r q a b b c d d b b s r q. 7

15 Ptri Nts A graphical rprsntation of intracting finit automata: s r q a b b b c d d s r q. 7

16 Ptri Nts A graphical rprsntation of intracting finit automata: s r q a b b b c d d s r q. 7

17 Ptri Nts A graphical rprsntation of intracting finit automata: s r q a b b b c d d d s r q. 7

18 Ptri Nts A graphical rprsntation of intracting finit automata: s r q a b b b c d d d s r q. 7

19 Ptri Nts A graphical rprsntation of intracting finit automata: s r q a a b b b c c d d d s r q. 7

20 Ptri Nts A graphical rprsntation of intracting finit automata: s r q s r q a a b b b c c d d d s r q s r q. 7

21 Th intrlaving smantics of Ptri nts An xcution smantics Stat: marking (distribution of tokns) Transitions: M a M a Excutions: M a M M

22 s r q a b c d s r q. 9

23 s r q a b c d s r q s r q. 9

24 s r q a b c d s r q s r q. 9

25 s r q a b c d s r q c s r q. 9

26 s r q a b c d s r q c s r q. 9

27 s r q a b c d s r q c s r q b. 9

28 s r q a b c d s r q c s r q b. 9

29 s r q a b c d s r q c s r q b. 9

30 s r q s r q a b c d c b d s r q c b. 9

31 s r q s r q a b c d c b d s r q c b d. 9

32 s r q s r q a b c d c b d s r q c b d. 9

33 s r q s r q a b c d c b d s r q c b d. 9

34 s r q s r q a b c d c b d a s r q c b d. 9

35 s r q s r q a b c d c b d a s r q c b d a. 9

36 s r q s r q a b c d c b d a b s r q c b d a. 9

37 s r q s r q a b c d c b d a b s r q c b d a b. 9

38 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q.

39 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s r q.

40 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s r q.

41 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s r c r q.

42 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s r c r q.

43 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s s r c r b r q.

44 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s s r c r b r q.

45 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s s r c r b r q q.

46 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s s r c r b r q q.

47 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s s r c r b r r q q d q.

48 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s s r c r b r r q q d q.

49 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s s r c r b r r q q d q q.

50 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s s r c r b r r q q d q q.

51 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s s a s r c r b r r q q d q q.

52 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s s a s r c r b r r q q d q q.

53 Th tru concurrncy smantics of Ptri nts s r q a b c d s r q s s a s s r c r b r r b r q q d q q.

54 Intrlaving vs. tru concurrncy Th intrlaving thsis: Th total ordr assumption is a rasonabl abstraction, adquat for practical purposs, and lading to nic mathmatics Th tru concurrncy thsis: Th total ordr assumption dos not corrspond to physical rality and lads to awkward rprsntations of simpl phnomna.

55 Th standard xampl In intrlaving smantics, a systm composd of n indpndnt componnts a a n has n! diffrnt xcutions Th automaton accpting thm has 2 n stats In tru concurrncy smantics, it has only on nonsquntial xcution. 2

56 3 yars of concurrncy thory in on slid Intrlaving smantics Ptri nts/vctor addition systms (Hack, Kosaraju, Mayr,... 7s 8s) Procss algbras (Milnr 8) Tmporal logic (Pnuli 77) Modl chcking (Clark, Emrson, Quill, Sifakis 8) Tru concurrncy Axiomatic concurrncy thory (Bst, Frnandz, Ptri... 7s 8s) Trac thory (formal languags, Mazurkiwicz 77) Evnt structurs (domain thory, Winskl 8) Tru concurrncy smantics of procss algbras (Montanari, Winskl... 8s) Partial ordr modl chcking (E., Godfroid, Pld, Wolpr 9s) Tmporal logics for tru concurrncy (9s s). 3

57 Tmporal Logics for Tru Concurrncy. 4

58 LTL: a tmporal logic for squntial runs Syntax: ϕ ::= tru ϕ ϕ ψ a ϕ F ϕ G ϕ ϕ ϕ U ψ whr a blongs to a finit st Act of actions Formulas intrprtd on runs ovr Act : lmnts of Act ω Smantics: ρ = a ϕ if ρ = aρ and ρ = ϕ ρ = F ϕ if ρ = ϕ for som suffix ρ of ρ ρ = G ϕ if ρ = ϕ for all suffixs ρ of ρ ρ = ϕ U ψ if ρ = ψ for som suffix ρ of ρ and ρ = φ for all suffixs ρ btwn ρ and ρ. 5

59 Exampls Invariants: G ϕ G( a tru... a n tru) dadlock frdom Rspons, rcurrnc: G(ϕ F ψ) G( rqust tru F takn tru) G F activ tru vntual accss to a rsourc procss rmains activ Ractivity: G F ϕ G F ψ G F( rqust tru takn 2 tru) G F takn tru strong fairnss. 6

60 Modl chcking Fix a systm S with action alphabt Act W us LTL ovr Act to spcify proprtis of S S satisfis a formula ϕ, dnotd S = LTL ϕ, if all its xcutions satisfy ϕ Th modl chcking problm: givn S and ϕ, dcid if T = LTL ϕ. 7

61 Rsults on LTL Kamp s thorm: LTL has th sam xprssivity as th first-ordr thory of runs FO(Act) ::= R a (x) x y ϕ φ ψ x.ϕ Th satisfiability and modl-chcking problms ar PSPACE-complt Construct a Büchi automaton of siz 2 O( ϕ ) accpting th runs satisfying ϕ (Intrsct it with an automaton accpting all xcutions of S) Chck for mptinss. 8

62 LTrL: Intrprting LTL on nonsquntial runs Fix a distributd alphabt Act = (Act,..., Act n ) of actions a Act i Act j mans that a is a joint action of th i-th and th j-th agnts Dnot by NS(Act) th st of nonsquntial runs ovr Act Th lin of th i-th componnt only contains actions of Act i Joint actions synchroniz th lins of its agnts Exampl: Act = {a, b}, Act 2 = {a, d}, Act 3 = {c, d} 2 3 a c b d. 9

63 LTL now intrprtd on NS(Act) Sam smantics as LTL, but with a nw notion of suffix Prfixs of a nonsquntial run: All minimal placs blong to th prfix If a transition blongs to th prfix, so do its output placs Suffixs: complmnts of prfixs a b a b c d c d. 2

