Phase diagram and frustration of decoherence in Y-shaped Josephson junction networks. D.Giuliano(Cosenza), P. Sodano(Perugia)

Size: px
Start display at page:

Download "Phase diagram and frustration of decoherence in Y-shaped Josephson junction networks. D.Giuliano(Cosenza), P. Sodano(Perugia)"

Transcription

1 Phas dagram ad frustrato of dcohrc Y-shapd Josphso jucto tworks D.GulaoCosza, P. SodaoPruga Frz, Frz, Octobr Octobr

2 Ma da Y-Shapd twork of Josphso jucto chas YJJN wth a magtc frustrato Ft-couplg fxd pot FFP th phas dagram; YJJN workg ar th FFP Frustrato of dcohrc th mrgg two-lvl quatum systm QS; Applcato: grg of a rducd-dcohrc QS. Tchology: rormalzato groupboudary coformal fld thory.

3 Pla of th talk:.th YJJN as a jucto of chargd, o-dmsoal, bosoc systms;.th paramtrs ad th phas dagram of th YJJN: wakly coupld ad strogly coupld fxd pots;.emrgc of a FFP th phas dagram; 4. Currt s pattr th YJJN ar th fxd pots: th YJJN as a quatum swtch ; 5.Spctral dsty ad frustrato of dcohrc th YJJN workg ar th FFP; 6. Coclusos, possbl applcatos, prspctvs.

4 . Th YJJN ad ts fld-thortcal dscrpto E J λ ϕ ϕ λ Φ E J λ E J ϕ

5 Ctral rgo Hamltoa [ / * J g C hc E W E H ϕ φ φ φ E C >>E J Effctv -sp Hamltoa * h N W g [ 0 0 N S z φ 0 [ 0 S φ { } / [ [ [ J z c h S S E S h H ϕ

6 ow-rgy gstats h>e J ε0 h [ ε h EJ ϕ cos [ ε h E J ϕ cos [ ε E J h ϕ cos Oly ths stats wll b kpt th ffctv thory

7 Charg tulg at th r boudars HT λ cos[ φ 0 φ Wak tulg lmt:λ<<h,e J Schrffr-Wolff trasformato Boudary tracto trm H B φ φ EW [ γ h. c. E W λe 4h J [cos ϕ 9s ϕ ϕ γ arcta[ ta

8 Effctv fld thory of a JJ-cha. I. Glazma ad A. I. ark, PR 79, , D. Gulao ad P. Sodao, NPB 7, [ 0 6 cos k j k j k j C J Z j k j k j J j k j C E E E E N E H φ φ φ Mappg oto sp chajorda-wgr frmosbosozato uttgr lqud ffctv Hamltoa Φ Φ 0 4 k k k dx t u x u g H N/

9 paramtrs ad boudary codtos Wak boudary couplg E W /E J << Numa boudary codtos at th r boudary Φ k 0/x0; Couplg to th bulk suprcoductors Drchlt boudary codtos at th outr boudary Φ k k φ k ; g v v F F g g g g 4 4 u F v g g 4 g z J g4 4 a [coskf E 6E a C

10 X x Φ x χ x [ Φ x Φ x χ x [ Φ x Φ x Φ x 6 Normal flds χ ϕ ϕ φ φφ χ Boudary Hamltoa HBou E W xp[ r r χ0 γ,0;, ;, hc..

11 Dyamcal boudary codtos at th r boudary r ug χ r r r x EW s[ χ 0 γ 0 r χ x Wakly coupld FP 0 Strogly coupld FP Mmum of H Bou

12 . Phas dagram of th YJJN: wakly ad strogly coupld fxd pots Wakly coupld fxd pot ut x g t x cos[, ξ χ Mod xpaso for th plasmo flds ϕ ϕ ξ φ φ φ ξ

13 : : ' [ : :: : ' / ' τ χ τ χ τ χ τ τ r r r r r r k j g k j O.P.E. btw boudary vrtcs: Dmsolss boudary couplg GE W a/ /g

14 Scod-ordr rormalzato group quatos γ γ γ G G g d G d 0 [ / l [ cos [ / l 0 G G g d dg γ s / l 0 G d d γ γ

15 Phas dagram γ / / g< * g<:stabl fxd pot at Gγ0; fxd ls at γ0,/,/. γ / 0 / <g<9/4 *<g<9/4:strogly coupld fxd pot for γ /; ft couplg fxd pot for γ/. γ 0 / *9/4<g: strogly coupld stabl FP / 9/4<g 0 G

16 Strogly coupld fxd pot G-> Drchlt boudary codtos at th r boudary, as wll. χ 0, χ 0 spa a tragular lattc, dpdg o th valu of γ sublattc A sublattc B sublattc C For γ/ th mma l o a hoycomb lattc mrgg of two tragular sublattcs

17 Mod xpaso of th plasmo flds at th SFP ut x x P vt g t x θ ψ cos[, Dual flds ut x x P g t x ξ χ s[,

18 For γ k / th mma spa oly o of th thr sublattcs : ths cas, th ladg boudary prturbato s gv by a combato of log V- statos. H S Y V 0 h. c. V j τ : xp ± ρ j ψ τ : ρ 0,; ρ, ; ρ, Th V-stato oprators hav coformal dmso h S g4g/: for ¾<g< ad for γ k/ both th wakly coupld ad th strogly coupld fxd pot s stabl rpulsv FFP.

19 . Emrgc of a stabl ft couplg fxd pot For γk / two tragular sublattcs bcom dgrat rgy: thy mrg to form a hoycomb lattc. I ths cas, th ladg boudary prturbato s gv by a combato of short W-stato. HF ς τ W0 hc.. W j τ : xp ± j ψ τ : τ,τ - ar ffctv sosp oprators, coctg sts o quvalt sublattcs

20 Prturbatv rormalzato group quato for th rug couplg strgth d d ζ l / 0 4g 9 ζ ζ Th W-stato oprators hav coformal dmso h F g4g/9: for <g<9/4 thr th wakly coupld, or th strogly coupld fxd pot s stabl: th IR bhavor of th systm s drv by a attractv FFP

21 attc A attc B attc C Wstato Vstato

22 4. Currt pattr ar th W ad S fxd pots l * l 6 l * l 6 l * Z g I Z Z g I Z Z g I ϕ ϕ 6 ϕ ϕ ϕ Currt: logarthmc drvatvs of th partto fucto Z

23 Wakly coupld fxd pot Prturbatv calculato: th rsult s th typcal susodal bhavor, as a fucto of th appld phas dffrcs [ [ [ s s * s s * s s * γ γ γ γ γ γ g G I g G I g G I

24 Strogly coupld fxd pot Zro-mod cotrbuto to th rgy gvalus E E[, E osc E[, vg εl ε A B C 0, ε, ε O a ft-sz systm ths braks th dgracy btw th mma of th boudary pottal lablld by th s

