Trace Semantics for Polymorphic References. GaLoP 16 April 3rd 2016
|
|
- Ἀχιλλεύς Λαμέρας
- 6 χρόνια πριν
- Προβολές:
Transcript
1 Trace Semantics for Polymorphic References Guilhem Jaber & Nikos Tzevelekos PPS, IRIF, Université Paris Diderot Queen Mary University of London GaLoP 16 April 3rd / 19
2 Goals Build an intensional model for a call-by-value language with Church-style polymorphism and higher-order (nominal) references. No bad variable problems. Fully abstract for a big fragment of the language. 2 / 19
3 Goals Build an intensional model for a call-by-value language with Church-style polymorphism and higher-order (nominal) references. No bad variable problems. Fully abstract for a big fragment of the language. Denotations of terms as set of traces Generated operationally using an LTS. 2 / 19
4 Goals Build an intensional model for a call-by-value language with Church-style polymorphism and higher-order (nominal) references. No bad variable problems. Fully abstract for a big fragment of the language. Denotations of terms as set of traces Generated operationally using an LTS. Using names to represent functional and poylmorphic values Operational Nominal Game Semantics Refresh of names to control the observational power of Opponent. 2 / 19
5 Goals Build an intensional model for a call-by-value language with Church-style polymorphism and higher-order (nominal) references. No bad variable problems. Fully abstract for a big fragment of the language. Denotations of terms as set of traces Generated operationally using an LTS. Using names to represent functional and poylmorphic values Operational Nominal Game Semantics Refresh of names to control the observational power of Opponent. What kind of free theorems can we get for programs with polymorphic references? Some surprise appears: possibility to disclose abstract types, Strachey parametricity seems broken! 2 / 19
6 System ReF v def = x l () n λx.m Λα.M v 1, v 2 pack θ, v... (x Var, α TVar, l Loc, n Z) M, N def = v MN Mθ ref M!M M := N M == N M 1, M 2 π i M pack θ, M unpack M as α, x in N θ, θ def = Unit Int θ θ ref θ θ θ θ + θ α.θ α.θ S def = Loc Val Given a functional type θ and some u, we let the argument and return type of θ be: arg(θ θ) = θ arg( α.θ) = U ret u (θ θ) = θ ret u ( α.θ) = θ{u/α} 3 / 19
7 Operational semantics ((λx.m)v, S) (M{v/x}, S) (ref v, S) (l, S [l v]) (!l, S) (S(l), S) (l := v, S) ((), S[l v]) (l == l, S) (true, S) (l == l, S) (false, S) (π i M 1, M 2, S) (M i, S) ((Λα.M)θ, S) (M{θ/α}, S) (unpack pack θ, v as α, x in N, S) (N{θ/α}{v/x}, S) 4 / 19
8 Type System (Polymorphic Part), α; Σ, Γ M : θ ; Σ, Γ Λα.M : α.θ ; Σ, Γ M : α.θ ; Σ, Γ Mθ : θ{θ /α} ; Σ, Γ M : θ{θ /α} ; Σ, Γ pack θ, M : α.θ ; Σ, Γ M : α.θ, α; Γ, x : θ N : θ ; Σ, Γ unpack M as α, x in N : θ 5 / 19
9 Type System (Reference part) ; Σ, Γ M : θ ; Σ, Γ ref M : ref θ (l, θ) Σ ; Σ, Γ l : ref θ ; Σ, Γ M : ref θ ; Σ, Γ! M : θ ; Σ, Γ M : ref θ ; Σ, Γ N : θ ; Σ, Γ M := N : Unit ; Σ, Γ M : refθ ; Σ, Γ M : refθ ; Σ, Γ M == N : Bool 6 / 19
10 Example I : Fake Identity Is the identity function the only program of type α.α α up to contextual equivalence? 7 / 19
11 Example I : Fake Identity Is the identity function the only program of type α.α α up to contextual equivalence? No: Λα.let count = ref0 in let z = refλ.ω α in λx:α.(if!count = 0 then z := λ.x else ()); count++;!z() 7 / 19
12 Example II : Type Disclosure Interaction between references and polymorphism is complex. Example: α. (refα refint) α 8 / 19
13 Example II : Type Disclosure Interaction between references and polymorphism is complex. Example: α. (refα refint) α What happen when the same location is given as type refα and refint? Λα.λ x, y refα refint. y := 42;!x 8 / 19
14 Example II : Type Disclosure Interaction between references and polymorphism is complex. Example: α. (refα refint) α What happen when the same location is given as type refα and refint? Λα.λ x, y refα refint. y := 42;!x More complex example: Λα.λ x, y refα refint. let x = ref!x, y = ref!y in y++; x := x ; if y =!y then (y := 42;!x) else!x 8 / 19
15 Abstract values and Semantic Types AValues v, u def = () n l f p α u, v where n Z, l Loc, f Fun, p Pol and α TVar. Nominal set A def = Loc Pol Fun TVar 9 / 19
16 Abstract values and Semantic Types AValues v, u def = () n l f p α u, v where n Z, l Loc, f Fun, p Pol and α TVar. Nominal set A def = Loc Pol Fun TVar θ : P(AValues (Loc P(Types))) Unit = {((), ε)} Int = {(n, ε) n Z} refθ = {(l, {(l, refθ)}) l Loc} α = {(p, ε) p Pol α } θ θ = {(f, ε) f Fun θ θ } α.θ = {(f, ε) f Fun α.θ } α.θ = {( α, v, φ) (v, φ) θ{α /α} } θ 1 θ 2 = {( v 1, v 2, φ 1 φ 2 ) (v i, φ i ) θ i } 9 / 19
17 From Values to Abstract Values AVal(v, θ) : P(AValues ((Fun Pol) Values) (Loc P(Types))) AVal(u, ι) def = {(u, ε, )} for ι = Unit or Int and u ι AVal(l, refθ) def = {(l, ε, {(l, refθ)} l Loc} AVal(u, α) def = {(p, [p u], ) p Pol α } {(u, ε, ) u Pol α } AVal(u, θ) def = {(f, [f u], ) f Fun θ } for θ functional AVal( u 1, u 2, θ 1 θ 2 ) def = {( v 1, v 2, γ 1 γ 2, φ 1 φ 2 ) AVal( θ, u, α.θ) def = {( α, v, γ [α θ ], φ) (v i, γ i, φ i ) AVal(u i, θ i )} (v, γ, φ) AVal(u, θ{α /α})} 10 / 19
18 Traces Full moves: triple (m, S, ρ) where m is a move f u, f u, ū or u (f Fun, u AValues), S is a closed abstract store, ρ is a finite map Pol AValues Used to disclose polymorphic values whose type have been disclosed. 11 / 19