64 Smantics: ν = a ϕ if ν can b xtndd by an a-lablld vnt such that ν {} = ϕ ν = F ϕ if ν = ϕ for som suffix ν of ν ν = G ϕ if ν = ϕ for all suffixs ν of ν ν = ϕ U ψ if ν = ψ for som suffix ν of ρ and ν = φ for all suffixs ν btwn ν and ν. 2

65 Whr is th diffrnc? a tru b tru unsatisfiabl in LTL, satisfiabl in LTrL Exampl satisfis G F( a tru) as a formula of LTrL, but not as a formula of LTL s r q a b c d s r q Bttr spcification of rst stats. 22

66 Modl chcking Fix a systm S = (S,..., S n ) with distributd alphabt Act, W us LTL ovr Act to spcify proprtis of S S satisfis a formula ϕ if all its nonsquntial xcutions satisfy ϕ Th modl chcking problm: givn S and ϕ, dcid if T = LTrL ϕ. 23

67 Rsults on LTrL Exprssivly complt for th first ordr thory of nonsquntial runs FO(Act) ::= R a (x) x y ϕ φ ψ x.ϕ intrprtd on partial ordrs ovr Act that rspct th distribution Thiagarajan and Walukiwicz, LICS 97: LTrL + P a modalitis Dikrt and Gastin, CSL 99: LTrL + XA modalitis Dikrt and Gastin, ICALP Non-lmntary satisfiability and modl chcking problms (Walukiwicz ICALP 98) LTL allows to spcify 2 n -countrs with formulas of lngth O(n) LTrL allows to spcify Towr(2, n)-countrs with formulas of lngth O(n). 24

68 Local LTL: intrprting LTL on local stats Local stat of a componnt: a position in its tim lin Idntify a local stat (plac) with th prfix dtrmind by all its prdcssors A componnt always has complt information about its causal past Componnts xchang full information whn thy synchroniz Exampl: Act = {a, b}, Act 2 = {a, d}, Act 3 = {c, d} 2 3 a c b d. 25

69 Syntax: ϕ ::= tru ϕ ϕ ψ a i ϕ F i ϕ G i ϕ ϕ U i ψ whr a is an action and i n Smantics: a i ϕ mans ϕ holds at i s nxt local stat F i ϕ mans ϕ holds vntually at i s timlin G i ϕ mans ϕ holds always along i s timlin ϕ U i ψ mans ϕ holds until ψ holds along i s timlin Gts intrsting whn formulas us svral indics: F G 2 a tru. 26

70 Rsults on Local LTL PSPACE-complt satisfiability and modl chcking problms (Thiagarajan, LICS 94) Gnralization of th Büchi automaton construction Tchnical problm: to kp track of th latst gossip Exprsivnss still unclar Compltnss rsults for logics with similar flavours (Gastin, Mukund, Kumar MFCS 3) Difficult to spcify with. 27

71 Outlook Intrlaving smantics dfault smantics in practic Tru concurrncy brought in whn intrlaving fails Challng: automatic synthsis of distributd systms Intrlaving logics insnsitiv to distribution rquirmnts Mayb th killr application for tru concurrncy?. 28

TuLiP: A Software Toolbox for Receding Horizon Temporal Logic Planning & Computer Lab 2

TuLiP: A Software Toolbox for Receding Horizon Temporal Logic Planning & Computer Lab 2 TuLiP: A Softwar Toolbox for Rcding Horizon Tmporal Logic Planning & Computr Lab 2 Nok Wongpiromsarn Richard M. Murray Ufuk Topcu EECI, 21 March 2013 Outlin Ky Faturs of TuLiP Embddd control softwar synthsis

More information

CS 361 Meeting 12 10/3/18

CS 361 Meeting 12 10/3/18 CS 36 Mting 2 /3/8 Announcmnts. Homwork 4 is du Friday. If Friday is Mountain Day, homwork should b turnd in at my offic or th dpartmnt offic bfor 4. 2. Homwork 5 will b availabl ovr th wknd. 3. Our midtrm

More information

Addition of angular momentum

Addition of angular momentum Addition of angular momntum April, 0 Oftn w nd to combin diffrnt sourcs of angular momntum to charactriz th total angular momntum of a systm, or to divid th total angular momntum into parts to valuat th

More information

Addition of angular momentum

Addition of angular momentum Addition of angular momntum April, 07 Oftn w nd to combin diffrnt sourcs of angular momntum to charactriz th total angular momntum of a systm, or to divid th total angular momntum into parts to valuat

More information

Probability Translation Guide

Probability Translation Guide Quick Guid to Translation for th inbuilt SWARM Calculator If you s information looking lik this: Us this statmnt or any variant* (not th backticks) And this is what you ll s whn you prss Calculat Th chancs

More information

Propositional Logic. Combinatorial Problem Solving (CPS) Albert Oliveras Enric Rodríguez-Carbonell. May 17, 2018

Propositional Logic. Combinatorial Problem Solving (CPS) Albert Oliveras Enric Rodríguez-Carbonell. May 17, 2018 Propositional Logic Combinatorial Problm Solving (CPS) Albrt Olivras Enric Rodríguz-Carbonll May 17, 2018 Ovrviw of th sssion Dfinition of Propositional Logic Gnral Concpts in Logic Rduction to SAT CNFs

More information

CS 6353 Compiler Construction, Homework #1. 1. Write regular expressions for the following informally described languages:

CS 6353 Compiler Construction, Homework #1. 1. Write regular expressions for the following informally described languages: CS 6353 Compilr Construction, Homwork #1 1. Writ rgular xprssions for th following informally dscribd languags: a. All strings of 0 s and 1 s with th substring 01*1. Answr: (0 1)*01*1(0 1)* b. All strings

More information

Basic Polyhedral theory

Basic Polyhedral theory Basic Polyhdral thory Th st P = { A b} is calld a polyhdron. Lmma 1. Eithr th systm A = b, b 0, 0 has a solution or thr is a vctorπ such that π A 0, πb < 0 Thr cass, if solution in top row dos not ist

More information

On spanning trees and cycles of multicolored point sets with few intersections

On spanning trees and cycles of multicolored point sets with few intersections On spanning trs and cycls of multicolord point sts with fw intrsctions M. Kano, C. Mrino, and J. Urrutia April, 00 Abstract Lt P 1,..., P k b a collction of disjoint point sts in R in gnral position. W

