Meson baryon components in the states of the baryon decuplet

Size: px
Start display at page:

Download "Meson baryon components in the states of the baryon decuplet"

Transcription

1 Meson baryon components n the states of the baryon decuplet Insttuto de Físca Corpuscular, Unversdad de Valenca - CSIC Oct 1st, 2013 Collaborators: L. R. Da, L. S. Geng, E. Oset and Y. Zhang

2 Outlne ntroducton bref overvew of the formalsm nterpretaton of the sumrule applcaton to the J P = 3/2 + baryon decuplet results and conclusons

3 Resonances: composte states of hadrons or genune states? S. Wenberg, Phys. Rev. 137, B672-B678 (1965): - s-waves and small bndng energes - appled to the deuteron C. Hanhart, Y..S. Kalashnkova and A. V. Nefedev, Phys. Rev. D 81, (2010) - s-waves D. Gamermann, J. Neves, E. Oset and E. Ruz Arrola, Phys. Rev. D 81, (2010): - bound states n coupled channels (stll n s-waves) - bgger bndng energes J. Yamagata-Sekhara, J. Neves and E. Oset, Phys. Rev. D 83, (2011): - also resonances are consdered F. A. and E. Oset, Phys. Rev. D 86, (2012): - generalzaton to any partal waves, for both bound states and resonances - appled to the ρ and K mesons

4 Overvew of the formalsm We start from the potental: p V p = (2l + 1) v Θ(Λ p)θ(λ p ) p l p l P l (cos θ) Λ: cutoff n the momentum space v: N N matrx N: number of channels l-wave character of the process p l, p l, P l(cos θ) v s a constant matrx From the Lppmann-Schwnger equaton: T = (2l + 1)P l (ˆp, ˆp )Θ(Λ p)θ(λ p ) p l p l t where: t = v[1 vg] 1 does not contan the factors p l

5 Overvew of the formalsm G = p<λ d 3 p p 2l E m 1 m 2 p2 2µ modfed to contan the p 2l factor ths choce s necessary to get the generalzed sumrule g 2 [ ] dg = 1 de E=E P - g : couplng to the channel g g j = lm E E P (E E P)t j - E P: poston of the pole t holds for any partal waves t holds for both bound states and resonances [F. A. and E. Oset, Phys. Rev. D 86, (2012)] the nterpretaton of the sumrule s dfferent for bound states and resonances

6 Interpretaton of the sumrule the case of bound states the sumrule follows drectly from the normalzaton of the wave functon of the state, snce [ ] g 2 dg de = d 3 p Ψ (p) 2 d 3 p Ψ (p) 2 = 1 Z wth Z = d 3 p Ψ β (p) 2 E=E P each term s nterpreted as the probablty to fnd a certan channel n the wave functon Ψ β (p) : genune component the case of resonances - they show themselves as complex poles of the T -matrx, n the 2nd Remann sheet for open channels ( [ ] ) Re g 2 dg II de = 1 Z wth Z = Re d 3 p(ψ β(p)) 2 E=E P - nterpretaton n terms of probablty no more possble

7 Interpretaton of the sumrule related to the fact that the egenstates of a complex H are not generally orthogonal we need a borthogonal bass The relatonshp we have to use to derve the sumrule s d 3 p( Ψ (p)) Ψ (p) = d 3 pψ 2 (p) = 1 Ψ Ψ = [n the case of bound states we had Ψ Ψ = d 3 p Ψ (p) 2 ]

8 Interpretaton of the sumrule Snce the wave functon s gven by Ψ (p) = g Θ(Λ p)p E m 1 m 2 p 2 /2µ [F. A. and E. Oset, Phys. Rev. D 86, (2012)] d 3 p(ψ (p)) 2 = g 2 dg II de whch means g 2 dg II de = 1 g 2 dg II de extrapolaton of the probablty to the complex plane but t s not a probablty we can thnk of t as the weght of one gven channel n the wave functon

9 Sumrule and wave functons d 3 p(ψ (p)) 2 : can gve us nformaton about the wave functon n coordnate space snce Ψ ( r) = d 3 p (2π) 3/2 e p r Ψ ( p) and d 3 pψ ( p) 2 = d 3 rψ ( r) 2 for an open channel n the lmt r Ψ (r) 1 r e 2µ E R r e 2µ E Γ R r 4E R - E R = Re(E P ) - Γ = 2Im(E P ) and n the 2nd Remann sheet Ψ II (r) 1 r e 2µ E R r 2µ E e R Γ r 4E R = the concept of probablty s useless when we have open channels However, (Ψ II (r)) 2 oscllatory behavor d 3 r(ψ II (r)) 2 0 when r

10 πn component n the (1232) (model dependent test) We use v = α M 4 ( ) β 1 + sr s CDD pole not dependent on the momenta G(s) = d 3 q M N q 2 (2π) 3 2ω(q)E N (q) s ω(q) EN (q) + ɛ relatvstc modfed to contan the factor q 2 (p-waves) regularzed by a cutoff q max The phaseshft s gven by: T = p 2 t = 4π s M N 1 p cot δ(p) p From the best ft to the πn data we get: α = MeV sr = MeV β = MeV q max = MeV

11 πn component n the (1232) (model dependent test) In order to apply the sumrule we have to extrapolate the ampltude to the complex plane: s a + b go to the second Remann sheet: G(s) G II (s) = G I (s) + M N p3 2π s look for the complex pole s 0 correspondng to the resonance evaluate the couplngs as the resdues at the pole of t II wth Im(p) > 0 We fnd: s0 = ( ) MeV g = ( ) 10 3 MeV 1 [Re( s 0) 1210 MeV, Im( s 0) 50 MeV [PDG]] From where we get: g 2 [ dg II d s ] s0 = ( ) 1 Z = 0.62 szeable amount of πn