19 Traces Full moves: triple (m, S, ρ) where m is a move f u, f u, ū or u (f Fun, u AValues), S is a closed abstract store, ρ is a finite map Pol AValues Used to disclose polymorphic values whose type have been disclosed. Traces: finite sequences of full moves. 11 / 19
20 Configurations A configuration is a tuple E, γ, φ, S, λ with: 12 / 19
21 Configurations A configuration is a tuple E, γ, φ, S, λ with: an evaluation stack E, 12 / 19
22 Configurations A configuration is a tuple E, γ, φ, S, λ with: an evaluation stack E, a typing function φ for locations, 12 / 19
23 Configurations A configuration is a tuple E, γ, φ, S, λ with: an evaluation stack E, a typing function φ for locations, a closed store S, 12 / 19
24 Configurations A configuration is a tuple E, γ, φ, S, λ with: an evaluation stack E, a typing function φ for locations, a closed store S, an environment γ mapping names to values, 12 / 19
25 Configurations A configuration is a tuple E, γ, φ, S, λ with: an evaluation stack E, a typing function φ for locations, a closed store S, an environment γ mapping names to values, an ownership function λ (A {O, P}). 12 / 19
26 Configurations A configuration is a tuple E, γ, φ, S, λ with: an evaluation stack E, a typing function φ for locations, a closed store S, an environment γ mapping names to values, an ownership function λ (A {O, P}). They satisfy: dom(γ) = {a Pol Fun TVar λ(a) = P} dom(φ) = {l Loc dom(λ)} dom(s) for all a ν(e, codom(s), codom(γ))\loc, λ(a) = O 12 / 19
27 LTS generating Traces (Int) (M, θ) :: E, γ, φ, S, λ (M, θ) :: E, γ, φ, S, λ given (M, S) (M, S ). 13 / 19
28 LTS generating Traces (Int) (M, θ) :: E, γ, φ, S, λ (M, θ) :: E, γ, φ, S, λ given (M, S) (M, S ). (PA) (u, θ) :: E, γ, φ, S, λ v,s, ρ E, γ γ, φ φ, S, λ λ given (v, γ v, φ v ) AVal(u, θ) 13 / 19
29 LTS generating Traces (Int) (M, θ) :: E, γ, φ, S, λ (M, θ) :: E, γ, φ, S, λ given (M, S) (M, S ). (PA) (PQ) (u, θ) :: E, γ, φ, S, λ v,s, ρ E, γ γ, φ φ, S, λ λ given (v, γ v, φ v ) AVal(u, θ) (E[f u], θ) :: E, γ, φ, S, λ f v,s, ρ (E, θ θ) :: E, γ γ, φ φ, S, λ λ (v, γ v, φ v ) AVal(u, arg(θ f )), θ = ret v (θ f ) 13 / 19
30 LTS generating Traces (Int) (M, θ) :: E, γ, φ, S, λ (M, θ) :: E, γ, φ, S, λ given (M, S) (M, S ). (PA) (PQ) (OA) (u, θ) :: E, γ, φ, S, λ v,s, ρ E, γ γ, φ φ, S, λ λ given (v, γ v, φ v ) AVal(u, θ) (E[f u], θ) :: E, γ, φ, S, λ f v,s, ρ (E, θ θ) :: E, γ γ, φ φ, S, λ λ (v, γ v, φ v ) AVal(u, arg(θ f )), θ = ret v (θ f ) (E, θ θ) :: E, γ, φ, S, λ v,s, ρ (Ẽ[ṽ], θ) :: Ẽ, γ, φ φ, S[ S ], λ λ given (v, φ v ) θ 13 / 19
31 LTS generating Traces (Int) (M, θ) :: E, γ, φ, S, λ (M, θ) :: E, γ, φ, S, λ given (M, S) (M, S ). (PA) (PQ) (OA) (OQ) (u, θ) :: E, γ, φ, S, λ v,s, ρ E, γ γ, φ φ, S, λ λ given (v, γ v, φ v ) AVal(u, θ) (E[f u], θ) :: E, γ, φ, S, λ f v,s, ρ (E, θ θ) :: E, γ γ, φ φ, S, λ λ (v, γ v, φ v ) AVal(u, arg(θ f )), θ = ret v (θ f ) (E, θ θ) :: E, γ, φ, S, λ v,s, ρ (Ẽ[ṽ], θ) :: Ẽ, γ, φ φ, S[ S ], λ λ given (v, φ v ) θ E, γ, φ, S, λ f v,s, ρ (ũ ṽ, θ) :: Ẽ, γ, φ φ, S[ S ], λ λ (v, φ v ) arg(θ), θ = ret v (θ ) and γ(f ) = u 13 / 19
32 A Simple Example: Polymorphic projection Consider the term v Λα.λx : α α. π 1 x of type θ = α. α α α. (v, θ), ε,, ε, ε ḡ γ 1 λ 1 {}}{{}}{, [g v],, ε, (g, P) 14 / 19
33 A Simple Example: Polymorphic projection Consider the term v Λα.λx : α α. π 1 x of type θ = α. α α α. (v, θ), ε,, ε, ε ḡ γ 1 λ 1 {}}{{}}{, [g v],, ε, (g, P) g α {}}{ (v α, α α α ), γ 1,, ε, λ 1 (α, O) λ 2 14 / 19
34 A Simple Example: Polymorphic projection Consider the term v Λα.λx : α α. π 1 x of type θ = α. α α α. (v, θ), ε,, ε, ε ḡ γ 1 λ 1 {}}{{}}{, [g v],, ε, (g, P) { }} { g α (v α, α α α ), γ 1,, ε, λ 1 (α, O) (λx. π 1 (x), α α α ), γ 1,, ε, λ 2 λ 2 14 / 19
35 A Simple Example: Polymorphic projection Consider the term v Λα.λx : α α. π 1 x of type θ = α. α α α. (v, θ), ε,, ε, ε ḡ γ 1 λ 1 {}}{{}}{, [g v],, ε, (g, P) { }} { g α (v α, α α α ), γ 1,, ε, λ 1 (α, O) (λx. π 1 (x), α α α ), γ 1,, ε, λ 2 f γ 2 {}}{{}}{, γ 1 [f λx. π 1 x],, ε, λ 2 (f, P) λ 3 λ 2 14 / 19
36 A Simple Example: Polymorphic projection Consider the term v Λα.λx : α α. π 1 x of type θ = α. α α α. (v, θ), ε,, ε, ε ḡ γ 1 λ 1 {}}{{}}{, [g v],, ε, (g, P) { }} { g α (v α, α α α ), γ 1,, ε, λ 1 (α, O) (λx. π 1 (x), α α α ), γ 1,, ε, λ 2 f γ 2 {}}{{}}{, γ 1 [f λx. π 1 x],, ε, λ 2 (f, P) f p 1,p 2 {}}{ ((λx. π 1 x) p 1, p 2, α ), γ 2,, ε, λ 3 (p 1, O) (p 2, O) λ 3 λ 2 λ 4 14 / 19
37 A Simple Example: Polymorphic projection Consider the term v Λα.λx : α α. π 1 x of type θ = α. α α α. (v, θ), ε,, ε, ε ḡ γ 1 λ 1 {}}{{}}{, [g v],, ε, (g, P) { }} { g α (v α, α α α ), γ 1,, ε, λ 1 (α, O) (λx. π 1 (x), α α α ), γ 1,, ε, λ 2 f γ 2 {}}{{}}{, γ 1 [f λx. π 1 x],, ε, λ 2 (f, P) f p 1,p 2 {}}{ ((λx. π 1 x) p 1, p 2, α ), γ 2,, ε, λ 3 (p 1, O) (p 2, O) (p 1, α ), γ 2,, ε, λ 4 λ 3 λ 2 λ 4 14 / 19
38 A Simple Example: Polymorphic projection Consider the term v Λα.λx : α α. π 1 x of type θ = α. α α α. (v, θ), ε,, ε, ε ḡ γ 1 λ 1 {}}{{}}{, [g v],, ε, (g, P) { }} { g α (v α, α α α ), γ 1,, ε, λ 1 (α, O) (λx. π 1 (x), α α α ), γ 1,, ε, λ 2 f γ 2 {}}{{}}{, γ 1 [f λx. π 1 x],, ε, λ 2 (f, P) f p 1,p 2 {}}{ ((λx. π 1 x) p 1, p 2, α ), γ 2,, ε, λ 3 (p 1, O) (p 2, O) (p 1, α ), γ 2,, ε, λ 4 λ 3 λ 2 λ 4 p 1, γ 2,, ε, λ 4 14 / 19
39 A Simple Example: Polymorphic projection Consider the term v Λα.λx : α α. π 1 x of type θ = α. α α α. (v, θ), ε,, ε, ε ḡ γ 1 λ 1 {}}{{}}{, [g v],, ε, (g, P) { }} { g α (v α, α α α ), γ 1,, ε, λ 1 (α, O) (λx. π 1 (x), α α α ), γ 1,, ε, λ 2 f γ 2 {}}{{}}{, γ 1 [f λx. π 1 x],, ε, λ 2 (f, P) f p 1,p 2 {}}{ ((λx. π 1 x) p 1, p 2, α ), γ 2,, ε, λ 3 (p 1, O) (p 2, O) (p 1, α ), γ 2,, ε, λ 4 λ 3 λ 2 λ 4 p 1, γ 2,, ε, λ 4 Trace? ḡ g α f f p 1, p 2 p 1 14 / 19