More information

Construction of asymmetric orthogonal arrays of strength three via a replacement method

Construction of asymmetric orthogonal arrays of strength three via a replacement method isid/ms/26/2 Fbruary, 26 http://www.isid.ac.in/ statmath/indx.php?modul=prprint Construction of asymmtric orthogonal arrays of strngth thr via a rplacmnt mthod Tian-fang Zhang, Qiaoling Dng and Alok Dy

More information

CHAPTER 1. Introductory Concepts Elements of Vector Analysis Newton s Laws Units The basis of Newtonian Mechanics D Alembert s Principle

CHAPTER 1. Introductory Concepts Elements of Vector Analysis Newton s Laws Units The basis of Newtonian Mechanics D Alembert s Principle CHPTER 1 Introductory Concpts Elmnts of Vctor nalysis Nwton s Laws Units Th basis of Nwtonian Mchanics D lmbrt s Principl 1 Scinc of Mchanics: It is concrnd with th motion of matrial bodis. odis hav diffrnt

More information

1 Isoparametric Concept

1 Isoparametric Concept UNIVERSITY OF CALIFORNIA BERKELEY Dpartmnt of Civil Enginring Spring 06 Structural Enginring, Mchanics and Matrials Profssor: S. Govindj Nots on D isoparamtric lmnts Isoparamtric Concpt Th isoparamtric

More information

Solution of Assignment #2

Solution of Assignment #2 olution of Assignmnt #2 Instructor: Alirza imchi Qustion #: For simplicity, assum that th distribution function of T is continuous. Th distribution function of R is: F R ( r = P( R r = P( log ( T r = P(log

More information

On the irreducibility of some polynomials in two variables

On the irreducibility of some polynomials in two variables ACTA ARITHMETICA LXXXII.3 (1997) On th irrducibility of som polynomials in two variabls by B. Brindza and Á. Pintér (Dbrcn) To th mmory of Paul Erdős Lt f(x) and g(y ) b polynomials with intgral cofficints

More information

Fourier Transforms and the Wave Equation. Key Mathematics: More Fourier transform theory, especially as applied to solving the wave equation.

Fourier Transforms and the Wave Equation. Key Mathematics: More Fourier transform theory, especially as applied to solving the wave equation. Lur 7 Fourir Transforms and th Wav Euation Ovrviw and Motivation: W first discuss a fw faturs of th Fourir transform (FT), and thn w solv th initial-valu problm for th wav uation using th Fourir transform

More information

Dealing with quantitative data and problem solving life is a story problem! Attacking Quantitative Problems

Dealing with quantitative data and problem solving life is a story problem! Attacking Quantitative Problems Daling with quantitati data and problm soling lif is a story problm! A larg portion of scinc inols quantitati data that has both alu and units. Units can sa your butt! Nd handl on mtric prfixs Dimnsional

More information

EXST Regression Techniques Page 1

EXST Regression Techniques Page 1 EXST704 - Rgrssion Tchniqus Pag 1 Masurmnt rrors in X W hav assumd that all variation is in Y. Masurmnt rror in this variabl will not ffct th rsults, as long as thy ar uncorrlatd and unbiasd, sinc thy

More information

A Propagating Wave Packet Group Velocity Dispersion

A Propagating Wave Packet Group Velocity Dispersion Lctur 8 Phys 375 A Propagating Wav Packt Group Vlocity Disprsion Ovrviw and Motivation: In th last lctur w lookd at a localizd solution t) to th 1D fr-particl Schrödingr quation (SE) that corrsponds to

More information

A Uniform Approach to Three-Valued Semantics for µ-calculus on Abstractions of Hybrid Automata

A Uniform Approach to Three-Valued Semantics for µ-calculus on Abstractions of Hybrid Automata A Uniform Approach to Thr-Valud Smantics for µ-calculus on Abstractions of Hybrid Automata (Haifa Vrification Confrnc 2008) Univrsity of Kaisrslautrn Octobr 28, 2008 Ovrviw 1. Prliminaris and 2. Gnric

More information

Computing and Communications -- Network Coding

Computing and Communications -- Network Coding 89 90 98 00 Computing and Communications -- Ntwork Coding Dr. Zhiyong Chn Institut of Wirlss Communications Tchnology Shanghai Jiao Tong Univrsity China Lctur 5- Nov. 05 0 Classical Information Thory Sourc

More information

Abstract Interpretation: concrete and abstract semantics

Abstract Interpretation: concrete and abstract semantics Abstract Intrprtation: concrt and abstract smantics Concrt smantics W considr a vry tiny languag that manags arithmtic oprations on intgrs valus. Th (concrt) smantics of th languags cab b dfind by th funzcion

More information

Estimation of apparent fraction defective: A mathematical approach

Estimation of apparent fraction defective: A mathematical approach Availabl onlin at www.plagiarsarchlibrary.com Plagia Rsarch Library Advancs in Applid Scinc Rsarch, 011, (): 84-89 ISSN: 0976-8610 CODEN (USA): AASRFC Estimation of apparnt fraction dfctiv: A mathmatical

More information

Physical Organization

Physical Organization Lctur usbasd symmtric multiprocssors (SM s): combin both aspcts Compilr support? rchitctural support? Static and dynamic locality of rfrnc ar critical for high prformanc M I M ccss to local mmory is usually

More information

Chemical Physics II. More Stat. Thermo Kinetics Protein Folding...