12 πn component n the (1232) (phenomenologcal test) We make an estmate of the same quanttes usng a phenomenologcal test g relatvstc ampltude: t = 2 s M + Γon ( ) p 3 wth g 2 = 2πM Γon ponm N 2 pon we have to go to the 2nd Remann sheet: s a + b and p p we evaluate agan the complex pole of t II and the new couplngs as the resdue at the pole We fnd: s0 = ( ) MeV g = ( ) 10 3 MeV 1 [Re( s 0) 1210 MeV, Im( s 0) 50 MeV [PDG]] q max [GeV ] 2 II dg g d s 1 Z rather stable and consstent wth the prevous results

13 The J P = 3/2 + baryon decuplet We apply the phenomenologcal test to the other partcles of the decuplet the πλ and πσ content n the Σ(1385): the branchng ratos to the dfferent channels must be taken nto account: BR πλ = 87% BR πσ = 11.7% [J. Bernger et al. [Partcle Data Group Collaboraton], Phys. Rev. D 86, (2012).] g 2 Σ, = 2πM Σ Γon p 3 () on M BR = πλ, πσ the πξ content n the Ξ(1535): we proceed n complete analogy wth the (1232) snce BR πξ = 100% [J. Bernger et al. [Partcle Data Group Collaboraton], Phys. Rev. D 86, (2012).]

14 The J P = 3/2 + baryon decuplet the KΞ content n the Ω : - the Ω s stable to strong decays and ths prevents us from evaluatng the couplngs as before - the couplng g Ω, KΞ can be related to g,πn usng SU(3) symmetry and we fnd: - the pole of the ampltude s found on the real axs g 2 Ω, KΞ = 2 g 2,πN The results we fnd are: Σ(1385) Channel πλ πσ s0 [MeV ] g [MeV ] 1 g 2 GII E 1 Z ( ) 10 3 ( ) ( ) 10 3 ( ) Ξ(1535) πξ ( ) Ω KΞ ( ) [for dg II /d s we used q max 450 MeV ]

15 The ρ and K mesons the ππ content n the ρ [F. A. and E. Oset, Phys. Rev. D 86, (2012)] Model dependent test s0 = ( ) MeV g ρ = ( ) 1 Z = Phenomenologcal test s0 = ( ) MeV g ρ = ( ) q max [GeV ] 1 Z the Kπ content n the K [C. W. Xao, F. A. and M. Bayar, Eur. Phys. J. A 49, 22 (2013)] Model dependent test s0 = ( ) MeV g ρ = ( ) 1 Z = 0.12 Phenomenologcal test s0 = ( ) MeV g ρ = ( ) q max [GeV ] 1 Z

16 Conclusons we clarfed the meanng of extendng the Wenberg sumrule to the case of resonances - d 3 p( p Ψ ) 2 measures the weght of an open channel n the wave functon - the concept of probablty s no longer useful n the case of resonances - the sum of d 3 p( p Ψ ) 2 for dfferent coupled channels s unty and ths s the generalzed sumrule for the amount of πn n the (1232) we found 60% for the other members of the decuplet we found - decreasng sze of meson baryon component at hgher energy Σ and Ξ better represented by a genune component - an amount of the bound KΞ component n the Ω of 25%

17 Meson baryon components n the states of the baryon decuplet Insttuto de Físca Corpuscular, Unversdad de Valenca - CSIC Oct 1st, 2013 Collaborators: L. R. Da, L. S. Geng, E. Oset and Y. Zhang

Open Systems: Chemical Potential and Partial Molar Quantities Chemical Potential

Open Systems: Chemical Potential and Partial Molar Quantities Chemical Potential Open Systems: Chemcal Potental and Partal Molar Quanttes Chemcal Potental For closed systems, we have derved the followng relatonshps: du = TdS pdv dh = TdS + Vdp da = SdT pdv dg = VdP SdT For open systems,

More information

The Feynman path integral

The Feynman path integral The Feynman path ntegral Aprl 3, 205 Hesenberg and Schrödnger pctures The Schrödnger wave functon places the tme dependence of a physcal system n the state, ψ, t, where the state s a vector n Hlbert space

More information

The ρ(ω)b (B) interaction and states of J = 0, 1, 2

The ρ(ω)b (B) interaction and states of J = 0, 1, 2 Eur. Phys. J. C (26) 76:82 DOI.4/epc/s52-6-398-y Regular Artcle - Theoretcal Physcs The (ω) (B) nteracton and states of J =,, 2 P. Fernandez-Soler,a, Zh-Feng Sun,J.Neves 2,E.Oset Departamento de Físca

More information

Poisson brackets and canonical transformations

Poisson brackets and canonical transformations rof O B Wrght Mechancs Notes osson brackets and canoncal transformatons osson Brackets Consder an arbtrary functon f f ( qp t) df f f f q p q p t But q p p where ( qp ) pq q df f f f p q q p t In order

More information

NUMERICAL DIFFERENTIATION

NUMERICAL DIFFERENTIATION NUMERICAL DIFFERENTIATION 1 Introducton Dfferentaton s a method to compute the rate at whch a dependent output y changes wth respect to the change n the ndependent nput x. Ths rate of change s called the