40 Computing Type Disclosure cast relations κ: relations over types. (θ, θ ) κ: we can cast values of type θ to θ. 15 / 19
41 Computing Type Disclosure cast relations κ: relations over types. (θ, θ ) κ: we can cast values of type θ to θ. Atomic casts from typing function of locations φ: {(θ, θ ) l Loc.(refθ, refθ ) φ(l)} cast term: y θ : refθ, y θ : refθ λx θ.let z =!y θ in y θ := x; let z =!y θ in y θ := z; z 15 / 19
42 Computing Type Disclosure cast relations κ: relations over types. (θ, θ ) κ: we can cast values of type θ to θ. Atomic casts from typing function of locations φ: {(θ, θ ) l Loc.(refθ, refθ ) φ(l)} cast term: y θ : refθ, y θ : refθ λx θ.let z =!y θ in y θ := x; let z =!y θ in y θ := z; z Take the closure of κ: to represent all the cast than can be build from these atomic casts Problem on ref types! No global substitution possible. 15 / 19
43 Computing Type Disclosure cast relations κ: relations over types. (θ, θ ) κ: we can cast values of type θ to θ. Atomic casts from typing function of locations φ: {(θ, θ ) l Loc.(refθ, refθ ) φ(l)} cast term: y θ : refθ, y θ : refθ λx θ.let z =!y θ in y θ := x; let z =!y θ in y θ := z; z Take the closure of κ: to represent all the cast than can be build from these atomic casts Problem on ref types! No global substitution possible. Quiz: Suppose f : (refint refint) Unit, g : α. refα refα and? let x, y = ref0 in f (x, y); let u = g Int x in if (u = y) then 1 else 2 =? let x, y = ref0 in f (x, y); let u = g Int x in if (u = y) then 3 else 2 15 / 19
44 An Example with Type Disclosure θ def v def = refα refint α = Λα.λ x, y, z θ. if x = y then (y := 42;!x) else z }{{} M 16 / 19
45 An Example with Type Disclosure θ def = refα refint α v def = Λα.λ x, y, z θ. if x = y then (y := 42;!x) else z }{{} M λ f {}} 1 { (v, α.θ α), ε,, ε, ε, [f v],, ε, (f, P) 16 / 19
46 An Example with Type Disclosure θ def = refα refint α v def = Λα.λ x, y, z θ. if x = y then (y := 42;!x) else z }{{} M λ f {}} 1 { (v, α.θ α), ε,, ε, ε, [f v],, ε, (f, P) f α {}}{ (vα, θ α), γ 1,, ε, λ 1 (α, O) λ 2 16 / 19
47 An Example with Type Disclosure θ def = refα refint α v def = Λα.λ x, y, z θ. if x = y then (y := 42;!x) else z }{{} M λ f {}} 1 { (v, α.θ α), ε,, ε, ε, [f v],, ε, (f, P) f α {}}{ (vα, θ α), γ 1,, ε, λ 1 (α, O) γ {}} 2 { ḡ, γ 1 [g λz θ.m],, ε, λ 2 g l,l,p,s,ρ {}}{{}}{ (M{l/x, y}{p/z}, α), γ 2, {(l, Int),(l, α)}, S, λ 2 (l, O) (p, O)) λ 2 φ 1 λ 3 16 / 19
48 An Example with Type Disclosure θ def = refα refint α v def = Λα.λ x, y, z θ. if x = y then (y := 42;!x) else z }{{} M λ f {}} 1 { (v, α.θ α), ε,, ε, ε, [f v],, ε, (f, P) f α {}}{ (vα, θ α), γ 1,, ε, λ 1 (α, O) γ {}} 2 { ḡ, γ 1 [g λz θ.m],, ε, λ 2 g l,l,p,s,ρ {}}{{}}{ (M{l/x, y}{p/z}, α), γ 2, {(l, Int),(l, α)}, S, λ 2 (l, O) (p, O)) 42,S, γ 1, φ 1, S, λ 3 e.g. for S =[l 9], ρ = [p 7]. λ 2 φ 1 λ 3 16 / 19
49 Soundness M : Set of complete traces generated by the initial configurations of M. 17 / 19
50 Soundness M : Set of complete traces generated by the initial configurations of M. : effective equivalent relation on (set of) traces which substitute disclosed polymorphic names by their concrete values given by the ρ s. 17 / 19
51 Soundness M : Set of complete traces generated by the initial configurations of M. : effective equivalent relation on (set of) traces which substitute disclosed polymorphic names by their concrete values given by the ρ s. Theorem (Soundness) For all terms ; Σ, Γ M 1, M 2 : θ, M 1 M 2 implies M 1 ctx M / 19
52 Full Abstraction SystemReF*: Forbid binders, to appear in the scope of a ref, any type variable α inside a refθ must be reachably inhabited: an abstract value of type α must have been played before. 18 / 19
53 Full Abstraction SystemReF*: Forbid binders, to appear in the scope of a ref, any type variable α inside a refθ must be reachably inhabited: an abstract value of type α must have been played before. Theorem (Completeness) Given SystemReF* terms ; Σ, Γ M 1, M 2 : θ, if M 1 ctx M 2 then M 1 M / 19
54 Full Abstraction SystemReF*: Forbid binders, to appear in the scope of a ref, any type variable α inside a refθ must be reachably inhabited: an abstract value of type α must have been played before. Theorem (Completeness) Given SystemReF* terms ; Σ, Γ M 1, M 2 : θ, if M 1 ctx M 2 then M 1 M 2. A type outside SystemReF* : h : α, α.(ref(α α) ref(α Int) α) α 18 / 19
55 Full Abstraction SystemReF*: Forbid binders, to appear in the scope of a ref, any type variable α inside a refθ must be reachably inhabited: an abstract value of type α must have been played before. Theorem (Completeness) Given SystemReF* terms ; Σ, Γ M 1, M 2 : θ, if M 1 ctx M 2 then M 1 M 2. A type outside SystemReF* : h : α, α.(ref(α α) ref(α Int) α) α let x = ref(λy.1) in let u = h Int Int (x, x, 0) in if u then 1 else 2 =? let x = ref(λy.1) in let u = h Int Int (x, x, 0) in if u then 3 else 2 18 / 19
56 Conclusion On the fragment without refθ: an operational variant of Laird s CBV game model of polymorphism. Link with Levy s Ultimate Patterns and Operational Bisimulations? Next Step: Hindley-Milner (Curry-style) Polymorphism Towards fully abstract model of ML! Deduce reasoning techniques for proof equivalences Examples that cannot be handle by Kripke Logical Relations and Environmental Bisimulations! 19 / 19
The Simply Typed Lambda Calculus