Chemical Physics II. More Stat. Thermo Kinetics Protein Folding... Chmical Physics II Mor Stat. Thrmo Kintics Protin Folding... http://www.nmc.ctc.com/imags/projct/proj15thumb.jpg http://nuclarwaponarchiv.org/usa/tsts/ukgrabl2.jpg http://www.photolib.noaa.gov/corps/imags/big/corp1417.jpg

More information

ELECTRON-MUON SCATTERING

ELECTRON-MUON SCATTERING ELECTRON-MUON SCATTERING ABSTRACT Th lctron charg is considrd to b distributd or xtndd in spac. Th diffrntial of th lctron charg is st qual to a function of lctron charg coordinats multiplid by a four-dimnsional

More information

That is, we start with a general matrix: And end with a simpler matrix:

That is, we start with a general matrix: And end with a simpler matrix: DIAGON ALIZATION OF THE STR ESS TEN SOR INTRO DUCTIO N By th us of Cauchy s thorm w ar abl to rduc th numbr of strss componnts in th strss tnsor to only nin valus. An additional simplification of th strss

More information

ECE 407 Computer Aided Design for Electronic Systems. Instructor: Maria K. Michael. Overview. CAD tools for multi-level logic synthesis:

ECE 407 Computer Aided Design for Electronic Systems. Instructor: Maria K. Michael. Overview. CAD tools for multi-level logic synthesis: 407 Computr Aidd Dsign for Elctronic Systms Multi-lvl Logic Synthsis Instructor: Maria K. Michal 1 Ovrviw Major Synthsis Phass Logic Synthsis: 2-lvl Multi-lvl FSM CAD tools for multi-lvl logic synthsis:

More information

What are those βs anyway? Understanding Design Matrix & Odds ratios

What are those βs anyway? Understanding Design Matrix & Odds ratios Ral paramtr stimat WILD 750 - Wildlif Population Analysis of 6 What ar thos βs anyway? Undrsting Dsign Matrix & Odds ratios Rfrncs Hosmr D.W.. Lmshow. 000. Applid logistic rgrssion. John Wily & ons Inc.

More information

(Upside-Down o Direct Rotation) β - Numbers

(Upside-Down o Direct Rotation) β - Numbers Amrican Journal of Mathmatics and Statistics 014, 4(): 58-64 DOI: 10593/jajms0140400 (Upsid-Down o Dirct Rotation) β - Numbrs Ammar Sddiq Mahmood 1, Shukriyah Sabir Ali,* 1 Dpartmnt of Mathmatics, Collg

More information

Continuous probability distributions

Continuous probability distributions Continuous probability distributions Many continuous probability distributions, including: Uniform Normal Gamma Eponntial Chi-Squard Lognormal Wibull EGR 5 Ch. 6 Uniform distribution Simplst charactrizd

More information

Observer Bias and Reliability By Xunchi Pu

Observer Bias and Reliability By Xunchi Pu Obsrvr Bias and Rliability By Xunchi Pu Introduction Clarly all masurmnts or obsrvations nd to b mad as accuratly as possibl and invstigators nd to pay carful attntion to chcking th rliability of thir

More information

Discovery of Cancellation Regions within Process Mining Techniques

Discovery of Cancellation Regions within Process Mining Techniques Discovry of Cancllation Rgions within Procss Mining Tchniqus A. A. Kalnkova and I. A. Lomazova 1 National Rsarch Univrsity Highr School of Economics, Moscow, Russia {akalnkova, ilomazova}@hs.ru 2 Program

More information

Numerical considerations regarding the simulation of an aircraft in the approaching phase for landing

Numerical considerations regarding the simulation of an aircraft in the approaching phase for landing INCAS BULLETIN, Volum, Numbr 1/ 1 Numrical considrations rgarding th simulation of an aircraft in th approaching phas for landing Ionl Cristinl IORGA ionliorga@yahoo.com Univrsity of Craiova, Alxandru

More information

Problem Statement. Definitions, Equations and Helpful Hints BEAUTIFUL HOMEWORK 6 ENGR 323 PROBLEM 3-79 WOOLSEY

Problem Statement. Definitions, Equations and Helpful Hints BEAUTIFUL HOMEWORK 6 ENGR 323 PROBLEM 3-79 WOOLSEY Problm Statmnt Suppos small arriv at a crtain airport according to Poisson procss with rat α pr hour, so that th numbr of arrivals during a tim priod of t hours is a Poisson rv with paramtr t (a) What

More information

International Journal of Scientific & Engineering Research, Volume 6, Issue 7, July ISSN

International Journal of Scientific & Engineering Research, Volume 6, Issue 7, July ISSN Intrnational Journal of Scintific & Enginring Rsarch, Volum 6, Issu 7, July-25 64 ISSN 2229-558 HARATERISTIS OF EDGE UTSET MATRIX OF PETERSON GRAPH WITH ALGEBRAI GRAPH THEORY Dr. G. Nirmala M. Murugan

More information

Slide 1. Slide 2. Slide 3 DIGITAL SIGNAL PROCESSING CLASSIFICATION OF SIGNALS

Slide 1. Slide 2. Slide 3 DIGITAL SIGNAL PROCESSING CLASSIFICATION OF SIGNALS Slid DIGITAL SIGAL PROCESSIG UIT I DISCRETE TIME SIGALS AD SYSTEM Slid Rviw of discrt-tim signals & systms Signal:- A signal is dfind as any physical quantity that varis with tim, spac or any othr indpndnt

More information

Behavioral Automata Composition for Automatic Topology Independent Verification of Parameterized Systems

Behavioral Automata Composition for Automatic Topology Independent Verification of Parameterized Systems Bhavioral Automata Composition for Automatic Topology Indpndnt Vrification of Paramtrizd Systms Youssf Hanna Samik Basu Hridsh Rajan Computr Scinc, Iowa Stat Univrsity 226 Atanasoff Hall, Ams, IA, USA

More information

Category Theory Approach to Fusion of Wavelet-Based Features

Category Theory Approach to Fusion of Wavelet-Based Features Catgory Thory Approach to Fusion of Wavlt-Basd Faturs Scott A. DLoach Air Forc Institut of Tchnology Dpartmnt of Elctrical and Computr Enginring Wright-Pattrson AFB, Ohio 45433 Scott.DLoach@afit.af.mil

More information

Derangements and Applications

Derangements and Applications 2 3 47 6 23 Journal of Intgr Squncs, Vol. 6 (2003), Articl 03..2 Drangmnts and Applications Mhdi Hassani Dpartmnt of Mathmatics Institut for Advancd Studis in Basic Scincs Zanjan, Iran mhassani@iasbs.ac.ir

More information

10. The Discrete-Time Fourier Transform (DTFT)

10. The Discrete-Time Fourier Transform (DTFT) Th Discrt-Tim Fourir Transform (DTFT Dfinition of th discrt-tim Fourir transform Th Fourir rprsntation of signals plays an important rol in both continuous and discrt signal procssing In this sction w

More information

A=P=E M-A=N Alpha particle Beta Particle. Periodic table

A=P=E M-A=N Alpha particle Beta Particle. Periodic table Nam Pr. Atomic Structur/Nuclar Chmistry (Ch. 3 & 21) OTHS Acadmic Chmistry Objctivs: Undrstand th xprimntal dsign and conclusions usd in th dvlopmnt of modrn atomic thory, including Dalton's Postulats,

More information

Searching Linked Lists. Perfect Skip List. Building a Skip List. Skip List Analysis (1) Assume the list is sorted, but is stored in a linked list.