25 Th ma cotrbuto to th total currt coms from th zro-mod trm th total rgy: ths mpls abrupt jumps prturbatvly roudd by V-statos at th dgracy btw two gvalus * 6 * 6 * vg I vg I vg I

26 Tug two gstats of th zro-mod oprator ar by a dgracy ffctv two-lvl quatum dvc For stac: sttg < < 6 6 δ δ << Th followg two stats df a ffctv QD 0,0> ; 0,> >, > A A

27 Opratg th systm as a quatum swtch I I I > δ Strog couplg δ δ 0 > a b δ masurs th dtug off th dgracy: actg o ths paramtr o maks th systm swtch btw th two stats

28 5. Th systm workg ar th FFP: currt pattr ad frustrato of dcohrc Th currt pattr ar th FFP Though t s possbl to st up a slf-cosstt formalsm to formally drv th currt pattr ar th FFP, a closd-formula ca b gv oly for g9/4-ε, wth ε<<. I ths cas, o may st th paramtrs as g * δ δ 6 ζ * ε

29 * 6 * 4 * 6 * 4 * ζ δ ζ δ vg I v I v I Currt across th thr arms

30 I I Ft couplg δ δ δ 0 a b Aga, ths s a smoothd sawtooth-lk bhavor but, ow, t s assocatd to a stabl FP > >

31 W rlat th dcohrc to th taglmt of th systm wth th plasmo bath spctral dsty of stats of th ffctv QD, Χ Ω/Ω E. Novas t al., Phys. Rv. B 7, a χ [ Ω b [ χ RPA Ω χ 0 [ Ω χ 0 [ Ω ζ ζ [ χ RPA Ω

32 ε ε ς χ 8 9 * [ 8 9 [ Ω Γ Ω Ω r RPA / [ * * E ς r r

33 Usg th RPA approxmato sktchd abov ylds χ Ω/Ω FFP DFP NFP Ω

34 Nar th SFP: o taglmt btw th QD ad th bath, but o quatum tulg btw th stats thr o rgy rormalzato; Nar th WFP: full taglmt btw th QD ad th bath full dcohrc; Nar th FFP: cosstt ad robust tul splttg of th two stats, wth a accttabl lvl of frustratd dcohrc

35 6. Coclusos. A Y-shapd JJ-twork may xhbt a FFP ts phas dagram;. At th FFP a ffctv -lvl quatum dvcs mrgs, wth hacd quatum cohrc;. Rlvat ssus for a practcal ralzato: stablzg γ, applyg th xtral phass, cotrollg othr sourcs of os

3.4 Properties of the Stress Tensor

3.4 Properties of the Stress Tensor cto.4.4 Proprts of th trss sor.4. trss rasformato Lt th compots of th Cauchy strss tsor a coordat systm wth bas vctors b. h compots a scod coordat systm wth bas vctors j,, ar gv by th tsor trasformato

More information

Lecture #11. A Note of Caution

Lecture #11. A Note of Caution ctur #11 OUTE uctos rvrs brakdow dal dod aalyss» currt flow (qualtatv)» morty carrr dstrbutos Radg: Chatr 6 Srg 003 EE130 ctur 11, Sld 1 ot of Cauto Tycally, juctos C dvcs ar formd by coutr-dog. Th quatos

More information

Pion Production via Proton Synchrotron Radiation in Strong Magnetic Fields in Relativistic Quantum Approach

Pion Production via Proton Synchrotron Radiation in Strong Magnetic Fields in Relativistic Quantum Approach Po Producto va Proto Sychrotro Radato Strog Magtc Flds Rlatvstc Quatum Approach Partcl Productos TV Ergy Rgo Collaborators Toshtaka Kajo Myog-K Chou Grad. J. MATHEWS Tomoyuk Maruyama BRS. Nho Uvrsty NaO,

More information

The real E-k diagram of Si is more complicated (indirect semiconductor). The bottom of E C and top of E V appear for different values of k.

The real E-k diagram of Si is more complicated (indirect semiconductor). The bottom of E C and top of E V appear for different values of k. Modr Smcoductor Dvcs for Itgratd rcuts haptr. lctros ad Hols Smcoductors or a bad ctrd at k=0, th -k rlatoshp ar th mmum s usually parabolc: m = k * m* d / dk d / dk gatv gatv ffctv mass Wdr small d /

More information

Lecture 14. P-N Junction Diodes: Part 3 Quantitative Analysis (Math, math and more math) Reading: Pierret 6.1

Lecture 14. P-N Junction Diodes: Part 3 Quantitative Analysis (Math, math and more math) Reading: Pierret 6.1 Lctur 4 - ucto ods art 3 Quattatv alyss Math, math ad mor math Radg rrt 6. Gorga Tch ECE 3040 - r. la oolttl Quattatv - od Soluto ssumtos stady stat codtos o- dgrat dog 3 o- dmsoal aalyss 4 low- lvl jcto

More information

Superbosonization meets Free Probability

Superbosonization meets Free Probability Suprbosoato mts Fr Probablty M Zrbaur jot wor wth S Madt Eulr Symposum St Ptrsburg Ju 3 009 Itroducto From momts to cumulats Larg- charactrstc fucto by fr probablty Suprbosoato Applcato to dsordrd scattrg

More information

Chapter 6. pn-junction diode: I-V characteristics

Chapter 6. pn-junction diode: I-V characteristics Chatr 6. -jucto dod: -V charactrstcs Tocs: stady stat rsos of th jucto dod udr ald d.c. voltag. ucto udr bas qualtatv dscusso dal dod quato Dvatos from th dal dod Charg-cotrol aroach Prof. Yo-S M Elctroc

More information

Lecture 1: Empirical economic relations

Lecture 1: Empirical economic relations Ecoomcs 53 Lctur : Emprcal coomc rlatos What s coomtrcs? Ecoomtrcs s masurmt of coomc rlatos. W d to kow What s a coomc rlato? How do w masur such a rlato? Dfto: A coomc rlato s a rlato btw coomc varabls.

More information

Department of Mathematics and Statistics Indian Institute of Technology Kanpur MSO202A/MSO202 Assignment 3 Solutions Introduction To Complex Analysis

Department of Mathematics and Statistics Indian Institute of Technology Kanpur MSO202A/MSO202 Assignment 3 Solutions Introduction To Complex Analysis Dpartmt of Mathmatcs ad Statstcs Ida Isttut of Tchology Kapur MSOA/MSO Assgmt 3 Solutos Itroducto To omplx Aalyss Th problms markd (T) d a xplct dscusso th tutoral class. Othr problms ar for hacd practc..

