Part II Statistical Mechanics, Lent 2005

Size: px
Start display at page:

Download "Part II Statistical Mechanics, Lent 2005"

Transcription

1 Part II Statstcal Mechancs, Lent 25 Prof. R.R. Horgan February 14, 25 1 Statstcal Mechancs 1.1 Introducton The classcal and quantum dynamcs of smple systems wth few degrees of freedom s well understood n that we know the equatons of moton whch govern ther tme evoluton and, n most cases, we can solve these equatons exactly or, n any case, to the requred degree of accuracy. Even systems wth many degrees of freedom can be analyzed, for example, many problems n electromagnetc theory, where the feld degrees of freedom are large, can be solved usng Maxwell s equatons. However, t remans that there are physcal systems, whch are typfed by possessng a large number of degrees of freedom, for whch analyss of ths knd n napproprate or, n practce, mpossble, Whlst these systems are made up of dentfable consttuents whose nteractons are well known, dfferent concepts are needed to descrbe the evoluton of the system and the way t nteracts wth an observer. In partcular, the concepts of heat, temperature, pressure, entropy, etc. must arse from a proper analyss they are certanly not evdent n the equatons of moton, even though knowledge of the equatons of moton s ndspensable. These are deas whch come from a noton of statstcal averagng over the detaled propertes of the system. Ths s because they only make sense when thought of as propertes whch apply on the large scales typcal of the observer, rather than the mcroscopc scales of the ndvdual consttuents. Statstcal mechancs was developed to address ths conceptual problem. It enables one to answer questons lke how do you calculate the physcal propertes of a system n thermal contact wth large reservor of heat (known as a heat bath) at temperature T? Statstcal mechancs deals wth macroscopc systems wth very many degrees of freedom. For example, a gas wth a large number of partcles or a complex quantum system wth a large number of quantum states. A thermally solated or closed system s one whose boundary nether lets heat n or out. Consder such a system, S, that s not subject to any external forces. No matter how t s prepared, t s an expermental fact that after suffcent tme S reaches a steady state n that t can be specfed by a set, Σ, of tme-ndependent macroscopc or thermodynamc, varables whch usefully descrbe all the large-scale propertes of the system for all practcal purposes. The system s then sad to be n a state of thermal equlbrum specfed By macroscopc we mean that the system s large on the scale of the typcal lengths assocated wth the mcroscopc descrpton, such as the nter-atomc spacng n a sold or mean partcle separaton n a gas. That beng sad, t can be the case that systems wth as few as a hundred partcles can be successfully descrbed by statstcal mechancs. 1

2 1 STATISTICAL MECHANICS 2 by Σ. For example, for a gas solated n ths manner, Σ ncludes the pressure P, volume, temperature T, energy E, and entropy S. Although the state of thermal equlbrum descrbed by Σ s unque and tmendependent n ths sense, the ndvdual degrees of freedom such as partcle postons and momenta are changng wth tme. It s certanly not practcal to know the detals of how each degree of freedom behaves, and t s a basc tenet of statstcal mechancs that t s not necessary to know them n order to fully specfy the equlbrum state: they are not of any practcal mportance to calculatng the accessble expermental propertes of the equlbrum system. The task of statstcal mechancs s to use averagng technques and statstcal methods to predct the varables Σ characterzng the equlbrum state. We are generally able to descrbe the dynamcs of such systems at the mcroscopc level. For nstance, we can specfy the nteracton between neghbourng atoms n a crystal or between pars of partcles n a gas. Ths descrpton arses ultmately from our knowledge of quantum mechancs (and relatvty), but t may also be legtmate and useful to rely on classcal mechancs whch we vew as dervable from quantum mechancs by the correspondence prncple. We shall develop the deas of statstcal mechancs usng quantum mechancs n what follows. We defne (a) The mcroscopc states of S are the statonary quantum states. Ths s the Drac bra ( ) and ket ( ) notaton for states. The label stands mplctly for the complete set of quantum numbers whch specfy the state unquely. For example, H = E. The matrx element of an operator X between states and j s X j whch, n wave-functon notaton, s the same as dx φ Xφ j. Then X s the expectaton value, X, of X. (b) The macroscopc states of S are the possble states of thermodynamc equlbrum and are descrbed by the correspondng set of thermodynamc varables, Σ. These are not states n the quantum mechancal sense but nvolve a vast number of mcrostates. An mportant dea s the ergodc hypothess (whch has only been proved for a few systems ) whch states that: A system S evolves n tme through all accessble mcrostates compatble wth ts state of thermodynamc equlbrum. Ths means that tme averages for a sngle system S can be replaced by averages at a fxed tme over a sutable ensemble E of systems, each member dentcal to S n ts macroscopc propertes. An mportant feature s that the ensemble, E, can be realzed n dfferent ways whlst gvng the same results for the thermodynamc propertes of the orgnal system. The major realzatons of E are: the mcrocanoncal ensemble: each member of E has the same value of E and N. Ths s approprate to an solated system for whch the energy s fxed. There are many examples n one dmenson where the ergodc hypothess does not hold. Ths s a current research area

3 1 STATISTICAL MECHANICS 3 the canoncal ensemble: each member of E has N partcles but E s not fxed but the average energy over E s fxed. Ths s approprate to a system of a fxed number of partcles but whch s n thermal contact wth a heat bath wth whch t can exchange energy. The heat bath s all the other systems of the ensemble. the grand canoncal ensemble: nether E nor N s fxed for each member but the ensemble averaged values are fxed. Ths descrbes a system n thermal contact wth a heat bath wth whch partcles can also be exchanged. Members of the last two ensembles represent the orgnal system n the average. The reason why they all gve the same thermal physcs s that the fluctuatons of E and N about ther average values are very small because the number of partcles nvolved s very large. For example, consder the probablty p m of obtanng N/2 + m heads from N con tosses: ( ) p m = 2 N N 2 /N N/2 + m πn e 2m2, usng Strlng s formula (log n! = n log n n log 2πn) for N m 1. We see that only for m N s p m apprecable n sze. Hence the mean fluctuaton, m/n 1/ N, s very small. The densty of a volume of gas, ρ = N/, s a macroscopc quantty on whch thermodynamc varables depend. If the fluctuatons n N are O( N) then δρ ρ, whch vanshes as. Hence, we expect the results from the dfferent ensembles to be the same n the nfnte volume lmt but to dffer by correctons of O(1/ ). The large volume lmt s always assumed n what follows. In ths course we manly study the canoncal ensemble, but for fermons and bosons t wll be smpler to use the grand canoncal ensemble. 1.2 The Canoncal Ensemble We study a system S of N partcles n a volume wth N and fxed. The mcrostates of S are the complete orthogonal set. We assume that the spectrum s dscrete wth possble degeneracy. We assocate wth S a canoncal ensemble E. Ths s a very large number A of dstngushable replcas S 1, S 2, S 3,... of S. Suppose we were to measure a complete set of commutng observables for all members of E smultaneously. Then let a be the number of members found n state. Then a = A, and a E = AE, (1.2.1) where E s the fxed, tme-ndependent ensemble average energy of the members of E. In other words a /A s the (quantum mechancal) probablty for fndng the system n mcrostate. The set {a } s called a confguraton of E, and the number of ways of parttonng A nto the set {a } s W (a) = A! a!. (1.2.2)

4 1 STATISTICAL MECHANICS 4 The mportant prncple underlyng statstcal mechancs s that we assgn equal a pror probablty to each way of realzng each allowed confguraton. Ths means that the probablty of fndng confguraton {a } s proportonal to W (a). In the lght of the earler dscusson, the probablty dstrbuton for the {a } wll be sharply peaked and the fluctuatons about the peak value wll be very small: O(1/ A). Snce we can take A as large as we lke, the average of any varable over the ensemble wll be overwhelmngly domnated by the value t takes n the most probable confguraton, {ā }. For fxed N, and E, we shall assocate the state of thermodynamc equlbrum of S wth the most probable confguraton of E that s consstent wth the constrants (1.2.1). We fnd {ā } by maxmzng log W (a) w.r.t. {a }. Usng Strlng s formula, (log n! = n log n n log 2πn), we have log W A log A A a (log a 1) = A log A a log a, (1.2.3) snce a = A. We maxmze ths expresson subject to the constrants (1.2.1) by usng Lagrange multplers. Then we have ( A log A a log a α a β ) a E =,. (1.2.4) a j Thus = log a j α + βe j =, a j = e 1 α βe j. (1.2.5) We elmnate α usng (1.2.1), and defne Z, the canoncal partton functon: A = a = e 1 α Z, wth Z = e βe = E Ω(E)e βe, (1.2.6) where Ω(E) s the degeneracy of levels wth energy E, and E runs over all dstnct values n the spectrum of the system. The fracton of members of E found n mcrostate n the macrostate of thermodynamc equlbrum s ρ = a A = 1 Z e βe. (1.2.7) Ths s the Boltzmann dstrbuton and s thought of as the (quantum mechancal) probablty of fndng n the state of thermodynamc equlbrum. The average X of a physcal observable s then X = X ρ. (1.2.8) For example, E = E ρ = 1 a E = E, (1.2.9) A