Searching Linked Lists. Perfect Skip List. Building a Skip List. Skip List Analysis (1) Assume the list is sorted, but is stored in a linked list. 3 3 4 8 6 3 3 4 8 6 3 3 4 8 6 () (d) 3 Sarching Linkd Lists Sarching Linkd Lists Sarching Linkd Lists ssum th list is sortd, but is stord in a linkd list. an w us binary sarch? omparisons? Work? What if

More information

Forces. Quantum ElectroDynamics. α = = We have now:

Forces. Quantum ElectroDynamics. α = = We have now: W hav now: Forcs Considrd th gnral proprtis of forcs mdiatd by xchang (Yukawa potntial); Examind consrvation laws which ar obyd by (som) forcs. W will nxt look at thr forcs in mor dtail: Elctromagntic

More information

In the previous two chapters, we clarified what it means for a problem to be decidable or undecidable.

In the previous two chapters, we clarified what it means for a problem to be decidable or undecidable. Chaptr 7 Computational Complxity 7.1 Th Class P In th prvious two chaptrs, w clarifid what it mans for a problm to b dcidabl or undcidabl. In principl, if a problm is dcidabl, thn thr is an algorithm (i..,

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by Dan Klain Vrsion 28928 Corrctions and commnts ar wlcom Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix () A A k I + A + k!

More information

On the construction of pullbacks for safe Petri nets

On the construction of pullbacks for safe Petri nets On th construction of pullbacks for saf Ptri nts Eric Fabr Irisa/Inria Campus d Bauliu 35042 Rnns cdx, Franc Eric.Fabr@irisa.fr Abstract. Th product of saf Ptri nts is a wll known opration : it gnralizs

More information

Image Filtering: Noise Removal, Sharpening, Deblurring. Yao Wang Polytechnic University, Brooklyn, NY11201

Image Filtering: Noise Removal, Sharpening, Deblurring. Yao Wang Polytechnic University, Brooklyn, NY11201 Imag Filtring: Nois Rmoval, Sharpning, Dblurring Yao Wang Polytchnic Univrsity, Brooklyn, NY http://wb.poly.du/~yao Outlin Nois rmoval by avraging iltr Nois rmoval by mdian iltr Sharpning Edg nhancmnt

More information

Lecture 2: Discrete-Time Signals & Systems. Reza Mohammadkhani, Digital Signal Processing, 2015 University of Kurdistan eng.uok.ac.

Lecture 2: Discrete-Time Signals & Systems. Reza Mohammadkhani, Digital Signal Processing, 2015 University of Kurdistan eng.uok.ac. Lctur 2: Discrt-Tim Signals & Systms Rza Mohammadkhani, Digital Signal Procssing, 2015 Univrsity of Kurdistan ng.uok.ac.ir/mohammadkhani 1 Signal Dfinition and Exampls 2 Signal: any physical quantity that

More information

PHYSICS 489/1489 LECTURE 7: QUANTUM ELECTRODYNAMICS

PHYSICS 489/1489 LECTURE 7: QUANTUM ELECTRODYNAMICS PHYSICS 489/489 LECTURE 7: QUANTUM ELECTRODYNAMICS REMINDER Problm st du today 700 in Box F TODAY: W invstigatd th Dirac quation it dscribs a rlativistic spin /2 particl implis th xistnc of antiparticl

More information

Data Assimilation 1. Alan O Neill National Centre for Earth Observation UK

Data Assimilation 1. Alan O Neill National Centre for Earth Observation UK Data Assimilation 1 Alan O Nill National Cntr for Earth Obsrvation UK Plan Motivation & basic idas Univariat (scalar) data assimilation Multivariat (vctor) data assimilation 3d-Variational Mthod (& optimal

More information

EEO 401 Digital Signal Processing Prof. Mark Fowler

EEO 401 Digital Signal Processing Prof. Mark Fowler EEO 401 Digital Signal Procssing Prof. Mark Fowlr Dtails of th ot St #19 Rading Assignmnt: Sct. 7.1.2, 7.1.3, & 7.2 of Proakis & Manolakis Dfinition of th So Givn signal data points x[n] for n = 0,, -1

More information

Einstein Equations for Tetrad Fields

Einstein Equations for Tetrad Fields Apiron, Vol 13, No, Octobr 006 6 Einstin Equations for Ttrad Filds Ali Rıza ŞAHİN, R T L Istanbul (Turky) Evry mtric tnsor can b xprssd by th innr product of ttrad filds W prov that Einstin quations for

More information

Mor Tutorial at www.dumblittldoctor.com Work th problms without a calculator, but us a calculator to chck rsults. And try diffrntiating your answrs in part III as a usful chck. I. Applications of Intgration

More information

Homework #3. 1 x. dx. It therefore follows that a sum of the

Homework #3. 1 x. dx. It therefore follows that a sum of the Danil Cannon CS 62 / Luan March 5, 2009 Homwork # 1. Th natural logarithm is dfind by ln n = n 1 dx. It thrfor follows that a sum of th 1 x sam addnd ovr th sam intrval should b both asymptotically uppr-

More information

Deriving protocol specifications from service specifications written as Predicate/Transition-nets

Deriving protocol specifications from service specifications written as Predicate/Transition-nets Computr Ntworks 51 (2007) 258 284 www.lsvir.com/locat/comnt Driving protocol spcifications from srvic spcifications writtn as Prdicat/Transition-nts Hirozumi Yamaguchi a, *, Khald El-Fakih b,1, Grgor v.

