On Self-Avoiding Walks across n-dimensional Dice and Combinatorial Optimization: An Introduction

Size: px
Start display at page:

Download "On Self-Avoiding Walks across n-dimensional Dice and Combinatorial Optimization: An Introduction"

Transcription

1 On Sf-Avoiing Waks acoss n-dimnsiona Dic an ombinatoia Optimization: An Intoction Fanc Bgz ompt Scinc Raigh, N, USA Vsion: Sn Sp 5:5: EDT 3 ontnts Th fab -- Abot Gt an Hans saching fo ks (an abot Jok hiing th ks) Notation an finitions -- ombinatoia pobm: fin b fnction an (concatnat) cooinat tp(s) Th foing pobm amps: n pan A, pan B, an pan -- cooinat nighbohoo(s) fin b cooinat tp(s) -- a sf-avoiing wak (SAW): a sqnc of stps that chain a niq st of pivot cooinats Goba sach n SAW an pimnta sts -- potin foing on ctanga attic in D Smma an concsions Appni -- Epimnts with SAW in pogss: gaph {V, iq, IS, A}, abs, Goomb, masat, npp, jobs,...

2 Th Fab (abot Gt, Hans, an Jok who kps hiing th ks) -- Jok isgiss th fist st of ks as ab tickts in two ns: Gt an Hans sach fo ks b tiving thm fom th spctiv ns nti ach fins a tickt whos ab psnt th combination fo th ock on th oo to thi apatmnt. -- Onc Gt an Hans opn oos to thi apatmnts, ach stps onto a patfom (o a fac) of a hg patonic soi (pohon) -- so th think at fist In fact, Jok pac ach n not with a pohon bt with a hphon (sam nmb of facs, iffnt fac ajacnc stct) an hi anoth st of ks, this tim n th ab tickts, attach to fac cnts of ach hphon. -- Jok asks Gt an Hans to sach fo ks b waking thi spctiv hphons, fom fac-to-fac, nti th fin th a k to thi apatmnt. 3 Gt, Hans, an Jok (invisib bt omnipsnt) Majoing in ompt Scinc Majoing in an Sving Both a tning to thi ajacnt apatmnts (aft a pat) 4

3 Jok pacs ocks on oos an posts two ns with cs Gt Gt taks th tickt fom th n an if sh os not scc in opning th oo, sh pts th tickt into h hanbag an tivs anoth tickt. W sa that Gt is samping contnts of th n withot pacmnt: th pobabiit of Gt fining th coct tickt on tia k foows nifom istibtion, givn k maining tickts: pobabiit is /k, man va is (k + )/, an vaianc is (k )/. Gt an Hans iscov not on that ocks hav bn chang on both apatmnt oos with pnch-k ocks bt aso that mats that hi th ks w pac with two ns, ach containing a st 36 tickts. Each tickt has a pint ab with fiv igits in th fomat.:z (. is a bina/tna cooinat, z is a va) (^)*(3^) = 36 niq cooinats! On on ab opns Gt s oo, an on on opns Hans s oo. Th two sts a intica. Who gts in fist? Hans Hans, who ha a fw inks at th pat, taks th tickt an if h os not scc in opning th oo, tns th tickt to th n. W sa that Hans is samping contnts of th n with pacmnt: th pobabiit of Hans fining th coct tickt on tia k foows gomtic istibtion: pobabiit is (/n)( (/n)) k, man va is n, an vaianc is n ( (/n)). Th point of th fab so fa: w an that in a sach scnaios sch as scib h, on can impov th chanc of fist sccss b namica cing th sach spac aft ach tia. In th avag cas, Gt s sach, vn with hanbag of imit capacit, awas qis fw tias than Hans s. 5 On nting spctiv apatmnts, ach stps onto what appas as a patonic soi, bt on Jok knows what it is....:9.:.:9.:.:.:.:6.:5.:6.:5 Gt s Ent Hans s Ent () Upon nt, both a staning on a fat patfom (a fac) of an objct, with fo ajacnt facs soping ownwas -- an a th can s is th ab of th fac on which th a staning an th fo abs on th ajacnt facs. Each objct has 36 facs with 36 abs takn fom ach n, spctiv. () Jok asks thm to wak fom fac-to-fac an sach fo th ab that his th k to thi a oo (th k is now n th ab). H givs thm on, an on on, c abot th ab: th ab with va of o ss than has th k. 6

4 On Jok has a goba viw of this objct: a hphon Jok cats this viw as foows: Hass ank istanc fom th initia cooinat (th bottom vt) :9.:9.:9.:6.:5.:9.:9.:9.:9.:.:4.:.:.:9.:9.:9.:.:.:3.:3.:.:.:.:9.:9.:9.:.:4.:.:.:.:9.:6.:5.:.: fnction = BT.in. V = 36, E = vtics an abs a o -> R b fnction vas (fo cootp=bt, vt istibtion at ach ank ma pn on cooinit) -- H movs insi th hphon, fins th cnt of th fac, an attachs on n of a sting to th cnt an attachs th oth sting to th cnt of th ajacnt fac. -- H pats th pocss fo a facs an ths cats a gaph; in this cas an nict gaph with 36 facs an 4 gs. Not that th pohon with 36 facs, with ach fac having on 4 nighbos, has gs tota! -- H aso assigns fnction vas to ach cooinat: his choic of vas is pct to confon Gt an Hans in thi sach. -- To psnt this gaph in th pan, h fins a istanc btwn th cooinats assign to ach ab an maks a pojction of th gaph as a a gaph. -- This gaph (now a Hass gaph) is not visib to Gt an Hans, howv, th gaph nabs Jok to tac ach stp th wo mak ing thi sach. Tacing th sf-avoiing wak b Gt :9.:9.:9.:6.:5.:9.:9.:9.:9.:.:4.:.:.:9.:9.:9.:.:.:3.:3.:.:.:.:9.:9.:9.:.:4.:.:.:.:9.:6.:5.:.: Sia nmb fo Gt's k:.: Wak hains Un Hamitonian chain = soi wak, b Gt taks chain 5 stps = ott to fin Hans's chain k = soi an gn 3 stps chain h own? = tc... k. 4 6 vtics an abs a o -> R b fnction vas (fo cootp=bt, vt istibtion at ach ank ma pn on cooinit) Gt is a compt scinc majo an mmbs a ct abot Hamitonian waks in gaphs. Sh knows that sh is staning on on of 36 facs an that if sh associats ach fac with a vt in a gaph an th gs btwn ajacnt facs with gs in this gaph, sh can compt an mmb th path that visits ach fac on onc. In th wost cas, sh wi tak 35 stps to fin th k. Th poc sh ss to compt th cooinats fo ach stp in th Hamitonian wak is not as simp to pain as th poc s b Hans an pain nt. Sffic it to sa that fnction vas associat with ach cooinat hav no o in tmining th Hamitonian path in th gaph. An amp of Gt s wak, as tac b Jok, is shown on ft. Sh taks 5 stps to fin Hans s k an ns to contin fo a tota of 3 stps bfo fining h k. Th fist stp, fom.: to.:6, is a ibat stp in this Hamitonian wak a stp that Hans wo nv hav takn fom this stating position fo asons w pain nt.