5 1 STATISTICAL MECHANICS 5 from (1.2.1), as we expect t should. Z s very mportant snce we shall see that t allows us to calculate the thermodynamc and large-scale propertes of a system n equlbrum from the quantum mechancal descrpton of the system. An mportant example s that ( ) log Z E =. (1.2.1) β Holdng fxed means holdng the E fxed snce these latter depend on. As emphaszed earler for the canoncal ensemble we can thnk of each ndvdual system as beng n contact wth a heat bath made up of the rest of the ensemble. What are the fluctuatons n energy of a system? Usng above results, we have E β = 1 2 Z Z β ( ) Z 2 Z 2 β = E 2 + E 2 = ( E) 2. (1.2.11) For large systems typcally E N and, as E depends smoothly on β we expect E β N, = E E N N = N (1.2.12) We have found that energy plays a vtally central rôle n determnng the probablty for fndng a system n a gven state. In prncple, the ρ can depend on other varables too. For example, the partcle number N, correspondng to the grand ensemble, or even angular momenta where relevant. In general, such quanttes must be be conserved and observable on the large scale. 1.3 Temperature Consder two systems S a and S b wth volumes a, b and partcle numbers N a, N b, respectvely. Form a jont ensemble E ab from the separate ensembles E a and E b by allowng all members of both to exchange energy whlst keepng the overall total energy fxed. By allowng S a and S b to exchange energy we are allowng for nteractons between the partcles of the two systems. These wll be suffcent to establsh equlbrum of S a wth S b but otherwse be neglgble. For nstance, they take place across a boundary common to the systems and so they contrbute energy correctons whch scale wth the boundary area and so are therefore neglgble compared wth the energy, whch scales wth volume. Now form a composte system S ab by jonng S a and S b together. Let S a have mcrostates a wth energy E a and S b have mcrostates b wth energy E b. Because the extra nteractons can be neglected n the bulk, then S ab wll have mcrostates j > ab = > a j > b wth energy Ej ab = Ea + Eb j. Now, E a and E b are separately n equlbrum characterzed by Lagrange multplers β a and β b, respectvely. Also, E ab s an equlbrum ensemble whch s characterzed by β ab, and so we must have ρ ab j (E a + E b j) = ρ a (E a )ρ b j(e b j), E a and E b j. (1.3.1) Then e β ab(e a +Eb j ) Z ab = e (βaea +β be b j ) Z a Z b, E a and E b j. (1.3.2)

6 1 STATISTICAL MECHANICS 6 Ths can only be satsfed f β ab = β a = β b and hence Z ab = Z a Z b. It s nterestng to note that the result (1.3.1) could be gven as the defnton of what t means for S a to be n thermal equlbrum wth S b. Ths s because we expect that n equlbrum these probabltes depend only on the energes of the systems. Then relaton (1.3.1) must hold snce energes add and probabltes multply. The only soluton to (1.3.1) s the Boltzmann dstrbuton (1.2.7). The relaton (1.3.1) can be establshed drectly by fndng the most probable dstrbuton for the ensemble E ab. Suppose a occurs a tmes, j b occurs b j tmes and j ab occurs c j tmes n E ab. Then we have a = A, b = A (1.3.3) a = j c j, b j = c j, c j = A. (1.3.4) j We only have one constrant on the energy whch s that the total energy of E ab s fxed: AE = a E a + j b j E b j, (1.3.5) AE = j c j (E a + E b j). (1.3.6) The confguraton {a, b j } arses n ways and the confguraton {c j } arses n W (a)w (b) A! A! a! j b j!, (1.3.7) W (c) A! j c j!, (1.3.8) ways. The most probable dstrbuton of {a, b j } s obtaned by maxmzng W (a)w (b) subject to (1.3.4) and (1.3.6) to get a = e 1 αa βea, ρ a = a A, b j = e 1 α b βe b j, ρ b j = b j A. Note that snce there s only one energy constrant the most probable {a } and {b j } depend on the same value of β. The temperature, T, s defned by the statement that two systems n thermal equlbrum have the same temperature. We therefore conclude that two systems n thermal equlbrum are descrbed by Boltzmann dstrbutons wth a common value of β whch can therefore be thought of as defnng the temperature The most probable dstrbuton of {c j } s obtaned by maxmzng W (c) subject to the constrants (1.3.4) and (1.3.6) to get c j = e 1 α ab β (E a +Eb j ), ρ ab j = c j A. (1.3.9)

7 1 STATISTICAL MECHANICS 7 So far β and β do not necessarly have the same value snce they are just Lagrange multplers mposng the energy constrant n two separate maxmzatons. However, the relatons between {c j } and {a, b j } gven n (1.3.4) can be only be satsfed f β = β. It then follows that (c.f. (1.3.1)) Z ab (β) = Z a (β)z b (β), and ρ ab j = ρ a ρ b j. (1.3.1) The temperature can be defned by β = 1 kt, (1.3.11) where k s Boltzmann s constant and T s n degrees Kelvn. Because the analyss apples to any par of systems k s a unversal constant: k = Joules/ K. Ths defnton ensures that the average energy ncreases as T ncreases. For a dlute gas wth N partcles ths mples Boyle s law, P = NkT, as we shall see. 1.4 Thermodynamc deas A system undergoes an adabatc change f () the system s thermally solated so that no energy n the form of heat can cross the system boundary: δq =, () the change s caused by purely by external forces actng on the system, () the change takes place arbtrarly slowly. By heat Q we mean energy that s transfered n a dsordered way by random processes. In contrast, work W s energy transfered through the agency of external forces n an ordered way. Work can be done on the system by movng one of the walls (lke a pston) wth an external force, whch corresponds to changng the volume. If the change s adabatc, no energy s permtted to enter or leave the system through the walls. Because the moton s slow the appled force just balances the pressure force P A (A s the area of the wall), and the work done on the system s then δw = P AδL = P δ. If the system s n a gven mcrostate wth energy E the change s slow enough that t remans n ths state there s no nduced quantum-mechancal transton to another level. Ths s the Ehrenfest prncple. The change n energy balances the work done and so δw = δe = E δ. (1.4.1) For a system n TE the work done n an adabatc change s the ensemble average of ths result P δ = δw = ρ E δ = P = ρ E. (1.4.2) Ths s reasonable snce f P exsts then t s a thermodynamc varable and so should be expressble as an ensemble average. These deas are most easly understood n the context of an deal gas. Consder the quantum mechancs of a gas of N non-nteractng partcles n a cube of sde L. The

8 1 STATISTICAL MECHANICS 8 sngle partcle energy levels are En = h 2 n 2 /2mL 2 wth n Z 3. Note that for gven n, En 2/3 generally, we expect E = E( ). Then E = 2 E 3 = P = 2 3 ρ E = 2 3ɛ, (1.4.3) where ɛ = E/ s the energy densty. Ths s the formula relatng the pressure to the energy densty for a non-relatvstc system of partcles. We also deduce the energy conservaton equaton for an adabatc change (δq = ): P δ + δe =. (1.4.4) For the deal gas an adabatc change does not change the occupaton probabltes ρ of the energy levels just the energes of the levels change. Ths s the Ehrenfest prncple. For systems wth E ( ) s the ρ are stll Boltzmann equlbrum probabltes n + δ but wth a dfferent temperature s = 2/3 for the deal gas. If the change s not adabatc then heat energy can enter or leave the system. Snce E = ρ E, n the most general case we have δe = ρ δe + E δρ or δe = P δ + E δρ. (note that δρ =.) (1.4.5) To deal wth ths eventualty we ntroduce the concept of entropy. Defne the entropy, S, of a system by S = k log W (a), (1.4.6) A where, as before, W (a) s the number of ways of realzng the ensemble confguraton {a }. Snce there are A members n the ensemble ths s the entropy per system. Note that the ensemble s not necessarly an equlbrum one. However, wth ths defnton we see that for an equlbrum ensemble S eq = k A log W max, (1.4.7) and from (1.4.6) and (1.4.7) we deduce that S s maxmzed for the an equlbrum ensemble. Usng (1.2.2) we get S = k ( A log A ) a log a A = k ( A log A a log ρ log A ) a, A = S = k ρ log ρ (1.4.8) where we have used ρ = a /A, a = A. Ths s an mportant formula whch can be derved n many dfferent ways from varous reasonable requrements. However, for

9 1 STATISTICAL MECHANICS 9 complex systems t needs some nterpretaton but for the free gas there s no dffculty. More on entropy shortly. Let us apply the dea to a general change between nearby states of TE, e.g., an sothermal change (dt = ). Change the volume of the system arbtrarly slowly and allow heat energy to be absorbed/emtted, e.g., by contact wth a heat bath. At every stage the system wll have tme to equlbrate and so although the ρ wll be tme-dependent they wll take ther equlbrum values approprate to the condtons prevalng (.e., values of, T ). In ths case we have (S wll stand for the equlbrum value unless otherwse stated) ρ = = δs = k 1 Z(, T ) e βe ( ), δρ (log ρ + 1), = k δρ ( βe log Z + 1), = 1 E δρ T = E δρ = T δs. (1.4.9) So, for a slow change, usng (1.4.5), we get n general δe = T δs P δ, or, n exact dfferentals de = T ds P d. (1.4.1) We can thnk of ths as a comparson between two nfntesmally dfferent states of thermodynamc equlbrum. Ths equaton s an expresson of the Frst Law of Thermodynamcs whch s the statement of energy conservaton: The Frst Law of Thermodynamcs states that de = δq + δw. (1.4.11) Here de s the dfferental change n the nternal energy of S, δq s the heat energy suppled to S, and δw s the work done on S (e.g., δw = P d ). For a slow change where the system s nstantaneously always n thermal equlbrum the change s sad to be reversble. Ths s because no work done s dsspated as unrecoverable energy such as through frctonal forces or strrng of the system. In prncple, the work done on the system can be recovered by allowng t to do work on another system, for example, a slowly compressed sprng. From above, comparng (1.4.1) and (1.4.11), for a reversble change we have reversble change = δq = T ds. (1.4.12)

10 1 STATISTICAL MECHANICS 1 Note that nether δq or δw are exact dervatves even though de, ds and d are. For an adabatc change we have ds = δq/t =. So the defnton of an adabatc change may be taken to be ds =. From (1.4.1) we see that T = ( ) E S, P = ( ) E S. (1.4.13) For a system n equlbrum we can derve S S eq from the partton functon. We have S = k = k ρ log ρ ρ ( βe log Z) = 1 E + k log Z. (1.4.14) T We defne the free energy, F, to be F = kt log Z = F = E T S. (1.4.15) In dfferental form we then have df = de T ds SdT, or, usng the frst law n the form (1.4.1) for nearby equlbrum states ( ) F df = P d SdT, = P = T ( ) F, S = T. (1.4.16) We shall see that the dea of the free energy, F, s a very mportant one n thermodynamcs. From (1.4.16) we deduce that F s a functon of the ndependent varables and T. Smlarly, from (1.4.16), F = F (, T ), = P = P (, T ), S = S(, T ). (1.4.17) Note also that E = E(S, ) snce S, are the ndependent varables. Thus the thermodynamc state of equlbrum characterzed by P,, T, S can be determned from the partton functon, Z, through the dea of the free energy, F. The equaton whch relates P, and T, n ether of the forms shown n (1.4.16) and (1.4.17), s known as the equaton of state. Remember, all these quanttes depend mplctly on the fxed value of N and hence on the partcle densty n = N/. 1.5 Extensve and ntensve varables Suppose an equlbrum system s placed next to an exact copy and the partton between them s wthdrawn to make the system twce the sze. arables that double n ths process are called extensve and those whose value s the same as the orgnal are called ntensve. For example, N,, S, E are extensve and P, T are ntensve.