More information

Introduction to logistic regression

Introduction to logistic regression Itroducto to logstc rgrsso Gv: datast D { 2 2... } whr s a k-dmsoal vctor of ral-valud faturs or attrbuts ad s a bar class labl or targt. hus w ca sa that R k ad {0 }. For ampl f k 4 a datast of 3 data

More information

On the Possible Coding Principles of DNA & I Ching

On the Possible Coding Principles of DNA & I Ching Sctfc GOD Joural May 015 Volum 6 Issu 4 pp. 161-166 Hu, H. & Wu, M., O th Possbl Codg Prcpls of DNA & I Chg 161 O th Possbl Codg Prcpls of DNA & I Chg Hupg Hu * & Maox Wu Rvw Artcl ABSTRACT I ths rvw artcl,

More information

Numerical Method: Finite difference scheme

Numerical Method: Finite difference scheme Numrcal Mthod: Ft dffrc schm Taylor s srs f(x 3 f(x f '(x f ''(x f '''(x...(1! 3! f(x 3 f(x f '(x f ''(x f '''(x...(! 3! whr > 0 from (1, f(x f(x f '(x R Droppg R, f(x f(x f '(x Forward dffrcg O ( x from

More information

On Estimation of Unknown Parameters of Exponential- Logarithmic Distribution by Censored Data

On Estimation of Unknown Parameters of Exponential- Logarithmic Distribution by Censored Data saqartvlos mcrbata rovul akadms moamb, t 9, #2, 2015 BULLETIN OF THE GEORGIAN NATIONAL ACADEMY OF SCIENCES, vol 9, o 2, 2015 Mathmatcs O Estmato of Ukow Paramtrs of Epotal- Logarthmc Dstrbuto by Csord

More information

Reliability of time dependent stress-strength system for various distributions

Reliability of time dependent stress-strength system for various distributions IOS Joural of Mathmatcs (IOS-JM ISSN: 78-578. Volum 3, Issu 6 (Sp-Oct., PP -7 www.osrjourals.org lablty of tm dpdt strss-strgth systm for varous dstrbutos N.Swath, T.S.Uma Mahswar,, Dpartmt of Mathmatcs,

More information

signal amplification; design of digital logic; memory circuits

signal amplification; design of digital logic; memory circuits hatr Th lctroc dvc that s caabl of currt ad voltag amlfcato, or ga, cojucto wth othr crcut lmts, s th trasstor, whch s a thr-trmal dvc. Th dvlomt of th slco trasstor by Bard, Bratta, ad chockly at Bll

More information

LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES

LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES TRANSFORMATION OF FUNCTION OF A RANDOM VARIABLE UNIVARIATE TRANSFORMATIONS TRANSFORMATION OF RANDOM VARIABLES If s a rv wth cdf F th Y=g s also a rv. If w wrt

More information

MATHEMATICAL IDEAS AND NOTIONS OF QUANTUM FIELD THEORY. e S(A)/ da, h N

MATHEMATICAL IDEAS AND NOTIONS OF QUANTUM FIELD THEORY. e S(A)/ da, h N MATHEMATICAL IDEAS AND NOTIONS OF QUANTUM FIELD THEORY 9 4. Matrx tgrals Lt h N b th spac of Hrmta matrcs of sz N. Th r product o h N s gv by (A, B) = Tr(AB). I ths scto w wll cosdr tgrals of th form Z

More information

ASYMPTOTIC AND TOLERANCE 2D-MODELLING IN ELASTODYNAMICS OF CERTAIN THIN-WALLED STRUCTURES

ASYMPTOTIC AND TOLERANCE 2D-MODELLING IN ELASTODYNAMICS OF CERTAIN THIN-WALLED STRUCTURES AYMPTOTIC AD TOLERACE D-MODELLIG I ELATODYAMIC OF CERTAI THI-WALLED TRUCTURE B. MICHALAK Cz. WOŹIAK Dpartmt of tructural Mchacs Lodz Uvrsty of Tchology Al. Poltrchk 6 90-94 Łódź Polad Th objct of aalyss

More information

Statistical Thermodynamics Essential Concepts. (Boltzmann Population, Partition Functions, Entropy, Enthalpy, Free Energy) - lecture 5 -

Statistical Thermodynamics Essential Concepts. (Boltzmann Population, Partition Functions, Entropy, Enthalpy, Free Energy) - lecture 5 - Statstcal Thrmodyamcs sstal Cocpts (Boltzma Populato, Partto Fuctos, tropy, thalpy, Fr rgy) - lctur 5 - uatum mchacs of atoms ad molculs STATISTICAL MCHANICS ulbrum Proprts: Thrmodyamcs MACROSCOPIC Proprts

More information

Binary Choice. Multiple Choice. LPM logit logistic regresion probit. Multinomial Logit

Binary Choice. Multiple Choice. LPM logit logistic regresion probit. Multinomial Logit (c Pogsa Porchawssul, Faculty of Ecoomcs, Chulalogor Uvrsty (c Pogsa Porchawssul, Faculty of Ecoomcs, Chulalogor Uvrsty 3 Bary Choc LPM logt logstc rgrso probt Multpl Choc Multomal Logt (c Pogsa Porchawssul,

More information

Weights Interpreting W and lnw What is β? Some Endnotes = n!ω if we neglect the zero point energy then ( )

Weights Interpreting W and lnw What is β? Some Endnotes = n!ω if we neglect the zero point energy then ( ) Sprg Ch 35: Statstcal chacs ad Chcal Ktcs Wghts... 9 Itrprtg W ad lw... 3 What s?... 33 Lt s loo at... 34 So Edots... 35 Chaptr 3: Fudatal Prcpls of Stat ch fro a spl odl (drvato of oltza dstrbuto, also

More information

Lecture 12: Introduction to nonlinear optics II.

Lecture 12: Introduction to nonlinear optics II. Lcur : Iroduco o olar opcs II r Kužl ropagao of srog opc sgals propr olar ffcs Scod ordr ffcs! Thr-wav mxg has machg codo! Scod harmoc grao! Sum frqucy grao! aramrc grao Thrd ordr ffcs! Four-wav mxg! Opcal

More information

Math Tricks. Basic Probability. x k. (Combination - number of ways to group r of n objects, order not important) (a is constant, 0 < r < 1)

Math Tricks. Basic Probability. x k. (Combination - number of ways to group r of n objects, order not important) (a is constant, 0 < r < 1) Math Trcks r! Combato - umbr o was to group r o objcts, ordr ot mportat r! r! ar 0 a r a s costat, 0 < r < k k! k 0 EX E[XX-] + EX Basc Probablt 0 or d Pr[X > ] - Pr[X ] Pr[ X ] Pr[X ] - Pr[X ] Proprts

More information

In 1991 Fermat s Last Theorem Has Been Proved

In 1991 Fermat s Last Theorem Has Been Proved I 99 Frmat s Last Thorm Has B Provd Chu-Xua Jag P.O.Box 94Bg 00854Cha Jcxua00@s.com;cxxxx@6.com bstract I 67 Frmat wrot: It s mpossbl to sparat a cub to two cubs or a bquadrat to two bquadrats or gral