More information

MODIFICATION OF ππ AMPLITUDES AND POSITION OF THE σ POLE

MODIFICATION OF ππ AMPLITUDES AND POSITION OF THE σ POLE Vol. 45 (2014) ACTA PHYSICA POLONICA B No 7 MODIFICATION OF ππ AMPLITUDES AND POSITION OF THE σ POLE V. Nazar a, Petr Bydžovský b, Robert Kamńsk a a The Henryk Newodnczańnsk Insttute of Nuclear Physcs

More information

Solutions to Exercises in Astrophysical Gas Dynamics

Solutions to Exercises in Astrophysical Gas Dynamics 1 Solutons to Exercses n Astrophyscal Gas Dynamcs 1. (a). Snce u 1, v are vectors then, under an orthogonal transformaton, u = a j u j v = a k u k Therefore, u v = a j a k u j v k = δ jk u j v k = u j

More information

Composite Hypotheses testing

Composite Hypotheses testing Composte ypotheses testng In many hypothess testng problems there are many possble dstrbutons that can occur under each of the hypotheses. The output of the source s a set of parameters (ponts n a parameter

More information

Quantum Mechanics I - Session 4

Quantum Mechanics I - Session 4 Quantum Mechancs I - Sesson 4 Aprl 3, 05 Contents Operators Change of Bass 4 3 Egenvectors and Egenvalues 5 3. Denton....................................... 5 3. Rotaton n D....................................

More information

Frequency dependence of the permittivity

Frequency dependence of the permittivity Frequency dependence of the permttvty February 7, 016 In materals, the delectrc constant and permeablty are actually frequency dependent. Ths does not affect our results for sngle frequency modes, but

More information

Structure and compositeness of hadrons

Structure and compositeness of hadrons Structure and compositeness of hadrons Tetsuo Hyodo Yukawa Institute for Theoretical Physics, Kyoto Univ. 2014, Feb. 20th 1 Contents Contents Introduction: structure of Λ(1405) - Comparison of model and

More information

14 The Postulates of Quantum mechanics

14 The Postulates of Quantum mechanics 14 The Postulates of Quantum mechancs Postulate 1: The state of a system s descrbed completely n terms of a state vector Ψ(r, t), whch s quadratcally ntegrable. Postulate 2: To every physcally observable

More information

763622S ADVANCED QUANTUM MECHANICS Solution Set 1 Spring c n a n. c n 2 = 1.

763622S ADVANCED QUANTUM MECHANICS Solution Set 1 Spring c n a n. c n 2 = 1. 7636S ADVANCED QUANTUM MECHANICS Soluton Set 1 Sprng 013 1 Warm-up Show that the egenvalues of a Hermtan operator  are real and that the egenkets correspondng to dfferent egenvalues are orthogonal (b)

More information

PHYS 705: Classical Mechanics. Calculus of Variations II

PHYS 705: Classical Mechanics. Calculus of Variations II 1 PHYS 705: Classcal Mechancs Calculus of Varatons II 2 Calculus of Varatons: Generalzaton (no constrant yet) Suppose now that F depends on several dependent varables : We need to fnd such that has a statonary

More information

Generalized Linear Methods

Generalized Linear Methods Generalzed Lnear Methods 1 Introducton In the Ensemble Methods the general dea s that usng a combnaton of several weak learner one could make a better learner. More formally, assume that we have a set

More information

Thermodynamics and statistical mechanics in materials modelling II

Thermodynamics and statistical mechanics in materials modelling II Course MP3 Lecture 8/11/006 (JAE) Course MP3 Lecture 8/11/006 Thermodynamcs and statstcal mechancs n materals modellng II A bref résumé of the physcal concepts used n materals modellng Dr James Ellott.1

More information

Structure of near-threshold s-wave resonances

Structure of near-threshold s-wave resonances Structure of near-threshold s-wave resonances Tetsuo Hyodo Yukawa Institute for Theoretical Physics, Kyoto 203, Sep. 0th Introduction Structure of hadron excited states Various excitations of baryons M

More information

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal Inner Product Defnton 1 () A Eucldean space s a fnte-dmensonal vector space over the reals R, wth an nner product,. Defnton 2 (Inner Product) An nner product, on a real vector space X s a symmetrc, blnear,

More information

Lecture 12: Discrete Laplacian

Lecture 12: Discrete Laplacian Lecture 12: Dscrete Laplacan Scrbe: Tanye Lu Our goal s to come up wth a dscrete verson of Laplacan operator for trangulated surfaces, so that we can use t n practce to solve related problems We are mostly

More information

PHYS 215C: Quantum Mechanics (Spring 2017) Problem Set 3 Solutions

PHYS 215C: Quantum Mechanics (Spring 2017) Problem Set 3 Solutions PHYS 5C: Quantum Mechancs Sprng 07 Problem Set 3 Solutons Prof. Matthew Fsher Solutons prepared by: Chatanya Murthy and James Sully June 4, 07 Please let me know f you encounter any typos n the solutons.