11 1 STATISTICAL MECHANICS 11 To elaborate. Consder two equlbrum systems at temperature T, S 1 and S 2, whch are dentcal n every way except that they have volumes 1 and 2, respectvely. Put them next to each other but do not remove the partton. Then for the whole system, S 12, we have 12 = 1 + 2, N 12 = N 1 + N 2. Snce, Z 12 = Z 1 Z 2, we see that E = E 1 + E 2, S = S 1 + S 2 etc. If these varables are extensve as clamed then these equaltes wll hold after the partton s removed. We expect ths to be the case f S 1, S 2 are homogeneous (whch means S 12 wll be, too). The partcles n each system are of the same nature and are not dstngushable and so by removng the partton we do not mx the systems n a detectable way. Hence, the entropy S 12 should reman unchanged. Then we expect that, E, S are proportonal to N. Clearly, S 1 and S 2 have the same T, P and so T, P are ntensve. Ths expectaton can fal, for example, (a) f surface energes are not neglgble compared wth volume energes the partton matters too much, (b) there are long-range forces such as gravty. The systems are no longer homogeneous. Thnk of the atmosphere dfferent parcels of ar at dfferent heghts may have the same temperature but the pressure and densty are functons of heght. 1.6 General Remarks () Let S be the sum of two systems, S = S 1 + S 2, nether of whch s necessarly n equlbrum. Although the partton functon s not useful we can stll show that the entropy defned by (1.4.8) s addtve. Let the level occupaton probabltes for S 1, S 2 be ρ, σ, respectvely. Then S = k j = k j ρ σ j log ρ σ j ρ σ j (log ρ + log σ j ) = k ρ log ρ + j σ j log σ j where we have used ρ = j σ j = 1. = S 1 + S 2, (1.6.1) () From the defnton of entropy (1.4.6) we see that the entropy s a maxmum for a system n equlbrum. Indeed, t was the entropy that we maxmzed to determne the equlbrum state. More on ths later. () Of the four varables, P,, T, S, any two can be treated as ndependent on whch the others depend. We have naturally found above, T to be ndependent, but we can defne G = F + P whch leads to dg = df + P d + dp, = dg = dp SdT. (1.6.2) G s called the Gbbs functon. Clearly, G = G(P, T ) and now and S are functons of P, T. Ths merely means that the expermenter chooses to control P, T and see how, S vary as they are changed. The transformaton G = F + P, whch changes the set of ndependent varables, s called a Legendre transformaton.

12 1 STATISTICAL MECHANICS The example of a perfect gas A perfect gas conssts of a system of free partcles whch therefore do not nteract wth each other. The gas s n a cubcal box wth walls at temperature T, and energy wll be exchanged between the partcles and the walls when the partcle collde (nelastcally) wth the walls. The gas wll come nto equlbrum wth the box and wll have temperature T, also the densty of states Let the number of partcles be N, the box be of sde L wth volume = L 3, and the mass of each partcle be m. We use perodc boundary condtons to mpose the condton of fnte volume so that the sngle partcle wavefuncton n the box satsfes ψ(x + Le ) = ψ(x), ( ) where the e, = 1, 2, 3 are unt vectors spannng R 3. For free non-relatvstc partcles we then have energy egenstates ψ k (x) = 1 e k x wth k = 2π L n, n Z3, ( ) p = hk, ɛ(p) = h2 k 2 2m. ( ) We are nterested n the lmt L and so for fxed momentum, p, we have that n, n /L fxed. Snce, n s large we can treat n as a contnuous varable. The number of states n n n + dn s d 3 n whch s therefore the number of states n k k + dk wth dk = (2π/L)dn. Thus, The number of states n k k + dk s ( ) L 3 d 3 k. ( ) 2π Because the state label can be treated as contnuous we have ( ) L 3 d 3 d 3 k k = 2π (2π) 3 = = where g(ɛ) = (2π h) 3 g(ɛ)dɛ 4πp 2 dp = 2π 2 h 3 p 2 dp dɛ dɛ d 3 p (2π h) 3 dp 3 p2 2π2 h dɛ. ( ) For partcles wth spn there s an extra factor of g s = 2s + 1. Then, usng ( ), we have = m g(ɛ) = g s 3 (2mɛ) 2mɛ, 2π2 h g(ɛ) = g s 4π 2 ( ) 3 2m 2 1 ɛ h 2 2. ( )

13 1 STATISTICAL MECHANICS 13 The functon g(ɛ) s the densty of states. A general analyss n D-dmensons gves S D g(ɛ) = g s (2π h) D pd 1 dp dɛ, ( ) where S D s the surface area of the unt sphere n D-dmensons, and = L D. Agan for non-relatvstc partcles we can use ( ) to get D = 1 g(ɛ) = g s 2π D = 2 g(ɛ) = g s 4π ( 2m h 2 ( 2m h 2 ) 1 2 ɛ 1 2 ). ( ) Note that for D = 2 g(ɛ) s a constant ndependent of ɛ. For relatvstc partcles of rest mass m, the analyss s dentcal and we can use the general formula ( ) wth the relatvstc dsperson relaton ɛ(p) = p 2 c 2 + m 2 c 4. In partcular, photons have m = and g s = 2 snce there are two dstnct polarzaton states. In ths case, and for D = 3 we get g(ɛ) = ɛ 2 π 2 h 3 c 3. ( ) Snce ɛ = hω we get the densty of states n ω ω + dω, g(ω), to be g(ω) = g(ɛ) dɛ dω = ω2 π 2 c 3. ( ) the partton functon for free spnless partcles Consder N partcles n volume = L 3. Then the sngle partcle partton functon s z = e βɛ dɛ g(ɛ)e βɛ. ( ) From ( ), and settng y = βɛ, ths gves z = ( ) 3 2mkT 2 4π 2 h 2 dy y 1 2 e y ( 2mπkT = In D-dmensons a smlar results holds and we fnd from ( ) h 2 ) 3 2. ( ) z (kt ) D/2. ( ) Now, from before, we have Z = z N and so log Z = N log z. Then E = N β log z = N β ( D 2 log β + const.) = D NkT. ( ) 2 Ths s an mportant result of classcal statstcal mechancs and s called the equpartton of energy whch states that The average energy per partcle degree of freedom s 1 2 kt

14 1 STATISTICAL MECHANICS 14 Combnng ths result wth P = 2 3E from (1.4.3) we get the equaton of state for a perfect gas. P = N kt Boyle s Law. ( ) Note that ths result holds n D-dmensons snce the generalzaton of (1.4.3) s P = 2 D ɛ entropy and the Gbbs paradox Usng (1.4.15) and (1.4.16), whch states that we get F = kt log Z, S = ( ) F T, S = Nk log z Nk = Nk log Nk log ( 2mπkT h 2 ) + 3 Nk, ( ) 2 whch s not extensve snce N. Ths s Gbbs paradox. The resoluton s to realze that usng Z = z N treats the partcles as dstngushable snce t corresponds to summng ndependently over the states of each partcle. In realty the partcles are ndstngushable, and we should not count states as dfferent f they can be transformed nto each other merely by shufflng the partcles. The paradox s resolved by accountng for ths fact and takng Z = z N /N!. Usng Strlng s approxmaton, we fnd ( ) S = Nk log + 3 ( ) 2mπkT N 2 Nk log h Nk, ( ) 2 whch s extensve. We should note at ths stage that dvdng by N! correctly removes the overcountng only n the case where the probablty that two partcles occupy the same level s neglgble. Ths s the stuaton where Boltzmann statstcs s vald and certanly t works for T large enough or the number densty s low enough. In other cases we must be more careful and we shall see that the consequences are very mportant. 1.8 The Increase of Entropy We saw n secton 1.4 from the defnton of entropy (1.4.6) and (1.4.7), that S s maxmzed for an equlbrum ensemble. Ths s a general prncple whch states that For a system wth fxed external condtons the entropy, S, s a maxmum n the state of thermodynamc equlbrum. By fxed external condtons we mean varables lke, E, N for an solated system or, T, N for a system n contact wth a heat bath at temperature T. For example, let S 1 be a perfect gas of volume 1 wth N 1 molecules of speces 1, and S 2 be a perfect gas of volume 2 wth N 2 molecules of speces 2. Both systems are

