text
stringlengths
16
3.88k
source
stringlengths
60
201
5.8 The Harmonic Oscillator To illustrate the beauty and efficiency in describing the dynamics of a quan- tum system using the dirac notation and operator algebra, we reconsider the one-dimensional harmonic oscillator discussed in section 4.4.2 and described by the Hamiltonian operator with H = p2 2m + 1 2 K x2, [x, p] =...
https://ocw.mit.edu/courses/6-974-fundamentals-of-photonics-quantum-electronics-spring-2006/575470ae5ba3cafa4fd36e35b0d29e17_harmonic_oscil.pdf
+ = ~ω0 ¡ a+a+ µ ¢ . 1 2 ¶ We introduce the operator N = a+a, (5.138) (5.139) (5.140) which is a hermitian operator. Up to an additive constant 1/2 and a scaling factor ~ω0 equal to the energy of one quantum of the harmonic oscillator it is equal to the Hamiltonian operator of the harmonic oscillator. Obviously, N is t...
https://ocw.mit.edu/courses/6-974-fundamentals-of-photonics-quantum-electronics-spring-2006/575470ae5ba3cafa4fd36e35b0d29e17_harmonic_oscil.pdf
constant. This constant follows from the normalization of this state and being an eigenvector to the number operator. a+a n | h n C = | | i | C = √n. 2 , (5.147) (5.148) (5.149) Thus a n i | = √n n | , 1 i − Clearly, if there is a state with n = 0 application of the annihilation operator leads to the null-vector in thi...
https://ocw.mit.edu/courses/6-974-fundamentals-of-photonics-quantum-electronics-spring-2006/575470ae5ba3cafa4fd36e35b0d29e17_harmonic_oscil.pdf
155) (5.156) (5.157) 5.8.2 Matrix Representation We can express the normalized position and momentum operators as func- tions of the creation and annihilation operators X = P = 1 √2 j √2 a+ + a , ¡ a+ a − ¢ . (5.158) (5.159) These operators do have the following matrix representations ¡ ¢ a m h | a+a m | h m | h X n i ...
https://ocw.mit.edu/courses/6-974-fundamentals-of-photonics-quantum-electronics-spring-2006/575470ae5ba3cafa4fd36e35b0d29e17_harmonic_oscil.pdf
MASSACHUSETTS INSTITUTE OF TECHNOLOGY SLOAN SCHOOL OF MANAGEMENT 15.565 Integrating Information Systems: Technology, Strategy, and Organizational Factors 15.578 Global Information Systems: Communications & Connectivity Among Information Systems Spring 2002 Lecture 9 NETWORK PROTOCOLS COMPLEXITY OF COMMUNICATION N...
https://ocw.mit.edu/courses/15-565j-integrating-esystems-global-information-systems-spring-2002/57599d12f997dc9b58d783ce08d5353b_lecture09.pdf
(E.G., LIBRARY) 5. SESSION: PROCESS-TO-PROCESS (E.G., OS SOFTWARE) 4. TRANSPORT: HOST-TO-HOST (E.G., OS SOFTWARE) 3. NETWORK: ROUTING (E.G., DEVICE DRIVER) 2. DATA: RELIABLE BIT STREAM (E.G., SPECIAL CHIP) 1. PHYSICAL: RAW BIT STREAM (E.G., HARDWARE) 7 6 5 4 3 2 1 APPLICATION LAYER PROTOCOL PRESENTATION L...
https://ocw.mit.edu/courses/15-565j-integrating-esystems-global-information-systems-spring-2002/57599d12f997dc9b58d783ce08d5353b_lecture09.pdf
MULTIPLE ACCESS/COLLISION DETECT) – SATELLITE • 5-10 CHANNELS, EACH 50M bps • UP-LINK & DOWN-LINK = 270 MILLISECONDS • VSAT – FIBER-OPTIC • 100M - 10G bps (Typical) • INTERNET II (622M -> 2G) • PROJECT OXYGEN = 1.28T bps (before 2003) 8 2. DATA LINK LAYER FOCUS: RELIABLE TRANSMISSION: ERROR HANDLING & FLOW ...
https://ocw.mit.edu/courses/15-565j-integrating-esystems-global-information-systems-spring-2002/57599d12f997dc9b58d783ce08d5353b_lecture09.pdf
• SIMILAR FOR SHARED LAN (E.G., ETHERNET) • IEEE 802 STANDARDS – MEDIA ACCESS: CSMA/CD AND TOKEN RING HAWAII TOKYO 11 3. NETWORK LAYER ROUTE DETERMINATION (TO BE DISCUSSED MORE LATER) VIRTUAL CIRCUIT • • vs DATAGRAM • E.G., X.25 NETWORK CCITT 3-LAYER PROTOCOL • -- VIRTUAL CIRCUIT ORIGINALLY • PROCEDURE ...
https://ocw.mit.edu/courses/15-565j-integrating-esystems-global-information-systems-spring-2002/57599d12f997dc9b58d783ce08d5353b_lecture09.pdf
AVINGS (LIKE SOFTWARE MULTIPLEXING) -- TO USE MULTIPLE “VIRTUAL CIRCUITS” • FOR INCREASED TRANSMISSION CAPACITY 14 5. SESSION LAYER • PROVIDE PROCESS-TO-PROCESS COMMUNICATION (E.G., WEB BROWSER VS. FILE TRANSFER VS. E-MAIL -- SIMULTANEOUS) 6. PRESENTATION LAYER • TYPICAL ACTIVITIES -- -- TEXT COMPRESSION & EN...