More information

Density matrix. c α (t)φ α (q)

Density matrix. c α (t)φ α (q) Densty matrx Note: ths s supplementary materal. I strongly recommend that you read t for your own nterest. I beleve t wll help wth understandng the quantum ensembles, but t s not necessary to know t n

More information

Salmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2

Salmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2 Salmon: Lectures on partal dfferental equatons 5. Classfcaton of second-order equatons There are general methods for classfyng hgher-order partal dfferental equatons. One s very general (applyng even to

More information

Lecture 20: Noether s Theorem

Lecture 20: Noether s Theorem Lecture 20: Noether s Theorem In our revew of Newtonan Mechancs, we were remnded that some quanttes (energy, lnear momentum, and angular momentum) are conserved That s, they are constant f no external

More information

Note on the Electron EDM

Note on the Electron EDM Note on the Electron EDM W R Johnson October 25, 2002 Abstract Ths s a note on the setup of an electron EDM calculaton and Schff s Theorem 1 Basc Relatons The well-known relatvstc nteracton of the electron

More information

Canonical description of charm and bottom

Canonical description of charm and bottom Canoncal descrpton of charm and bottom producton n e + e, pa, π A, pp and pp collsons Krzysztof Redlch Statstcal Model and exact charge conservaton laws: e Its phenomenologcal consequences + e n HIC SM

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 5 Lecture 0 Canoncal Transformatons (Chapter 9) What We Dd Last Tme Hamlton s Prncple n the Hamltonan formalsm Dervaton was smple δi δ p H(, p, t) = 0 Adonal end-pont constrants δ t ( )

More information

Electron-Impact Double Ionization of the H 2

Electron-Impact Double Ionization of the H 2 I R A P 6(), Dec. 5, pp. 9- Electron-Impact Double Ionzaton of the H olecule Internatonal Scence Press ISSN: 9-59 Electron-Impact Double Ionzaton of the H olecule. S. PINDZOLA AND J. COLGAN Department

More information

Ensemble Methods: Boosting

Ensemble Methods: Boosting Ensemble Methods: Boostng Ncholas Ruozz Unversty of Texas at Dallas Based on the sldes of Vbhav Gogate and Rob Schapre Last Tme Varance reducton va baggng Generate new tranng data sets by samplng wth replacement

More information

Temperature. Chapter Heat Engine

Temperature. Chapter Heat Engine Chapter 3 Temperature In prevous chapters of these notes we ntroduced the Prncple of Maxmum ntropy as a technque for estmatng probablty dstrbutons consstent wth constrants. In Chapter 9 we dscussed the

More information

6.3.4 Modified Euler s method of integration

6.3.4 Modified Euler s method of integration 6.3.4 Modfed Euler s method of ntegraton Before dscussng the applcaton of Euler s method for solvng the swng equatons, let us frst revew the basc Euler s method of numercal ntegraton. Let the general from

More information

Quantum Statistical Mechanics

Quantum Statistical Mechanics Chapter 8 Quantum Statstcal Mechancs 8.1 Mcrostates For a collecton of N partcles the classcal mcrostate of the system s unquely specfed by a vector (q, p) (q 1...q N, p 1...p 3N )(q 1...q 3N,p 1...p 3N

More information

where the sums are over the partcle labels. In general H = p2 2m + V s(r ) V j = V nt (jr, r j j) (5) where V s s the sngle-partcle potental and V nt

where the sums are over the partcle labels. In general H = p2 2m + V s(r ) V j = V nt (jr, r j j) (5) where V s s the sngle-partcle potental and V nt Physcs 543 Quantum Mechancs II Fall 998 Hartree-Fock and the Self-consstent Feld Varatonal Methods In the dscusson of statonary perturbaton theory, I mentoned brey the dea of varatonal approxmaton schemes.

More information

Interval Estimation in the Classical Normal Linear Regression Model. 1. Introduction

Interval Estimation in the Classical Normal Linear Regression Model. 1. Introduction ECONOMICS 35* -- NOTE 7 ECON 35* -- NOTE 7 Interval Estmaton n the Classcal Normal Lnear Regresson Model Ths note outlnes the basc elements of nterval estmaton n the Classcal Normal Lnear Regresson Model

More information

Ph 219a/CS 219a. Exercises Due: Wednesday 23 October 2013

Ph 219a/CS 219a. Exercises Due: Wednesday 23 October 2013 1 Ph 219a/CS 219a Exercses Due: Wednesday 23 October 2013 1.1 How far apart are two quantum states? Consder two quantum states descrbed by densty operators ρ and ρ n an N-dmensonal Hlbert space, and consder

More information

Scattering of two identical particles in the center-of. of-mass frame. (b)

Scattering of two identical particles in the center-of. of-mass frame. (b) Lecture # November 5 Scatterng of two dentcal partcle Relatvtc Quantum Mechanc: The Klen-Gordon equaton Interpretaton of the Klen-Gordon equaton The Drac equaton Drac repreentaton for the matrce α and

More information

THEOREMS OF QUANTUM MECHANICS

THEOREMS OF QUANTUM MECHANICS THEOREMS OF QUANTUM MECHANICS In order to develop methods to treat many-electron systems (atoms & molecules), many of the theorems of quantum mechancs are useful. Useful Notaton The matrx element A mn

More information

Singular Value Decomposition: Theory and Applications

Singular Value Decomposition: Theory and Applications Sngular Value Decomposton: Theory and Applcatons Danel Khashab Sprng 2015 Last Update: March 2, 2015 1 Introducton A = UDV where columns of U and V are orthonormal and matrx D s dagonal wth postve real

More information

Dynamics of a Superconducting Qubit Coupled to an LC Resonator

Dynamics of a Superconducting Qubit Coupled to an LC Resonator Dynamcs of a Superconductng Qubt Coupled to an LC Resonator Y Yang Abstract: We nvestgate the dynamcs of a current-based Josephson juncton quantum bt or qubt coupled to an LC resonator. The Hamltonan of

More information

Solution 1 for USTC class Physics of Quantum Information

Solution 1 for USTC class Physics of Quantum Information Soluton 1 for 017 018 USTC class Physcs of Quantum Informaton Shua Zhao, Xn-Yu Xu and Ka Chen Natonal Laboratory for Physcal Scences at Mcroscale and Department of Modern Physcs, Unversty of Scence and

More information

A how to guide to second quantization method.