More information

T and V be the total kinetic energy and potential energy stored in the dynamic system. The Lagrangian L, can be defined by

T and V be the total kinetic energy and potential energy stored in the dynamic system. The Lagrangian L, can be defined by From MEC '05 Itrgratg Prosthtcs ad Mdc, Procdgs of th 005 MyoElctrc Cotrols/Powrd Prosthtcs Symposum, hld Frdrcto, Nw Bruswc, Caada, ugust 7-9, 005. EECROMECHNIC NYSIS OF COMPEE RM PROSHESIS (EMS) Prmary

More information

Washington State University

Washington State University he 3 Ktics ad Ractor Dsig Sprg, 00 Washgto Stat Uivrsity Dpartmt of hmical Egrg Richard L. Zollars Exam # You will hav o hour (60 muts) to complt this xam which cosists of four (4) problms. You may us

More information

Chapter 4 NUMERICAL METHODS FOR SOLVING BOUNDARY-VALUE PROBLEMS

Chapter 4 NUMERICAL METHODS FOR SOLVING BOUNDARY-VALUE PROBLEMS Chaptr 4 NUMERICL METHODS FOR SOLVING BOUNDRY-VLUE PROBLEMS 00 4. Varatoal formulato two-msoal magtostatcs Lt th followg magtostatc bouar-valu problm b cosr ( ) J (4..) 0 alog ΓD (4..) 0 alog ΓN (4..)

More information

MODEL QUESTION. Statistics (Theory) (New Syllabus) dx OR, If M is the mode of a discrete probability distribution with mass function f

MODEL QUESTION. Statistics (Theory) (New Syllabus) dx OR, If M is the mode of a discrete probability distribution with mass function f MODEL QUESTION Statstcs (Thory) (Nw Syllabus) GROUP A d θ. ) Wrt dow th rsult of ( ) ) d OR, If M s th mod of a dscrt robablty dstrbuto wth mass fucto f th f().. at M. d d ( θ ) θ θ OR, f() mamum valu

More information

Chp6. pn Junction Diode: I-V Characteristics II

Chp6. pn Junction Diode: I-V Characteristics II Ch6. Jucto od: -V Charactrstcs 147 6. 1. 3 rvato Pror 163 Hols o th quas utral -sd For covc s sak, df coordat as, - Th, d h d' ' B.C. 164 1 ) ' ( ' / qv L P qv P P P P L q d d q J '/ / 1) ( ' ' 같은방법으로

More information

Total Prime Graph. Abstract: We introduce a new type of labeling known as Total Prime Labeling. Graphs which admit a Total Prime labeling are

Total Prime Graph. Abstract: We introduce a new type of labeling known as Total Prime Labeling. Graphs which admit a Total Prime labeling are Itratoal Joural Of Computatoal Egrg Rsarch (crol.com) Vol. Issu. 5 Total Prm Graph M.Rav (a) Ramasubramaa 1, R.Kala 1 Dpt.of Mathmatcs, Sr Shakth Isttut of Egrg & Tchology, Combator 641 06. Dpt. of Mathmatcs,

More information

ERDOS-SMARANDACHE NUMBERS. Sabin Tabirca* Tatiana Tabirca**

ERDOS-SMARANDACHE NUMBERS. Sabin Tabirca* Tatiana Tabirca** ERDO-MARANDACHE NUMBER b Tbrc* Tt Tbrc** *Trslv Uvrsty of Brsov, Computr cc Dprtmt **Uvrsty of Mchstr, Computr cc Dprtmt Th strtg pot of ths rtcl s rprstd by rct work of Fch []. Bsd o two symptotc rsults

More information

Unbalanced Panel Data Models

Unbalanced Panel Data Models Ubalacd Pal Data odls Chaptr 9 from Baltag: Ecoomtrc Aalyss of Pal Data 5 by Adrás alascs 4448 troducto balacd or complt pals: a pal data st whr data/obsrvatos ar avalabl for all crosssctoal uts th tr

More information

Self-interaction mass formula that relates all leptons and quarks to the electron

Self-interaction mass formula that relates all leptons and quarks to the electron Slf-intraction mass formula that rlats all lptons and quarks to th lctron GERALD ROSEN (a) Dpartmnt of Physics, Drxl Univrsity Philadlphia, PA 19104, USA PACS. 12.15. Ff Quark and lpton modls spcific thoris

More information

Grand Canonical Ensemble

Grand Canonical Ensemble Th nsmbl of systms mmrsd n a partcl-hat rsrvor at constant tmpratur T, prssur P, and chmcal potntal. Consdr an nsmbl of M dntcal systms (M =,, 3,...M).. Thy ar mutually sharng th total numbr of partcls

More information

Aotomorphic Functions And Fermat s Last Theorem(4)

Aotomorphic Functions And Fermat s Last Theorem(4) otomorphc Fuctos d Frmat s Last Thorm(4) Chu-Xua Jag P. O. Box 94 Bg 00854 P. R. Cha agchuxua@sohu.com bsract 67 Frmat wrot: It s mpossbl to sparat a cub to two cubs or a bquadrat to two bquadrats or gral

More information

Correlation in tree The (ferromagnetic) Ising model

Correlation in tree The (ferromagnetic) Ising model 5/3/00 :\ jh\slf\nots.oc\7 Chaptr 7 Blf propagato corrlato tr Corrlato tr Th (frromagtc) Isg mol Th Isg mol s a graphcal mol or par ws raom Markov fl cosstg of a urct graph wth varabls assocat wth th vrtcs.

More information

Note: Torque is prop. to current Stationary voltage is prop. to speed

Note: Torque is prop. to current Stationary voltage is prop. to speed DC Mach Cotrol Mathmatcal modl. Armatr ad orq f m m a m m r a a a a a dt d ψ ψ ψ ω Not: orq prop. to crrt Statoary voltag prop. to pd Mathmatcal modl. Fld magtato f f f f d f dt a f ψ m m f f m fλ h torq

More information

ECE606: Solid State Devices Lecture 7

ECE606: Solid State Devices Lecture 7 C606: Sold Stat vcs Lctur 7 Grhard Klmck gkco@purdu.du Rfrc: Vol. 6, Ch. 3 & 4 Prstato Outl Itrsc carrr coctrato Pottal, fld, ad charg -k dagram vs. bad-dagram Basc cocpts of doors ad accptors Law of mass-acto

More information

Heisenberg Model. Sayed Mohammad Mahdi Sadrnezhaad. Supervisor: Prof. Abdollah Langari