5 Tacing th sf-avoiing wak b Hans B-nighbos T-nighbos.:9.:9.:9.:6.:5 Sia nmb fo Hans's k:.:.:9.:9.:9.:9.:.:4.:.:.:9.:9.:9.:.:.:3.:3.:.:.:.:9.:9.:9.:.:4.:.:.:.:9.:6.:5.:.: fnction = BT.in. V = 36, E = vtics an abs a o -> R b fnction vas (fo cootp=bt, vt istibtion at ach ank ma pn on cooinit) Hans s majo is an sving an taks th hint abot fnction vas sios. H viss a fw s bfo stating th wak: () mak th fac fom wh th wak stats with an as-to-spot tokn; at on in th pap, w ca this fac th initia pivot. () pob ach ajacnt fac that has not t bn mak an wit its va on a ist. (3) sct th ajacnt fac with th smast va, stp on this fac, ca it a cnt pivot, an mak it with a nw tokn. If th a sva facs with th sam va, mak a anom sction. (4) pat stp () fom th cnt pivot nti aching th tagt va. Th pocss of making th pivots ing th wak with tokns maks this wak sf-avoiing. Hans can n into a pobm with ths s in two cass: () h ns ot of tokns, () th wak is tapp. In ith cas, Hans stats th wak fom a nw fac. Hans can fin th tickt that his his pass-k in 3 stps o ss fom man initia positions. What w show is ik his ongst wak: stps. 9 Notation an finitions -- ombinatoia pobm: fin b fnction an (concatnat) cooinat tp(s) th foing pobm: amps n pan A, pan B, an pan -- cooinat nighbohoo(s) fin b cooinat tp(s) -- a sf-avoiing wak (SAW): a sqnc of stps that chain a niq st of pivot cooinats

6 A combinatoia pobm amp (th foing pobm, D) -- fin b fnction va(s) an (concatnat) cooinat tp(s) cooinat: concatnation of tp B(ina) an tp T(na). bbwwbwbwwb.ccc Two-coo configation (=, wight=5) onfomation in D (ctanga attic) c c b b w w b w b w w b c Fnction va: ngativ sm of bb bons = -4 A combinatoia pobm amp (th foing pobm) -- n pan A, pan B, an pan pan A (th taitiona foing pobm fomation) Inpt: a fi configation -- a bina cooinat of ngth an wight W Sach fo minimm ng confimation in E (fnction va): tn a bst-va confomation as a tna cooinat of ngth - pan B (aka as th invs foing pobm fomation) Inpt: a fi confomation -- a tna cooinat of ngth -, wight Wma Sach fo minimm ng configation in E (fnction va): tn a bst-va configation as a bina cooinat of ngth an wight <= Wma pan (os ma w b th fist sts n this fomation) Inpt: a anom configation AND a anom confomation, i.. a bina cooinat of ngth an wight Wma an a tna cooinat of ngth - Sach fo minimm ng E (fnction va): tn a bst-va configation AND confomation as a bst-va bina cooinat of ngth an wight <= Wma AND a bst-va tna cooinat of ngth -

7 ooinat nighbohoo(s) fin b cooinat tp(s) Pob th nighbohoo bfo making th nt stp! (caw bfo o wak).:9.:9.:9.:6.:5.:9.:9.:9.:9.:.:4.:.:.:9.:9.:9.:.:.:3.:3.:.:.:.:9.:9.:9.:.:4.:.:.:.:9.:6.:5.:.: B-nighbos T-nighbos 4 6 vtics an abs a o -> R b fnction vas (fo cootp=bt, vt istibtion at ach ank ma pn on cooinit) Th Hass gaph is th on intoc b Jok to tac waks b Gt an Hans. abs in this gaph a a concatnation of bina cooinats an tna cooinats, a tota of (^) * (3^) = 36 Each bina cooinat has awas a nighbohoo of (ott gs). Each tna cooinat has awas a nighbohoo that vais fom to 4 (ott gs). Fo amp, th cooinat. has bina an tna nighbos; th cooinat. has bina an 4 tna nighbos. 3 ooinat nighbohoo(s) fin b cooinat tp(s) (pobing n pan... th most gna cas) % fnc.bt.nighb.saw fohp. ib it coob.coot Bst n p coot NA NA NA NA NA NA NA NA NA NA NA NA NA. - + NA NA NA * NA NA NA NA NA <-- th nt stp to tak In this amp, = an th a (^)*(3^9) =,55,39 cooinats -- w cannot show thm in a Hass gaph -- w can on obsv th pobing of nighbohoo fom a tab sch as shown h. Inics ib an it that ass vas in bina an tna cooinats a awas anom pmt in o to pvnt biasing th o of choics fo bst fnction va. Fnction vas > psnt not on nfasib confomations bt aso th ativ v of nfasibiit. Th conts n an p pot th siz of th nighbohoo an th nmb pobs to fin ach va of Bst. Th pobing of 9 nighbos of an initia pivot cooinat. as, in this amp -- an in a sing stp, to an optima confomation with a tagt ng of

8 ---> A sf-avoiing wak (SAW): Hamitonian of ngth 4 -- a sqnc of stps that chain a niq st of pivot cooinats (a) - - : :4 : :6 :9 :3 : :5 : : : :4 : : :5 :3 ---> - - Hass ank istanc fom th bottom fac of th ic 3 4 : :5 : :4 : : : : :6 :3 : :4 : :9 :5 :3 Wak hains chain = soi b chain = ott chain = soi gn chain? = tc vtics an abs a o > R b fnction vas (fo cootp=b, vt istibtion at ach ank is binomia) Two sis of th sam coin: an instanc in -D in a nit c, sbsts of points on a gi in a attic, vss an instanc of a Hamitonian wak of th sam ngth in a Hass gaph fin b imnsion 4 (wt to bas ). Th wak in th nit c is contigos on with spct to cooinats fin in th attic. Simia, th wak in Hass gaphs is contigos on with spct to cooinats fin in th Hass gaph. 5 A sf-avoiing wak (SAW): Hamitonian of ngth 4 -- a sqnc of stps that chain a niq st of pivot cooinats (b) U = ft R = ight U = p D = own U R U R R U R R U D D Hass ank istanc fom th bottom fac of th ic : 3:9 3:6 3: :5 3: 3:4 3: :4 : :3 :3 : :5 : : Wak hains chain = soi b chain = ott chain = soi gn chain? = tc... R vtics an abs a o > R b fnction vas (fo cootp=q, vt istibtion at ach ank pns on cooinit) Two sis of th sam coin: an instanc in 3-D in a nit c, sbsts of points on a gi in a attic, vss an instanc of a Hamitonian wak of th sam ngth in a Hass gaph fin b imnsion (wt to bas 4). Th wak in th nit c is contigos on with spct to cooinats fin in th attic. Simia, th wak in Hass gaphs is contigos on with spct to cooinats fin in th Hass gaph. 6

9 A sf-avoiing wak (SAW): Hamitonian of ngth a sqnc of stps that chain a niq st of pivot cooinats (c) U = contin = ft U = p U Hass ank istanc fom th bottom fac of th ic :6 :5 :3 : :5 :4 : : :6 :4 :4 : : :9 :5 :3 : :3 : :9 : : : :6 : : : Wak hains chain = soi b chain = ott chain = soi gn chain? = tc vtics an abs a o > R b fnction vas (fo cootp=t, vt istibtion at ach ank pns on cooinit) Two sis of th sam coin: an instanc in 3-D in a nit c, sbsts of points on a gi in a attic, vss an instanc of a Hamitonian wak of th sam ngth in a Hass gaph fin b imnsion 3 (wt to bas 3). Th wak in th nit c is contigos on with spct to cooinats fin in th attic. Simia, th wak in Hass gaphs is contigos on with spct to cooinats fin in th Hass gaph. A sf-avoiing wak (SAW): amp of Hans s wak -- a sqnc of stps that chain a niq st of pivot cooinats Hass ank istanc fom th initia cooinat (th bottom vt) B-nighbos T-nighbos.:9.:9.:9.:6.:5 Sia nmb fo Hans's k:.:.:9.:9.:9.:9.:.:4.:.:.:9.:9.:9.:.:.:3.:3.:.:.:.:9.:9.:9.:.:4.:.:.:.:9.:6.:5.:.: fnction = BT.in. V = 36, E = vtics an abs a o -> R b fnction vas (fo cootp=bt, vt istibtion at ach ank ma pn on cooinit) Pobing fom th initia pivot.:9 th bst-va nighbo is a T- nighbo.: foow b a B-nighbo.: which tns p th Gt s k, so Hans ns to contin th wak. H, Hans wo ach his tagt in two stps if h choos.: as th nt pivot. Howv, b anom choic, his nt pivot is a T- nighbo.: fom wh h ns to contin th wak fo mo stps nti aching th pivot with tagt va that aso tns p his k:.:

10 Goba sach n SAW an Smma of pimnts Goba sach n SAW (an fnction, an cooinats) -- compt pso co -- tai: poc cooupat.saw Smma of pimnts (th potin foing pobm, D) -- Fo =, wight =, 3, 4, 5, -- Fo =, wight = ** -- Fo = 4, wight = ** -- Fo = 5, wight = 9** ** Aso fating significant impov sotions vss th sotions pot in [] 9 SAW in contt of goba sach (): tais in th pap A concpts in this pso co hav bn infoma intoc b Gt, Hans, an Jok ai.