A how to guide to second quantization method. Phys. 67 (Graduate Quantum Mechancs Sprng 2009 Prof. Pu K. Lam. Verson 3 (4/3/2009 A how to gude to second quantzaton method. -> Second quantzaton s a mathematcal notaton desgned to handle dentcal partcle

More information

Textbook Problem 4.2: The theory in question has two scalar fields Φ(x) and φ(x) and the Lagrangian. 2 Φ ( µφ) 2 m2

Textbook Problem 4.2: The theory in question has two scalar fields Φ(x) and φ(x) and the Lagrangian. 2 Φ ( µφ) 2 m2 PHY 396 K. Solutons for problem set #11. Textbook Problem 4.2: The theory n queston has two scalar felds Φx) and φx) and the Lagrangan L 1 2 µφ) 2 M2 2 Φ2 + 1 2 µφ) 2 m2 2 φ2 µφφ 2, S.1) where the frst

More information

Math 426: Probability MWF 1pm, Gasson 310 Homework 4 Selected Solutions

Math 426: Probability MWF 1pm, Gasson 310 Homework 4 Selected Solutions Exercses from Ross, 3, : Math 26: Probablty MWF pm, Gasson 30 Homework Selected Solutons 3, p. 05 Problems 76, 86 3, p. 06 Theoretcal exercses 3, 6, p. 63 Problems 5, 0, 20, p. 69 Theoretcal exercses 2,

More information

Homework & Solution. Contributors. Prof. Lee, Hyun Min. Particle Physics Winter School. Park, Ye

Homework & Solution. Contributors. Prof. Lee, Hyun Min. Particle Physics Winter School. Park, Ye Homework & Soluton Prof. Lee, Hyun Mn Contrbutors Park, Ye J(yej.park@yonse.ac.kr) Lee, Sung Mook(smlngsm0919@gmal.com) Cheong, Dhong Yeon(dhongyeoncheong@gmal.com) Ban, Ka Young(ban94gy@yonse.ac.kr) Ro,

More information

Grover s Algorithm + Quantum Zeno Effect + Vaidman

Grover s Algorithm + Quantum Zeno Effect + Vaidman Grover s Algorthm + Quantum Zeno Effect + Vadman CS 294-2 Bomb 10/12/04 Fall 2004 Lecture 11 Grover s algorthm Recall that Grover s algorthm for searchng over a space of sze wors as follows: consder the

More information

1 Vectors over the complex numbers

1 Vectors over the complex numbers Vectors for quantum mechancs 1 D. E. Soper 2 Unversty of Oregon 5 October 2011 I offer here some background for Chapter 1 of J. J. Sakura, Modern Quantum Mechancs. 1 Vectors over the complex numbers What

More information

Feature Selection: Part 1

Feature Selection: Part 1 CSE 546: Machne Learnng Lecture 5 Feature Selecton: Part 1 Instructor: Sham Kakade 1 Regresson n the hgh dmensonal settng How do we learn when the number of features d s greater than the sample sze n?

More information

Prediction for several narrow N* and Λ* * resonances with hidden charm around 4 GeV

Prediction for several narrow N* and Λ* * resonances with hidden charm around 4 GeV Prediction for several narrow N* and Λ* * resonances with hidden charm around 4 GeV Jiajun Wu R. Molina E. Oset B. S. Zou Outline Introduction Theory for the new bound states Width and Coupling constant

More information

One-sided finite-difference approximations suitable for use with Richardson extrapolation

One-sided finite-difference approximations suitable for use with Richardson extrapolation Journal of Computatonal Physcs 219 (2006) 13 20 Short note One-sded fnte-dfference approxmatons sutable for use wth Rchardson extrapolaton Kumar Rahul, S.N. Bhattacharyya * Department of Mechancal Engneerng,

More information

STAT 511 FINAL EXAM NAME Spring 2001

STAT 511 FINAL EXAM NAME Spring 2001 STAT 5 FINAL EXAM NAME Sprng Instructons: Ths s a closed book exam. No notes or books are allowed. ou may use a calculator but you are not allowed to store notes or formulas n the calculator. Please wrte

More information

Applied Stochastic Processes

Applied Stochastic Processes STAT455/855 Fall 23 Appled Stochastc Processes Fnal Exam, Bref Solutons 1. (15 marks) (a) (7 marks) The dstrbuton of Y s gven by ( ) ( ) y 2 1 5 P (Y y) for y 2, 3,... The above follows because each of

More information

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0 MODULE 2 Topcs: Lnear ndependence, bass and dmenson We have seen that f n a set of vectors one vector s a lnear combnaton of the remanng vectors n the set then the span of the set s unchanged f that vector

More information

Entropy generation in a chemical reaction

Entropy generation in a chemical reaction Entropy generaton n a chemcal reacton E Mranda Área de Cencas Exactas COICET CCT Mendoza 5500 Mendoza, rgentna and Departamento de Físca Unversdad aconal de San Lus 5700 San Lus, rgentna bstract: Entropy

More information

Economics 130. Lecture 4 Simple Linear Regression Continued

Economics 130. Lecture 4 Simple Linear Regression Continued Economcs 130 Lecture 4 Contnued Readngs for Week 4 Text, Chapter and 3. We contnue wth addressng our second ssue + add n how we evaluate these relatonshps: Where do we get data to do ths analyss? How do

More information

Integrals and Invariants of Euler-Lagrange Equations

Integrals and Invariants of Euler-Lagrange Equations Lecture 16 Integrals and Invarants of Euler-Lagrange Equatons ME 256 at the Indan Insttute of Scence, Bengaluru Varatonal Methods and Structural Optmzaton G. K. Ananthasuresh Professor, Mechancal Engneerng,