https://ocw.mit.edu/courses/15-565j-integrating-esystems-global-information-systems-spring-2002/57599d12f997dc9b58d783ce08d5353b_lecture09.pdf
Lecture 8 8.321 Quantum Theory I, Fall 2017 40 Lecture 8 (Oct. 2, 2017) 8.1 General Time Dependent Hamiltonians The Schr¨odinger equation dictates that quantum states evolve in time according to i(cid:126) d d t | (t)(cid:105) = H(t)|ψ(t) ψ (cid:105) . (8.1) In the last class, we saw that if the Hamiltonian is independ...
https://ocw.mit.edu/courses/8-321-quantum-theory-i-fall-2017/579cb61c4eaa494b9adb90830d921099_MIT8_321F17_lec8.pdf
.6) (8.7) 2. If [H(t), H(t(cid:48))] = 0 for all t, t(cid:48), then we can simultaneously diagonalize the Hamiltonian at all times, meaning we can choose a basis of states that are eigenstates of H(t) for all time (the associated eigenvalues may change as a function of time). We then have (cid:18) U (t, t0) = exp − ˆ t...
https://ocw.mit.edu/courses/8-321-quantum-theory-i-fall-2017/579cb61c4eaa494b9adb90830d921099_MIT8_321F17_lec8.pdf
2 . (cid:0) i (cid:126) If we are ignoring terms of order (∆t)2, then we can write U (t i+1 , t ) ≈ e−iH(ti)∆t/(cid:126) i . We then build up the finite time-evolution operator as (8.11) (8.12) U (t, t0) = U (t, tN −1)U (tN 1, tN 2) · · · U (ti+1, ti) · · · U (t1, t0) = − − N −1 (cid:89) i=0 U (ti+1, ti) . (8.13) Note t...
https://ocw.mit.edu/courses/8-321-quantum-theory-i-fall-2017/579cb61c4eaa494b9adb90830d921099_MIT8_321F17_lec8.pdf
arding commutation rules when moving the operators around). What guarantees that this limit is well-defined and exists? This is guaranteed because the operator U (t, t0) is well-defined, and can be written as a composition of infinitesimal time evolution operators for any partition of the time interval [t0, t]. An alterna...
https://ocw.mit.edu/courses/8-321-quantum-theory-i-fall-2017/579cb61c4eaa494b9adb90830d921099_MIT8_321F17_lec8.pdf
(cid:48) t0 i (cid:126) (cid:0) (cid:1) (cid:0) dt(cid:48)(cid:48) H t(cid:48)(cid:48) U t(cid:48)(cid:48), t (cid:1) 0 , (8.18) (cid:48) We can carry this process out an infinite where the integrand is evaluated at values t(cid:48)(cid:48) ≤ t . number of times and compose the results to give (cid:19)2 ˆ ˆ (cid:18) t t...
https://ocw.mit.edu/courses/8-321-quantum-theory-i-fall-2017/579cb61c4eaa494b9adb90830d921099_MIT8_321F17_lec8.pdf
)(cid:48)(cid:1)(cid:3) . (8.20) The factor of 1 here deals with overcounting. If we rewrite each term in Eq. (8.19) in a similar way, there will be a factor of 1 on the nth term to deal with overcounting. We then have 2 n! ˆ t i U (t, t0) = 1 − (cid:126) 1 n! + dt1 H(t1) + · · · ˆ ˆ (cid:19) n t t0 (cid:18) − i (cid:1...
https://ocw.mit.edu/courses/8-321-quantum-theory-i-fall-2017/579cb61c4eaa494b9adb90830d921099_MIT8_321F17_lec8.pdf
I(t)(cid:105) = U −1 0 (t)|ψS(t)(cid:105) , (8.24) with U0(t) the time-evolution operator generated by H0. Contrast this with the expression in the Heisenberg picture, where the states were defined as The state |ψI(t)(cid:105) evolves in time according to |ψH(t)(cid:105) = U −1(t)|ψS(t)(cid:105) , i(cid:126) d t d |ψI(t...
https://ocw.mit.edu/courses/8-321-quantum-theory-i-fall-2017/579cb61c4eaa494b9adb90830d921099_MIT8_321F17_lec8.pdf
= i(cid:126) (cid:18) dU0 dt UI + U0 (cid:19) . dUI dt Using Eq. (8.31) on the first term of the right-hand side yields i(cid:126) d dt U (t) = H0U0UI + i(cid:126)U0 dUI dt = H0U + i(cid:126)U0 dUI . dt On the other hand, from Eq. (8.30), we have Thus, which gives us i(cid:126) U (t) = H0U + V U . d dt i(cid:126) U0 dU ...