Type Inference Instead of writing type annotations, can we use an algorithm to infer what the type annotations should be? That depends on the type system. For simple type systems the answer is yes, and
A Lambda Model Characterizing Computational Behaviours of Terms
A Lambda Model Characterizing Computational Behaviours of Terms joint paper with Silvia Ghilezan RPC 01, Sendai, October 26, 2001 1 Plan of the talk normalization properties inverse limit model Stone dualities
Dynamic types, Lambda calculus machines Section and Practice Problems Apr 21 22, 2016
Harvard School of Engineering and Applied Sciences CS 152: Programming Languages Dynamic types, Lambda calculus machines Apr 21 22, 2016 1 Dynamic types and contracts (a) To make sure you understand the
Lecture 2. Soundness and completeness of propositional logic
Lecture 2 Soundness and completeness of propositional logic February 9, 2004 1 Overview Review of natural deduction. Soundness and completeness. Semantics of propositional formulas. Soundness proof. Completeness
C.S. 430 Assignment 6, Sample Solutions
C.S. 430 Assignment 6, Sample Solutions Paul Liu November 15, 2007 Note that these are sample solutions only; in many cases there were many acceptable answers. 1 Reynolds Problem 10.1 1.1 Normal-order
Overview. Transition Semantics. Configurations and the transition relation. Executions and computation
Overview Transition Semantics Configurations and the transition relation Executions and computation Inference rules for small-step structural operational semantics for the simple imperative language Transition
Example Sheet 3 Solutions
Example Sheet 3 Solutions. i Regular Sturm-Liouville. ii Singular Sturm-Liouville mixed boundary conditions. iii Not Sturm-Liouville ODE is not in Sturm-Liouville form. iv Regular Sturm-Liouville note
EE512: Error Control Coding
EE512: Error Control Coding Solution for Assignment on Finite Fields February 16, 2007 1. (a) Addition and Multiplication tables for GF (5) and GF (7) are shown in Tables 1 and 2. + 0 1 2 3 4 0 0 1 2 3
Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit
Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit Ting Zhang Stanford May 11, 2001 Stanford, 5/11/2001 1 Outline Ordinal Classification Ordinal Addition Ordinal Multiplication Ordinal
Every set of first-order formulas is equivalent to an independent set
Every set of first-order formulas is equivalent to an independent set May 6, 2008 Abstract A set of first-order formulas, whatever the cardinality of the set of symbols, is equivalent to an independent
HOMEWORK 4 = G. In order to plot the stress versus the stretch we define a normalized stretch:
HOMEWORK 4 Problem a For the fast loading case, we want to derive the relationship between P zz and λ z. We know that the nominal stress is expressed as: P zz = ψ λ z where λ z = λ λ z. Therefore, applying
2 Composition. Invertible Mappings
Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan Composition. Invertible Mappings In this section we discuss two procedures for creating new mappings from old ones, namely,
Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3
Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3 1 State vector space and the dual space Space of wavefunctions The space of wavefunctions is the set of all
Sequent Calculi for the Modal µ-calculus over S5. Luca Alberucci, University of Berne. Logic Colloquium Berne, July 4th 2008
Sequent Calculi for the Modal µ-calculus over S5 Luca Alberucci, University of Berne Logic Colloquium Berne, July 4th 2008 Introduction Koz: Axiomatisation for the modal µ-calculus over K Axioms: All classical
Finite Field Problems: Solutions
Finite Field Problems: Solutions 1. Let f = x 2 +1 Z 11 [x] and let F = Z 11 [x]/(f), a field. Let Solution: F =11 2 = 121, so F = 121 1 = 120. The possible orders are the divisors of 120. Solution: The
About these lecture notes. Simply Typed λ-calculus. Types
About these lecture notes Simply Typed λ-calculus Akim Demaille akim@lrde.epita.fr EPITA École Pour l Informatique et les Techniques Avancées Many of these slides are largely inspired from Andrew D. Ker
Econ 2110: Fall 2008 Suggested Solutions to Problem Set 8 questions or comments to Dan Fetter 1
Eon : Fall 8 Suggested Solutions to Problem Set 8 Email questions or omments to Dan Fetter Problem. Let X be a salar with density f(x, θ) (θx + θ) [ x ] with θ. (a) Find the most powerful level α test
Matrices and Determinants
Matrices and Determinants SUBJECTIVE PROBLEMS: Q 1. For what value of k do the following system of equations possess a non-trivial (i.e., not all zero) solution over the set of rationals Q? x + ky + 3z
5. Choice under Uncertainty
5. Choice under Uncertainty Daisuke Oyama Microeconomics I May 23, 2018 Formulations von Neumann-Morgenstern (1944/1947) X: Set of prizes Π: Set of probability distributions on X : Preference relation
Other Test Constructions: Likelihood Ratio & Bayes Tests
Other Test Constructions: Likelihood Ratio & Bayes Tests Side-Note: So far we have seen a few approaches for creating tests such as Neyman-Pearson Lemma ( most powerful tests of H 0 : θ = θ 0 vs H 1 :
The λ-calculus. Lecturer: John Wickerson. Phil Wadler
The λ-calculus Lecturer: John Wickerson Phil Wadler A tiny bit of Java expr ::= expr + expr expr < expr x n block ::= cmd { cmd... cmd } cmd ::= expr; if(cmd) block else block; if(cmd) block; try{cmd}
Uniform Convergence of Fourier Series Michael Taylor
Uniform Convergence of Fourier Series Michael Taylor Given f L 1 T 1 ), we consider the partial sums of the Fourier series of f: N 1) S N fθ) = ˆfk)e ikθ. k= N A calculation gives the Dirichlet formula