Heisenberg Model. Sayed Mohammad Mahdi Sadrnezhaad. Supervisor: Prof. Abdollah Langari snbrg Modl Sad Mohammad Mahd Sadrnhaad Survsor: Prof. bdollah Langar bstract: n ths rsarch w tr to calculat analtcall gnvalus and gnvctors of fnt chan wth ½-sn artcls snbrg modl. W drov gnfuctons for closd

More information

pn Junction Under Reverse-Bias Conditions 3.3 Physical Operation of Diodes

pn Junction Under Reverse-Bias Conditions 3.3 Physical Operation of Diodes 3.3 Physcal Orato of os Jucto Ur vrs-bas Cotos rft Currt S : ato to th ffuso Currt comot u to majorty carrr ffuso, caus by thrmally grat morty carrrs, thr ar two currt comots lctros mov by rft from to

More information

Today s topics. How did we solve the H atom problem? CMF Office Hours

Today s topics. How did we solve the H atom problem? CMF Office Hours CMF Offc ous Wd. Nov. 4 oo-p Mo. Nov. 9 oo-p Mo. Nov. 6-3p Wd. Nov. 8 :30-3:30 p Wd. Dc. 5 oo-p F. Dc. 7 4:30-5:30 Mo. Dc. 0 oo-p Wd. Dc. 4:30-5:30 p ouly xa o Th. Dc. 3 Today s topcs Bf vw of slctd sults

More information

Almost all Cayley Graphs Are Hamiltonian

Almost all Cayley Graphs Are Hamiltonian Acta Mathmatca Sca, Nw Srs 199, Vol1, No, pp 151 155 Almost all Cayly Graphs Ar Hamltoa Mg Jxag & Huag Qogxag Abstract It has b cocturd that thr s a hamltoa cycl vry ft coctd Cayly graph I spt of th dffculty

More information

Second Handout: The Measurement of Income Inequality: Basic Concepts

Second Handout: The Measurement of Income Inequality: Basic Concepts Scod Hadout: Th Masurmt of Icom Iqualty: Basc Cocpts O th ormatv approach to qualty masurmt ad th cocpt of "qually dstrbutd quvalt lvl of com" Suppos that that thr ar oly two dvduals socty, Rachl ad Mart

More information

Entropy Equation for a Control Volume

Entropy Equation for a Control Volume Fudamtals of Thrmodyamcs Chaptr 7 Etropy Equato for a Cotrol Volum Prof. Syoug Jog Thrmodyamcs I MEE2022-02 Thrmal Egrg Lab. 2 Q ds Srr T Q S2 S1 1 Q S S2 S1 Srr T t t T t S S s m 1 2 t S S s m tt S S

More information

COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES

COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES DEFINITION OF A COMPLEX NUMBER: A umbr of th form, whr = (, ad & ar ral umbrs s calld a compl umbr Th ral umbr, s calld ral part of whl s calld

More information

and one unit cell contains 8 silicon atoms. The atomic density of silicon is

and one unit cell contains 8 silicon atoms. The atomic density of silicon is Chaptr Vsualzato o th Slo Crystal (a) Plas rr to Fgur - Th 8 orr atoms ar shar by 8 ut lls a thror otrbut atom Smlarly, th 6 a atoms ar ah shar by ut lls a otrbut atoms A, 4 atoms ar loat s th ut ll H,

More information

Phase-Field Modeling for Dynamic Recrystallization

Phase-Field Modeling for Dynamic Recrystallization 0 (0000) 0 0 Plas lav ths spac mpty Phas-Fld Modlg for Dyamc Rcrystallzato T. Takak *, A. Yamaaka, Y. Tomta 3 Faculty of Martm Sccs, Kob Uvrsty, 5--, Fukamam, Hgashada, Kob, 658-00, Japa (Emal : takak@martm.kob-u.ac.p)

More information

Course 10 Shading. 1. Basic Concepts: Radiance: the light energy. Light Source:

Course 10 Shading. 1. Basic Concepts: Radiance: the light energy. Light Source: Cour 0 Shadg Cour 0 Shadg. Bac Coct: Lght Sourc: adac: th lght rg radatd from a ut ara of lght ourc or urfac a ut old agl. Sold agl: $ # r f lght ourc a ot ourc th ut ara omttd abov dfto. llumato: lght

More information

Statics. Consider the free body diagram of link i, which is connected to link i-1 and link i+1 by joint i and joint i-1, respectively. = r r r.

Statics. Consider the free body diagram of link i, which is connected to link i-1 and link i+1 by joint i and joint i-1, respectively. = r r r. Statcs Th cotact btw a mapulato ad ts vomt sults tactv ocs ad momts at th mapulato/vomt tac. Statcs ams at aalyzg th latoshp btw th actuato dv tous ad th sultat oc ad momt appld at th mapulato dpot wh

More information

Three-Dimensional Theory of Nonlinear-Elastic. Bodies Stability under Finite Deformations

Three-Dimensional Theory of Nonlinear-Elastic. Bodies Stability under Finite Deformations Appld Mathmatcal Sccs ol. 9 5 o. 43 75-73 HKAR Ltd www.m-hkar.com http://dx.do.org/.988/ams.5.567 Thr-Dmsoal Thory of Nolar-Elastc Bods Stablty udr Ft Dformatos Yu.. Dmtrko Computatoal Mathmatcs ad Mathmatcal

More information

Counting the compositions of a positive integer n using Generating Functions Start with, 1. x = 3 ), the number of compositions of 4.

Counting the compositions of a positive integer n using Generating Functions Start with, 1. x = 3 ), the number of compositions of 4. Coutg th compostos of a postv tgr usg Gratg Fuctos Start wth,... - Whr, for ampl, th co-ff of s, for o summad composto of aml,. To obta umbr of compostos of, w d th co-ff of (...) ( ) ( ) Hr for stac w

More information

ME 501A Seminar in Engineering Analysis Page 1

ME 501A Seminar in Engineering Analysis Page 1 St Ssts o Ordar Drtal Equatos Novbr 7 St Ssts o Ordar Drtal Equatos Larr Cartto Mcacal Er 5A Sar Er Aalss Novbr 7 Outl Mr Rsults Rvw last class Stablt o urcal solutos Stp sz varato or rror cotrol Multstp

More information

Eigenvalue Distributions of Quark Matrix at Finite Isospin Chemical Potential

Eigenvalue Distributions of Quark Matrix at Finite Isospin Chemical Potential Tim: Tusday, 5: Room: Chsapak A Eignvalu Distributions of Quark Matri at Finit Isospin Chmical Potntial Prsntr: Yuji Sasai Tsuyama National Collg of Tchnology Co-authors: Grnot Akmann, Atsushi Nakamura

More information

The probability of Riemann's hypothesis being true is. equal to 1. Yuyang Zhu 1

The probability of Riemann's hypothesis being true is. equal to 1. Yuyang Zhu 1 Th robablty of Ra's hyothss bg tru s ual to Yuyag Zhu Abstract Lt P b th st of all r ubrs P b th -th ( ) lt of P ascdg ordr of sz b ostv tgrs ad s a rutato of wth Th followg rsults ar gv ths ar: () Th