More information

Credit Card Pricing and Impact of Adverse Selection

Credit Card Pricing and Impact of Adverse Selection Credt Card Prcng and Impact of Adverse Selecton Bo Huang and Lyn C. Thomas Unversty of Southampton Contents Background Aucton model of credt card solctaton - Errors n probablty of beng Good - Errors n

More information

Robert Eisberg Second edition CH 09 Multielectron atoms ground states and x-ray excitations

Robert Eisberg Second edition CH 09 Multielectron atoms ground states and x-ray excitations Quantum Physcs 量 理 Robert Esberg Second edton CH 09 Multelectron atoms ground states and x-ray exctatons 9-01 By gong through the procedure ndcated n the text, develop the tme-ndependent Schroednger equaton

More information

Module 14: THE INTEGRAL Exploring Calculus

Module 14: THE INTEGRAL Exploring Calculus Module 14: THE INTEGRAL Explorng Calculus Part I Approxmatons and the Defnte Integral It was known n the 1600s before the calculus was developed that the area of an rregularly shaped regon could be approxmated

More information

Goodness of fit and Wilks theorem

Goodness of fit and Wilks theorem DRAFT 0.0 Glen Cowan 3 June, 2013 Goodness of ft and Wlks theorem Suppose we model data y wth a lkelhood L(µ) that depends on a set of N parameters µ = (µ 1,...,µ N ). Defne the statstc t µ ln L(µ) L(ˆµ),

More information

Week 9 Chapter 10 Section 1-5

Week 9 Chapter 10 Section 1-5 Week 9 Chapter 10 Secton 1-5 Rotaton Rgd Object A rgd object s one that s nondeformable The relatve locatons of all partcles makng up the object reman constant All real objects are deformable to some extent,

More information

Physics 5153 Classical Mechanics. Principle of Virtual Work-1

Physics 5153 Classical Mechanics. Principle of Virtual Work-1 P. Guterrez 1 Introducton Physcs 5153 Classcal Mechancs Prncple of Vrtual Work The frst varatonal prncple we encounter n mechancs s the prncple of vrtual work. It establshes the equlbrum condton of a mechancal

More information

1 Derivation of Rate Equations from Single-Cell Conductance (Hodgkin-Huxley-like) Equations

1 Derivation of Rate Equations from Single-Cell Conductance (Hodgkin-Huxley-like) Equations Physcs 171/271 -Davd Klenfeld - Fall 2005 (revsed Wnter 2011) 1 Dervaton of Rate Equatons from Sngle-Cell Conductance (Hodgkn-Huxley-lke) Equatons We consder a network of many neurons, each of whch obeys

More information

From Biot-Savart Law to Divergence of B (1)

From Biot-Savart Law to Divergence of B (1) From Bot-Savart Law to Dvergence of B (1) Let s prove that Bot-Savart gves us B (r ) = 0 for an arbtrary current densty. Frst take the dvergence of both sdes of Bot-Savart. The dervatve s wth respect to

More information

/ n ) are compared. The logic is: if the two

/ n ) are compared. The logic is: if the two STAT C141, Sprng 2005 Lecture 13 Two sample tests One sample tests: examples of goodness of ft tests, where we are testng whether our data supports predctons. Two sample tests: called as tests of ndependence

More information

SIMPLE LINEAR REGRESSION

SIMPLE LINEAR REGRESSION Smple Lnear Regresson and Correlaton Introducton Prevousl, our attenton has been focused on one varable whch we desgnated b x. Frequentl, t s desrable to learn somethng about the relatonshp between two

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION do: 0.08/nature09 I. Resonant absorpton of XUV pulses n Kr + usng the reduced densty matrx approach The quantum beats nvestgated n ths paper are the result of nterference between two exctaton paths of

More information

Georgia Tech PHYS 6124 Mathematical Methods of Physics I

Georgia Tech PHYS 6124 Mathematical Methods of Physics I Georga Tech PHYS 624 Mathematcal Methods of Physcs I Instructor: Predrag Cvtanovć Fall semester 202 Homework Set #7 due October 30 202 == show all your work for maxmum credt == put labels ttle legends

More information

Kernel Methods and SVMs Extension

Kernel Methods and SVMs Extension Kernel Methods and SVMs Extenson The purpose of ths document s to revew materal covered n Machne Learnng 1 Supervsed Learnng regardng support vector machnes (SVMs). Ths document also provdes a general

More information

1 The Mistake Bound Model

1 The Mistake Bound Model 5-850: Advanced Algorthms CMU, Sprng 07 Lecture #: Onlne Learnng and Multplcatve Weghts February 7, 07 Lecturer: Anupam Gupta Scrbe: Bryan Lee,Albert Gu, Eugene Cho he Mstake Bound Model Suppose there

More information

Feynman parameter integrals

Feynman parameter integrals Feynman parameter ntegrals We often deal wth products of many propagator factors n loop ntegrals. The trck s to combne many propagators nto a sngle fracton so that the four-momentum ntegraton can be done

More information

Internal Mobility Edge in Doped Graphene: Frustration in a Renormalized Lattice

Internal Mobility Edge in Doped Graphene: Frustration in a Renormalized Lattice PIERS ONLINE, VOL. 4, NO. 3, 2008 305 Internal Moblty Edge n Doped Graphene: Frustraton n a Renormalzed Lattce Gerardo G. Naums Departamento de Físca-Químca, Insttuto de Físca Unversdad Naconal Autónoma

More information

Turbulence classification of load data by the frequency and severity of wind gusts. Oscar Moñux, DEWI GmbH Kevin Bleibler, DEWI GmbH

Turbulence classification of load data by the frequency and severity of wind gusts. Oscar Moñux, DEWI GmbH Kevin Bleibler, DEWI GmbH Turbulence classfcaton of load data by the frequency and severty of wnd gusts Introducton Oscar Moñux, DEWI GmbH Kevn Blebler, DEWI GmbH Durng the wnd turbne developng process, one of the most mportant

More information

For now, let us focus on a specific model of neurons. These are simplified from reality but can achieve remarkable results.