The challenges of non-stable predicates
The challenges of non-stable predicates Consider a non-stable predicate Φ encoding, say, a safety property. We want to determine whether Φ holds for our program. The challenges of non-stable predicates
Chap. 6 Pushdown Automata
Chap. 6 Pushdown Automata 6.1 Definition of Pushdown Automata Example 6.1 L = {wcw R w (0+1) * } P c 0P0 1P1 1. Start at state q 0, push input symbol onto stack, and stay in q 0. 2. If input symbol is
Finitary proof systems for Kozen s µ
Finitary proof systems for Kozen s µ Bahareh Afshari Graham Leigh TU Wien University of Gothenburg homc & cdps 16, Singapore 1 / 17 Modal µ-calculus Syntax: p p φ ψ φ ψ φ φ x µx φ νx φ Semantics: For Kripke
Formal Semantics. 1 Type Logic
Formal Semantics Principle of Compositionality The meaning of a sentence is determined by the meanings of its parts and the way they are put together. 1 Type Logic Types (a measure on expressions) The
Commutative Monoids in Intuitionistic Fuzzy Sets
Commutative Monoids in Intuitionistic Fuzzy Sets S K Mala #1, Dr. MM Shanmugapriya *2 1 PhD Scholar in Mathematics, Karpagam University, Coimbatore, Tamilnadu- 641021 Assistant Professor of Mathematics,
derivation of the Laplacian from rectangular to spherical coordinates
derivation of the Laplacian from rectangular to spherical coordinates swapnizzle 03-03- :5:43 We begin by recognizing the familiar conversion from rectangular to spherical coordinates (note that φ is used
Concrete Mathematics Exercises from 30 September 2016
Concrete Mathematics Exercises from 30 September 2016 Silvio Capobianco Exercise 1.7 Let H(n) = J(n + 1) J(n). Equation (1.8) tells us that H(2n) = 2, and H(2n+1) = J(2n+2) J(2n+1) = (2J(n+1) 1) (2J(n)+1)
CS-XXX: Graduate Programming Languages. Lecture 27 Higher-Order Polymorphism. Matthew Fluet 2012
CS-XXX: Graduate Programming Languages Lecture 27 Higher-Order Polymorphism Matthew Fluet 2012 Looking back, looking forward Have defined System F. Metatheory (what properties does it have) What (else)
6.1. Dirac Equation. Hamiltonian. Dirac Eq.
6.1. Dirac Equation Ref: M.Kaku, Quantum Field Theory, Oxford Univ Press (1993) η μν = η μν = diag(1, -1, -1, -1) p 0 = p 0 p = p i = -p i p μ p μ = p 0 p 0 + p i p i = E c 2 - p 2 = (m c) 2 H = c p 2
Reminders: linear functions
Reminders: linear functions Let U and V be vector spaces over the same field F. Definition A function f : U V is linear if for every u 1, u 2 U, f (u 1 + u 2 ) = f (u 1 ) + f (u 2 ), and for every u U
From the finite to the transfinite: Λµ-terms and streams
From the finite to the transfinite: Λµ-terms and streams WIR 2014 Fanny He f.he@bath.ac.uk Alexis Saurin alexis.saurin@pps.univ-paris-diderot.fr 12 July 2014 The Λµ-calculus Syntax of Λµ t ::= x λx.t (t)u
ST5224: Advanced Statistical Theory II
ST5224: Advanced Statistical Theory II 2014/2015: Semester II Tutorial 7 1. Let X be a sample from a population P and consider testing hypotheses H 0 : P = P 0 versus H 1 : P = P 1, where P j is a known
3.4 SUM AND DIFFERENCE FORMULAS. NOTE: cos(α+β) cos α + cos β cos(α-β) cos α -cos β
3.4 SUM AND DIFFERENCE FORMULAS Page Theorem cos(αβ cos α cos β -sin α cos(α-β cos α cos β sin α NOTE: cos(αβ cos α cos β cos(α-β cos α -cos β Proof of cos(α-β cos α cos β sin α Let s use a unit circle
Models for Probabilistic Programs with an Adversary
Models for Probabilistic Programs with an Adversary Robert Rand, Steve Zdancewic University of Pennsylvania Probabilistic Programming Semantics 2016 Interactive Proofs 2/47 Interactive Proofs 2/47 Interactive
Statistical Inference I Locally most powerful tests
Statistical Inference I Locally most powerful tests Shirsendu Mukherjee Department of Statistics, Asutosh College, Kolkata, India. shirsendu st@yahoo.co.in So far we have treated the testing of one-sided
Fractional Colorings and Zykov Products of graphs
Fractional Colorings and Zykov Products of graphs Who? Nichole Schimanski When? July 27, 2011 Graphs A graph, G, consists of a vertex set, V (G), and an edge set, E(G). V (G) is any finite set E(G) is
Nowhere-zero flows Let be a digraph, Abelian group. A Γ-circulation in is a mapping : such that, where, and : tail in X, head in
Nowhere-zero flows Let be a digraph, Abelian group. A Γ-circulation in is a mapping : such that, where, and : tail in X, head in : tail in X, head in A nowhere-zero Γ-flow is a Γ-circulation such that
PARTIAL NOTES for 6.1 Trigonometric Identities
PARTIAL NOTES for 6.1 Trigonometric Identities tanθ = sinθ cosθ cotθ = cosθ sinθ BASIC IDENTITIES cscθ = 1 sinθ secθ = 1 cosθ cotθ = 1 tanθ PYTHAGOREAN IDENTITIES sin θ + cos θ =1 tan θ +1= sec θ 1 + cot
Phys460.nb Solution for the t-dependent Schrodinger s equation How did we find the solution? (not required)
Phys460.nb 81 ψ n (t) is still the (same) eigenstate of H But for tdependent H. The answer is NO. 5.5.5. Solution for the tdependent Schrodinger s equation If we assume that at time t 0, the electron starts
Abstract Storage Devices
Abstract Storage Devices Robert König Ueli Maurer Stefano Tessaro SOFSEM 2009 January 27, 2009 Outline 1. Motivation: Storage Devices 2. Abstract Storage Devices (ASD s) 3. Reducibility 4. Factoring ASD
D Alembert s Solution to the Wave Equation
D Alembert s Solution to the Wave Equation MATH 467 Partial Differential Equations J. Robert Buchanan Department of Mathematics Fall 2018 Objectives In this lesson we will learn: a change of variable technique