11 SAW in contt of goba sach (): tais in th pap A concpts in this pso co hav bn infoma intoc b Gt, Hans, an Jok ai. =, w =,3,4 n pan ; initia cooinats wakngth mian man stv ma pobspstp mian man stv..3. bon_tagt niq_sotions 3 wakngth mian man stv ma pobspstp mian man stv bon_tagt niq_sotions 5 wakngth mian man stv ma pobspstp mian man stv bon_tagt niq_sotions 95 4 f q n c Fqnc Histogam of wight = ng = wakngth f q n c Fqnc 4 6 Histogam of wight = 3 ng = wakngth f q n c Fqnc 4 6 Histogam of wight = 4 ng = wakngth wight = : ng = -: wight = 3: ng = -: wight = 4: ng = -3:

12 =, w = 4,5, n pan ; initia cooinats wakngth mian man stv ma pobspstp mian man stv bon_tagt niq_sotions wakngth mian man stv ma pobspstp mian man stv bon_tagt niq_sotions 5 wakngth mian man stv ma pobspstp mian man stv bon_tagt niq_sotions 9 f q n c Fqnc Histogam of wight = 4 ng = wakngth f q n c Fqnc 4 6 Histogam of wight = 5 ng = wakngth f q n c Fqnc 4 6 Histogam of wight = ng = wakngth wight = 4: ng = -4: wight = 5: ng = -4: wight = : ng = -4: 3 =, w = 4 n pan ; initia cooinats wakngth mian man stv ma pobspstp mian man stv bon_tagt niq_sotions f q n c Fqnc Histogam of wight = 4 ng = wakngth Impotant obsvations fo this cas: -- on two niq sotions (fom initia cooinats) -- wakngth has amost ctain gomtic istibtion -- th avag wakngth to ach on of th two sotions n Hamitonian wak =.5 ( 3 9 ) = 5,3,4 wight = 4: ng = -4: -- th avag wakngth to ach on of th two sotions n th Hans s wak, aso a SAW, is,4.3 4

13 =, fom fnc, to qivant, to btt sotions statistics a bas on anom initia cooinats Pan A Pan Pan vabst = -9 bbsiz = vabst = -9 bbsiz = vabst = - bbsiz = <wakngth> =.5+4 (wost-cas = (9/)*(^)*(3^9) = = 4, fom fnc, to qivant, to btt sotions statistics a bas on anom initia cooinats Pan A vabst = -9 bbsiz = Pan vabst = -9 bbsiz = Pan 9 vabst = - bbsiz = <wakngth> = (wost-cas = (5/)*(^4)*(3^3) =

14 = 5, fom fnc, to qivant, to btt sotions statistics a bas on anom initia cooinats Tt... bas on th samp siz of 6 ath than Pan A vabst = - bbsiz = Pan 4 vabst = - bbsiz = 3 <wakngth> =.43+6 (wost-cas = (/6)*(^5)*(3^4) =.636+) Pan vabst = - bbsiz = oncsions an Ft Wok -- O pimnts with a SAW sov ais th pctation that th sotion of th potin foing pobm, wh th chain configation an its confimation a optimiz simtanos, ma b fasib at an accptab cost. -- Epimnts on potin foing pobm a bing pann aso fo tianga an hagona gis in - an 3-imnsions. -- W a fining SAW sovs to sca to v ag pobms in a nmb of iffnt omains n iffnt cooinat tps: -- ow atocoation bina sqnc (abs, aka in phsics as th apioic on-imnsiona Ising spin sstm with ong ang 4-spin intactions) -- gaph {vt cov, ciq, inpnnt st, ina aangmnt,...} -- optima Goomb (og) -- masat -- pasimon -- nmb patitioning pobm (npp) -- job sching pobm (jobs) -- cptogaph -- tc

The local orthonormal basis set (r,θ,φ) is related to the Cartesian system by:

The local orthonormal basis set (r,θ,φ) is related to the Cartesian system by: TIS in Sica Cooinats As not in t ast ct, an of t otntias tat w wi a wit a cnta otntias, aning tat t a jst fnctions of t istanc btwn a atic an so oint of oigin. In tis cas tn, (,, z as a t Coob otntia an

More information

Who is this Great Team? Nickname. Strangest Gift/Friend. Hometown. Best Teacher. Hobby. Travel Destination. 8 G People, Places & Possibilities

Who is this Great Team? Nickname. Strangest Gift/Friend. Hometown. Best Teacher. Hobby. Travel Destination. 8 G People, Places & Possibilities Who i thi Gt Tm? Exi Sh th foowing i of infomtion bot of with o tb o tm mt. Yo o not hv to wit n of it own. Yo wi b givn on 5 mint to omih thi tk. Stngt Gift/Fin Niknm Homtown Bt Th Hobb Tv Dtintion Robt

More information

The angle between L and the z-axis is found from

The angle between L and the z-axis is found from Poblm 6 This is not a ifficult poblm but it is a al pain to tansf it fom pap into Mathca I won't giv it to you on th quiz, but know how to o it fo th xam Poblm 6 S Figu 6 Th magnitu of L is L an th z-componnt

More information

CDS 101: Lecture 7.1 Loop Analysis of Feedback Systems

CDS 101: Lecture 7.1 Loop Analysis of Feedback Systems CDS : Lct 7. Loop Analsis of Fback Sstms Richa M. Ma Goals: Show how to compt clos loop stabilit fom opn loop poptis Dscib th Nqist stabilit cition fo stabilit of fback sstms Dfin gain an phas magin an

More information

Rectification and Depth Computation

Rectification and Depth Computation Dpatmnt of Comput Engnng Unvst of Cafona at Santa Cuz Rctfcaton an Dpth Computaton CMPE 64: mag Anass an Comput Vson Spng 0 Ha ao 4/6/0 mag cosponncs Dpatmnt of Comput Engnng Unvst of Cafona at Santa Cuz

More information

FI 3103 Quantum Physics

FI 3103 Quantum Physics 7//7 FI 33 Quantum Physics Axan A. Iskana Physics of Magntism an Photonics sach oup Institut Tknoogi Banung Schoing Equation in 3D Th Cnta Potntia Hyognic Atom 7//7 Schöing quation in 3D Fo a 3D pobm,

More information

CDS 110b: Lecture 8-1 Robust Stability

CDS 110b: Lecture 8-1 Robust Stability DS 0b: Lct 8- Robst Stabilit Richad M. Ma 3 Fba 006 Goals: Dscib mthods fo psnting nmodld dnamics Div conditions fo obst stabilit Rading: DFT, Sctions 4.-4.3 3 Fb 06 R. M. Ma, altch Gam lan: Robst fomanc

More information

Mid Year Examination F.4 Mathematics Module 1 (Calculus & Statistics) Suggested Solutions

Mid Year Examination F.4 Mathematics Module 1 (Calculus & Statistics) Suggested Solutions Mid Ya Eamination 3 F. Matmatics Modul (Calculus & Statistics) Suggstd Solutions Ma pp-: 3 maks - Ma pp- fo ac qustion: mak. - Sam typ of pp- would not b countd twic fom wol pap. - In any cas, no pp maks

More information

P a g e 5 1 of R e p o r t P B 4 / 0 9

P a g e 5 1 of R e p o r t P B 4 / 0 9 P a g e 5 1 of R e p o r t P B 4 / 0 9 J A R T a l s o c o n c l u d e d t h a t a l t h o u g h t h e i n t e n t o f N e l s o n s r e h a b i l i t a t i o n p l a n i s t o e n h a n c e c o n n e