More information

MCE503: Modeling and Simulation of Mechatronic Systems Discussion on Bond Graph Sign Conventions for Electrical Systems

MCE503: Modeling and Simulation of Mechatronic Systems Discussion on Bond Graph Sign Conventions for Electrical Systems MCE503: Modling and Simulation o Mchatronic Systms Discussion on Bond Graph Sign Convntions or Elctrical Systms Hanz ichtr, PhD Clvland Stat Univrsity, Dpt o Mchanical Enginring 1 Basic Assumption In a

More information

4. Money cannot be neutral in the short-run the neutrality of money is exclusively a medium run phenomenon.

4. Money cannot be neutral in the short-run the neutrality of money is exclusively a medium run phenomenon. PART I TRUE/FALSE/UNCERTAIN (5 points ach) 1. Lik xpansionary montary policy, xpansionary fiscal policy rturns output in th mdium run to its natural lvl, and incrass prics. Thrfor, fiscal policy is also

More information

Sec 2.3 Modeling with First Order Equations

Sec 2.3 Modeling with First Order Equations Sc.3 Modling with First Ordr Equations Mathmatical modls charactriz physical systms, oftn using diffrntial quations. Modl Construction: Translating physical situation into mathmatical trms. Clarly stat

More information

Lecture 37 (Schrödinger Equation) Physics Spring 2018 Douglas Fields

Lecture 37 (Schrödinger Equation) Physics Spring 2018 Douglas Fields Lctur 37 (Schrödingr Equation) Physics 6-01 Spring 018 Douglas Filds Rducd Mass OK, so th Bohr modl of th atom givs nrgy lvls: E n 1 k m n 4 But, this has on problm it was dvlopd assuming th acclration

More information

Checking Timed Büchi Automata Emptiness on Simulation Graphs

Checking Timed Büchi Automata Emptiness on Simulation Graphs Chcking Timd Büchi Automata Emptinss on Simulation Graphs Stavros Tripakis Cadnc Rsarch Laboratoris Timd automata [Alur and Dill 1994] ar a popular modl for dscribing ral-tim and mbddd systms and rasoning

More information

VALUING SURRENDER OPTIONS IN KOREAN INTEREST INDEXED ANNUITIES

VALUING SURRENDER OPTIONS IN KOREAN INTEREST INDEXED ANNUITIES VALUING SURRENDER OPTIONS IN KOREAN INTEREST INDEXED ANNUITIES Changi Kim* * Dr. Changi Kim is Lcturr at Actuarial Studis Faculty of Commrc & Economics Th Univrsity of Nw South Wals Sydny NSW 2052 Australia.

More information

Inheritance Gains in Notional Defined Contributions Accounts (NDCs)

Inheritance Gains in Notional Defined Contributions Accounts (NDCs) Company LOGO Actuarial Tachrs and Rsarchrs Confrnc Oxford 14-15 th July 211 Inhritanc Gains in Notional Dfind Contributions Accounts (NDCs) by Motivation of this papr In Financial Dfind Contribution (FDC)

More information

What is the product of an integer multiplied by zero? and divided by zero?

What is the product of an integer multiplied by zero? and divided by zero? IMP007 Introductory Math Cours 3. ARITHMETICS AND FUNCTIONS 3.. BASIC ARITHMETICS REVIEW (from GRE) Which numbrs form th st of th Intgrs? What is th product of an intgr multiplid by zro? and dividd by

More information

1973 AP Calculus AB: Section I

1973 AP Calculus AB: Section I 97 AP Calculus AB: Sction I 9 Minuts No Calculator Not: In this amination, ln dnots th natural logarithm of (that is, logarithm to th bas ).. ( ) d= + C 6 + C + C + C + C. If f ( ) = + + + and ( ), g=

More information

The Equitable Dominating Graph

The Equitable Dominating Graph Intrnational Journal of Enginring Rsarch and Tchnology. ISSN 0974-3154 Volum 8, Numbr 1 (015), pp. 35-4 Intrnational Rsarch Publication Hous http://www.irphous.com Th Equitabl Dominating Graph P.N. Vinay

More information

Search sequence databases 3 10/25/2016

Search sequence databases 3 10/25/2016 Sarch squnc databass 3 10/25/2016 Etrm valu distribution Ø Suppos X is a random variabl with probability dnsity function p(, w sampl a larg numbr S of indpndnt valus of X from this distribution for an

More information

Einstein Rosen inflationary Universe in general relativity

Einstein Rosen inflationary Universe in general relativity PRAMANA c Indian Acadmy of Scincs Vol. 74, No. 4 journal of April 2010 physics pp. 669 673 Einstin Rosn inflationary Univrs in gnral rlativity S D KATORE 1, R S RANE 2, K S WANKHADE 2, and N K SARKATE

More information

CE 530 Molecular Simulation

CE 530 Molecular Simulation CE 53 Molcular Simulation Lctur 8 Fr-nrgy calculations David A. Kofk Dpartmnt of Chmical Enginring SUNY Buffalo kofk@ng.buffalo.du 2 Fr-Enrgy Calculations Uss of fr nrgy Phas quilibria Raction quilibria

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by D. Klain Vrsion 207.0.05 Corrctions and commnts ar wlcom. Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix A A k I + A + k!

More information

Engineering 323 Beautiful HW #13 Page 1 of 6 Brown Problem 5-12

Engineering 323 Beautiful HW #13 Page 1 of 6 Brown Problem 5-12 Enginring Bautiful HW #1 Pag 1 of 6 5.1 Two componnts of a minicomputr hav th following joint pdf for thir usful liftims X and Y: = x(1+ x and y othrwis a. What is th probability that th liftim X of th

More information

First derivative analysis

First derivative analysis Robrto s Nots on Dirntial Calculus Chaptr 8: Graphical analysis Sction First drivativ analysis What you nd to know alrady: How to us drivativs to idntiy th critical valus o a unction and its trm points

More information

2 AN OVERVIEW OF THE TENSOR PRODUCT

2 AN OVERVIEW OF THE TENSOR PRODUCT 98 IEEE TRASACTIS PARALLEL AD DISTRIBUTED SYSTEMS, VL 10, 3, MARCH 1999 1 Th choic of data distribution has a larg influnc on th prformanc of th synthsizd programs, ur simpl algorithm for slcting th appropriat