15 1 STATISTICAL MECHANICS 15 n equlbrum at temperature T. Place them next to each other wth the partton n place. The total entropy s S 1 + S 2 wth S = ( ) ( ( ) 3 kn log + kn N 2 log 2m πkt h ) 2 }{{} B (T ). (1.8.1) Now remove the partton. Because the speces are dstngushable, the new system, S 12, s not ntally n equlbrum but ntally has entropy S 1 + S 2. The gases mx and after equlbrum has been attaned the partton functon of the new system, of volume = 1 + 2, s Z 12 = z 1 N 1 N 1! z 2 N 2 N 2! Note, not (N 1 + N 2 )! n the denomnator. Ths gves entropy. (1.8.2) S 12 = k [(N 1 + N 2 ) log( ) N 1 log N 1 N 2 log N 2 + N 1 B 1 (T ) + N 2 B 2 (T )] [ = k N 1 log ( N 1 ) + N 2 log ( ) N 2 ] + N 1 B 1 (T ) + N 2 B 2 (T ). (1.8.3) So S 12 S 1 S 2 [ = k N 1 log ( ) ( )] N 2 log 1 2 >. (1.8.4) The entropy has ncreased because the gases have mxed. To separate the two speces requres to system to become more ordered all the boys to the left and all the grls to the rght. Ths s unlkely to happen spontaneously. From the defnton of the entropy (1.4.6) the more ordered a system s, the smaller s W (a) and the lower s the entropy. Notce that S 12 s the sum of the entropes that each gas would have f they each occuped the volume separately. Ths s the law of partal entropes whch holds for deal gases. Remarks: () Entropy s a measure of nformaton. When a system s n equlbrum we know the least about t snce all avalable mcrostates are equally lkely. In contrast, the entropy s low when we know that the system s n one or very few mcrostates. Informaton theory s based on ths observaton. () The mcroscopc defnton of entropy S = k ρ log ρ, for a complex system s subtle. In partcular, reconclng the mcroscopc and thermodynamc defntons of an adabatc change (δs = ) s not smple but the perfect gas s an deal system to examne these deas. () When S 1 and S 2 separately come nto equlbrum we maxmze S 1 and S 2 separately each wth two constrants (for E 1, N 1 and E 2, N 2 ), makng four n all. When S 1 and S 2 are combned there are only two constrants (for E 1 + E 2 and N 1 + N 2 ) whch are a subset of the orgnal four. We expect that the maxmum of S 1 + S 2 subject to these two constrants wll be greater than the maxmum attaned when t s subject

16 2 THERMODYNAMICS 16 to the four constrants (t may be unchanged c.f. Gbbs paradox). Hence, the entropy wll generally ncrease when the systems are combned. Mxng just corresponds to removal of some constrants. (v) We have not ever dscussed how a system reaches equlbrum. In practce, t takes a certan tme to evolve to equlbrum and some parts of the system may reach equlbrum faster than others. Indeed, the tme constants characterzng the approach to equlbrum may dffer markedly. Ths can mean that although equlbrum wll be establshed t mght not occur on tme scales relevant to observaton. For example, some knds of naturally occurrng sugar molecules are found n one somerc form or handedness. In equlbrum, there would be equal of each somer but ths s not relevant to nature. The descrpton of the system at equlbrum need not nclude those forces whch are neglgble for most purposes. For example, exactly how a gas molecule nteracts wth the vessel walls s a surface effect and does not affect any thermodynamc property n the nfnte volume lmt. However, t s generally assumed that t s such small randomzng nteractons whch allow energy to be transfered between levels, allowng the most probable state to be acheved. They are vtal to the workng of the ergodc hypothess. Ths s by no means certan to hold and n one dmenson t s qute hard to establsh that t does. The pont s, that f a closed system s not n equlbrum then, gven enough tme, the most probable consequence s an evoluton to more probable macrostates and a consequent steady ncrease n the entropy. Gven ergodcty, the probablty of transton to a state of hgher entropy s enormously larger than to a state of lower entropy. Chance fluctuatons to a state of lower entropy wll never be observed. The law of ncrease of entropy states that: If at some nstant the entropy of a closed system does not have ts maxmum value, then at subsequent nstants the entropy wll not decrease. It wll ncrease or at least reman constant. 2 Thermodynamcs Consder a volume of gas wth fxed number N of partcles. From the work on statstcal mechancs we have found a number of concepts whch enable us to descrbe the thermodynamc propertes of systems: () E: the total energy of the system. Ths arose as the average ensemble energy and whch has neglgble fluctuatons. It s extensve. () S: the entropy. Ths s a new dea whch measures the number of mcrostates contrbutng to the system macrostate. S s a maxmum at equlbrum and s an extensve property of the system. It has meanng for systems not n equlbrum. () For nearby equlbrum states de = T ds P d.

17 2 THERMODYNAMICS 17 (v) F : the free energy. It s naturally derved from the partton functon and, lke E, s a property of the system. For nearby equlbrum states df = SdT P d. It s extensve. (v) All thermodynamc varables are functons of two sutably chosen ndependent varables: F = F (T, ), E = E(S, T ). Note, f X s extensve we cannot have X = X(P, T ). (v) Equatons of state express the relatonshp between thermodynamc varables. example, P = NkT for a perfect gas. For It s because E, S, P,, T, F etc. are propertes of the equlbrum state that we are able to wrte nfntesmal changes n ther values as exact dervatves. The changes n ther values are ndependent of the path taken from an ntal to fnal equlbrum state. Ths s not true of the heat δq absorbed or emtted n a change between nearby equlbrum states t does depend on the path: δq s not an exact dervatve. However, ds = δq/t s an exact dervatve, and 1/T s the ntegratng factor just lke n the theory of frst-order o.d.es. Energy conservaton s expressed by the fst law: δe = δq + δw for nfntesmal change E = Q + W for fnte change (2.1) where δq( Q) s the heat suppled to the system and δw ( W ) s the work done on the system. Suppose the state changes from E(S 1, 1 ) to E(S 2, 2 ) then n general we expect 2 W P d (2.2) 1 because addtonal work s done aganst frcton, generatng turbulence etc. However, de = T ds P d whch mples Q S2 S 1 T ds. (2.3) 2.1 reversble and rreversble changes These nequaltes hold as equaltes for reversble changes. Ths wll hold f the change s non-dsspatve and quasstatc. Quasstatc means a change so slow that the system s always arbtrarly close to a state of equlbrum. The path between ntal and fnal states can then be plotted n the space of relevant thermodynamc varables. Ths s necessary because otherwse thermodynamc varables such as P, T etc. are not defned on the path and we cannot express δw = P δ as must be the case for reversblty. In ths case, no energy s dsspated n a way that cannot be recovered by reversng the process. For an rreversble change the extra ncrease n entropy s due to the extra randomzng effects due to frcton, turbulence etc. A smple example s rapd pston movement as well as mxng of dstngushable gases and free expanson of gas nto a vacuum. For an solated, or closed, system Q = but S, the equalty holdng for a reversble change. In real lfe there s always some dsspaton and so even f δq = we expect δs >. These deas are compatble wth common sense notons. For reversble transtons the system can be returned to ts orgnal state by manpulatng the external condtons.

18 2 THERMODYNAMICS 18 E.g., a sprng that has been quasstatcally compressed. Snce the change s through a sequence of equlbrum confguratons there s no thermodynamc reason why t could not be traversed n the opposte drecton, thus reversng the change. For an rreversble change, such as mxng of dfferent gases, no such reverse transton can occur. In the case of mxng t would requre the gases to be separated wthn a closed system. It must be emphaszed that the entropes of the ndvdual parts of the closed system need not all ncrease or reman constant, but the total for the whole system must. Of course, chemcal means can be used to separate mxed gases but only at the cost of ncreasng the entropy elsewhere snce the closed system must nclude all parts of the experment. If ths were not the case then, overall, entropy would have decreased. 2.2 Applcatons The Maxwell Relatons The varables we have consdered so far, F, G, E, P,, T, S, are all propertes of the equlbrum state. They each depend on an approprate par of varables chosen as ndependent and are dfferentable. These propertes are encoded n dfferental relatons between the varables. Usng de = T ds P d we have Free energy F = E T S : = df = SdT P d = F = F (T, ) Enthalpy H = E + P : = dh = T ds + dp = H = H(S, P ) ( ) Gbbs functon G = E T S + P : = dg = SdT + dp = G = G(T, P ) Because these are all exact dfferentals we have, for example, ( 2 ) ( E 2 ) E =. ( ) S S Snce T = ( ) E S, P = ( ) E S we have ( ) ( ) P T = S S Ths s a Maxwell relaton. Another such Maxwell relaton arses from S = ( F T ), P = ( F, ( ). ( ) ) T, ( ) we fnd ( ) ( ) S P =. ( ) T T Two more Maxwell relatons can be derved from G and H gvng four n all. However, they are not all ndependent. Ths can be seen by consderng z = z(x, y). Then δz = ( ) z δx + x y ( ) z δy = y x

19 2 THERMODYNAMICS 19 1 = = ( ) z x ( ) z x y y ( ) x z y ( ) z + y x and ( ) y x z. ( ) Multply the last equaton by ( x/ z) y and use the second equaton to get ( ) z y x ( ) y x z ( ) x z y = 1. ( ) Substtute any three of P,, T, S for x, y, z to relate the terms n Maxwell s relatons. We note that E, F, H, G are all extensve. Note that G explctly only depends on the ntensve quanttes T, P and so ts extensve character s due to N and we can wrte G = µ(p, T )N, where µ s called the chemcal potental. More on ths later. Consder E = E(, S) and change varables (, S) (, T ). Then we have ( E ) T = Usng de = T ds P d ths gves ( ) E T ( E ) S + ( E S = P + T ) ( S ( ) S T and usng ( ) (from dfferentablty of F ) we have ( ) ( ) E P = P + T T T, ) T.. ( ) For a perfect gas the equaton of state s P = NkT whch mples ( ) E =. ( ) T Snce we only need two ndependent varables we have n ths case that E = E(T ) a functon of T only. Ths s an example of equpartton where E = 3 2 NkT specfc heats Because δq s not an exact dervatve there s no concept of the amount of heat stored n a system. Instead δq s the amount of energy absorbed or emtted by the system by random processes and excludng work done by mechancal or other means. If we specfy the condtons under whch the heat s suppled then we can determne δq usng δq = de + δw, ( ) where de s an exact dervatve. It may be the case that absorpton/emsson of heat s not accompaned by a change n T. An example, s the latent heat of evaporaton of water to a gas. However, ths s a phase change whch we exclude from the current dscusson. We can wrte δq = CdT where C s the heat capacty of the system. Clearly, to gve C meanng we need to specfy the condtons under whch the change takes place. Important cases are where the change s reversble and at fxed or fxed P. Then δq = T ds and we defne C = T ( S T ), C P = T ( ) S T P, ( )