https://ocw.mit.edu/courses/8-321-quantum-theory-i-fall-2017/579cb61c4eaa494b9adb90830d921099_MIT8_321F17_lec8.pdf
(cid:0)(cid:1)(cid:2)(cid:3)(cid:4)(cid:5) Last modi(cid:0)ed(cid:1) September (cid:2)(cid:3)(cid:4) (cid:2)(cid:5)(cid:5)(cid:6) Many(cid:0)body phenomena in condensed matter and atomic physics (cid:0) Lecture (cid:1)(cid:2) Vortices(cid:3) super(cid:4)uidity(cid:2) Trapped gases(cid:2) BEC at (cid:5)nite temperature(...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
ow v elocity (cid:8)h v (cid:4) (cid:4) (cid:6)(cid:19)(cid:7) m r The (cid:18)ow is irrotational(cid:1) (cid:4) (cid:15) (cid:6)this is true away from singularities in (cid:4)(cid:7)(cid:1) and v r (cid:1) (cid:1) (cid:1) (cid:1) h (cid:8) m(cid:2) (cid:4) (cid:5) (cid:20) (cid:10) m (cid:6)(cid:9) (cid:3) (cid:5) (ci...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
(cid:2) It follows from the relation b e t ween the velocity and the phase(cid:1) Eq(cid:2) (cid:6)(cid:19)(cid:7)(cid:1) that the circulation around any contour C obeys (cid:22) (cid:4) d (cid:4) (cid:9)(cid:7) l (cid:6)(cid:23)(cid:7) v r (cid:8)h C (cid:2) m I with some integer l(cid:2) We see that The circulation i...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
8)(cid:6) (cid:7) (cid:1) Doppler(cid:0)shifted due to the (cid:18)ow(cid:1) should b e positive(cid:1) to prevent massive k v k (cid:0) (cid:2) production of quasiparticles(cid:2) This criterion de(cid:3)nes a critical velocity v (cid:4) min (cid:8)(cid:6) (cid:7)(cid:6) (cid:6)(cid:26)(cid:7) k k c k j j above which ...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
are concentric circles parallel to the (cid:6)x(cid:3) y (cid:7) plane(cid:2) Constant circulation requires that the velocity falls inversely with the distance (cid:9) from the z axis(cid:25) (cid:8)hl (cid:4) (cid:5) v r (cid:6) (cid:7) (cid:4) (cid:6)(cid:11)(cid:15)(cid:7) m (cid:9)(cid:7)(cid:9) where (cid:4) is th...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
The so(cid:0)called healing length (cid:11) determines the size of the vortes core where density is depleted b e l o w its bulk value(cid:2) This qualitative picture can be con(cid:3)rmed by an analysis based on the Gross(cid:0)Pitaevskii equation(cid:2) One can look for a solution of the equation that describes a vort...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
cid:8)(cid:7)(cid:1) which gives r (cid:4) (cid:9)(cid:11) (cid:1) in agreement with the estimate (cid:4) above(cid:2) H Let us consider The energy of the vortex(cid:1) that can be estimated as the kinetic energy of the (cid:18)ow(cid:1) is positive(cid:2) Thus vortices do not appear unless the system is driven(cid:1) ...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
)(cid:9)(cid:7) the density can b e approximated by a constant for (cid:9) (cid:10) (cid:11) (cid:1) while the depletion of density in the vortex core(cid:1) at (cid:9) (cid:11) (cid:1) cuts the log divergence at small (cid:9)(cid:2)(cid:7) the contribution to the energy due to the core(cid:1) which can b e estimated u...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
omes energetically favorable at Z Z Z (cid:1) (cid:4) (cid:4) (cid:6)(cid:3)(cid:7) (cid:8)h b (cid:27) (cid:10) (cid:27) (cid:4) E (cid:6)M (cid:4) ln (cid:6)(cid:11)(cid:17)(cid:7) c v v (cid:1) mb (cid:11) (cid:0) (cid:1) Note the inverse square dependence of (cid:27) on the radius b(cid:1) which means that it is ea...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
1) d (cid:4) (cid:27) (cid:7)b (cid:1) which gives a linear dependence v r (cid:2) m H (cid:1) N (cid:6)(cid:27)(cid:7) (cid:7)b (cid:27) (cid:6)(cid:11)(cid:19)(cid:7) (cid:9) (cid:8)h (cid:14) ...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
gasses di(cid:28)ers somewhat from BEC in a uniform system that we discussed so far(cid:2) Most importantly(cid:1) t h e BEC transition is accompanied by an abrupt change of density distribution(cid:2) This is due to the fact that the lowest energy quantum state in which atoms condense is p e a k ed at the trap center ...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
that the density of this state(cid:1) at the peak(cid:1) (cid:4) n N (cid:6)l (cid:1) can b e extremely high when the numb e r of atoms is large(cid:2) In the presence of (cid:5) (cid:2) (cid:9) interactions(cid:1) on can easily reach the limit when the interaction energy per particle is much larger than the level spac...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
7) (cid:0)(cid:6)x(cid:7) (cid:10) (cid:1) (cid:0)(cid:6)x(cid:7) dx (cid:6)(cid:11)(cid:21)(cid:7) (cid:1) h (cid:8) (cid:11) (cid:1) (cid:1) (cid:8) (cid:0) (cid:9)m jr j (cid:0) j j j j (cid:1) (cid:9) Z with the particle numb e r N (cid:4) (cid:0) dx being (cid:3)xed by a c hemical potential (cid:5)(cid:2) (cid:1) ...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
6)(cid:1)N(cid:6)m(cid:13) (cid:7) (cid:2) At large (cid:9) (cid:3)(cid:3)(cid:9) (cid:1) 2 2 (cid:9) ; h (cid:2) m(cid:2) (cid:1) (cid:1) N N (cid:1) the value R is much larger than l that satis(cid:3)es l (cid:4) l (cid:2) Hence the c (cid:2) (cid:1)m (cid:1) (cid:2) (cid:2) (cid:10) 2 2 (cid:2)h m(cid:2) (cid:1) (c...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
each small part of the BEC cloud as a uniform system(cid:2) For the latter(cid:1) as we already know(cid:1) (cid:16) ...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