More information

Group Consensus of Second-Order Multi-agent Networks with Multiple Time Delays

Group Consensus of Second-Order Multi-agent Networks with Multiple Time Delays Itratoal Cofrc o Appld Mathmatcs, Smulato ad Modllg (AMSM 6) Group Cossus of Scod-Ordr Mult-agt Ntworks wth Multpl Tm Dlays Laghao J* ad Xyu Zhao Chogqg Ky Laboratory of Computatoal Itllgc, Chogqg Uvrsty

More information

IX.2. A Semiconductor Device Primer

IX.2. A Semiconductor Device Primer 1 IX.2. Smcoductor vc Prmr blograhy: 1. Grov,.S., Physcs ad chology of Smcoductor vcs (Joh Wly & Sos, w Yor, 1967) 2. Sz, S.M., Physcs of Smcoductor vcs (Joh Wly & Sos, w Yor, 1981) K 7871.85.S988, IS

More information

School of Aerospace Engineering Origins of Quantum Theory. Measurements of emission of light (EM radiation) from (H) atoms found discrete lines

School of Aerospace Engineering Origins of Quantum Theory. Measurements of emission of light (EM radiation) from (H) atoms found discrete lines Ogs of Quatu Thoy Masuts of sso of lght (EM adato) fo (H) atos foud dsct ls 5 4 Abl to ft to followg ss psso ν R λ c λwavlgth, νfqucy, cspd lght RRydbg Costat (~09,7677.58c - ),,, +, +,..g.,,.6, 0.6, (Lya

More information

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory ROAD MAP... AE301 Aerodyamcs I UNIT C: 2-D Arfols C-1: Aerodyamcs of Arfols 1 C-2: Aerodyamcs of Arfols 2 C-3: Pael Methods C-4: Th Arfol Theory AE301 Aerodyamcs I Ut C-3: Lst of Subects Problem Solutos?

More information

Repeated Trials: We perform both experiments. Our space now is: Hence: We now can define a Cartesian Product Space.

Repeated Trials: We perform both experiments. Our space now is: Hence: We now can define a Cartesian Product Space. Rpatd Trals: As w hav lood at t, th thory of probablty dals wth outcoms of sgl xprmts. I th applcatos o s usually trstd two or mor xprmts or rpatd prformac or th sam xprmt. I ordr to aalyz such problms

More information

Notation for Mixed Models for Finite Populations

Notation for Mixed Models for Finite Populations 30- otato for d odl for Ft Populato Smpl Populato Ut ad Rpo,..., Ut Labl for,..., Epctd Rpo (ovr rplcatd maurmt for,..., Rgro varabl (Luz r for,...,,,..., p Aular varabl for ut (Wu z μ for,...,,,..., p

More information

Large N phase transitions in Supersymmetric gauge theories with massive matter

Large N phase transitions in Supersymmetric gauge theories with massive matter Lar phas trastos Suprsytrc au thors wth assv attr Mul Trz trz@uc.s Uvrsdad Copluts d Madrd Basd o: J. Russo ad K. arbo arv:309.004 3.4 30.6968 A. Barraco ad J. Russo arv:40.367 J. Russo G. Slva ad M.T.

More information

Coupled Pendulums. Two normal modes.

Coupled Pendulums. Two normal modes. Tim Dpndnt Two Stat Problm Coupld Pndulums Wak spring Two normal mods. No friction. No air rsistanc. Prfct Spring Start Swinging Som tim latr - swings with full amplitud. stationary M +n L M +m Elctron

More information

Kondo vs Fano resonances in Quantum Dot

Kondo vs Fano resonances in Quantum Dot ivrsita Frio II i Napoli Italy Koo vs Fao rsoas i Quatum Dot Capri Capri 4/5 4/5 P.tfasi, B.Bula (Poza) A.T., P.Luigao, A.Nao B.ouault (CNR Motpllir) D.Giuliao ( iv. Calabria, Italy) P.Luigao, B.ouault,

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

' 1.00, has the form of a rhomb with

' 1.00, has the form of a rhomb with Problm I Rflcto ad rfracto of lght A A trstg prsm Th ma scto of a glass prsm stuatd ar ' has th form of a rhomb wth A th yllow bam of moochromatc lght propagatg towards th prsm paralll wth th dagoal AC

More information

Control Systems. Lecture 8 Root Locus. Root Locus. Plant. Controller. Sensor

Control Systems. Lecture 8 Root Locus. Root Locus. Plant. Controller. Sensor Cotol Syt ctu 8 Root ocu Clacal Cotol Pof. Eugo Schut hgh Uvty Root ocu Cotoll Plat R E C U Y - H C D So Y C C R C H Wtg th loo ga a w a ttd tackg th clod-loo ol a ga va Clacal Cotol Pof. Eugo Schut hgh

More information

Estimating the Variance in a Simulation Study of Balanced Two Stage Predictors of Realized Random Cluster Means Ed Stanek

Estimating the Variance in a Simulation Study of Balanced Two Stage Predictors of Realized Random Cluster Means Ed Stanek Etatg th Varac a Sulato Study of Balacd Two Stag Prdctor of Ralzd Rado Clutr Ma Ed Stak Itroducto W dcrb a pla to tat th varac copot a ulato tudy N ( µ µ W df th varac of th clutr paratr a ug th N ulatd

More information

Chiang Mai J. Sci. 2014; 41(2) 457 ( 2) ( ) ( ) forms a simply periodic Proof. Let q be a positive integer. Since

Chiang Mai J. Sci. 2014; 41(2) 457 ( 2) ( ) ( ) forms a simply periodic Proof. Let q be a positive integer. Since 56 Chag Ma J Sc 0; () Chag Ma J Sc 0; () : 56-6 http://pgscccmuacth/joural/ Cotrbutd Papr Th Padova Sucs Ft Groups Sat Taș* ad Erdal Karaduma Dpartmt of Mathmatcs, Faculty of Scc, Atatürk Uvrsty, 50 Erzurum,

More information

Module 8 Non equilibrium Thermodynamics

Module 8 Non equilibrium Thermodynamics Modul 8 Non quilibrium hrmodynamics ctur 8.1 Basic Postulats NON-EQUIIRIBIUM HERMODYNAMICS Stady Stat procsss. (Stationary) Concpt of ocal thrmodynamic qlbm Extnsiv proprty Hat conducting bar dfin proprtis