20 2 THERMODYNAMICS 2 where C s the heat capacty at constant volume and C P s heat capacty at constant pressure. Usng de = T ds P d and dh = T ds + dp. ( ) we have also ( ) E C = T Changng varables from T, P to T, we have ( S T ) P = ( S T, C P = ) + ( S ) ( ) H T P T ( ) T P. ( ), ( ) and usng the Maxwell relaton ( ) and the defntons of C P and C we have ( ) ( ) S C P = C + T T = C P = C + T For any physcal system we expect ( ) >, T P ( T T ) P ( ) P T ( P T P ). ( ) >, ( ) and hence that C P > C. Ths makes sense because for a gven ncrement dt the system at fxed P expands and does work P d on ts surroundngs whereas the system at fxed does no work. The extra energy expended n the former case must be suppled by δq whch s correspondngly larger than n the latter case. An mportant example s that of a perfect gas. An amount of gas wth N A (Avogadro s number) of molecules s called a mole. The deal gas law tells us that at fxed T, P a mole of any deal gas occupes the same volume. The deal gas law for n moles s P = nn A kt = nrt, ( ) where R s the gas constant, and s the same for all deal gases. Note that at suffcently low densty all gases are essentally deal. The heat capacty per mole, c, s called the specfc heat: c = C/n. Then from ( ) we have c p c v = R. ( ) We defne γ = c p = c v + R = γ > 1. ( ) c v c v If the number of degrees of freedom per molecule s denoted N F then equpartton of energy gves that the energy of 1 mole s = E = N F 2 RT c v = N F 2 R, c p = ( NF ) R, γ = ( NF + 2 N F ). ( ) For a monatomc gas N F = 3, for a datomc gas N F = 5 (3 poston, 2 orentaton), etc, and so γ = 5/3, 7/5,....

21 2 THERMODYNAMICS adabatc changes δq = for an adabatc change. For n moles of an deal gas E = nc v T, P = nrt and then = RdE + RP d (extra R for convenence). ( ) As a functon of (, T ) we have ( ) E de = T dt + ( ) E d = nc v dt, ( ) T snce ( E/ ) T = (eqns. ( ),( )) for a perfect gas. (Note, ths wll be true for all systems where E does not depend on at fxed N.) Then Thus Thus = Rnc v dt + RP d = c v (P d + dp ) + RP d (usng P = nrt ) = c p P d + c v dp. ( ) c p P d + c v dp =. ( ) P γ s constant on adabatcs ( ) Note that adabatcs, P γ constant, are steeper than sothermals, P constant. We can use these results to calculate the entropy of n moles of deal gas. We have = = T ds = de + P d = nc v dt + nrt d ds = nc v dt T + nrd S = nc v log T + nr log + S. S s the unknown constant of ntegraton. Thermodynamcs cannot determne S and does not care whether S s extensve. Ths s resolved by the more complete approach of statstcal mechancs gven earler. Ths result s the same as we found before ( ) f all the constant parts are lumped nto S. Usng P = nrt we get S = nc v log P γ + S, ( ) and so, as expected, S s constant on adabatcs (sentropcs) van der Waals equaton In realty even a low densty gas s not deal because there are nteractons between the gas molecules. Ultmately, at temperatures low enough these nteractons cause a phase transton to occur and the gas lquefes. We can account approxmately for the nteractons by correctng the deal gas law to gve van der Waals equaton. The form of the nter-partcle potental s shown n fgure 1. There s a repulsve, hard-core, part at small separatons and an attractve part for ntermedate separatons. The effect of these two regons s qualtatvely modeled as follows:

22 2 THERMODYNAMICS 22 Fgure 1: () The hard-core s represented as an excluded volume snce the volume avalable s reduced. We replace b. () The pressure measured by an observer, P, s due to the partcles on the surface httng the walls. Whlst n the bulk the attractve forces roughly cancel out because the partcles are n homogeneous envronment, ths s not true at the surface snce they are pulled back nto the bulk. Consequently, P s less than the bulk pressure, P B. Now, P s gven by P = d(momentum/unt-area)/dt nmv 2 where n s the number densty. The reducton n K.E. (and hence n v 2 ) due to the unbalanced attractons near the surface s also proportonal to n. Hence the reducton n pressure takes the form for fxed N snce n = N/. P B P n 2 = P B P = a 2, ( ) The deal gas equaton corrected for the excluded volume apples n the bulk so that P B ( b) = NkT = ( P + a ) 2 ( b) = RT. van der Waals equaton a N 2, b N, R = Nk. ( ) 2.3 the Second Law of Thermodynamcs Kelvn-Planck: It s mpossble to construct an engne that, operatng n a cycle, wll produce no other effect than the extracton of heat from a reservor and the performance of an equvalent amount of work. Clausus: It s mpossble to construct a devce that, operatng n a cycle, wll produce no other effect than the transfer of heat from a cooler to a hotter body. These two versons can be shown to be equvalent. By a cycle we mean a seres of processes operatng on a system for whch the ntal and fnal states are the same. Clearly, the most effcent cycle s a reversble one for

23 2 THERMODYNAMICS 23 Fgure 2: whch all the consttuent processes are reversble. Such a cycle can be drawn as a closed curve n the 2D space of the ndependent thermodynamc varables (see fgure 3). Consder system shown n fgure 2 whch, actng n a reversble cycle, extracts heat Q 1 from the hot reservor at temperature T 1 and delvers heat Q 2 to the cold reservor at temperature T 2 and does work W = Q 1 Q 2. Because the cycle s reversble the total change n entropy s zero. Thus, S = Q 2 T 2 Q 1 T 1 =, = Q 2 = Q 1T 2 T 1. (2.3.1) The law of ncrease of entropy tells us that for realstc systems whch have frctonal losses etc. Q 2 Q 1T 2 T 1. (2.3.2) Ths clearly agrees wth the Kelvn-Planck statement of the second law whch says that Q 2 >. The effcency of the cycle s defned as η = W Q 1 = Q 1 Q 2 Q 1 T 1 T 2 T 1. (2.3.3) and we see that the reversble cycle (or engne) has the greatest effcency. The work done by the cycle s the areaof the cycle: W = P d. Ths mportant example of a reversble cycle s the Carnot cycle shown n fgure 3 n whch a sample S of perfect gas s taken around a closed curve n the P plane by a sequence of adabatc and sothermal reversble processes wth T 1 > T 2. On AB the heat bath supples heat Q 1 to S at temperature T 1. On CD the heat bath extracts heat Q 2 from S at temperature T 2. On the adabatcs, BC and DA, T γ 1 s constant so that T 1 γ 1 A = T 2 γ 1 D, T 1 γ 1 B = T 2 γ 1 C = A B = D C. (2.3.4) The drect connecton of the second law n the form of Clausus wth the law of ncrease of entropy can be seen as follows. Suppose there exsts an engne I whch s

24 P=RT 2 3 THE GRAND CANONICAL ENSEMBLE 24 P=RT 1 P γ = K 1 P γ = K 2 Fgure 3: Fgure 4: more effcent that a Carnot engne, C, and so volates the law of ncrease of entropy. Let I drve C backwards as a Carnot refrgerator n the manner shown n fgure 4. Note that no work s suppled or absorbed by the external surroundngs snce the output, W, of I s absorbed by C. Then η I > η C = W Q > W Q = Q < Q. (2.3.5) However, the heat suppled to the hot heat bath s then Q = Q Q > and ths has been wholly transfered from the cold heat bath wthout the external nput of work. Ths volates the Clausus statement of the second law. It also shows that the most effcent cycle s the Carnot cycle. Remember W and Q are path-dependent even for reversble paths and hence η also depends on the path used to defne the cycle. 3 The Grand Canoncal Ensemble 3.1 formalsm We follow an dentcal procedure to before. We consder a grand (canoncal) ensemble, G of A replcas of the system S n mcrostates of S wth N partcles and energes

25 3 THE GRAND CANONICAL ENSEMBLE 25 E. Suppose a members of G are n mcrostate so that a = A, a E = AE, a N = AN. (3.1.1) As before we assocate thermodynamc equlbrum of S wth the most probable confguraton of G subject to the gven constrants. We maxmze the same log W as before: ( δ log W α a β a E γ ) a N =. (3.1.2) δa Ths gves us a = e (1+α) e β(e µn ), (3.1.3) where we have defned the chemcal potental µ by βµ = γ. The grand partton functon s then Z = e β(e µn ). (3.1.4) The fracton of members n mcrostate s The grand ensemble average s ρ = a A Ô = = e β(e µn) Z. (3.1.5) ρ O, (3.1.6) whch gves Ê = E, ˆN = N. What we have done s exchange a fxed value of N for a value that s mantaned n the average by choosng the correspondng value for µ just as we dd for E by choosng β. Ths has bg advantages snce t s often dffcult to mpose fxed N as a constrant on a system. It s somethng that we have not needed to explctly encode htherto. By ntroducng µ the ablty to tune ˆN to the rght value usng a varable that s explctly part of the formalsm s a huge advantage, as we shall see. Then we have N = 1 ( ) log Z, β µ β, ( ) log Z E µn =. (3.1.7) β Remember, the dependence s n E E ( ). As before, we consderng adabatc changes n (e.g., constant ρ for the deal gas). Then, as before, δe = P δ and so P = ρ δe δ = 1 β µ, ( ) log Z β,µ. (3.1.8) Followng the famlar argument, more general changes δρ, n whch heat enters or leaves the system, obey δρ =, δρ N = δn, δe = P δ + δρ E. (3.1.9)