More information

Differential Kinematics

Differential Kinematics Lctu Diffntia Kinmatic Acknowgmnt : Pof. Ouama Khatib, Robotic Laboato, tanfo Univit, UA Pof. Ha Aaa, AI Laboato, MIT, UA Guiing Qution In obotic appication, not on th poition an ointation, but th vocit

More information

Kinetics. Central Force Motion & Space Mechanics

Kinetics. Central Force Motion & Space Mechanics Kintics Cntal Foc Motion & Spac Mcanics Outlin Cntal Foc Motion Obital Mcanics Exampls Cntal-Foc Motion If a paticl tavls un t influnc of a foc tat as a lin of action ict towas a fix point, tn t motion

More information

T h e C S E T I P r o j e c t

T h e C S E T I P r o j e c t T h e P r o j e c t T H E P R O J E C T T A B L E O F C O N T E N T S A r t i c l e P a g e C o m p r e h e n s i v e A s s es s m e n t o f t h e U F O / E T I P h e n o m e n o n M a y 1 9 9 1 1 E T

More information

European and American options with a single payment of dividends. (About formula Roll, Geske & Whaley) Mark Ioffe. Abstract

European and American options with a single payment of dividends. (About formula Roll, Geske & Whaley) Mark Ioffe. Abstract 866 Uni Naions Plaza i 566 Nw Yo NY 7 Phon: + 3 355 Fa: + 4 668 info@gach.com www.gach.com Eoan an Amican oions wih a singl amn of ivins Abo fomla Roll Gs & Whal Ma Ioff Absac Th aicl ovis a ivaion of

More information

Self-Adjusting Top Trees

Self-Adjusting Top Trees Th Polm Sl-jsting Top Ts ynmi ts: ol: mintin n n-tx ost tht hngs o tim. link(,w): ts n g twn tis n w. t(,w): lts g (,w). pplition-spii t ssoit with gs n/o tis. ont xmpls: in minimm-wight g in th pth twn

More information

PLS-CADD DRAWING N IC TR EC EL L RA IVE ) R U AT H R ER 0. IDT FO P 9-1 W T OO -1 0 D EN C 0 E M ER C 3 FIN SE W SE DE EA PO /4 O 1 AY D E ) (N W AN N

PLS-CADD DRAWING N IC TR EC EL L RA IVE ) R U AT H R ER 0. IDT FO P 9-1 W T OO -1 0 D EN C 0 E M ER C 3 FIN SE W SE DE EA PO /4 O 1 AY D E ) (N W AN N A IV ) H 0. IT FO P 9-1 W O -1 0 C 0 M C FI S W S A PO /4 O 1 AY ) ( W A 7 F 4 H T A GH 1 27 IGO OU (B. G TI IS 1/4 X V -S TO G S /2 Y O O 1 A A T H W T 2 09 UT IV O M C S S TH T ) A PATO C A AY S S T

More information

A L A BA M A L A W R E V IE W

A L A BA M A L A W R E V IE W A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N

More information

Overview. 1 Recall: continuous-time Markov chains. 2 Transient distribution. 3 Uniformization. 4 Strong and weak bisimulation

Overview. 1 Recall: continuous-time Markov chains. 2 Transient distribution. 3 Uniformization. 4 Strong and weak bisimulation Rcall: continuous-tim Makov chains Modling and Vification of Pobabilistic Systms Joost-Pit Katon Lhstuhl fü Infomatik 2 Softwa Modling and Vification Goup http://movs.wth-aachn.d/taching/ws-89/movp8/ Dcmb

More information

GUIDE FOR SUPERVISORS 1. This event runs most efficiently with two to four extra volunteers to help proctor students and grade the student

GUIDE FOR SUPERVISORS 1. This event runs most efficiently with two to four extra volunteers to help proctor students and grade the student GUIDE FOR SUPERVISORS 1. This vn uns mos fficinly wih wo o fou xa voluns o hlp poco sudns and gad h sudn scoshs. 2. EVENT PARAMETERS: Th vn supviso will povid scoshs. You will nd o bing a im, pns and pncils

More information

Lecture 3.2: Cosets. Matthew Macauley. Department of Mathematical Sciences Clemson University

Lecture 3.2: Cosets. Matthew Macauley. Department of Mathematical Sciences Clemson University Lctu 3.2: Costs Matthw Macauly Dpatmnt o Mathmatical Scincs Clmson Univsity http://www.math.clmson.du/~macaul/ Math 4120, Modn Algba M. Macauly (Clmson) Lctu 3.2: Costs Math 4120, Modn Algba 1 / 11 Ovviw

More information

Merging to ordered sequences. Efficient (Parallel) Sorting. Merging (cont.)

Merging to ordered sequences. Efficient (Parallel) Sorting. Merging (cont.) Efficient (Paae) Soting One of the most fequent opeations pefomed by computes is oganising (soting) data The access to soted data is moe convenient/faste Thee is a constant need fo good soting agoithms

More information

ORBITAL TO GEOCENTRIC EQUATORIAL COORDINATE SYSTEM TRANSFORMATION. x y z. x y z GEOCENTRIC EQUTORIAL TO ROTATING COORDINATE SYSTEM TRANSFORMATION

ORBITAL TO GEOCENTRIC EQUATORIAL COORDINATE SYSTEM TRANSFORMATION. x y z. x y z GEOCENTRIC EQUTORIAL TO ROTATING COORDINATE SYSTEM TRANSFORMATION ORITL TO GEOCENTRIC EQUTORIL COORDINTE SYSTEM TRNSFORMTION z i i i = (coωcoω in Ωcoiinω) (in Ωcoω + coωcoiinω) iniinω ( coωinω in Ωcoi coω) ( in Ωinω + coωcoicoω) in icoω in Ωini coωini coi z o o o GEOCENTRIC

More information

Chemistry 342 Spring, The Hydrogen Atom.

Chemistry 342 Spring, The Hydrogen Atom. Th Hyrogn Ato. Th quation. Th first quation w want to sov is φ This quation is of faiiar for; rca that for th fr partic, w ha ψ x for which th soution is Sinc k ψ ψ(x) a cos kx a / k sin kx ± ix cos x

More information

GRAVITATION. (d) If a spring balance having frequency f is taken on moon (having g = g / 6) it will have a frequency of (a) 6f (b) f / 6

GRAVITATION. (d) If a spring balance having frequency f is taken on moon (having g = g / 6) it will have a frequency of (a) 6f (b) f / 6 GVITTION 1. Two satllits and o ound a plant P in cicula obits havin adii 4 and spctivly. If th spd of th satllit is V, th spd of th satllit will b 1 V 6 V 4V V. Th scap vlocity on th sufac of th ath is

More information

Partial Fraction Expansion

Partial Fraction Expansion Paial Facion Expanion Whn ying o find h inv Laplac anfom o inv z anfom i i hlpfl o b abl o bak a complicad aio of wo polynomial ino fom ha a on h Laplac Tanfom o z anfom abl. W will illa h ing Laplac anfom.

More information

Executive Committee and Officers ( )

Executive Committee and Officers ( ) Gifted and Talented International V o l u m e 2 4, N u m b e r 2, D e c e m b e r, 2 0 0 9. G i f t e d a n d T a l e n t e d I n t e r n a t i o n a2 l 4 ( 2), D e c e m b e r, 2 0 0 9. 1 T h e W o r

More information

Shape parameterization

Shape parameterization Shap paatization λ ( θ, φ) α ( θ ) λµ λµ, φ λ µ λ axially sytic quaupol axially sytic octupol λ α, α ± α ± λ α, α ±,, α, α ±, Inian Institut of Tchnology opa Hans-Jügn Wollshi - 7 Octupol collctivity coupling

More information

VISUALIZATION OF TRIVARIATE NURBS VOLUMES

VISUALIZATION OF TRIVARIATE NURBS VOLUMES ISUALIZATIO OF TRIARIATE URS OLUMES SAMUELČÍK Mat SK Abstact. I ths pap fcs patca st f f-f bcts a ts sazat. W xt appach f g cs a sfacs a ppa taat s bas z a -sp xpsss. O a ga s t saz g paatc s. Th sazat

More information

Trade Patterns, Production networks, and Trade and employment in the Asia-US region

Trade Patterns, Production networks, and Trade and employment in the Asia-US region Trade Patterns, Production networks, and Trade and employment in the Asia-U region atoshi Inomata Institute of Developing Economies ETRO Development of cross-national production linkages, 1985-2005 1985

More information

Electric Potential. Outline. Potential Energy per Unit Charge. Potential Difference. Potential Energy Difference. Quiz Thursday on Chapters 23, 24.