More information

MB DISTRIBUTION AND ITS APPLICATION USING MAXIMUM ENTROPY APPROACH

MB DISTRIBUTION AND ITS APPLICATION USING MAXIMUM ENTROPY APPROACH Yugoslav Joural of Opratos Rsarch 6 (06), Numbr, 89-98 DOI: 0.98/YJOR405906B MB DISTRIBUTION AND ITS APPLICATION USING MAXIMUM ENTROPY APPROACH Suma BHADRA Rsarch Scholar Dpartmt of Mathmatcs IIEST, Shbpur

More information

EE 570: Location and Navigation: Theory & Practice

EE 570: Location and Navigation: Theory & Practice EE 570: ocato ad Navgato: Thory & Practc Navgato Mathmatcs Thursay 7 F 2013 NMT EE 570: ocato ad Navgato: Thory & Practc Sld 1 of 15 Navgato Mathmatcs : Coordat Fram Trasformatos Dtrm th dtald kmatc rlatoshps

More information

Complex Numbers. Prepared by: Prof. Sunil Department of Mathematics NIT Hamirpur (HP)

Complex Numbers. Prepared by: Prof. Sunil Department of Mathematics NIT Hamirpur (HP) th Topc Compl Nmbrs Hyprbolc fctos ad Ivrs hyprbolc fctos, Rlato btw hyprbolc ad crclar fctos, Formla of hyprbolc fctos, Ivrs hyprbolc fctos Prpard by: Prof Sl Dpartmt of Mathmatcs NIT Hamrpr (HP) Hyprbolc

More information

MOLECULAR VIBRATIONS

MOLECULAR VIBRATIONS MOLECULAR VIBRATIONS Here we wsh to vestgate molecular vbratos ad draw a smlarty betwee the theory of molecular vbratos ad Hückel theory. 1. Smple Harmoc Oscllator Recall that the eergy of a oe-dmesoal

More information

Machine Learning. Principle Component Analysis. Prof. Dr. Volker Sperschneider

Machine Learning. Principle Component Analysis. Prof. Dr. Volker Sperschneider Mach Larg Prcpl Compot Aalyss Prof. Dr. Volkr Sprschdr AG Maschlls Lr ud Natürlchsprachlch Systm Isttut für Iformatk chsch Fakultät Albrt-Ludgs-Uvrstät Frburg sprschdr@formatk.u-frburg.d I. Archtctur II.

More information

4D SIMPLICIAL QUANTUM GRAVITY

4D SIMPLICIAL QUANTUM GRAVITY T.YUKAWA and S.HORATA Soknda/KEK D SIMPLICIAL QUATUM GRAITY Plan of th talk Rvw of th D slcal quantu gravty Rvw of nurcal thods urcal rsult and dscusson Whr dos th slcal quantu gravty stand? In short dstanc

More information

EAcos θ, where θ is the angle between the electric field and

EAcos θ, where θ is the angle between the electric field and 8.4. Modl: Th lctric flux flows out of a closd surfac around a rgion of spac containing a nt positiv charg and into a closd surfac surrounding a nt ngativ charg. Visualiz: Plas rfr to Figur EX8.4. Lt A

More information

Different types of Domination in Intuitionistic Fuzzy Graph

Different types of Domination in Intuitionistic Fuzzy Graph Aals of Pur ad Appld Mathmatcs Vol, No, 07, 87-0 ISSN: 79-087X P, 79-0888ol Publshd o July 07 wwwrsarchmathscorg DOI: http://dxdoorg/057/apama Aals of Dffrt typs of Domato Itutostc Fuzzy Graph MGaruambga,

More information

Introduction to logistic regression

Introduction to logistic regression Itroducto to logstc rgrsso Gv: datast D {... } whr s a k-dmsoal vctor of ral-valud faturs or attrbuts ad s a bar class labl or targt. hus w ca sa that R k ad {0 }. For ampl f k 4 a datast of 3 data pots

More information

ECE594I Notes set 6: Thermal Noise

ECE594I Notes set 6: Thermal Noise C594I ots, M. odwll, copyrightd C594I Nots st 6: Thrmal Nois Mark odwll Uivrsity of Califoria, ata Barbara rodwll@c.ucsb.du 805-893-344, 805-893-36 fax frcs ad Citatios: C594I ots, M. odwll, copyrightd

More information

Session : Plasmas in Equilibrium

Session : Plasmas in Equilibrium Sssio : Plasmas i Equilibrium Ioizatio ad Coductio i a High-prssur Plasma A ormal gas at T < 3000 K is a good lctrical isulator, bcaus thr ar almost o fr lctros i it. For prssurs > 0.1 atm, collisio amog

More information

EFFECT OF PLASMA-WALL RECOMBINATION AND TURBULENT RESISTIVITY ON THE CONDUCTIVITY IN HALL THRUSTERS

EFFECT OF PLASMA-WALL RECOMBINATION AND TURBULENT RESISTIVITY ON THE CONDUCTIVITY IN HALL THRUSTERS EFFEC OF PLASMA-WALL RECOMBINAION AND URBULEN RESISIVIY ON E CONDUCIVIY IN ALL RUSERS A.A. Ivaov, A.A. Ivaov Jr ad M. Bacal Laborator d Physqu t cholog ds Plasmas, Ecol Polytchqu, UMR 7648 du CNRS, 98

More information

6.012 Electronic Devices and Circuits Formula Sheet for Final Exam, Fall q = 1.6x10 19 Coul III IV V = x10 14 o. = 3.

6.012 Electronic Devices and Circuits Formula Sheet for Final Exam, Fall q = 1.6x10 19 Coul III IV V = x10 14 o. = 3. 6.0 Elctc Dvcs ad Ccuts ula Sht f al Exa, all 003 Paat Valus: Pdc Tabl: q.6x0 9 Cul III IV V 8.854 x0 4 /c,,s.7,,so 3.9 B C N 0 S /c, SO 3.5 x0 3 /c Al S P [S@R.T] 0 0 c 3 Ga G As /q 0.05 V ; ( /q) l0

More information

Solid State Theory Physics 545. Crystal Vibrations and Phonons

Solid State Theory Physics 545. Crystal Vibrations and Phonons Sold Stat Thory Physcs 545 Crystal Vbratos ad Phoos Ovrvw Ioc oto ad th haroc approxato Itrodcto to vbratos ad th s of labl k, th wav vctor, dxg th Rcprocal spac rvstd Vbratos a ft oatoc lattc, cocpt of

More information

X ε ) = 0, or equivalently, lim

X ε ) = 0, or equivalently, lim Revew for the prevous lecture Cocepts: order statstcs Theorems: Dstrbutos of order statstcs Examples: How to get the dstrbuto of order statstcs Chapter 5 Propertes of a Radom Sample Secto 55 Covergece

More information

LINEAR REGRESSION ANALYSIS

LINEAR REGRESSION ANALYSIS LINEAR REGRESSION ANALYSIS MODULE V Lecture - Correctg Model Iadequaces Through Trasformato ad Weghtg Dr. Shalabh Departmet of Mathematcs ad Statstcs Ida Isttute of Techology Kapur Aalytcal methods for