) compensates the potential U (cid:6)x(cid:7) variation in space(cid:1) which gives n(cid:6)x(cid:7) (cid:4) (cid:6)(cid:11)(cid:26)(cid:7) (cid:0) (cid:6)(cid:5) U (cid:6)x(cid:7)(cid:7) (cid:6)(cid:1) (cid:3) U (cid:15) (cid:5) (cid:15) (cid:3) U (cid:10) (cid:5) (cid:4) We note that the argument used to (cid:3)nd th...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
for typical density n (cid:4) N(cid:6) R (cid:1) which determines the scale of spatial nonlo(cid:0) (cid:5) (cid:10) (cid:8) (cid:4) (cid:5) cality in BEC correlations(cid:2) This means that the Thomas(cid:0)Fermi approximation is indeed a local density approximation(cid:2) The above discussion summarizes the situation...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
scattering (cid:1) (cid:0) (cid:0) int k k 4 3 k k (cid:4) a a a 2 a 1 (cid:6)(cid:9)(cid:14)(cid:7) H (cid:9) 1 2 3 4 k (cid:0)k (cid:10)k (cid:0)k X (cid:17) ...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
(cid:6)(cid:11) (cid:10) f (cid:7)(cid:6)(cid:11) (cid:10) f (cid:7)(cid:16) (cid:6)(cid:8) (cid:10) (cid:8) (cid:8) (cid:8) (cid:7) (cid:6)(cid:9)(cid:17)(cid:7) ij(cid:5)mn i j m n i j m n df (cid:9)(cid:7) i (cid:1) dt h(cid:8) (cid:0) j j (cid:0) (cid:0) ij(cid:5)mn X while the rate of scattering in i is j i df (ci...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
T (cid:6)m (cid:7) T Despite scattering(cid:1) quasiparticles are well de(cid:3)ned(cid:25) (cid:8)(cid:6) (cid:7) k (cid:3) (cid:8) q (cid:3) (cid:10) In the BEC state(cid:1) scattering is by the presence of the condensate(cid:25) stimulated (cid:0) (cid:0) p a (cid:3) a a (cid:3) a (cid:4) N (cid:6)(cid:9)(cid:23)(ci...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
6)(cid:9)(cid:7)(cid:8) h(cid:7) j (cid:0) j (cid:0) At small velocities(cid:1) have (cid:1) (cid:5) (cid:1) (cid:9) (cid:8) (cid:5) p d p (cid:6)(cid:9)(cid:7) (cid:6)(cid:16)(cid:17)(cid:8) c h (cid:7)T T T (cid:9) (cid:9) (cid:4) (cid:6) (cid:2) f (cid:6)(cid:2) (cid:8) (cid:7) (cid:4) p p n (cid:5) (cid:5)(cid:3)(c...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
discuss the two(cid:0)(cid:18)uid hydrodynamics in full generality(cid:2) Instead(cid:1) we describe a particular phenomenon(cid:1) the II sound(cid:1) a collective mode that appears in the two(cid:0)(cid:18)uid regime(cid:2) In this mode(cid:1) the relative fraction of the normal and super(cid:18)uid component oscilla...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
For super(cid:18)uid velocity(cid:1) o n e can write m(cid:2) (cid:4) (cid:5) (cid:6)(cid:14)(cid:17)(cid:7) v t s (cid:0)r This relation(cid:1) derived above from the Gross(cid:0)Pitaevskii equation(cid:1) is in fact very general(cid:1) and is true for any super(cid:18)uid(cid:2) It follows from the relation between t...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
9)C (cid:2)(cid:9) (cid:2)T n T (cid:10) (cid:20) (cid:20) The constants c and c are the isothermal sound velocity and the velocity of temperature (cid:3) (cid:1) waves at constant density(cid:1) while C (cid:4) T (cid:6)(cid:2)(cid:18)(cid:6)(cid:2)T (cid:7) is the speci(cid:3)c heat at constant v olume(cid:1) (cid:10...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
10) c (cid:10) c (cid:6)c (cid:10) c (cid:10) c (cid:7) (cid:16)c c (cid:6)(cid:16)(cid:19)(cid:7) I(cid:5) II (cid:3) (cid:1) (cid:5) (cid:3) (cid:1) (cid:5) (cid:3) (cid:1) (cid:9) (cid:11) (cid:9) (cid:0) (cid:2) (cid:3) q So far(cid:1) the treatment w as completely general(cid:1) applicable to any Bose system(cid:1...
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
(cid:31)detect it people had to use oscillatory thermal sources and heat sensors(cid:2) (cid:26)
https://ocw.mit.edu/courses/8-514-strongly-correlated-systems-in-condensed-matter-physics-fall-2003/57fb8bd5b6d291ec7eda1bc1c920a403_lec6.pdf
18.409 An Algorithmist’s Toolkit October 6, 2009 Lecturer: Jonathan Kelner Scribe: Alessandro Chiesa (2009) Lecture 8 1 Administrivia You should probably know that • the first problem set (due October 15) is posted on the class website, and • its hints are also posted there. Also, today in class there was a maj...
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
subset of vertices that defines a cut with low conductance. However, we want the running time of our algorithm to depend on the cluster size, and not on the size of the graph. Last time we mentioned that a good example of a problem of this sort is trying to find a cluster of web pages around mit.edu; we surely do not ...
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
2.3 Obstacles We need a bound that says that our general strategy works, and that is why we proved the Lov´asz-Simonovits theorem. However, the bound we have is global, i.e., it involves the conductance φ(G) and we do not have the time to compute λ2 for the whole graph to bound the conductance. Moreover, if we exact...
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
x, 2m − x � 1 1 − φ(W )2 2 �t . Note that in the last lecture we stated a slightly weaker form of the theorem, where the conductance ϕ(W ) of the cut (W, W ) was replaced by the conductance φ(G) of the whole graph. Nevertheless, we did actually prove the stronger version stated above. The bound above has noth...