More information

I R I S A P U B L I C A T I O N I N T E R N E N o ON THE CONSTRUCTION OF PULLBACKS FOR SAFE PETRI NETS ERIC FABRE ISSN

I R I S A P U B L I C A T I O N I N T E R N E N o ON THE CONSTRUCTION OF PULLBACKS FOR SAFE PETRI NETS ERIC FABRE ISSN I R I P U B L I C A T I O N I N T E R N E 1750 N o S INSTITUT DE RECHERCHE EN INFORMATIQUE ET SYSTÈMES ALÉATOIRES A ON THE CONSTRUCTION OF PULLBACKS FOR SAFE PETRI NETS ERIC FABRE ISSN 1166-8687 I R I

More information

Introduction to Condensed Matter Physics

Introduction to Condensed Matter Physics Introduction to Condnsd Mattr Physics pcific hat M.P. Vaughan Ovrviw Ovrviw of spcific hat Hat capacity Dulong-Ptit Law Einstin modl Dby modl h Hat Capacity Hat capacity h hat capacity of a systm hld at

More information

Higher order derivatives

Higher order derivatives Robrto s Nots on Diffrntial Calculus Chaptr 4: Basic diffrntiation ruls Sction 7 Highr ordr drivativs What you nd to know alrady: Basic diffrntiation ruls. What you can larn hr: How to rpat th procss of

More information

Outline. Thanks to Ian Blockland and Randy Sobie for these slides Lifetimes of Decaying Particles Scattering Cross Sections Fermi s Golden Rule

Outline. Thanks to Ian Blockland and Randy Sobie for these slides Lifetimes of Decaying Particles Scattering Cross Sections Fermi s Golden Rule Outlin Thanks to Ian Blockland and andy obi for ths slids Liftims of Dcaying Particls cattring Cross ctions Frmi s Goldn ul Physics 424 Lctur 12 Pag 1 Obsrvabls want to rlat xprimntal masurmnts to thortical

More information

Estimation of odds ratios in Logistic Regression models under different parameterizations and Design matrices

Estimation of odds ratios in Logistic Regression models under different parameterizations and Design matrices Advancs in Computational Intllignc, Man-Machin Systms and Cybrntics Estimation of odds ratios in Logistic Rgrssion modls undr diffrnt paramtrizations and Dsign matrics SURENDRA PRASAD SINHA*, LUIS NAVA

More information

Detecting Temporal Logic Predicates on the Happened-Before Model

Detecting Temporal Logic Predicates on the Happened-Before Model Dtcting Tmporal Logic Prdicats on th Happnd-Bor Modl Alpr Sn and Vijay K. Garg Dpartmnt o Elctrical and Computr Enginring Th Univrsity o Txas at Austin Austin TX 787 USA sngarg @c.utxas.du Abstract Dtction

More information

4. (5a + b) 7 & x 1 = (3x 1)log 10 4 = log (M1) [4] d = 3 [4] T 2 = 5 + = 16 or or 16.

4. (5a + b) 7 & x 1 = (3x 1)log 10 4 = log (M1) [4] d = 3 [4] T 2 = 5 + = 16 or or 16. . 7 7 7... 7 7 (n )0 7 (M) 0(n ) 00 n (A) S ((7) 0(0)) (M) (7 00) 8897 (A). (5a b) 7 7... (5a)... (M) 7 5 5 (a b ) 5 5 a b (M)(A) So th cofficint is 75 (A) (C) [] S (7 7) (M) () 8897 (A) (C) [] 5. x.55

More information

Mutually Independent Hamiltonian Cycles of Pancake Networks

Mutually Independent Hamiltonian Cycles of Pancake Networks Mutually Indpndnt Hamiltonian Cycls of Pancak Ntworks Chng-Kuan Lin Dpartmnt of Mathmatics National Cntral Univrsity, Chung-Li, Taiwan 00, R O C discipl@ms0urlcomtw Hua-Min Huang Dpartmnt of Mathmatics

More information

From Elimination to Belief Propagation

From Elimination to Belief Propagation School of omputr Scinc Th lif Propagation (Sum-Product lgorithm Probabilistic Graphical Modls (10-708 Lctur 5, Sp 31, 2007 Rcptor Kinas Rcptor Kinas Kinas X 5 ric Xing Gn G T X 6 X 7 Gn H X 8 Rading: J-hap

More information

The second condition says that a node α of the tree has exactly n children if the arity of its label is n.

The second condition says that a node α of the tree has exactly n children if the arity of its label is n. CS 6110 S14 Hanout 2 Proof of Conflunc 27 January 2014 In this supplmntary lctur w prov that th λ-calculus is conflunt. This is rsult is u to lonzo Church (1903 1995) an J. arkly Rossr (1907 1989) an is

More information

MCB137: Physical Biology of the Cell Spring 2017 Homework 6: Ligand binding and the MWC model of allostery (Due 3/23/17)

MCB137: Physical Biology of the Cell Spring 2017 Homework 6: Ligand binding and the MWC model of allostery (Due 3/23/17) MCB37: Physical Biology of th Cll Spring 207 Homwork 6: Ligand binding and th MWC modl of allostry (Du 3/23/7) Hrnan G. Garcia March 2, 207 Simpl rprssion In class, w drivd a mathmatical modl of how simpl

More information

CPSC 665 : An Algorithmist s Toolkit Lecture 4 : 21 Jan Linear Programming

CPSC 665 : An Algorithmist s Toolkit Lecture 4 : 21 Jan Linear Programming CPSC 665 : An Algorithmist s Toolkit Lctur 4 : 21 Jan 2015 Lcturr: Sushant Sachdva Linar Programming Scrib: Rasmus Kyng 1. Introduction An optimization problm rquirs us to find th minimum or maximum) of

More information

dr Bartłomiej Rokicki Chair of Macroeconomics and International Trade Theory Faculty of Economic Sciences, University of Warsaw

dr Bartłomiej Rokicki Chair of Macroeconomics and International Trade Theory Faculty of Economic Sciences, University of Warsaw dr Bartłomij Rokicki Chair of Macroconomics and Intrnational Trad Thory Faculty of Economic Scincs, Univrsity of Warsaw dr Bartłomij Rokicki Opn Economy Macroconomics Small opn conomy. Main assumptions

More information

GEOMETRICAL PHENOMENA IN THE PHYSICS OF SUBATOMIC PARTICLES. Eduard N. Klenov* Rostov-on-Don, Russia