26 3 THE GRAND CANONICAL ENSEMBLE 26 The entropy s defned n general, as before, to be S = k A log W = k ρ log ρ. (3.1.1) For an equlbrum ensemble we then fnd δs = k = k δρ log ρ ρ 1 ρ δρ δρ ( β(e µn ) log Z + 1). (3.1.11) Ths gves the fundamental thermodynamc relaton T ds = de + P d µdn, (3.1.12) whch corresponds to the frst law de = δq+δw mech +δw chem, where δw chem = µdn s the work done n addng dn partcles to the system. Note, we have conformed to the conventon that an exact dervatve s denoted as e.g., de, whereas an nexact dervatve s denoted as δq. The chemcal potental s then gven by ( ) E µ =. (3.1.13) N S, From the defnton the entropy n equlbrum s whch can be rewrtten as S = kβ(e µn) + k log Z, (3.1.14) S = ( ) kt log Z T µ,. (3.1.15) A smlar argument to the one gven earler n secton 1.3 shows that two systems placed n thermal and dffusve contact (.e., they can exchange partcles through, say, a permeable membrane) wll reach a thermal equlbrum characterzed by a common value of β, µ. The argument s smply that when the systems are separate there are sx Lagrange multplers leadng to equlbrum characterzed by (α 1, β 1, µ 1 ), (α 2, β 2, µ 2 ), but that when they are n contact there are only three Lagrange multplers and hence common values for these two sets. The frst law states that de = T ds P d + µdn and so E can be vewed as a functon of (S,, N), and when E, S, and N are extensve (as s the case for many large systems) we get E(λS, λ, λn) = λe(s,, N) ( ) ( ) ( ) E E E = E = S + + N S,N S,N N S, = E = T S P + µn. (3.1.16) We defne the grand potental Ω for a state of thermodynamc equlbrum by the Legendre transformaton Ω = E T S µn = E µn (E µn + kt log Z) = kt log Z, = Z = e βω. (3.1.17)

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

University of Washington Department of Chemistry Chemistry 453 Winter Quarter 2015

University of Washington Department of Chemistry Chemistry 453 Winter Quarter 2015 Lecture 2. 1/07/15-1/09/15 Unversty of Washngton Department of Chemstry Chemstry 453 Wnter Quarter 2015 We are not talkng about truth. We are talkng about somethng that seems lke truth. The truth we want

More information

Thermodynamics General

Thermodynamics General Thermodynamcs General Lecture 1 Lecture 1 s devoted to establshng buldng blocks for dscussng thermodynamcs. In addton, the equaton of state wll be establshed. I. Buldng blocks for thermodynamcs A. Dmensons,

More information

STATISTICAL MECHANICAL ENSEMBLES 1 MICROSCOPIC AND MACROSCOPIC VARIABLES PHASE SPACE ENSEMBLES. CHE 524 A. Panagiotopoulos 1

STATISTICAL MECHANICAL ENSEMBLES 1 MICROSCOPIC AND MACROSCOPIC VARIABLES PHASE SPACE ENSEMBLES. CHE 524 A. Panagiotopoulos 1 CHE 54 A. Panagotopoulos STATSTCAL MECHACAL ESEMBLES MCROSCOPC AD MACROSCOPC ARABLES The central queston n Statstcal Mechancs can be phrased as follows: f partcles (atoms, molecules, electrons, nucle,

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

Lecture 4. Macrostates and Microstates (Ch. 2 )

Lecture 4. Macrostates and Microstates (Ch. 2 ) Lecture 4. Macrostates and Mcrostates (Ch. ) The past three lectures: we have learned about thermal energy, how t s stored at the mcroscopc level, and how t can be transferred from one system to another.

More information

Review of Classical Thermodynamics

Review of Classical Thermodynamics Revew of Classcal hermodynamcs Physcs 4362, Lecture #1, 2 Syllabus What s hermodynamcs? 1 [A law] s more mpressve the greater the smplcty of ts premses, the more dfferent are the knds of thngs t relates,

More information

Introduction to Statistical Methods

Introduction to Statistical Methods Introducton to Statstcal Methods Physcs 4362, Lecture #3 hermodynamcs Classcal Statstcal Knetc heory Classcal hermodynamcs Macroscopc approach General propertes of the system Macroscopc varables 1 hermodynamc

More information

STATISTICAL MECHANICS

STATISTICAL MECHANICS STATISTICAL MECHANICS Thermal Energy Recall that KE can always be separated nto 2 terms: KE system = 1 2 M 2 total v CM KE nternal Rgd-body rotaton and elastc / sound waves Use smplfyng assumptons KE of

More information

Lecture 7: Boltzmann distribution & Thermodynamics of mixing

Lecture 7: Boltzmann distribution & Thermodynamics of mixing Prof. Tbbtt Lecture 7 etworks & Gels Lecture 7: Boltzmann dstrbuton & Thermodynamcs of mxng 1 Suggested readng Prof. Mark W. Tbbtt ETH Zürch 13 März 018 Molecular Drvng Forces Dll and Bromberg: Chapters

More information

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

Thermodynamics Second Law Entropy

Thermodynamics Second Law Entropy Thermodynamcs Second Law Entropy Lana Sherdan De Anza College May 8, 2018 Last tme the Boltzmann dstrbuton (dstrbuton of energes) the Maxwell-Boltzmann dstrbuton (dstrbuton of speeds) the Second Law of

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

Physics 240: Worksheet 30 Name:

Physics 240: Worksheet 30 Name: (1) One mole of an deal monatomc gas doubles ts temperature and doubles ts volume. What s the change n entropy of the gas? () 1 kg of ce at 0 0 C melts to become water at 0 0 C. What s the change n entropy

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

PHY688, Statistical Mechanics

PHY688, Statistical Mechanics Department of Physcs & Astronomy 449 ESS Bldg. Stony Brook Unversty January 31, 2017 Nuclear Astrophyscs James.Lattmer@Stonybrook.edu Thermodynamcs Internal Energy Densty and Frst Law: ε = E V = Ts P +

More information

...Thermodynamics. If Clausius Clapeyron fails. l T (v 2 v 1 ) = 0/0 Second order phase transition ( S, v = 0)

...Thermodynamics. If Clausius Clapeyron fails. l T (v 2 v 1 ) = 0/0 Second order phase transition ( S, v = 0) If Clausus Clapeyron fals ( ) dp dt pb =...Thermodynamcs l T (v 2 v 1 ) = 0/0 Second order phase transton ( S, v = 0) ( ) dp = c P,1 c P,2 dt Tv(β 1 β 2 ) Two phases ntermngled Ferromagnet (Excess spn-up

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

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1 P. Guterrez Physcs 5153 Classcal Mechancs D Alembert s Prncple and The Lagrangan 1 Introducton The prncple of vrtual work provdes a method of solvng problems of statc equlbrum wthout havng to consder the

More information

and Statistical Mechanics Material Properties

and Statistical Mechanics Material Properties Statstcal Mechancs and Materal Propertes By Kuno TAKAHASHI Tokyo Insttute of Technology, Tokyo 15-855, JAPA Phone/Fax +81-3-5734-3915 takahak@de.ttech.ac.jp http://www.de.ttech.ac.jp/~kt-lab/ Only for

More information

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law:

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law: CE304, Sprng 2004 Lecture 4 Introducton to Vapor/Lqud Equlbrum, part 2 Raoult s Law: The smplest model that allows us do VLE calculatons s obtaned when we assume that the vapor phase s an deal gas, 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

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

Rate of Absorption and Stimulated Emission

Rate of Absorption and Stimulated Emission MIT Department of Chemstry 5.74, Sprng 005: Introductory Quantum Mechancs II Instructor: Professor Andre Tokmakoff p. 81 Rate of Absorpton and Stmulated Emsson The rate of absorpton nduced by the feld

More information

Physics 181. Particle Systems

Physics 181. Particle Systems Physcs 181 Partcle Systems Overvew In these notes we dscuss the varables approprate to the descrpton of systems of partcles, ther defntons, ther relatons, and ther conservatons laws. We consder a system

More information

Monte Carlo method II

Monte Carlo method II Course MP3 Lecture 5 14/11/2006 Monte Carlo method II How to put some real physcs nto the Monte Carlo method Dr James Ellott 5.1 Monte Carlo method revsted In lecture 4, we ntroduced the Monte Carlo (MC)

More information

Statistical mechanics handout 4

Statistical mechanics handout 4 Statstcal mechancs handout 4 Explan dfference between phase space and an. Ensembles As dscussed n handout three atoms n any physcal system can adopt any one of a large number of mcorstates. For a quantum

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

Numerical Heat and Mass Transfer

Numerical Heat and Mass Transfer Master degree n Mechancal Engneerng Numercal Heat and Mass Transfer 06-Fnte-Dfference Method (One-dmensonal, steady state heat conducton) Fausto Arpno f.arpno@uncas.t Introducton Why we use models and

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

Solution Thermodynamics

Solution Thermodynamics Soluton hermodynamcs usng Wagner Notaton by Stanley. Howard Department of aterals and etallurgcal Engneerng South Dakota School of nes and echnology Rapd Cty, SD 57701 January 7, 001 Soluton hermodynamcs

More information

10. Canonical Transformations Michael Fowler

10. Canonical Transformations Michael Fowler 10. Canoncal Transformatons Mchael Fowler Pont Transformatons It s clear that Lagrange s equatons are correct for any reasonable choce of parameters labelng the system confguraton. Let s call our frst

More information

A quote of the week (or camel of the week): There is no expedience to which a man will not go to avoid the labor of thinking. Thomas A.

A quote of the week (or camel of the week): There is no expedience to which a man will not go to avoid the labor of thinking. Thomas A. A quote of the week (or camel of the week): here s no expedence to whch a man wll not go to avod the labor of thnkng. homas A. Edson Hess law. Algorthm S Select a reacton, possbly contanng specfc compounds

More information

Outline. Unit Eight Calculations with Entropy. The Second Law. Second Law Notes. Uses of Entropy. Entropy is a Property.