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
of conductance φ, otherwise the random walk would mix too quickly.) 8-2 3 PageRank 3.1 Definition Consider an undirected1 connected graph G = (V, E). Recall that a simple random walk on G is a walk that, starting at some initial vertex, at each step moves from the current vertex to a randomly chosen neighbor of ...
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
α(s) is the unique solution to the following equation: prα(s) = αs + (1 − α)W prα(s) , (1) where W is the transition matrix corresponding to a lazy random walk on G. The point is that one can show that the Lov´asz-Simonovits theorem and its corollary hold for the PageRank vector prα(s), where s corresponds to the...
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
dominant2 because the off-diagonal elements in each column add up to 1/2, while each diagonal element is 1 − (1 − α)(1/2). By the Gershgorin circle theorem [2], it must be nonsingular, so that the equation has a unique solution. Proposition 2 allows us to extend the definition of PageRank: given any vector s ∈ Rn , no...
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
≡ prα(W s) satisfies the following equation Let us verify that x(cid:3) ≡ W prα(s) satisfies the same equation: x = α(cv + dw) + (1 − α)W x . α(cv + dw) + (1 − α)W x(cid:3) = αW s + (1 − α)W 2 prα(s) = W (αs + (1 − α)W prα(s)) = W prα(s) (cid:3) = x . By Proposition 2, the equation has a unique solution, so that ...
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
Given a fixed (cid:9) > 0, we keep iterating as long as there exists some vertex u such that r(u) ≥ (cid:9)d(u). First, we prove that each iteration of the algorithm preserves the invariant p = prα(s − r). Proposition 5 p(cid:3) = prα(s − r(cid:3)). 8-4 Proof By Proposition 3, it suffices to show that p(cid:3) + prα...
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
procedure works. Theorem 7 Fix (cid:9) > 0. Suppose that in each iteration we pick a vertex u with the property that r(u) ≥ (cid:9)d(u). � � Then the process terminates in O 1 (cid:4)α iterations with vectors p and r that satisfy the following properties: v r( 1. maxv d v ( ) ) ≤ (cid:9). 2. vol(supp(p)) ≤ 1 , ...
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
note that every vertex in supp(p) must have been picked at least once during the execution of the algorithm, so that � T i =1 i=1 (cid:4)α thus showing (2), and completing the proof of the theorem. i=1 vol(supp(p)) ≤ di ≤ T � 1 (cid:9)α , The theorem we just proved gives the approximation to the PageRank v...
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
total running time is almost linear because the running time on each chunk is almost linear in its volume. In a random walk scheme, we need to take 1/φ steps in order to get a cut of conductance Caveat. √ 1/ φ; hence, that takes time that is about (size of chunk) · poly(1√/φ). Similarly, in a PageRank scheme, we ...
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
out a lot of edges from G and still get an approximate answer, because the running time of the algorithm for the resulting graph will be close to that for a sparse graph. More precisely, is there any way to “approximate” our graph G with a sparse graph G(cid:3) that has the property that all of its cuts have more or...
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
our Terms of Use, visit: http://ocw.mit.edu/terms.
https://ocw.mit.edu/courses/18-409-topics-in-theoretical-computer-science-an-algorithmists-toolkit-fall-2009/5823d396bfe2ae2c5bea9c431601276e_MIT18_409F09_scribe8.pdf
MIT 2.852 Manufacturing Systems Analysis Lecture 14-16 Line Optimization Stanley B. Gershwin Spring, 2007 Copyright c�2007 Stanley B. Gershwin. Line Design • Given a process, find the best set of machines and buffers on which it can be implemented. • Best: least capital cost; least operating cost; least average ...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
(ie, required accuracy). • Reducing computation time per iteration is accomplished by � using analytical models rather than simulations � using coarser approximations in early iterations and more accurate evaluations later. Copyright c �2007 Stanley B. Gershwin. 5 Problem Statement X is a set of possible choices. ...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
Copyright c �2007 Stanley B. Gershwin. 9 Continuous Variables and Objective Assume f (t) is decreasing. • Binary search: Guess t0 and t1 such that f (t0) > 0 and f (t1) < 0. Let t2 = (t0 + t1)/2. � If f (t2) < 0, then repeat � 1 = t2. with t = t0 and t � 0 � If f (t2) > 0, then repeat = t1. t2 and t � w...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
99237060547 2.00000381469727 1.99999809265137 2.00000095367432 t1 3 3 2.25 2.25 2.0625 2.0625 2.015625 2.015625 2.00390625 2.00390625 2.0009765625 2.0009765625 2.000244140625 2.000244140625 2.00006103515625 2.00006103515625 2.00001525878906 2.00001525878906 2.00000381469727 2.00000381469727 Copyright �2007 Stanley B...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
f(t1 ) Unconstrained One-dimensional search f(t) t0 t2 t1 t � Repeat with t� 0 = t1 and t� = t2 until |f (t� )| is small 1 enough. 0 Copyright �2007 Stanley B. Gershwin. c 14 Continuous Variables and Objective Unconstrained One-dimensional search Example: f (t) = 4 − t2 t0 0 3 1.33333333333333 ...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
Constrained Constrained Optimum Equality constrained: solution is on the constraint surface. x2 h(x , x ) = 0 1 2 x1 Problems are much easier when constraint is linear, ie, when the surface is a plane. • In that case, replace �J/�x by its projection onto the constraint plane. • But first: find an initial ...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