Electric Potential. Outline. Potential Energy per Unit Charge. Potential Difference. Potential Energy Difference. Quiz Thursday on Chapters 23, 24. lectic otential Quiz Thusay on Chaptes 3, 4. Outline otential as enegy pe unit chage. Thi fom of Coulomb s Law. elations between fiel an potential. otential negy pe Unit Chage Just as the fiel is efine

More information

Physics 111. Lecture 38 (Walker: ) Phase Change Latent Heat. May 6, The Three Basic Phases of Matter. Solid Liquid Gas

Physics 111. Lecture 38 (Walker: ) Phase Change Latent Heat. May 6, The Three Basic Phases of Matter. Solid Liquid Gas Physics 111 Lctu 38 (Walk: 17.4-5) Phas Chang May 6, 2009 Lctu 38 1/26 Th Th Basic Phass of Matt Solid Liquid Gas Squnc of incasing molcul motion (and ngy) Lctu 38 2/26 If a liquid is put into a sald contain

More information

GRAVITATION 4) R. max. 2 ..(1) ...(2)

GRAVITATION 4) R. max. 2 ..(1) ...(2) GAVITATION PVIOUS AMCT QUSTIONS NGINING. A body is pojctd vtically upwads fom th sufac of th ath with a vlocity qual to half th scap vlocity. If is th adius of th ath, maximum hight attaind by th body

More information

Gantry-Tau A New Three Degrees of Freedom Parallel Kinematic Robot

Gantry-Tau A New Three Degrees of Freedom Parallel Kinematic Robot Gant-au A w h Dg of Fom Paa Kinmatic Robot La Johannon, Vikto Bbuk, ogn Bogåh. Dpatmnt of Machin an Vhic Stm Cham Univit of chnoog, 4 9 Götbog, Swn -mai: a.johannon@m.cham.. Dpatmnt of Machin an Vhic Stm

More information

P a g e 3 6 of R e p o r t P B 4 / 0 9

P a g e 3 6 of R e p o r t P B 4 / 0 9 P a g e 3 6 of R e p o r t P B 4 / 0 9 p r o t e c t h um a n h e a l t h a n d p r o p e r t y fr om t h e d a n g e rs i n h e r e n t i n m i n i n g o p e r a t i o n s s u c h a s a q u a r r y. J

More information

Homework 1 Solutions CSE 101 Summer 2017

Homework 1 Solutions CSE 101 Summer 2017 Homewok 1 Soutions CSE 101 Summe 2017 1 Waming Up 1.1 Pobem and Pobem Instance Find the smaest numbe in an aay of n integes a 1, a 2,..., a n. What is the input? What is the output? Is this a pobem o a

More information

Instruction Execution

Instruction Execution MIPS Piplining Cpt280 D Cuti Nlon Intuction Excution C intuction: x = a + b; Ambly intuction: a a,b,x Stp 1: Stp 2: Stp 3: Stp : Stp 5: Stp 6: Ftch th intuction Dtmin it i an a intuction Ftch th ata a

More information

Housing Market Monitor

Housing Market Monitor M O O D Y È S A N A L Y T I C S H o u s i n g M a r k e t M o n i t o r I N C O R P O R A T I N G D A T A A S O F N O V E M B E R İ Ī Ĭ Ĭ E x e c u t i v e S u m m a r y E x e c u t i v e S u m m a r y

More information

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent oucms Couga Gas Mchal Kazha (6.657) Ifomao abou h Sma (6.757) hav b pos ol: hp://www.cs.hu.u/~msha Tch Spcs: o M o Tusay afoo. o Two paps scuss ach w. o Vos fo w s caa paps u by Thusay vg. Oul Rvw of Sps

More information

Math-3. Lesson 5-6 Euler s Number e Logarithmic and Exponential Modeling (Newton s Law of Cooling)

Math-3. Lesson 5-6 Euler s Number e Logarithmic and Exponential Modeling (Newton s Law of Cooling) Math-3 Lsson 5-6 Eulr s Numbr Logarithmic and Eponntial Modling (Nwton s Law of Cooling) f ( ) What is th numbr? is th horizontal asymptot of th function: 1 1 ~ 2.718... On my 3rd submarin (USS Springfild,

More information

Fourier transforms (Chapter 15) Fourier integrals are generalizations of Fourier series. The series representation

Fourier transforms (Chapter 15) Fourier integrals are generalizations of Fourier series. The series representation Pof. D. I. Nass Phys57 (T-3) Sptmb 8, 03 Foui_Tansf_phys57_T3 Foui tansfoms (Chapt 5) Foui intgals a gnalizations of Foui sis. Th sis psntation a0 nπx nπx f ( x) = + [ an cos + bn sin ] n = of a function

More information

E F. and H v. or A r and F r are dual of each other.

E F. and H v. or A r and F r are dual of each other. A Duality Thom: Consid th following quations as an xampl = A = F μ ε H A E A = jωa j ωμε A + β A = μ J μ A x y, z = J, y, z 4π E F ( A = jω F j ( F j β H F ωμε F + β F = ε M jβ ε F x, y, z = M, y, z 4π

More information

2011 HSC Mathematics Extension 1 Solutions

2011 HSC Mathematics Extension 1 Solutions 0 HSC Mathmatics Etsio Solutios Qustio, (a) A B 9, (b) : 9, P 5 0, 5 5 7, si cos si d d by th quotit ul si (c) 0 si cos si si cos si 0 0 () I u du d u cos d u.du cos (f) f l Now 0 fo all l l fo all Rag

More information

Period vs. Length of a Pendulum

Period vs. Length of a Pendulum Gaphcal Mtho n Phc Gaph Intptaton an Lnazaton Pat 1: Gaphng Tchnqu In Phc w u a vat of tool nclung wo, quaton, an gaph to mak mol of th moton of objct an th ntacton btwn objct n a tm. Gaph a on of th bt

More information

PHYS 705: Classical Mechanics. Central Force Problems II

PHYS 705: Classical Mechanics. Central Force Problems II PHYS 75: Cassica Mechanics Centa Foce Pobems II Obits in Centa Foce Pobem Sppose we e inteested moe in the shape of the obit, (not necessay the time evotion) Then, a sotion fo = () o = () wod be moe sef!