GEOMETRICAL PHENOMENA IN THE PHYSICS OF SUBATOMIC PARTICLES. Eduard N. Klenov* Rostov-on-Don, Russia GEOMETRICAL PHENOMENA IN THE PHYSICS OF SUBATOMIC PARTICLES Eduard N. Klnov* Rostov-on-Don, Russia Th articl considrs phnomnal gomtry figurs bing th carrirs of valu spctra for th pairs of th rmaining additiv

More information

INC 693, 481 Dynamics System and Modelling: Linear Graph Modeling II Dr.-Ing. Sudchai Boonto Assistant Professor

INC 693, 481 Dynamics System and Modelling: Linear Graph Modeling II Dr.-Ing. Sudchai Boonto Assistant Professor INC 69, 48 Dynamics Systm and Modlling: Linar Graph Modling II Dr.-Ing. Sudchai Boonto Assistant Profssor Dpartmnt of Control Systm and Instrumntation Enginring King Mongkut s Unnivrsity of Tchnology Thonuri

More information

Formal Languages: Review

Formal Languages: Review Formal Languags: Rviw Alphabt: a finit st of symbols String: a finit squnc of symbols Languag: a st of strings String lngth: numbr of symbols in it String concatnation: w 1 w 2 Empty string: or ^ Languag

More information

Principles of Humidity Dalton s law

Principles of Humidity Dalton s law Principls of Humidity Dalton s law Air is a mixtur of diffrnt gass. Th main gas componnts ar: Gas componnt volum [%] wight [%] Nitrogn N 2 78,03 75,47 Oxygn O 2 20,99 23,20 Argon Ar 0,93 1,28 Carbon dioxid

More information

PHASE-ONLY CORRELATION IN FINGERPRINT DATABASE REGISTRATION AND MATCHING

PHASE-ONLY CORRELATION IN FINGERPRINT DATABASE REGISTRATION AND MATCHING Anall Univrsităţii d Vst din Timişoara Vol. LII, 2008 Sria Fizică PHASE-OLY CORRELATIO I FIGERPRIT DATABASE REGISTRATIO AD ATCHIG Alin C. Tusda, 2 Gianina Gabor Univrsity of Orada, Environmntal Faculty,

More information

The van der Waals interaction 1 D. E. Soper 2 University of Oregon 20 April 2012

The van der Waals interaction 1 D. E. Soper 2 University of Oregon 20 April 2012 Th van dr Waals intraction D. E. Sopr 2 Univrsity of Orgon 20 pril 202 Th van dr Waals intraction is discussd in Chaptr 5 of J. J. Sakurai, Modrn Quantum Mchanics. Hr I tak a look at it in a littl mor

More information

Quasi-Classical States of the Simple Harmonic Oscillator

Quasi-Classical States of the Simple Harmonic Oscillator Quasi-Classical Stats of th Simpl Harmonic Oscillator (Draft Vrsion) Introduction: Why Look for Eignstats of th Annihilation Oprator? Excpt for th ground stat, th corrspondnc btwn th quantum nrgy ignstats

More information

Properties of Phase Space Wavefunctions and Eigenvalue Equation of Momentum Dispersion Operator

Properties of Phase Space Wavefunctions and Eigenvalue Equation of Momentum Dispersion Operator Proprtis of Phas Spac Wavfunctions and Eignvalu Equation of Momntum Disprsion Oprator Ravo Tokiniaina Ranaivoson 1, Raolina Andriambololona 2, Hanitriarivo Rakotoson 3 raolinasp@yahoo.fr 1 ;jacqulinraolina@hotmail.com

More information

Massachusetts Institute of Technology Department of Mechanical Engineering

Massachusetts Institute of Technology Department of Mechanical Engineering Massachustts Institut of Tchnolog Dpartmnt of Mchanical Enginring. Introduction to Robotics Mid-Trm Eamination Novmbr, 005 :0 pm 4:0 pm Clos-Book. Two shts of nots ar allowd. Show how ou arrivd at our

More information

Radiation Physics Laboratory - Complementary Exercise Set MeBiom 2016/2017

Radiation Physics Laboratory - Complementary Exercise Set MeBiom 2016/2017 Th following qustions ar to b answrd individually. Usful information such as tabls with dtctor charactristics and graphs with th proprtis of matrials ar availabl in th cours wb sit: http://www.lip.pt/~patricia/fisicadaradiacao.

More information

COUNTING TAMELY RAMIFIED EXTENSIONS OF LOCAL FIELDS UP TO ISOMORPHISM

COUNTING TAMELY RAMIFIED EXTENSIONS OF LOCAL FIELDS UP TO ISOMORPHISM COUNTING TAMELY RAMIFIED EXTENSIONS OF LOCAL FIELDS UP TO ISOMORPHISM Jim Brown Dpartmnt of Mathmatical Scincs, Clmson Univrsity, Clmson, SC 9634, USA jimlb@g.clmson.du Robrt Cass Dpartmnt of Mathmatics,

More information

Brief Introduction to Statistical Mechanics

Brief Introduction to Statistical Mechanics Brif Introduction to Statistical Mchanics. Purpos: Ths nots ar intndd to provid a vry quick introduction to Statistical Mchanics. Th fild is of cours far mor vast than could b containd in ths fw pags.

More information

Introduction to Arithmetic Geometry Fall 2013 Lecture #20 11/14/2013

Introduction to Arithmetic Geometry Fall 2013 Lecture #20 11/14/2013 18.782 Introduction to Arithmtic Gomtry Fall 2013 Lctur #20 11/14/2013 20.1 Dgr thorm for morphisms of curvs Lt us rstat th thorm givn at th nd of th last lctur, which w will now prov. Thorm 20.1. Lt φ:

More information

Collisions between electrons and ions

Collisions between electrons and ions DRAFT 1 Collisions btwn lctrons and ions Flix I. Parra Rudolf Pirls Cntr for Thortical Physics, Unirsity of Oxford, Oxford OX1 NP, UK This rsion is of 8 May 217 1. Introduction Th Fokkr-Planck collision

More information

Content Skills Assessments Lessons. Identify, classify, and apply properties of negative and positive angles.

Content Skills Assessments Lessons. Identify, classify, and apply properties of negative and positive angles. Tachr: CORE TRIGONOMETRY Yar: 2012-13 Cours: TRIGONOMETRY Month: All Months S p t m b r Angls Essntial Qustions Can I idntify draw ngativ positiv angls in stard position? Do I hav a working knowldg of

More information