+ y) − (x4 + y4)/4 subject to x − (x − y)2 + 1 ≈ 0 −6 −4 −2 0 2 4 6 −2 0 2 4 6 Solving a nonlinearly-constrained problem is not so easy. Searching within the boundary is numerically difficult. Copyright �2007 Stanley B. Gershwin. c 21 Continuous Nonlinear and Linear Programming Variables and Objecti...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
g(x) � 0 f (x) � F Copyright �2007 Stanley B. Gershwin. c 25 Buffer Space Allocation Problem statement M 1 B 1 M 2 B 2 M 3 B 3 M 4 B 4 M 5 B 5 M6 Problem: Design the buffer space for a line. The machines have already been selected. Minimize the total buffer space needed to achieve a target pr...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
appears to be a concave function of the vector (N1, ..., Nk−1). Copyright �2007 Stanley B. Gershwin. c 28 Buffer Space Allocation Properties of P (N1, ..., Nk−1) Example — 3-machine line P 0.91 0.9 0.89 0.88 0.87 0.86 0.85 0.84 0.83 10 20 30 40 50 60 N1 70 80 90 100 30 20 10 Optimal curve P=0.8800 ...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
many iterations. It would be desirable to transform this problem into one with linear constraints. Copyright �2007 Stanley B. Gershwin. c 30 Buffer Space Allocation Solution Dual problem Maximize P (N1, ..., Nk−1) subject to k−1 � i=1 Ni � N TOTAL specified Ni � N MIN, i = 1, ..., k − 1. All the constrain...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
N, . . . , Nk−1) − P (N1, . . . , Ni, . . . , Nk−1) �N • Calculate the projected gradient vector (ˆg1, ..., gˆk−1): gˆi = gi − g¯ where g¯ = 1 k − 1 k−1 � i=1 gi Copyright �2007 Stanley B. Gershwin. c 34 Buffer Space Allocation Solution Dual Algorithm • The projected gradient gˆ satisfies k−1 k−1 k−1...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
point N on the constraint plane, the best improvement is to move in the direction of gˆ; that is, N + Agˆ. • To find the best possible improvement, we find A�, the value of A that maximizes P (N + Agˆ). A is a scalar, so this is a one-dimensional search. • N + A�gˆ is the next guess for N , and the process repeats....
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
imal algorithm e t a r n o i t c u d o r p e g a r e v a m u m x a M i 0.92 0.9 0.88 0.86 0.84 0.82 0.8 0.78 0 50 100 Total buffer space 150 200 P MAX(N TOTAL) as a function of N TOTAL. Copyright �2007 Stanley B. Gershwin. c 40 Buffer Space Allocation Solution Primal algorithm Then, we can...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
i = 1, ..., 19 50 40 30 20 10 l e v e l r e f f u b e g a r e v A 0 0 2 4 6 8 10 Buffer 12 14 16 18 20 Copyright �2007 Stanley B. Gershwin. c 43 Buffer Space Allocation Example The “Bowl Phenomena” • This shows the optimal distribution of buffer space and the resulting distribution of av...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
a R 0 0 5 10 Buffer 15 20 Copyright �2007 Stanley B. Gershwin. c 46 Buffer Space Allocation Example • Design the buffers for a 20-machine production line. • The machines have been selected, and the only decision remaining is the amount of space to allocate for in-process inventory. • The goal ...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
minute). Copyright c �2007 Stanley B. Gershwin. 51 Example Buffer Space Allocation Are buffers really needed? Line Case 1 Case 2 Case 3 Production rate with no buffers, parts per minute .487 .475 .475 Yes. How were these numbers calculated? Copyright c �2007 Stanley B. Gershwin. 52 Example Buffer Space Al...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
0.45 0.4 0.35 e z S i r e f f u B / l e v e l r e f f u b e g a r e v A = o i t a R 0.3 0 5 10 Buffer 15 20 Copyright �2007 Stanley B. Gershwin. c 55 Buffer Space Allocation • Case 4: Same as Case 3 except bottleneck is at Machine 15. • This shows the optimal distribution of buffer space and t...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
c 57 Buffer Space Allocation • Case 5: MTTF bottleneck at Machine 5, MTTR bottleneck at Machine 15. • This shows the optimal distribution of buffer space and the resulting Example distribution of average inventory for Case 5. l e v e l r e f f u b e g a r e v A / e z S i r e f f u B 55 50 45 40 35 ...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
50 45 40 35 30 25 20 15 10 5 0 0 10 20 30 40 50 Buffer Copyright �2007 Stanley B. Gershwin. c 60 Buffer Space Allocation Example • This shows the ratio of average inventory to buffer size with optimal buffers for Case 6. e z S i r e f f u B / l e v e l r e f f u b e g a r e v A = o i t a R...
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
Spring 2010 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms.
https://ocw.mit.edu/courses/2-852-manufacturing-systems-analysis-spring-2010/5843df20ba98a98f34469fc47801c1e6_MIT2_852S10_line_opt.pdf
Lecture 5 8.821/8.871 Holographic duality Fall 2014 8.821/8.871 Holographic duality MIT OpenCourseWare Lecture Notes Hong Liu, Fall 2014 Lecture 5 Reminder from last lecture The vacuum of Minkowski space can be viewed as an entangled state of left Rindler patch and right Rindler patch |0(cid:105)M ∝ (cid:88) n e−πEn |n...
https://ocw.mit.edu/courses/8-821-string-theory-and-holographic-duality-fall-2014/584b62f85f319bd167efb65047336e0c_MIT8_821S15_Lec5.pdf
:105)M = |0(cid:105)M This can also be seen geometrically: η translation is a boost in (X, T ), i.e. HRind generates a boost. |0(cid:105)M is clearly invariant under a boost. Yet boosts act oppositely in the right and left quadrants as indicated in Fig. 1. 2. If we expand φR (φL) in terms of modes in the right (left) q...