More information

(, ) which is a positively sloping curve showing (Y,r) for which the money market is in equilibrium. The P = (1.4)

(, ) which is a positively sloping curve showing (Y,r) for which the money market is in equilibrium. The P = (1.4) ots lctu Th IS/LM modl fo an opn conomy is basd on a fixd pic lvl (vy sticky pics) and consists of a goods makt and a mony makt. Th goods makt is Y C+ I + G+ X εq (.) E SEK wh ε = is th al xchang at, E

More information

OH BOY! Story. N a r r a t iv e a n d o bj e c t s th ea t e r Fo r a l l a g e s, fr o m th e a ge of 9

OH BOY! Story. N a r r a t iv e a n d o bj e c t s th ea t e r Fo r a l l a g e s, fr o m th e a ge of 9 OH BOY! O h Boy!, was or igin a lly cr eat ed in F r en ch an d was a m a jor s u cc ess on t h e Fr en ch st a ge f or young au di enc es. It h a s b een s een by ap pr ox i ma t ely 175,000 sp ect at

More information

Helping you learn to save. Pigby s tips and tricks

Helping you learn to save. Pigby s tips and tricks Hlpg yu lan t av Pigby tip and tick Hlpg vy littl av Pigby ha bn tachg hi find all abut ny and hw t av f what ty want. Tuffl i avg f a nw tappy bubbl d and Pi can t wait t b abl t buy nw il pat. Pigby

More information

Extinction Ratio and Power Penalty

Extinction Ratio and Power Penalty Application Not: HFAN-.. Rv.; 4/8 Extinction Ratio and ow nalty AVALABLE Backgound Extinction atio is an impotant paamt includd in th spcifications of most fib-optic tanscivs. h pupos of this application

More information

Course Updates. Reminders: 1) Assignment #10 due next Wednesday. 2) Midterm #2 take-home Friday. 3) Quiz # 5 next week. 4) Inductance, Inductors, RLC

Course Updates. Reminders: 1) Assignment #10 due next Wednesday. 2) Midterm #2 take-home Friday. 3) Quiz # 5 next week. 4) Inductance, Inductors, RLC Couse Updates http://www.phys.hawaii.edu/~vane/phys7-sp10/physics7.htm Remindes: 1) Assignment #10 due next Wednesday ) Midtem # take-home Fiday 3) Quiz # 5 next week 4) Inductance, Inductos, RLC Mutua

More information

176 5 t h Fl oo r. 337 P o ly me r Ma te ri al s

176 5 t h Fl oo r. 337 P o ly me r Ma te ri al s A g la di ou s F. L. 462 E l ec tr on ic D ev el op me nt A i ng er A.W.S. 371 C. A. M. A l ex an de r 236 A d mi ni st ra ti on R. H. (M rs ) A n dr ew s P. V. 326 O p ti ca l Tr an sm is si on A p ps

More information

L...,,...lllM" l)-""" Si_...,...

L...,,...lllM l)- Si_...,... > 1 122005 14:8 S BF 0tt n FC DRE RE FOR C YER 2004 80?8 P01/ Rc t > uc s cttm tsus H D11) Rqc(tdk ;) wm1111t 4 (d m D m jud: US

More information

Solutions to Supplementary Problems

Solutions to Supplementary Problems Solution to Supplmntay Poblm Chapt Solution. Fomula (.4): g d G + g : E ping th void atio: G d 2.7 9.8 0.56 (56%) 7 mg Fomula (.6): S Fomula (.40): g d E ping at contnt: S m G 0.56 0.5 0. (%) 2.7 + m E

More information

Seidel s Trapezoidal Partitioning Algorithm

Seidel s Trapezoidal Partitioning Algorithm CS68: Geometic Agoithms Handout #6 Design and Anaysis Oigina Handout #6 Stanfod Univesity Tuesday, 5 Febuay 99 Oigina Lectue #7: 30 Januay 99 Topics: Seide s Tapezoida Patitioning Agoithm Scibe: Michae

More information

GMm. 10a-0. Satellite Motion. GMm U (r) - U (r ) how high does it go? Escape velocity. Kepler s 2nd Law ::= Areas Angular Mom. Conservation!!!!

GMm. 10a-0. Satellite Motion. GMm U (r) - U (r ) how high does it go? Escape velocity. Kepler s 2nd Law ::= Areas Angular Mom. Conservation!!!! F Satllt Moton 10a-0 U () - U ( ) 0 f ow g dos t go? scap locty Kpl s nd Law ::= Aas Angula Mo. Consaton!!!! Nwton s Unsal Law of Gaty 10a-1 M F F 1) F acts along t ln connctng t cnts of objcts Cntal Foc

More information

Neural Networks The ADALINE

Neural Networks The ADALINE Lat Lctu Summay Intouction to ua to Bioogica uon Atificia uon McCuoch an itt LU Ronbatt cton Aan Bnaino, a@i.it.ut.t Machin Laning, 9/ ua to h ADALI M A C H I L A R I G 9 / cton Limitation cton aning u

More information

be two non-empty sets. Then S is called a semigroup if it satisfies the conditions

be two non-empty sets. Then S is called a semigroup if it satisfies the conditions UZZY SOT GMM EGU SEMIGOUPS V. Chinndi* & K. lmozhi** * ssocit Pofsso Dtmnt of Mthmtics nnmli Univsity nnmling Tmilnd ** Dtmnt of Mthmtics nnmli Univsity nnmling Tmilnd bstct: In this w hv discssd bot th

More information

ME 522 PRINCIPLES OF ROBOTICS. FIRST MIDTERM EXAMINATION April 19, M. Kemal Özgören

ME 522 PRINCIPLES OF ROBOTICS. FIRST MIDTERM EXAMINATION April 19, M. Kemal Özgören ME 522 PINCIPLES OF OBOTICS FIST MIDTEM EXAMINATION April 9, 202 Nm Lst Nm M. Kml Özgörn 2 4 60 40 40 0 80 250 USEFUL FOMULAS cos( ) cos cos sin sin sin( ) sin cos cos sin sin y/ r, cos x/ r, r 0 tn 2(

More information

Estimation of a Random Variable

Estimation of a Random Variable Estimation of a andom Vaiabl Obsv and stimat. ˆ is an stimat of. ζ : outcom Estimation ul ˆ Sampl Spac Eampl: : Pson s Hight, : Wight. : Ailin Company s Stock Pic, : Cud Oil Pic. Cost of Estimation Eo

More information

CBSE-XII-2013 EXAMINATION (MATHEMATICS) The value of determinant of skew symmetric matrix of odd order is always equal to zero.

CBSE-XII-2013 EXAMINATION (MATHEMATICS) The value of determinant of skew symmetric matrix of odd order is always equal to zero. CBSE-XII- EXAMINATION (MATHEMATICS) Cod : 6/ Gnal Instuctions : (i) All qustions a compulso. (ii) Th qustion pap consists of 9 qustions dividd into th sctions A, B and C. Sction A compiss of qustions of

More information

APPROX. OVERALL 8 3/8" DISCHARGE 1 C L PUMP SUCTION

APPROX. OVERALL 8 3/8 DISCHARGE 1 C L PUMP SUCTION SOIS-HNIN WSTWT PUPS Z Z Y Y OUTIN WIN TYP H VISION SS- OTTION & POSITION X. IST O QUIPNT UNISH H_ PUP(S) T O P T T. TH WITH ISCH POSITION OU /" IN CONNCTIONS COUPIN U POW PPOX. OV WITH ISCH POSITION CH

More information

What Makes Production System Design Hard?

What Makes Production System Design Hard? What Maks Poduction Systm Dsign Had? 1. Things not always wh you want thm whn you want thm wh tanspot and location logistics whn invntoy schduling and poduction planning 2. Rsoucs a lumpy minimum ffctiv

More information

Midterm Exam. CS/ECE 181B Intro to Computer Vision. February 13, :30-4:45pm

Midterm Exam. CS/ECE 181B Intro to Computer Vision. February 13, :30-4:45pm Nam: Midtm am CS/C 8B Into to Comput Vision Fbua, 7 :-4:45pm las spa ouslvs to th dg possibl so that studnts a vnl distibutd thoughout th oom. his is a losd-boo tst. h a also a fw pags of quations, t.

More information

CS 491 G Combinatorial Optimization

CS 491 G Combinatorial Optimization CS 49 G Cobinatorial Optiization Lctur Nots Junhui Jia. Maiu Flow Probls Now lt us iscuss or tails on aiu low probls. Thor. A asibl low is aiu i an only i thr is no -augnting path. Proo: Lt P = A asibl

More information

How!do!humans!combine!sounds!into!an! infinite!number!of!utterances? How!do!they!use!these!utterances!!to! communicate!and!express!meaning?