ΚΥΠΡΙΑΚΟΣ ΣΥΝΔΕΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY 21 ος ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ Δεύτερος Γύρος - 30 Μαρτίου 2011
Διάρκεια Διαγωνισμού: 3 ώρες Απαντήστε όλες τις ερωτήσεις Μέγιστο Βάρος (20 Μονάδες) Δίνεται ένα σύνολο από N σφαιρίδια τα οποία δεν έχουν όλα το ίδιο βάρος μεταξύ τους και ένα κουτί που αντέχει μέχρι
Numerical Analysis FMN011
Numerical Analysis FMN011 Carmen Arévalo Lund University carmen@maths.lth.se Lecture 12 Periodic data A function g has period P if g(x + P ) = g(x) Model: Trigonometric polynomial of order M T M (x) =
Fourier Series. MATH 211, Calculus II. J. Robert Buchanan. Spring Department of Mathematics
Fourier Series MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Introduction Not all functions can be represented by Taylor series. f (k) (c) A Taylor series f (x) = (x c)
ΕΛΛΗΝΙΚΗ ΔΗΜΟΚΡΑΤΙΑ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΡΗΤΗΣ. Ψηφιακή Οικονομία. Διάλεξη 7η: Consumer Behavior Mαρίνα Μπιτσάκη Τμήμα Επιστήμης Υπολογιστών
ΕΛΛΗΝΙΚΗ ΔΗΜΟΚΡΑΤΙΑ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΡΗΤΗΣ Ψηφιακή Οικονομία Διάλεξη 7η: Consumer Behavior Mαρίνα Μπιτσάκη Τμήμα Επιστήμης Υπολογιστών Τέλος Ενότητας Χρηματοδότηση Το παρόν εκπαιδευτικό υλικό έχει αναπτυχθεί
Απόκριση σε Μοναδιαία Ωστική Δύναμη (Unit Impulse) Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο. Απόστολος Σ.
Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο The time integral of a force is referred to as impulse, is determined by and is obtained from: Newton s 2 nd Law of motion states that the action
Homomorphism in Intuitionistic Fuzzy Automata
International Journal of Fuzzy Mathematics Systems. ISSN 2248-9940 Volume 3, Number 1 (2013), pp. 39-45 Research India Publications http://www.ripublication.com/ijfms.htm Homomorphism in Intuitionistic
DESIGN OF MACHINERY SOLUTION MANUAL h in h 4 0.
DESIGN OF MACHINERY SOLUTION MANUAL -7-1! PROBLEM -7 Statement: Design a double-dwell cam to move a follower from to 25 6, dwell for 12, fall 25 and dwell for the remader The total cycle must take 4 sec
Practice Exam 2. Conceptual Questions. 1. State a Basic identity and then verify it. (a) Identity: Solution: One identity is csc(θ) = 1
Conceptual Questions. State a Basic identity and then verify it. a) Identity: Solution: One identity is cscθ) = sinθ) Practice Exam b) Verification: Solution: Given the point of intersection x, y) of the
A Note on Intuitionistic Fuzzy. Equivalence Relation
International Mathematical Forum, 5, 2010, no. 67, 3301-3307 A Note on Intuitionistic Fuzzy Equivalence Relation D. K. Basnet Dept. of Mathematics, Assam University Silchar-788011, Assam, India dkbasnet@rediffmail.com
Section 8.3 Trigonometric Equations
99 Section 8. Trigonometric Equations Objective 1: Solve Equations Involving One Trigonometric Function. In this section and the next, we will exple how to solving equations involving trigonometric functions.
CRASH COURSE IN PRECALCULUS
CRASH COURSE IN PRECALCULUS Shiah-Sen Wang The graphs are prepared by Chien-Lun Lai Based on : Precalculus: Mathematics for Calculus by J. Stuwart, L. Redin & S. Watson, 6th edition, 01, Brooks/Cole Chapter
An Inventory of Continuous Distributions
Appendi A An Inventory of Continuous Distributions A.1 Introduction The incomplete gamma function is given by Also, define Γ(α; ) = 1 with = G(α; ) = Z 0 Z 0 Z t α 1 e t dt, α > 0, >0 t α 1 e t dt, α >
ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 6/5/2006
Οδηγίες: Να απαντηθούν όλες οι ερωτήσεις. Ολοι οι αριθμοί που αναφέρονται σε όλα τα ερωτήματα είναι μικρότεροι το 1000 εκτός αν ορίζεται διαφορετικά στη διατύπωση του προβλήματος. Διάρκεια: 3,5 ώρες Καλή
Areas and Lengths in Polar Coordinates
Kiryl Tsishchanka Areas and Lengths in Polar Coordinates In this section we develop the formula for the area of a region whose boundary is given by a polar equation. We need to use the formula for the
Math 6 SL Probability Distributions Practice Test Mark Scheme
Math 6 SL Probability Distributions Practice Test Mark Scheme. (a) Note: Award A for vertical line to right of mean, A for shading to right of their vertical line. AA N (b) evidence of recognizing symmetry
Πρόβλημα 1: Αναζήτηση Ελάχιστης/Μέγιστης Τιμής
Πρόβλημα 1: Αναζήτηση Ελάχιστης/Μέγιστης Τιμής Να γραφεί πρόγραμμα το οποίο δέχεται ως είσοδο μια ακολουθία S από n (n 40) ακέραιους αριθμούς και επιστρέφει ως έξοδο δύο ακολουθίες από θετικούς ακέραιους
Congruence Classes of Invertible Matrices of Order 3 over F 2
International Journal of Algebra, Vol. 8, 24, no. 5, 239-246 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/.2988/ija.24.422 Congruence Classes of Invertible Matrices of Order 3 over F 2 Ligong An and
Chapter 6: Systems of Linear Differential. be continuous functions on the interval
Chapter 6: Systems of Linear Differential Equations Let a (t), a 2 (t),..., a nn (t), b (t), b 2 (t),..., b n (t) be continuous functions on the interval I. The system of n first-order differential equations
Inverse trigonometric functions & General Solution of Trigonometric Equations. ------------------ ----------------------------- -----------------
Inverse trigonometric functions & General Solution of Trigonometric Equations. 1. Sin ( ) = a) b) c) d) Ans b. Solution : Method 1. Ans a: 17 > 1 a) is rejected. w.k.t Sin ( sin ) = d is rejected. If sin
b. Use the parametrization from (a) to compute the area of S a as S a ds. Be sure to substitute for ds!