https://ocw.mit.edu/courses/8-821-string-theory-and-holographic-duality-fall-2014/584b62f85f319bd167efb65047336e0c_MIT8_821S15_Lec5.pdf
dE = 1 T (E) = 8πGN m (cid:126) since for a black hole E = m ˆ S(E) = dE T (E) = 4πGN E2 (cid:126) + const = 4πr2 s 4(cid:126)GN = AH e(cid:126)GN 2 Lecture 5 8.821/8.871 Holographic duality Fall 2014 The integral constant can be determined to be 0 since S(E) = 0 for E = 0, AH is the area of black hole horizon. So we ...
https://ocw.mit.edu/courses/8-821-string-theory-and-holographic-duality-fall-2014/584b62f85f319bd167efb65047336e0c_MIT8_821S15_Lec5.pdf
of thermodynamics with the identification Eq. 1. In particular the 1st law becomes dE = T dS + ΩdJ + ΦdQ Historically, before Hawking’s discovery of black hole radiation, Bekenstein (1972-1974) has found SBH ∝ AH , the motivation is to save the 2nd law of thermodynamics for a system with black holes. if an ordinary syst...
https://ocw.mit.edu/courses/8-821-string-theory-and-holographic-duality-fall-2014/584b62f85f319bd167efb65047336e0c_MIT8_821S15_Lec5.pdf
Lecture #2: Background READINGS AND FIGURES Readings: Instructor notes on boundary conditions Frisk, Chapter 3, sections 3.1, 3.2 and 3.3 (up to Eq. 3.38.) --------------------------------------------------------- DESCRIPTION OF NOTES Having the basic wave equation for ocean acoustics in hand, we now need to put ...
https://ocw.mit.edu/courses/2-682-acoustical-oceanography-spring-2012/58540cfbbdd42be15697f7a1523f343b_MIT2_682S12_bglec02.pdf
conditions for some calculations. The discussion in this section of notes loosely follows from Clay and Medwin’s “Acoustical Oceanography.” (Reference in separate attachment.) The next small class notes section concerns the “specific acoustic impedance.” In direct analogy to Ohm’s law, E=I*R, the resistance of the a...
https://ocw.mit.edu/courses/2-682-acoustical-oceanography-spring-2012/58540cfbbdd42be15697f7a1523f343b_MIT2_682S12_bglec02.pdf
is “intermediate” to the two above, called a “mixed” or impedance BC. Frisk shows this type in section 3.2.3. This type of BC is actually capable of representing reflection from a complex, fully layered medium, and finds wide use in ocean acoustics. The above three boundary conditions are well known mathematically a...
https://ocw.mit.edu/courses/2-682-acoustical-oceanography-spring-2012/58540cfbbdd42be15697f7a1523f343b_MIT2_682S12_bglec02.pdf
Lecture #1: Background READINGS AND FIGURES Readings: Frisk, Chapter 1, sections 1.3 and 1.4; Chapter 2, sections 2.1, 2.2, 2.3, 2.4. Figures used: COA, Figures 1.1, 1.2, 1.3, 1.5 --------------------------------------------------------- DESCRIPTION OF NOTES The first two pages of the notes are my own answers to ...
https://ocw.mit.edu/courses/2-682-acoustical-oceanography-spring-2012/58aeef5d8bd077782924c431bad2f2db_MIT2_682S12_bglec01.pdf
, scattering theory, and so on. The analogies to quantum mechanical systems are very close in many ways, and many researchers have exploited this. The next few pages are my own descriptions of the first few figures from COA (Figs 1.1, 1.2, 1.3, 1.5. The message in all these figures is that, to quote the old Marshal...
https://ocw.mit.edu/courses/2-682-acoustical-oceanography-spring-2012/58aeef5d8bd077782924c431bad2f2db_MIT2_682S12_bglec01.pdf
in cylindrical coordinates, which just turns out to be the familiar Bessel’s equation. The exact and asymptotic forms of the solution are shown, and a little emphasis made that the spreading law is cylindrical (intensity falls as R, not R^2). 2 MIT OpenCourseWare http://ocw.mit.edu 2.682 Acoustical Oceanogra...
https://ocw.mit.edu/courses/2-682-acoustical-oceanography-spring-2012/58aeef5d8bd077782924c431bad2f2db_MIT2_682S12_bglec01.pdf
MIT 3.016 Fall 2005 c � W.C Carter Lecture 3 16 Sept. 12 2005: Lecture 3: Introduction to Mathematica II Functions and Rules Besides Mathematica r� ’s large set of built­in mathematical and graphics functions, the most powerful aspects of Mathematica r� are its ability to recognize and replace patterns and to ...
https://ocw.mit.edu/courses/3-016-mathematics-for-materials-scientists-and-engineers-fall-2005/58b2b2f2478ab6e14599e1865b1e233e_lecture_03.pdf
of 10, which is probably not what was intended. It is much safer to localize variables—in other words, to limit the scope of their visibility to only those parts of the program that need the variable. Sometimes this is called a “Context” for the variable in a programming language; Mathematica r� has contexts as wel...
https://ocw.mit.edu/courses/3-016-mathematics-for-materials-scientists-and-engineers-fall-2005/58b2b2f2478ab6e14599e1865b1e233e_lecture_03.pdf
5 c � W.C Carter Lecture 3 19 Mathematica r� Example: Lecture­03 Patterns and Replacement The real power of patterns and replacement is obtained when defining your own functions. Mathematica r� Example: Lecture­03 Functions with Patterns It is probably a good idea to define all function with delayed assignment (:...