More information

The translational oscillations of a cylindrical bubble in a bounded volume of a liquid with free deformable interface

The translational oscillations of a cylindrical bubble in a bounded volume of a liquid with free deformable interface Joural of Physcs: Cofrc Srs PAPER OPEN ACCESS Th traslatoal oscllatos of a cyldrcal bubbl a boudd volum of a lqud wth fr dformabl trfac To ct ths artcl: A A Alabuzhv ad M I Kaysa 6 J. Phys.: Cof. Sr. 68

More information

The E vs k diagrams are in general a function of the k -space direction in a crystal

The E vs k diagrams are in general a function of the k -space direction in a crystal vs dagram p m m he parameter s called the crystal mometum ad s a parameter that results from applyg Schrödger wave equato to a sgle-crystal lattce. lectros travelg dfferet drectos ecouter dfferet potetal

More information

Independent Domination in Line Graphs

Independent Domination in Line Graphs Itratoal Joural of Sctfc & Egrg Rsarch Volum 3 Issu 6 Ju-1 1 ISSN 9-5518 Iddt Domato L Grahs M H Muddbhal ad D Basavarajaa Abstract - For ay grah G th l grah L G H s th trscto grah Thus th vrtcs of LG

More information

ENGI 4421 Joint Probability Distributions Page Joint Probability Distributions [Navidi sections 2.5 and 2.6; Devore sections

ENGI 4421 Joint Probability Distributions Page Joint Probability Distributions [Navidi sections 2.5 and 2.6; Devore sections ENGI 441 Jot Probablty Dstrbutos Page 7-01 Jot Probablty Dstrbutos [Navd sectos.5 ad.6; Devore sectos 5.1-5.] The jot probablty mass fucto of two dscrete radom quattes, s, P ad p x y x y The margal probablty

More information

Learning from Data with Information Theoretic Criteria II

Learning from Data with Information Theoretic Criteria II Larg from Data th Iformato Thortc Crtra II Jos C. Prcp, Ph.D. Dstgushd Profssor of Elctrcal ad Bomdcal Egrg ad BllSouth Profssor Computatoal uroegrg Laborator Uvrst of Florda http://.cl.ufl.du prcp@cl.ufl.du

More information

Round-Off Noise of Multiplicative FIR Filters Implemented on an FPGA Platform

Round-Off Noise of Multiplicative FIR Filters Implemented on an FPGA Platform Appl. Sc. 4, 4, 99-7; do:.339/app499 Artcl OPEN ACCESS appld sccs ISSN 76-347 www.mdp.com/joural/applsc Roud-Off Nos of Multplcatv FIR Fltrs Implmtd o a FPGA Platform Ja-Jacqus Vadbussch, *, Ptr L ad Joa

More information

On Approximation Lower Bounds for TSP with Bounded Metrics

On Approximation Lower Bounds for TSP with Bounded Metrics O Approxmato Lowr Bouds for TSP wth Boudd Mtrcs Mark Karpsk Rchard Schmd Abstract W dvlop a w mthod for provg xplct approxmato lowr bouds for TSP problms wth boudd mtrcs mprovg o th bst up to ow kow bouds.

More information

Chapter 14 Logistic Regression Models

Chapter 14 Logistic Regression Models Chapter 4 Logstc Regresso Models I the lear regresso model X β + ε, there are two types of varables explaatory varables X, X,, X k ad study varable y These varables ca be measured o a cotuous scale as

More information

Bifurcation Theory. , a stationary point, depends on the value of α. At certain values

Bifurcation Theory. , a stationary point, depends on the value of α. At certain values Dnamic Macroconomic Thor Prof. Thomas Lux Bifurcation Thor Bifurcation: qualitativ chang in th natur of th solution occurs if a paramtr passs through a critical point bifurcation or branch valu. Local

More information

Phy213: General Physics III 4/10/2008 Chapter 22 Worksheet 1. d = 0.1 m

Phy213: General Physics III 4/10/2008 Chapter 22 Worksheet 1. d = 0.1 m hy3: Gnral hyscs III 4/0/008 haptr Worksht lctrc Flds: onsdr a fxd pont charg of 0 µ (q ) q = 0 µ d = 0 a What s th agntud and drcton of th lctrc fld at a pont, a dstanc of 0? q = = 8x0 ˆ o d ˆ 6 N ( )

More information

Lecture 7 Diffusion. Our fluid equations that we developed before are: v t v mn t

Lecture 7 Diffusion. Our fluid equations that we developed before are: v t v mn t Cla ot fo EE6318/Phy 6383 Spg 001 Th doumt fo tutoal u oly ad may ot b opd o dtbutd outd of EE6318/Phy 6383 tu 7 Dffuo Ou flud quato that w dvlopd bfo a: f ( )+ v v m + v v M m v f P+ q E+ v B 13 1 4 34

More information

Transparency and stability of low density stellar plasma related to Boltzmann statistics, inverse stimulated bremsstrahlung and to dark matter

Transparency and stability of low density stellar plasma related to Boltzmann statistics, inverse stimulated bremsstrahlung and to dark matter Trasparcy ad stablty of low dsty stllar plasma rlatd to oltzma statstcs, vrs stmulatd brmsstrahlug ad to dark mattr Y. -Aryh Tcho-Isral Isttut of Tchology, Physc Dpartmt, Isral, Hafa, Emal: phr65yb@tcho.physcs.ac.l

More information

International Journal of Mathematical Archive-6(5), 2015, Available online through ISSN

International Journal of Mathematical Archive-6(5), 2015, Available online through  ISSN Itratoal Joural of Mathmatal Arhv-6), 0, 07- Avalabl ol through wwwjmafo ISSN 9 06 ON THE LINE-CUT TRANSFORMATION RAPHS B BASAVANAOUD*, VEENA R DESAI Dartmt of Mathmats, Karatak Uvrsty, Dharwad - 80 003,

More information

Standard Model - Electroweak Interactions. Standard Model. Outline. Weak Neutral Interactions. Electroweak Theory. Experimental Tests.

Standard Model - Electroweak Interactions. Standard Model. Outline. Weak Neutral Interactions. Electroweak Theory. Experimental Tests. Standard Modl - Elctrowak Intractions Outlin ak Nutral Intractions Nutral Currnts (NC) Elctrowak Thory ± and Z and γ Discovry of ± Exprimntal Tsts LEP Z Boson Mass and idth Numbr of Nutrinos ± Boson ±

More information

Simulation Output Analysis

Simulation Output Analysis Smulato Output Aalyss Summary Examples Parameter Estmato Sample Mea ad Varace Pot ad Iterval Estmato ermatg ad o-ermatg Smulato Mea Square Errors Example: Sgle Server Queueg System x(t) S 4 S 4 S 3 S 5

More information