How!do!humans!combine!sounds!into!an! infinite!number!of!utterances? How!do!they!use!these!utterances!!to! communicate!and!express!meaning? Linguistics How!o!humans!combin!s!into!an! H h bi i infinit!numb!of!uttancs? Supcomputing an Linguistics Kis Hyln Univsity of Luvn RU Quantitativ Lxicology an Vaiational Linguistics Linguistics Linguistics

More information

( ) ( ) ( ) 2011 HSC Mathematics Solutions ( 6) ( ) ( ) ( ) π π. αβ = = 2. α β αβ. Question 1. (iii) 1 1 β + (a) (4 sig. fig.

( ) ( ) ( ) 2011 HSC Mathematics Solutions ( 6) ( ) ( ) ( ) π π. αβ = = 2. α β αβ. Question 1. (iii) 1 1 β + (a) (4 sig. fig. HS Mathmatics Solutios Qustio.778.78 ( sig. fig.) (b) (c) ( )( + ) + + + + d d (d) l ( ) () 8 6 (f) + + + + ( ) ( ) (iii) β + + α α β αβ 6 (b) si π si π π π +,π π π, (c) y + dy + d 8+ At : y + (,) dy 8(

More information

Hydrogen atom. Energy levels and wave functions Orbital momentum, electron spin and nuclear spin Fine and hyperfine interaction Hydrogen orbitals

Hydrogen atom. Energy levels and wave functions Orbital momentum, electron spin and nuclear spin Fine and hyperfine interaction Hydrogen orbitals Hydogn atom Engy lvls and wav functions Obital momntum, lcton spin and nucla spin Fin and hypfin intaction Hydogn obitals Hydogn atom A finmnt of th Rydbg constant: R ~ 109 737.3156841 cm -1 A hydogn mas

More information

I N A C O M P L E X W O R L D

I N A C O M P L E X W O R L D IS L A M I C E C O N O M I C S I N A C O M P L E X W O R L D E x p l o r a t i o n s i n A g-b eanste d S i m u l a t i o n S a m i A l-s u w a i l e m 1 4 2 9 H 2 0 0 8 I s l a m i c D e v e l o p m e

More information

Math 34A. Final Review

Math 34A. Final Review Math A Final Rviw 1) Us th graph of y10 to find approimat valus: a) 50 0. b) y (0.65) solution for part a) first writ an quation: 50 0. now tak th logarithm of both sids: log() log(50 0. ) pand th right

More information

TMMI37, vt2, Lecture 8; Introductory 2-dimensional elastostatics; cont.

TMMI37, vt2, Lecture 8; Introductory 2-dimensional elastostatics; cont. Lctr 8; ntrodctor 2-dimnsional lastostatics; cont. (modifid 23--3) ntrodctor 2-dimnsional lastostatics; cont. W will now contin or std of 2-dim. lastostatics, and focs on a somwhat mor adancd lmnt thn

More information

Coordinate Geometry. = k2 e 2. 1 e + x. 1 e. ke ) 2. We now write = a, and shift the origin to the point (a, 0). Referred to

Coordinate Geometry. = k2 e 2. 1 e + x. 1 e. ke ) 2. We now write = a, and shift the origin to the point (a, 0). Referred to Coodinate Geomet Conic sections These ae pane cuves which can be descibed as the intesection of a cone with panes oiented in vaious diections. It can be demonstated that the ocus of a point which moves

More information

The Real Hydrogen Atom

The Real Hydrogen Atom T Ra Hydog Ato ov ad i fist od gt iddt of :.6V a us tubatio toy to dti: agti ffts si-obit ad yfi -A ativisti otios Aso av ab sift du to to sfitatio. Nd QD Dia q. ad dds o H wavfutio at sou of ti fid. Vy

More information

Lecture 19: Free Energies in Modern Computational Statistical Thermodynamics: WHAM and Related Methods

Lecture 19: Free Energies in Modern Computational Statistical Thermodynamics: WHAM and Related Methods Statistical Thrmodynamics Lctur 19: Fr Enrgis in Modrn Computational Statistical Thrmodynamics: WHAM and Rlatd Mthods Dr. Ronald M. Lvy ronlvy@tmpl.du Dfinitions Canonical nsmbl: A N, V,T = k B T ln Q

More information

Outline. Reinforcement Learning. What is RL? Reinforcement learning is learning what to do so as to maximize a numerical reward signal

Outline. Reinforcement Learning. What is RL? Reinforcement learning is learning what to do so as to maximize a numerical reward signal Otine Reinfocement Leaning Jne, 005 CS 486/686 Univesity of Wateoo Rsse & Novig Sect.-. What is einfocement eaning Tempoa-Diffeence eaning Q-eaning Machine Leaning Spevised Leaning Teache tes eane what

More information

2008 AP Calculus BC Multiple Choice Exam

2008 AP Calculus BC Multiple Choice Exam 008 AP Multipl Choic Eam Nam 008 AP Calculus BC Multipl Choic Eam Sction No Calculator Activ AP Calculus 008 BC Multipl Choic. At tim t 0, a particl moving in th -plan is th acclration vctor of th particl

More information

Load Equations. So let s look at a single machine connected to an infinite bus, as illustrated in Fig. 1 below.

Load Equations. So let s look at a single machine connected to an infinite bus, as illustrated in Fig. 1 below. oa Euatons Thoughout all of chapt 4, ou focus s on th machn tslf, thfo w wll only pfom a y smpl tatmnt of th ntwok n o to s a complt mol. W o that h, but alz that w wll tun to ths ssu n Chapt 9. So lt

More information

Credits. May Enhanced photo from clipart.com. June Enhanced photo from NASA. July Composite of photos from clipart.com.

Credits. May Enhanced photo from clipart.com. June Enhanced photo from NASA. July Composite of photos from clipart.com. 04 Cdits All spac photos cam fom NASA wbsit and hav bn nhancd. A dsciption of th photo is givn whn availabl. Imag Cdit: NASA, NOAO, ESA and Th Hubbl Hitag Tam (STScI/AURA) All oth photos w takn fom clipat.com,

More information

How to represent a joint, or a marginal distribution?

How to represent a joint, or a marginal distribution? School o Cou Scinc obabilisic Gahical ols Aoia Innc on Calo hos ic ing Lcu 8 Novb 9 2009 Raing ic ing @ CU 2005-2009 How o sn a join o a aginal isibuion? Clos-o snaion.g. Sal-bas snaion ic ing @ CU 2005-2009

More information

Y 0. Standing Wave Interference between the incident & reflected waves Standing wave. A string with one end fixed on a wall

Y 0. Standing Wave Interference between the incident & reflected waves Standing wave. A string with one end fixed on a wall Staning Wav Intrfrnc btwn th incint & rflct wavs Staning wav A string with on n fix on a wall Incint: y, t) Y cos( t ) 1( Y 1 ( ) Y (St th incint wav s phas to b, i.., Y + ral & positiv.) Rflct: y, t)

More information

Solid state physics. Lecture 3: chemical bonding. Prof. Dr. U. Pietsch

Solid state physics. Lecture 3: chemical bonding. Prof. Dr. U. Pietsch Solid stat physics Lctu 3: chmical bonding Pof. D. U. Pitsch Elcton chag dnsity distibution fom -ay diffaction data F kp ik dk h k l i Fi H p H; H hkl V a h k l Elctonic chag dnsity of silicon Valnc chag

More information

Date: Use the code to write each homophone. The first one has been for you. Handwriting and Vocabulary L1

Date: Use the code to write each homophone. The first one has been for you. Handwriting and Vocabulary L1 Wco to E pnisns g! x Hping you chid buid ssnti skis is sy! Ths tch-ppovd ctivitis hv bn spciy dvopd to k ning both ccssib nd njoyb. On ch pg, you find: hoophons Focus ski Th focus of ch ctivity pg is cy

More information

Bayesian Decision Theory

Bayesian Decision Theory Baysian Dcision Thory Baysian Dcision Thory Know probabiity distribution of th catgoris Amost nvr th cas in ra if! Nvrthss usfu sinc othr cass can b rducd to this on aftr som work Do not vn nd training

More information

Examples and applications on SSSP and MST

Examples and applications on SSSP and MST Exampls an applications on SSSP an MST Dan (Doris) H & Junhao Gan ITEE Univrsity of Qunslan COMP3506/7505, Uni of Qunslan Exampls an applications on SSSP an MST Dijkstra s Algorithm Th algorithm solvs