Outline. Unit Eight Calculations with Entropy. The Second Law. Second Law Notes. Uses of Entropy. Entropy is a Property. Unt Eght Calculatons wth Entropy Mechancal Engneerng 370 Thermodynamcs Larry Caretto October 6, 010 Outlne Quz Seven Solutons Second law revew Goals for unt eght Usng entropy to calculate the maxmum work

More information

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system Transfer Functons Convenent representaton of a lnear, dynamc model. A transfer functon (TF) relates one nput and one output: x t X s y t system Y s The followng termnology s used: x y nput output forcng

More information

Chapter 5 rd Law of Thermodynamics

Chapter 5 rd Law of Thermodynamics Entropy and the nd and 3 rd Chapter 5 rd Law o hermodynamcs homas Engel, hlp Red Objectves Introduce entropy. Derve the condtons or spontanety. Show how S vares wth the macroscopc varables,, and. Chapter

More information

ESCI 341 Atmospheric Thermodynamics Lesson 10 The Physical Meaning of Entropy

ESCI 341 Atmospheric Thermodynamics Lesson 10 The Physical Meaning of Entropy ESCI 341 Atmospherc Thermodynamcs Lesson 10 The Physcal Meanng of Entropy References: An Introducton to Statstcal Thermodynamcs, T.L. Hll An Introducton to Thermodynamcs and Thermostatstcs, H.B. Callen

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

5.62 Physical Chemistry II Spring 2008

5.62 Physical Chemistry II Spring 2008 MIT OpenCourseWare http://ocw.mt.edu 5.62 Physcal Chemstry II Sprng 2008 For nformaton about ctng these materals or our Terms of Use, vst: http://ocw.mt.edu/terms. 5.62 Lecture #8: Boltzmann, Ferm-Drac,

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

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

PES 2130 Fall 2014, Spendier Lecture 7/Page 1

PES 2130 Fall 2014, Spendier Lecture 7/Page 1 PES 2130 Fall 2014, Spender Lecture 7/Page 1 Lecture today: Chapter 20 (ncluded n exam 1) 1) Entropy 2) Second Law o hermodynamcs 3) Statstcal Vew o Entropy Announcements: Next week Wednesday Exam 1! -

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

Supplementary Notes for Chapter 9 Mixture Thermodynamics

Supplementary Notes for Chapter 9 Mixture Thermodynamics Supplementary Notes for Chapter 9 Mxture Thermodynamcs Key ponts Nne major topcs of Chapter 9 are revewed below: 1. Notaton and operatonal equatons for mxtures 2. PVTN EOSs for mxtures 3. General effects

More information

Chemical Equilibrium. Chapter 6 Spontaneity of Reactive Mixtures (gases) Taking into account there are many types of work that a sysem can perform

Chemical Equilibrium. Chapter 6 Spontaneity of Reactive Mixtures (gases) Taking into account there are many types of work that a sysem can perform Ths chapter deals wth chemcal reactons (system) wth lttle or no consderaton on the surroundngs. Chemcal Equlbrum Chapter 6 Spontanety of eactve Mxtures (gases) eactants generatng products would proceed

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

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U)

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U) Econ 413 Exam 13 H ANSWERS Settet er nndelt 9 deloppgaver, A,B,C, som alle anbefales å telle lkt for å gøre det ltt lettere å stå. Svar er gtt . Unfortunately, there s a prntng error n the hnt of

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

10.40 Appendix Connection to Thermodynamics and Derivation of Boltzmann Distribution

10.40 Appendix Connection to Thermodynamics and Derivation of Boltzmann Distribution 10.40 Appendx Connecton to Thermodynamcs Dervaton of Boltzmann Dstrbuton Bernhardt L. Trout Outlne Cannoncal ensemble Maxmumtermmethod Most probable dstrbuton Ensembles contnued: Canoncal, Mcrocanoncal,

More information

PHYS 705: Classical Mechanics. Newtonian Mechanics

PHYS 705: Classical Mechanics. Newtonian Mechanics 1 PHYS 705: Classcal Mechancs Newtonan Mechancs Quck Revew of Newtonan Mechancs Basc Descrpton: -An dealzed pont partcle or a system of pont partcles n an nertal reference frame [Rgd bodes (ch. 5 later)]

More information

PHYS 705: Classical Mechanics. Canonical Transformation II

PHYS 705: Classical Mechanics. Canonical Transformation II 1 PHYS 705: Classcal Mechancs Canoncal Transformaton II Example: Harmonc Oscllator f ( x) x m 0 x U( x) x mx x LT U m Defne or L p p mx x x m mx x H px L px p m p x m m H p 1 x m p m 1 m H x p m x m m

More information

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction ECONOMICS 5* -- NOTE (Summary) ECON 5* -- NOTE The Multple Classcal Lnear Regresson Model (CLRM): Specfcaton and Assumptons. Introducton CLRM stands for the Classcal Lnear Regresson Model. The CLRM s also

More information

Problem Set 9 Solutions

Problem Set 9 Solutions Desgn and Analyss of Algorthms May 4, 2015 Massachusetts Insttute of Technology 6.046J/18.410J Profs. Erk Demane, Srn Devadas, and Nancy Lynch Problem Set 9 Solutons Problem Set 9 Solutons Ths problem

More information

A particle in a state of uniform motion remain in that state of motion unless acted upon by external force.

A particle in a state of uniform motion remain in that state of motion unless acted upon by external force. The fundamental prncples of classcal mechancs were lad down by Galleo and Newton n the 16th and 17th centures. In 1686, Newton wrote the Prncpa where he gave us three laws of moton, one law of gravty,

More information

Fermi-Dirac statistics

Fermi-Dirac statistics UCC/Physcs/MK/EM/October 8, 205 Fer-Drac statstcs Fer-Drac dstrbuton Matter partcles that are eleentary ostly have a type of angular oentu called spn. hese partcles are known to have a agnetc oent whch

More information

Lecture. Polymer Thermodynamics 0331 L Chemical Potential

Lecture. Polymer Thermodynamics 0331 L Chemical Potential Prof. Dr. rer. nat. habl. S. Enders Faculty III for Process Scence Insttute of Chemcal Engneerng Department of Thermodynamcs Lecture Polymer Thermodynamcs 033 L 337 3. Chemcal Potental Polymer Thermodynamcs

More information

V T for n & P = constant

V T for n & P = constant Pchem 365: hermodynamcs -SUMMARY- Uwe Burghaus, Fargo, 5 9 Mnmum requrements for underneath of your pllow. However, wrte your own summary! You need to know the story behnd the equatons : Pressure : olume

More information

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number

More information

NAME and Section No.

NAME and Section No. Chemstry 391 Fall 2007 Exam I KEY (Monday September 17) 1. (25 Ponts) ***Do 5 out of 6***(If 6 are done only the frst 5 wll be graded)*** a). Defne the terms: open system, closed system and solated system

More information

Lecture 10. Reading: Notes and Brennan Chapter 5

Lecture 10. Reading: Notes and Brennan Chapter 5 Lecture tatstcal Mechancs and Densty of tates Concepts Readng: otes and Brennan Chapter 5 Georga Tech C 645 - Dr. Alan Doolttle C 645 - Dr. Alan Doolttle Georga Tech How do electrons and holes populate

More information

G4023 Mid-Term Exam #1 Solutions

G4023 Mid-Term Exam #1 Solutions Exam1Solutons.nb 1 G03 Md-Term Exam #1 Solutons 1-Oct-0, 1:10 p.m to :5 p.m n 1 Pupn Ths exam s open-book, open-notes. You may also use prnt-outs of the homework solutons and a calculator. 1 (30 ponts,

More information

CHAPTER 6. LAGRANGE S EQUATIONS (Analytical Mechanics)

CHAPTER 6. LAGRANGE S EQUATIONS (Analytical Mechanics) CHAPTER 6 LAGRANGE S EQUATIONS (Analytcal Mechancs) 1 Ex. 1: Consder a partcle movng on a fxed horzontal surface. r P Let, be the poston and F be the total force on the partcle. The FBD s: -mgk F 1 x O

More information

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4)

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4) I. Classcal Assumptons Econ7 Appled Econometrcs Topc 3: Classcal Model (Studenmund, Chapter 4) We have defned OLS and studed some algebrac propertes of OLS. In ths topc we wll study statstcal propertes

More information

Assortment Optimization under MNL

Assortment Optimization under MNL Assortment Optmzaton under MNL Haotan Song Aprl 30, 2017 1 Introducton The assortment optmzaton problem ams to fnd the revenue-maxmzng assortment of products to offer when the prces of products are fxed.

More information

Physics 106a, Caltech 11 October, Lecture 4: Constraints, Virtual Work, etc. Constraints

Physics 106a, Caltech 11 October, Lecture 4: Constraints, Virtual Work, etc. Constraints Physcs 106a, Caltech 11 October, 2018 Lecture 4: Constrants, Vrtual Work, etc. Many, f not all, dynamcal problems we want to solve are constraned: not all of the possble 3 coordnates for M partcles (or

More information

Difference Equations

Difference Equations Dfference Equatons c Jan Vrbk 1 Bascs Suppose a sequence of numbers, say a 0,a 1,a,a 3,... s defned by a certan general relatonshp between, say, three consecutve values of the sequence, e.g. a + +3a +1

More information

THERMAL DISTRIBUTION IN THE HCL SPECTRUM OBJECTIVE

THERMAL DISTRIBUTION IN THE HCL SPECTRUM OBJECTIVE ame: THERMAL DISTRIBUTIO I THE HCL SPECTRUM OBJECTIVE To nvestgate a system s thermal dstrbuton n dscrete states; specfcally, determne HCl gas temperature from the relatve occupatons of ts rotatonal states.

More information

Physics 53. Rotational Motion 3. Sir, I have found you an argument, but I am not obliged to find you an understanding.