For now, let us focus on a specific model of neurons. These are simplified from reality but can achieve remarkable results. Neural Networks : Dervaton compled by Alvn Wan from Professor Jtendra Malk s lecture Ths type of computaton s called deep learnng and s the most popular method for many problems, such as computer vson

More information

Math1110 (Spring 2009) Prelim 3 - Solutions

Math1110 (Spring 2009) Prelim 3 - Solutions Math 1110 (Sprng 2009) Solutons to Prelm 3 (04/21/2009) 1 Queston 1. (16 ponts) Short answer. Math1110 (Sprng 2009) Prelm 3 - Solutons x a 1 (a) (4 ponts) Please evaluate lm, where a and b are postve numbers.

More information

Finding Dense Subgraphs in G(n, 1/2)

Finding Dense Subgraphs in G(n, 1/2) Fndng Dense Subgraphs n Gn, 1/ Atsh Das Sarma 1, Amt Deshpande, and Rav Kannan 1 Georga Insttute of Technology,atsh@cc.gatech.edu Mcrosoft Research-Bangalore,amtdesh,annan@mcrosoft.com Abstract. Fndng

More information

U.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016

U.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016 U.C. Berkeley CS94: Spectral Methods and Expanders Handout 8 Luca Trevsan February 7, 06 Lecture 8: Spectral Algorthms Wrap-up In whch we talk about even more generalzatons of Cheeger s nequaltes, and

More information

Physics 607 Exam 1. ( ) = 1, Γ( z +1) = zγ( z) x n e x2 dx = 1. e x2

Physics 607 Exam 1. ( ) = 1, Γ( z +1) = zγ( z) x n e x2 dx = 1. e x2 Physcs 607 Exam 1 Please be well-organzed, and show all sgnfcant steps clearly n all problems. You are graded on your wor, so please do not just wrte down answers wth no explanaton! Do all your wor on

More information

NMT EE 589 & UNM ME 482/582 ROBOT ENGINEERING. Dr. Stephen Bruder NMT EE 589 & UNM ME 482/582

NMT EE 589 & UNM ME 482/582 ROBOT ENGINEERING. Dr. Stephen Bruder NMT EE 589 & UNM ME 482/582 NMT EE 589 & UNM ME 48/58 ROBOT ENGINEERING Dr. Stephen Bruder NMT EE 589 & UNM ME 48/58 7. Robot Dynamcs 7.5 The Equatons of Moton Gven that we wsh to fnd the path q(t (n jont space) whch mnmzes the energy

More information

Lecture 14: Forces and Stresses

Lecture 14: Forces and Stresses The Nuts and Bolts of Frst-Prncples Smulaton Lecture 14: Forces and Stresses Durham, 6th-13th December 2001 CASTEP Developers Group wth support from the ESF ψ k Network Overvew of Lecture Why bother? Theoretcal

More information

Digital Signal Processing

Digital Signal Processing Dgtal Sgnal Processng Dscrete-tme System Analyss Manar Mohasen Offce: F8 Emal: manar.subh@ut.ac.r School of IT Engneerng Revew of Precedent Class Contnuous Sgnal The value of the sgnal s avalable over

More information

Moments of Inertia. and reminds us of the analogous equation for linear momentum p= mv, which is of the form. The kinetic energy of the body is.

Moments of Inertia. and reminds us of the analogous equation for linear momentum p= mv, which is of the form. The kinetic energy of the body is. Moments of Inerta Suppose a body s movng on a crcular path wth constant speed Let s consder two quanttes: the body s angular momentum L about the center of the crcle, and ts knetc energy T How are these

More information

Learning Theory: Lecture Notes

Learning Theory: Lecture Notes Learnng Theory: Lecture Notes Lecturer: Kamalka Chaudhur Scrbe: Qush Wang October 27, 2012 1 The Agnostc PAC Model Recall that one of the constrants of the PAC model s that the data dstrbuton has to be

More information

1 Matrix representations of canonical matrices

1 Matrix representations of canonical matrices 1 Matrx representatons of canoncal matrces 2-d rotaton around the orgn: ( ) cos θ sn θ R 0 = sn θ cos θ 3-d rotaton around the x-axs: R x = 1 0 0 0 cos θ sn θ 0 sn θ cos θ 3-d rotaton around the y-axs:

More information

Week 5: Neural Networks

Week 5: Neural Networks Week 5: Neural Networks Instructor: Sergey Levne Neural Networks Summary In the prevous lecture, we saw how we can construct neural networks by extendng logstc regresson. Neural networks consst of multple

More information

Lecture Notes on Linear Regression

Lecture Notes on Linear Regression Lecture Notes on Lnear Regresson Feng L fl@sdueducn Shandong Unversty, Chna Lnear Regresson Problem In regresson problem, we am at predct a contnuous target value gven an nput feature vector We assume

More information

Notes on Analytical Dynamics

Notes on Analytical Dynamics Notes on Analytcal Dynamcs Jan Peters & Mchael Mstry October 7, 004 Newtonan Mechancs Basc Asssumptons and Newtons Laws Lonely pontmasses wth postve mass Newtons st: Constant velocty v n an nertal frame