https://ocw.mit.edu/courses/3-016-mathematics-for-materials-scientists-and-engineers-fall-2005/58b2b2f2478ab6e14599e1865b1e233e_lecture_03.pdf
fined so that they can be reused, either by you or someone else. The conditions for which the function can work should probably be encoded into the function. In Mathematica r� this can be done with restricted patterns: Mathematica r� Example: Lecture­03 Functions with Restricted Patterns
https://ocw.mit.edu/courses/3-016-mathematics-for-materials-scientists-and-engineers-fall-2005/58b2b2f2478ab6e14599e1865b1e233e_lecture_03.pdf
6.720J/3.43J - Integrated Microelectronic Devices - Spring 2007 Lecture 5-1 Lecture 5 - Carrier generation and recombination (cont.) February 14, 2007 Contents: 1. G&R rates outside thermal equilibrium (cont.) 2. Dynamics of excess carriers in uniform situations 3. Surface generation and recombination Reading assig...
https://ocw.mit.edu/courses/6-720j-integrated-microelectronic-devices-spring-2007/58cdd6312da243d9062e56ceee80f955_lecture5.pdf
Et Ev n>no ro,ec>ro,ee ro,hc>ro,he p>po thermal equilibrium with excess carriers Out of equilibrium, if rate constants are not affected: rec = cen(Nt − nt) ree = eent = cenint rhc = chpnt rhe = eh(Nt − nt) = chni(Nt − nt) Recombination: capture of one electron + one hole ⇒ net recombination rate = net elect...
https://ocw.mit.edu/courses/6-720j-integrated-microelectronic-devices-spring-2007/58cdd6312da243d9062e56ceee80f955_lecture5.pdf
n-type: - for p-type: po (cid:4) n (cid:3) (cid:5) p (cid:3) (cid:4) no no (cid:4) n (cid:3) (cid:5) p (cid:3) (cid:4) po Cite as: Jesús del Alamo, course materials for 6.720J Integrated Microelectronic Devices, Spring 2007. MIT OpenCourseWare (http://ocw.mit.edu/), Massachusetts Institute of Technology. Downloade...
https://ocw.mit.edu/courses/6-720j-integrated-microelectronic-devices-spring-2007/58cdd6312da243d9062e56ceee80f955_lecture5.pdf
(cid:3) n τ 1 τ = Σ 1 τi The G&R process with the smallest lifetime dominates. Physical meaning of carrier lifetime: • U is net recombination rate in unit volume in response to excess carrier concentration n(cid:3) (linear in n(cid:3)) [cm−3 · s−1] • n U (cid:3) is net recombination rate in unit volume per u...
https://ocw.mit.edu/courses/6-720j-integrated-microelectronic-devices-spring-2007/58cdd6312da243d9062e56ceee80f955_lecture5.pdf
∝ Nt Schroder, D. K. "Carrier Lifetimes in Silicon." IEEE Transactions on Electron Devices 44, no. 1 (1997): 160-170. Copyright 1997 IEEE. Used with permission. Cite as: Jesús del Alamo, course materials for 6.720J Integrated Microelectronic Devices, Spring 2007. MIT OpenCourseWare (http://ocw.mit.edu/), Massachusett...
https://ocw.mit.edu/courses/6-720j-integrated-microelectronic-devices-spring-2007/58cdd6312da243d9062e56ceee80f955_lecture5.pdf
1E+19 1E+20 1E+21 donor concentration (cm-3) acceptor concentration (cm-3) For low doping levels, NA,D < 1017 cm−3 , τtr dominates: • τ depends on material quality and process → wide data scatter • Nt correlated with NA,D → τ ∝ N −1 A,D For high doping levels, NA,D > 1018 cm−3 , τAuger dominates: • ”intrinsic” ...
https://ocw.mit.edu/courses/6-720j-integrated-microelectronic-devices-spring-2007/58cdd6312da243d9062e56ceee80f955_lecture5.pdf
combination, carrier concentrations change in time: dn dt = dp dt = G − R • if G > R ⇒ n, p ↑ • if G < R ⇒ n, p ↓ Distinguish between internal and external generation: G = Gext + Gint Cite as: Jesús del Alamo, course materials for 6.720J Integrated Microelectronic Devices, Spring 2007. MIT OpenCourseWare (htt...
https://ocw.mit.edu/courses/6-720j-integrated-microelectronic-devices-spring-2007/58cdd6312da243d9062e56ceee80f955_lecture5.pdf
few τ ’s) In steady state: or Then generation = recombination gl = (cid:3) n τ n (cid:3) = glτ Cite as: Jesús del Alamo, course materials for 6.720J Integrated Microelectronic Devices, Spring 2007. MIT OpenCourseWare (http://ocw.mit.edu/), Massachusetts Institute of Technology. Downloaded on [DD Month YYYY]. ...
https://ocw.mit.edu/courses/6-720j-integrated-microelectronic-devices-spring-2007/58cdd6312da243d9062e56ceee80f955_lecture5.pdf
amo, course materials for 6.720J Integrated Microelectronic Devices, Spring 2007. MIT OpenCourseWare (http://ocw.mit.edu/), Massachusetts Institute of Technology. Downloaded on [DD Month YYYY]. 6.720J/3.43J - Integrated Microelectronic Devices - Spring 2007 Lecture 5-17 Two extreme cases: n'(t) glT τ1>>T τ2 >>...
https://ocw.mit.edu/courses/6-720j-integrated-microelectronic-devices-spring-2007/58cdd6312da243d9062e56ceee80f955_lecture5.pdf