Physics 53. Rotational Motion 3. Sir, I have found you an argument, but I am not obliged to find you an understanding. Physcs 53 Rotatonal Moton 3 Sr, I have found you an argument, but I am not oblged to fnd you an understandng. Samuel Johnson Angular momentum Wth respect to rotatonal moton of a body, moment of nerta plays

More information

#64. ΔS for Isothermal Mixing of Ideal Gases

#64. ΔS for Isothermal Mixing of Ideal Gases #64 Carnot Heat Engne ΔS for Isothermal Mxng of Ideal Gases ds = S dt + S T V V S = P V T T V PV = nrt, P T ds = v T = nr V dv V nr V V = nrln V V = - nrln V V ΔS ΔS ΔS for Isothermal Mxng for Ideal Gases

More information

Module 1 : The equation of continuity. Lecture 1: Equation of Continuity

Module 1 : The equation of continuity. Lecture 1: Equation of Continuity 1 Module 1 : The equaton of contnuty Lecture 1: Equaton of Contnuty 2 Advanced Heat and Mass Transfer: Modules 1. THE EQUATION OF CONTINUITY : Lectures 1-6 () () () (v) (v) Overall Mass Balance Momentum

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

Lecture 3: Boltzmann distribution

Lecture 3: Boltzmann distribution Lecture 3: Boltzmann dstrbuton Statstcal mechancs: concepts Ams: Dervaton of Boltzmann dstrbuton: Basc postulate of statstcal mechancs. All states equally lkely. Equal a-pror probablty: Statstcal vew of

More information

Mathematical Preparations

Mathematical Preparations 1 Introducton Mathematcal Preparatons The theory of relatvty was developed to explan experments whch studed the propagaton of electromagnetc radaton n movng coordnate systems. Wthn expermental error the

More information

j) = 1 (note sigma notation) ii. Continuous random variable (e.g. Normal distribution) 1. density function: f ( x) 0 and f ( x) dx = 1

j) = 1 (note sigma notation) ii. Continuous random variable (e.g. Normal distribution) 1. density function: f ( x) 0 and f ( x) dx = 1 Random varables Measure of central tendences and varablty (means and varances) Jont densty functons and ndependence Measures of assocaton (covarance and correlaton) Interestng result Condtonal dstrbutons

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

Physics 207: Lecture 20. Today s Agenda Homework for Monday

Physics 207: Lecture 20. Today s Agenda Homework for Monday Physcs 207: Lecture 20 Today s Agenda Homework for Monday Recap: Systems of Partcles Center of mass Velocty and acceleraton of the center of mass Dynamcs of the center of mass Lnear Momentum Example problems

More information

EPR Paradox and the Physical Meaning of an Experiment in Quantum Mechanics. Vesselin C. Noninski

EPR Paradox and the Physical Meaning of an Experiment in Quantum Mechanics. Vesselin C. Noninski EPR Paradox and the Physcal Meanng of an Experment n Quantum Mechancs Vesseln C Nonnsk vesselnnonnsk@verzonnet Abstract It s shown that there s one purely determnstc outcome when measurement s made on

More information

PART I: MULTIPLE CHOICE (32 questions, each multiple choice question has a 2-point value, 64 points total).

PART I: MULTIPLE CHOICE (32 questions, each multiple choice question has a 2-point value, 64 points total). CHEMISTRY 123-07 Mdterm #2 answer key November 04, 2010 Statstcs: Average: 68 p (68%); Hghest: 91 p (91%); Lowest: 37 p (37%) Number of students performng at or above average: 58 (53%) Number of students

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

At zero K: All atoms frozen at fixed positions on a periodic lattice.

At zero K: All atoms frozen at fixed positions on a periodic lattice. September, 00 Readng: Chapter Four Homework: None Entropy and The Degree of Dsorder: Consder a sold crystallne materal: At zero K: All atoms frozen at fxed postons on a perodc lattce. Add heat to a fnte

More information

Q e E i /k B. i i i i

Q e E i /k B. i i i i Water and Aqueous Solutons 3. Lattce Model of a Flud Lattce Models Lattce models provde a mnmalst, or coarse-graned, framework for descrbng the translatonal, rotatonal, and conformatonal degrees of freedom

More information

Module 9. Lecture 6. Duality in Assignment Problems

Module 9. Lecture 6. Duality in Assignment Problems Module 9 1 Lecture 6 Dualty n Assgnment Problems In ths lecture we attempt to answer few other mportant questons posed n earler lecture for (AP) and see how some of them can be explaned through the concept

More information

Lecture Note 3. Eshelby s Inclusion II

Lecture Note 3. Eshelby s Inclusion II ME340B Elastcty of Mcroscopc Structures Stanford Unversty Wnter 004 Lecture Note 3. Eshelby s Incluson II Chrs Wenberger and We Ca c All rghts reserved January 6, 004 Contents 1 Incluson energy n an nfnte

More information

4 Analysis of Variance (ANOVA) 5 ANOVA. 5.1 Introduction. 5.2 Fixed Effects ANOVA

4 Analysis of Variance (ANOVA) 5 ANOVA. 5.1 Introduction. 5.2 Fixed Effects ANOVA 4 Analyss of Varance (ANOVA) 5 ANOVA 51 Introducton ANOVA ANOVA s a way to estmate and test the means of multple populatons We wll start wth one-way ANOVA If the populatons ncluded n the study are selected

More information

π e ax2 dx = x 2 e ax2 dx or x 3 e ax2 dx = 1 x 4 e ax2 dx = 3 π 8a 5/2 (a) We are considering the Maxwell velocity distribution function: 2πτ/m

π e ax2 dx = x 2 e ax2 dx or x 3 e ax2 dx = 1 x 4 e ax2 dx = 3 π 8a 5/2 (a) We are considering the Maxwell velocity distribution function: 2πτ/m Homework Solutons Problem In solvng ths problem, we wll need to calculate some moments of the Gaussan dstrbuton. The brute-force method s to ntegrate by parts but there s a nce trck. The followng ntegrals

More information

x = , so that calculated

x = , so that calculated Stat 4, secton Sngle Factor ANOVA notes by Tm Plachowsk n chapter 8 we conducted hypothess tests n whch we compared a sngle sample s mean or proporton to some hypotheszed value Chapter 9 expanded ths to

More information

4.2 Chemical Driving Force

4.2 Chemical Driving Force 4.2. CHEMICL DRIVING FORCE 103 4.2 Chemcal Drvng Force second effect of a chemcal concentraton gradent on dffuson s to change the nature of the drvng force. Ths s because dffuson changes the bondng n a

More information

Implicit Integration Henyey Method

Implicit Integration Henyey Method Implct Integraton Henyey Method In realstc stellar evoluton codes nstead of a drect ntegraton usng for example the Runge-Kutta method one employs an teratve mplct technque. Ths s because the structure

More information

Thermodynamics and Gases

Thermodynamics and Gases hermodynamcs and Gases Last tme Knetc heory o Gases or smple (monatomc) gases Atomc nature o matter Demonstrate deal gas law Atomc knetc energy nternal energy Mean ree path and velocty dstrbutons From

More information

χ x B E (c) Figure 2.1.1: (a) a material particle in a body, (b) a place in space, (c) a configuration of the body

χ x B E (c) Figure 2.1.1: (a) a material particle in a body, (b) a place in space, (c) a configuration of the body Secton.. Moton.. The Materal Body and Moton hyscal materals n the real world are modeled usng an abstract mathematcal entty called a body. Ths body conssts of an nfnte number of materal partcles. Shown

More information

Markov Chain Monte Carlo (MCMC), Gibbs Sampling, Metropolis Algorithms, and Simulated Annealing Bioinformatics Course Supplement

Markov Chain Monte Carlo (MCMC), Gibbs Sampling, Metropolis Algorithms, and Simulated Annealing Bioinformatics Course Supplement Markov Chan Monte Carlo MCMC, Gbbs Samplng, Metropols Algorthms, and Smulated Annealng 2001 Bonformatcs Course Supplement SNU Bontellgence Lab http://bsnuackr/ Outlne! Markov Chan Monte Carlo MCMC! Metropols-Hastngs

More information

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:

More information

APPENDIX A Some Linear Algebra

APPENDIX A Some Linear Algebra APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,

More information

Einstein-Podolsky-Rosen Paradox

Einstein-Podolsky-Rosen Paradox H 45 Quantum Measurement and Spn Wnter 003 Ensten-odolsky-Rosen aradox The Ensten-odolsky-Rosen aradox s a gedanken experment desgned to show that quantum mechancs s an ncomplete descrpton of realty. The

More information

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle

More information

Thermodynamics and Kinetics of Solids 33. III. Statistical Thermodynamics. Â N i = N (5.3) N i. i =0. Â e i = E (5.4) has a maximum.

Thermodynamics and Kinetics of Solids 33. III. Statistical Thermodynamics. Â N i = N (5.3) N i. i =0. Â e i = E (5.4) has a maximum. hermodynamcs and Knetcs of Solds 33 III. Statstcal hermodynamcs 5. Statstcal reatment of hermodynamcs 5.1. Statstcs and Phenomenologcal hermodynamcs. Calculaton of the energetc state of each atomc or molecular

More information

Lecture 10 Support Vector Machines II

Lecture 10 Support Vector Machines II Lecture 10 Support Vector Machnes II 22 February 2016 Taylor B. Arnold Yale Statstcs STAT 365/665 1/28 Notes: Problem 3 s posted and due ths upcomng Frday There was an early bug n the fake-test data; fxed

More information

Equilibrium Statistical Mechanics

Equilibrium Statistical Mechanics Equlbrum Statstcal Mechancs Ref. Davdson, Statstcal Mechancs McGraw-Hll, 96 We wsh to study plasmas n equlbrum for at least two reasons: (a) Many tmes real plasmas are near true equlbrum, at least locally

More information

Conjugacy and the Exponential Family

Conjugacy and the Exponential Family CS281B/Stat241B: Advanced Topcs n Learnng & Decson Makng Conjugacy and the Exponental Famly Lecturer: Mchael I. Jordan Scrbes: Bran Mlch 1 Conjugacy In the prevous lecture, we saw conjugate prors for the

More information

Appendix II Summary of Important Equations

Appendix II Summary of Important Equations W. M. Whte Geochemstry Equatons of State: Ideal GasLaw: Coeffcent of Thermal Expanson: Compressblty: Van der Waals Equaton: The Laws of Thermdynamcs: Frst Law: Appendx II Summary of Important Equatons

More information