MTH U341 urface Integrals, tokes theorem, the divergence theorem To be turned in Wed., Dec. 1. 1. Let be the sphere of radius a, x 2 + y 2 + z 2 a 2. a. Use spherical coordinates (with ρ a) to parametrize.
ΜΕΤΑΠΤΥΧΙΑΚΗ ΔΙΠΛΩΜΑΤΙΚΗ ΕΡΓΑΣΙΑ «ΘΕΜΑ»
ΠΑΝΕΠΙΣΤΗΜΙΟ ΑΙΓΑΙΟΥ ΣΧΟΛΗ ΑΝΘΡΩΠΙΣΤΙΚΩΝ ΕΠΙΣΤΗΜΩΝ ΤΜΗΜΑ ΕΠΙΣΤΗΜΩΝ ΤΗΣ ΠΡΟΣΧΟΛΙΚΗΣ ΑΓΩΓΗΣ ΚΑΙ ΤΟΥ ΕΚΠΑΙΔΕΥΤΙΚΟΥ ΣΧΕΔΙΑΣΜΟΥ Π.Μ.Σ. «ΠΕΡΙΒΑΛΛΟΝΤΙΚΗ ΕΚΠΑΙΔΕΥΣΗ» ΜΕΤΑΠΤΥΧΙΑΚΗ ΔΙΠΛΩΜΑΤΙΚΗ ΕΡΓΑΣΙΑ «ΘΕΜΑ» «Εφαρμογή
CHAPTER 25 SOLVING EQUATIONS BY ITERATIVE METHODS
CHAPTER 5 SOLVING EQUATIONS BY ITERATIVE METHODS EXERCISE 104 Page 8 1. Find the positive root of the equation x + 3x 5 = 0, correct to 3 significant figures, using the method of bisection. Let f(x) =
Type Theory and Coq. Herman Geuvers. Principal Types and Type Checking
Type Theory and Coq Herman Geuvers Principal Types and Type Checking 1 Overview of todays lecture Simple Type Theory à la Curry (versus Simple Type Theory à la Church) Principal Types algorithm Type checking
EPL 603 TOPICS IN SOFTWARE ENGINEERING. Lab 5: Component Adaptation Environment (COPE)
EPL 603 TOPICS IN SOFTWARE ENGINEERING Lab 5: Component Adaptation Environment (COPE) Performing Static Analysis 1 Class Name: The fully qualified name of the specific class Type: The type of the class
Generating Set of the Complete Semigroups of Binary Relations
Applied Mathematics 06 7 98-07 Published Online January 06 in SciRes http://wwwscirporg/journal/am http://dxdoiorg/036/am067009 Generating Set of the Complete Semigroups of Binary Relations Yasha iasamidze
SCITECH Volume 13, Issue 2 RESEARCH ORGANISATION Published online: March 29, 2018
Journal of rogressive Research in Mathematics(JRM) ISSN: 2395-028 SCITECH Volume 3, Issue 2 RESEARCH ORGANISATION ublished online: March 29, 208 Journal of rogressive Research in Mathematics www.scitecresearch.com/journals
Homework 3 Solutions
Homework 3 Solutions Igor Yanovsky (Math 151A TA) Problem 1: Compute the absolute error and relative error in approximations of p by p. (Use calculator!) a) p π, p 22/7; b) p π, p 3.141. Solution: For
Instruction Execution Times
1 C Execution Times InThisAppendix... Introduction DL330 Execution Times DL330P Execution Times DL340 Execution Times C-2 Execution Times Introduction Data Registers This appendix contains several tables
Assalamu `alaikum wr. wb.
LUMP SUM Assalamu `alaikum wr. wb. LUMP SUM Wassalamu alaikum wr. wb. Assalamu `alaikum wr. wb. LUMP SUM Wassalamu alaikum wr. wb. LUMP SUM Lump sum lump sum lump sum. lump sum fixed price lump sum lump
Proving with Computer Assistance Lecture 2. Herman Geuvers
Proving with Computer Assistance Lecture 2 Herman Geuvers 1 Typed λ calculus as the basis for a Proof Assistant (e.g. Coq) λ-term program proof type specification formula Integrated system for proving
Tridiagonal matrices. Gérard MEURANT. October, 2008
Tridiagonal matrices Gérard MEURANT October, 2008 1 Similarity 2 Cholesy factorizations 3 Eigenvalues 4 Inverse Similarity Let α 1 ω 1 β 1 α 2 ω 2 T =......... β 2 α 1 ω 1 β 1 α and β i ω i, i = 1,...,
Second Order RLC Filters
ECEN 60 Circuits/Electronics Spring 007-0-07 P. Mathys Second Order RLC Filters RLC Lowpass Filter A passive RLC lowpass filter (LPF) circuit is shown in the following schematic. R L C v O (t) Using phasor
Math221: HW# 1 solutions
Math: HW# solutions Andy Royston October, 5 7.5.7, 3 rd Ed. We have a n = b n = a = fxdx = xdx =, x cos nxdx = x sin nx n sin nxdx n = cos nx n = n n, x sin nxdx = x cos nx n + cos nxdx n cos n = + sin
Jesse Maassen and Mark Lundstrom Purdue University November 25, 2013
Notes on Average Scattering imes and Hall Factors Jesse Maassen and Mar Lundstrom Purdue University November 5, 13 I. Introduction 1 II. Solution of the BE 1 III. Exercises: Woring out average scattering
On the Galois Group of Linear Difference-Differential Equations
On the Galois Group of Linear Difference-Differential Equations Ruyong Feng KLMM, Chinese Academy of Sciences, China Ruyong Feng (KLMM, CAS) Galois Group 1 / 19 Contents 1 Basic Notations and Concepts
k A = [k, k]( )[a 1, a 2 ] = [ka 1,ka 2 ] 4For the division of two intervals of confidence in R +
Chapter 3. Fuzzy Arithmetic 3- Fuzzy arithmetic: ~Addition(+) and subtraction (-): Let A = [a and B = [b, b in R If x [a and y [b, b than x+y [a +b +b Symbolically,we write A(+)B = [a (+)[b, b = [a +b
Parametrized Surfaces
Parametrized Surfaces Recall from our unit on vector-valued functions at the beginning of the semester that an R 3 -valued function c(t) in one parameter is a mapping of the form c : I R 3 where I is some
ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 24/3/2007
Οδηγίες: Να απαντηθούν όλες οι ερωτήσεις. Όλοι οι αριθμοί που αναφέρονται σε όλα τα ερωτήματα μικρότεροι του 10000 εκτός αν ορίζεται διαφορετικά στη διατύπωση του προβλήματος. Αν κάπου κάνετε κάποιες υποθέσεις
Mean-Variance Analysis
Mean-Variance Analysis Jan Schneider McCombs School of Business University of Texas at Austin Jan Schneider Mean-Variance Analysis Beta Representation of the Risk Premium risk premium E t [Rt t+τ ] R1
Approximation of distance between locations on earth given by latitude and longitude
Approximation of distance between locations on earth given by latitude and longitude Jan Behrens 2012-12-31 In this paper we shall provide a method to approximate distances between two points on earth
ω ω ω ω ω ω+2 ω ω+2 + ω ω ω ω+2 + ω ω+1 ω ω+2 2 ω ω ω ω ω ω ω ω+1 ω ω2 ω ω2 + ω ω ω2 + ω ω ω ω2 + ω ω+1 ω ω2 + ω ω+1 + ω ω ω ω2 + ω
0 1 2 3 4 5 6 ω ω + 1 ω + 2 ω + 3 ω + 4 ω2 ω2 + 1 ω2 + 2 ω2 + 3 ω3 ω3 + 1 ω3 + 2 ω4 ω4 + 1 ω5 ω 2 ω 2 + 1 ω 2 + 2 ω 2 + ω ω 2 + ω + 1 ω 2 + ω2 ω 2 2 ω 2 2 + 1 ω 2 2 + ω ω 2 3 ω 3 ω 3 + 1 ω 3 + ω ω 3 +
Math 446 Homework 3 Solutions. (1). (i): Reverse triangle inequality for metrics: Let (X, d) be a metric space and let x, y, z X.