More information

Superposition. Thinning

Superposition. Thinning Suprposition STAT253/317 Wintr 213 Lctur 11 Yibi Huang Fbruary 1, 213 5.3 Th Poisson Procsss 5.4 Gnralizations of th Poisson Procsss Th sum of two indpndnt Poisson procsss with rspctiv rats λ 1 and λ 2,

More information

Mutual Inductance. If current i 1 is time varying, then the Φ B2 flux is varying and this induces an emf ε 2 in coil 2, the emf is

Mutual Inductance. If current i 1 is time varying, then the Φ B2 flux is varying and this induces an emf ε 2 in coil 2, the emf is Mutua Inductance If we have a constant cuent i in coi, a constant magnetic fied is ceated and this poduces a constant magnetic fux in coi. Since the Φ B is constant, thee O induced cuent in coi. If cuent

More information

Integral Control via Bias Estimation

Integral Control via Bias Estimation 1 Integal Contol via Bias stimation Consie the sstem ẋ = A + B +, R n, R p, R m = C +, R q whee is an nknown constant vecto. It is possible to view as a step istbance: (t) = 0 1(t). (If in fact (t) vaies

More information

Mon. Tues. Wed. Lab Fri Electric and Rest Energy

Mon. Tues. Wed. Lab Fri Electric and Rest Energy Mon. Tus. Wd. Lab Fi. 6.4-.7 lctic and Rst ngy 7.-.4 Macoscoic ngy Quiz 6 L6 Wok and ngy 7.5-.9 ngy Tansf R 6. P6, HW6: P s 58, 59, 9, 99(a-c), 05(a-c) R 7.a bing lato, sathon, ad, lato R 7.b v. i xal

More information

CHAPTER 5 CIRCULAR MOTION

CHAPTER 5 CIRCULAR MOTION CHAPTER 5 CIRCULAR MOTION and GRAVITATION 5.1 CENTRIPETAL FORCE It is known that if a paticl mos with constant spd in a cicula path of adius, it acquis a cntiptal acclation du to th chang in th diction

More information

8 - GRAVITATION Page 1

8 - GRAVITATION Page 1 8 GAVITATION Pag 1 Intoduction Ptolmy, in scond cntuy, gav gocntic thoy of plantay motion in which th Eath is considd stationay at th cnt of th univs and all th stas and th plants including th Sun volving

More information

STATISTICAL MECHANICS OF DIATOMIC GASES

STATISTICAL MECHANICS OF DIATOMIC GASES Pof. D. I. ass Phys54 7 -Ma-8 Diatomic_Gas (Ashly H. Cat chapt 5) SAISICAL MECHAICS OF DIAOMIC GASES - Fo monatomic gas whos molculs hav th dgs of fdom of tanslatoy motion th intnal u 3 ngy and th spcific

More information

Agenda Rationale for ETG S eek ing I d eas ETG fram ew ork and res u lts 2

Agenda Rationale for ETG S eek ing I d eas ETG fram ew ork and res u lts 2 Internal Innovation @ C is c o 2 0 0 6 C i s c o S y s t e m s, I n c. A l l r i g h t s r e s e r v e d. C i s c o C o n f i d e n t i a l 1 Agenda Rationale for ETG S eek ing I d eas ETG fram ew ork

More information

o Alphabet Recitation

o Alphabet Recitation Letter-Sound Inventory (Record Sheet #1) 5-11 o Alphabet Recitation o Alphabet Recitation a b c d e f 9 h a b c d e f 9 h j k m n 0 p q k m n 0 p q r s t u v w x y z r s t u v w x y z 0 Upper Case Letter

More information

Homework Set 3 Physics 319 Classical Mechanics

Homework Set 3 Physics 319 Classical Mechanics Homewok Set 3 Phsics 319 lassical Mechanics Poblem 5.13 a) To fin the equilibium position (whee thee is no foce) set the eivative of the potential to zeo U 1 R U0 R U 0 at R R b) If R is much smalle than

More information

CHAPTER-11 The SCHRODINGER EQUATION in 3D

CHAPTER-11 The SCHRODINGER EQUATION in 3D Lt Nots PH 4/5 C 598 A. La osa INTODUCTION TO QUANTU CHANICS CHAPT- Th SCHODING QUATION in 3D Dsiption of th otion of two intatin patis. Gna as of an abita intation potntia. Cas whn th potntia pns on on

More information

COMPSCI 230 Discrete Math Trees March 21, / 22

COMPSCI 230 Discrete Math Trees March 21, / 22 COMPSCI 230 Dict Math Mach 21, 2017 COMPSCI 230 Dict Math Mach 21, 2017 1 / 22 Ovviw 1 A Simpl Splling Chck Nomnclatu 2 aval Od Dpth-it aval Od Badth-it aval Od COMPSCI 230 Dict Math Mach 21, 2017 2 /

More information

Physics Courseware Physics II Electric Field and Force

Physics Courseware Physics II Electric Field and Force Physics Cousewae Physics II lectic iel an oce Coulomb s law, whee k Nm /C test Definition of electic fiel. This is a vecto. test Q lectic fiel fo a point chage. This is a vecto. Poblem.- chage of µc is

More information

θ θ φ EN2210: Continuum Mechanics Homework 2: Polar and Curvilinear Coordinates, Kinematics Solutions 1. The for the vector i , calculate:

θ θ φ EN2210: Continuum Mechanics Homework 2: Polar and Curvilinear Coordinates, Kinematics Solutions 1. The for the vector i , calculate: EN0: Continm Mchanics Homwok : Pola and Cvilina Coodinats, Kinmatics Soltions School of Engining Bown Univsity x δ. Th fo th vcto i ij xx i j vi = and tnso S ij = + 5 = xk xk, calclat: a. Thi componnts

More information

Where k is either given or determined from the data and c is an arbitrary constant.

Where k is either given or determined from the data and c is an arbitrary constant. Exponntial growth and dcay applications W wish to solv an quation that has a drivativ. dy ky k > dx This quation says that th rat of chang of th function is proportional to th function. Th solution is

More information

ESCI 341 Atmospheric Thermodynamics Lesson 16 Pseudoadiabatic Processes Dr. DeCaria

ESCI 341 Atmospheric Thermodynamics Lesson 16 Pseudoadiabatic Processes Dr. DeCaria ESCI 34 Atmohi hmoynami on 6 Puoaiabati Po D DCaia fn: Man, A an FE obitaill, 97: A omaion of th uialnt otntial tmatu an th tati ngy, J Atmo Si, 7, 37-39 Btt, AK, 974: Futh ommnt on A omaion of th uialnt

More information

Aakash. For Class XII Studying / Passed Students. Physics, Chemistry & Mathematics

Aakash. For Class XII Studying / Passed Students. Physics, Chemistry & Mathematics Aakash A UNIQUE PPRTUNITY T HELP YU FULFIL YUR DREAMS Fo Class XII Studying / Passd Studnts Physics, Chmisty & Mathmatics Rgistd ffic: Aakash Tow, 8, Pusa Road, Nw Dlhi-0005. Ph.: (0) 4763456 Fax: (0)

More information

Text: WMM, Chapter 5. Sections , ,

Text: WMM, Chapter 5. Sections , , Lcturs 6 - Continuous Probabilit Distributions Tt: WMM, Chaptr 5. Sctions 6.-6.4, 6.6-6.8, 7.-7. In th prvious sction, w introduc som of th common probabilit distribution functions (PDFs) for discrt sampl

More information

The Solutions of the Classical Relativistic Two-Body Equation

The Solutions of the Classical Relativistic Two-Body Equation T. J. of Physics (998), 07 4. c TÜBİTAK The Soutions of the Cassica Reativistic Two-Body Equation Coşkun ÖNEM Eciyes Univesity, Physics Depatment, 38039, Kaysei - TURKEY Received 3.08.996 Abstact With

More information