More information

1 Definition of Rademacher Complexity

1 Definition of Rademacher Complexity COS 511: Theoretcal Machne Learnng Lecturer: Rob Schapre Lecture #9 Scrbe: Josh Chen March 5, 2013 We ve spent the past few classes provng bounds on the generalzaton error of PAClearnng algorths for the

More information

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM An elastc wave s a deformaton of the body that travels throughout the body n all drectons. We can examne the deformaton over a perod of tme by fxng our look

More information

Advanced Circuits Topics - Part 1 by Dr. Colton (Fall 2017)

Advanced Circuits Topics - Part 1 by Dr. Colton (Fall 2017) Advanced rcuts Topcs - Part by Dr. olton (Fall 07) Part : Some thngs you should already know from Physcs 0 and 45 These are all thngs that you should have learned n Physcs 0 and/or 45. Ths secton s organzed

More information

THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructions

THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructions THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructons by George Hardgrove Chemstry Department St. Olaf College Northfeld, MN 55057 hardgrov@lars.acc.stolaf.edu Copyrght George

More information

Black Holes and the Hoop Conjecture. Black Holes in Supergravity and M/Superstring Theory. Penn. State University

Black Holes and the Hoop Conjecture. Black Holes in Supergravity and M/Superstring Theory. Penn. State University ˇ Black Holes and the Hoop Conjecture Black Holes n Supergravty and M/Superstrng Theory Penn. State Unversty 9 th September 200 Chrs Pope Based on work wth Gary Gbbons and Mrjam Cvetč When Does a Black

More information

5.03, Inorganic Chemistry Prof. Daniel G. Nocera Lecture 2 May 11: Ligand Field Theory

5.03, Inorganic Chemistry Prof. Daniel G. Nocera Lecture 2 May 11: Ligand Field Theory 5.03, Inorganc Chemstry Prof. Danel G. Nocera Lecture May : Lgand Feld Theory The lgand feld problem s defned by the followng Hamltonan, h p Η = wth E n = KE = where = m m x y z h m Ze r hydrogen atom

More information

9 Derivation of Rate Equations from Single-Cell Conductance (Hodgkin-Huxley-like) Equations

9 Derivation of Rate Equations from Single-Cell Conductance (Hodgkin-Huxley-like) Equations Physcs 171/271 - Chapter 9R -Davd Klenfeld - Fall 2005 9 Dervaton of Rate Equatons from Sngle-Cell Conductance (Hodgkn-Huxley-lke) Equatons We consder a network of many neurons, each of whch obeys a set

More information

8.323 Relativistic Quantum Field Theory I

8.323 Relativistic Quantum Field Theory I MI OpenCourseWare http://ocw.mt.edu 8.323 Relatvstc Quantum Feld heory I Sprng 2008 For nformaton about ctng these materals or our erms of Use, vst: http://ocw.mt.edu/terms. MASSACHUSES INSIUE OF ECHNOLOGY

More information

Primer on High-Order Moment Estimators

Primer on High-Order Moment Estimators Prmer on Hgh-Order Moment Estmators Ton M. Whted July 2007 The Errors-n-Varables Model We wll start wth the classcal EIV for one msmeasured regressor. The general case s n Erckson and Whted Econometrc

More information

9 Characteristic classes

9 Characteristic classes THEODORE VORONOV DIFFERENTIAL GEOMETRY. Sprng 2009 [under constructon] 9 Characterstc classes 9.1 The frst Chern class of a lne bundle Consder a complex vector bundle E B of rank p. We shall construct

More information

Marginal Effects in Probit Models: Interpretation and Testing. 1. Interpreting Probit Coefficients

Marginal Effects in Probit Models: Interpretation and Testing. 1. Interpreting Probit Coefficients ECON 5 -- NOE 15 Margnal Effects n Probt Models: Interpretaton and estng hs note ntroduces you to the two types of margnal effects n probt models: margnal ndex effects, and margnal probablty effects. It

More information

Canonical transformations

Canonical transformations Canoncal transformatons November 23, 2014 Recall that we have defned a symplectc transformaton to be any lnear transformaton M A B leavng the symplectc form nvarant, Ω AB M A CM B DΩ CD Coordnate transformatons,

More information

12. The Hamilton-Jacobi Equation Michael Fowler

12. The Hamilton-Jacobi Equation Michael Fowler 1. The Hamlton-Jacob Equaton Mchael Fowler Back to Confguraton Space We ve establshed that the acton, regarded as a functon of ts coordnate endponts and tme, satsfes ( ) ( ) S q, t / t+ H qpt,, = 0, and

More information

Lecture 6/7 (February 10/12, 2014) DIRAC EQUATION. The non-relativistic Schrödinger equation was obtained by noting that the Hamiltonian 2

Lecture 6/7 (February 10/12, 2014) DIRAC EQUATION. The non-relativistic Schrödinger equation was obtained by noting that the Hamiltonian 2 P470 Lecture 6/7 (February 10/1, 014) DIRAC EQUATION The non-relatvstc Schrödnger equaton was obtaned by notng that the Hamltonan H = P (1) m can be transformed nto an operator form wth the substtutons

More information

Research Article Green s Theorem for Sign Data

Research Article Green s Theorem for Sign Data Internatonal Scholarly Research Network ISRN Appled Mathematcs Volume 2012, Artcle ID 539359, 10 pages do:10.5402/2012/539359 Research Artcle Green s Theorem for Sgn Data Lous M. Houston The Unversty of

More information