Math 446 Homework 3 Solutions. (1). (i): Reverse triangle inequalit for metrics: Let (X, d) be a metric space and let x,, z X. Prove that d(x, z) d(, z) d(x, ). (ii): Reverse triangle inequalit for norms:
Areas and Lengths in Polar Coordinates
Kiryl Tsishchanka Areas and Lengths in Polar Coordinates In this section we develop the formula for the area of a region whose boundary is given by a polar equation. We need to use the formula for the
Section 7.6 Double and Half Angle Formulas
09 Section 7. Double and Half Angle Fmulas To derive the double-angles fmulas, we will use the sum of two angles fmulas that we developed in the last section. We will let α θ and β θ: cos(θ) cos(θ + θ)
Main source: "Discrete-time systems and computer control" by Α. ΣΚΟΔΡΑΣ ΨΗΦΙΑΚΟΣ ΕΛΕΓΧΟΣ ΔΙΑΛΕΞΗ 4 ΔΙΑΦΑΝΕΙΑ 1
Main source: "Discrete-time systems and computer control" by Α. ΣΚΟΔΡΑΣ ΨΗΦΙΑΚΟΣ ΕΛΕΓΧΟΣ ΔΙΑΛΕΞΗ 4 ΔΙΑΦΑΝΕΙΑ 1 A Brief History of Sampling Research 1915 - Edmund Taylor Whittaker (1873-1956) devised a
( ) 2 and compare to M.
Problems and Solutions for Section 4.2 4.9 through 4.33) 4.9 Calculate the square root of the matrix 3!0 M!0 8 Hint: Let M / 2 a!b ; calculate M / 2!b c ) 2 and compare to M. Solution: Given: 3!0 M!0 8
Capacitors - Capacitance, Charge and Potential Difference
Capacitors - Capacitance, Charge and Potential Difference Capacitors store electric charge. This ability to store electric charge is known as capacitance. A simple capacitor consists of 2 parallel metal
Srednicki Chapter 55
Srednicki Chapter 55 QFT Problems & Solutions A. George August 3, 03 Srednicki 55.. Use equations 55.3-55.0 and A i, A j ] = Π i, Π j ] = 0 (at equal times) to verify equations 55.-55.3. This is our third
Second Order Partial Differential Equations
Chapter 7 Second Order Partial Differential Equations 7.1 Introduction A second order linear PDE in two independent variables (x, y Ω can be written as A(x, y u x + B(x, y u xy + C(x, y u u u + D(x, y
Μηχανική Μάθηση Hypothesis Testing
ΕΛΛΗΝΙΚΗ ΔΗΜΟΚΡΑΤΙΑ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΡΗΤΗΣ Μηχανική Μάθηση Hypothesis Testing Γιώργος Μπορμπουδάκης Τμήμα Επιστήμης Υπολογιστών Procedure 1. Form the null (H 0 ) and alternative (H 1 ) hypothesis 2. Consider
CHAPTER 48 APPLICATIONS OF MATRICES AND DETERMINANTS
CHAPTER 48 APPLICATIONS OF MATRICES AND DETERMINANTS EXERCISE 01 Page 545 1. Use matrices to solve: 3x + 4y x + 5y + 7 3x + 4y x + 5y 7 Hence, 3 4 x 0 5 y 7 The inverse of 3 4 5 is: 1 5 4 1 5 4 15 8 3
Solution Series 9. i=1 x i and i=1 x i.
Lecturer: Prof. Dr. Mete SONER Coordinator: Yilin WANG Solution Series 9 Q1. Let α, β >, the p.d.f. of a beta distribution with parameters α and β is { Γ(α+β) Γ(α)Γ(β) f(x α, β) xα 1 (1 x) β 1 for < x
Section 9.2 Polar Equations and Graphs
180 Section 9. Polar Equations and Graphs In this section, we will be graphing polar equations on a polar grid. In the first few examples, we will write the polar equation in rectangular form to help identify
Step-Indexed Syntactic Logical Relations for Recursive and Quantified Types
Step-Indexed Syntactic Logical Relations for Recursive and Quantified Types Amal Ahmed Harvard University amal@eecs.harvard.edu March 2006 Abstract We present a proof technique, based on syntactic logical
Integrals in cylindrical, spherical coordinates (Sect. 15.7)
Integrals in clindrical, spherical coordinates (Sect. 5.7 Integration in spherical coordinates. Review: Clindrical coordinates. Spherical coordinates in space. Triple integral in spherical coordinates.
λρ-calculus 1. each λ-variable is a λρ-term, called an atom or atomic term; 2. if M and N are λρ-term then (MN) is a λρ-term called an application;
λρ-calculus Yuichi Komori komori@math.s.chiba-u.ac.jp Department of Mathematics, Faculty of Sciences, Chiba University Arato Cho aratoc@g.math.s.chiba-u.ac.jp Department of Mathematics, Faculty of Sciences,
SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM
SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM Solutions to Question 1 a) The cumulative distribution function of T conditional on N n is Pr T t N n) Pr max X 1,..., X N ) t N n) Pr max