THREE SPACES PROBLEM FOR LYAPUNOV THEOREM ON VECTOR MEASURE. V. M. Kadets, O. I. Vladimirskaya

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Serdica Math. J. 24 (998), 45-52 THREE SPACES PROBLEM FOR LYAPUNOV THEOREM ON VECTOR MEASURE V. M. Kadets, O. I. Vladimirskaya Communicated by G. Godefroy Abstract. It is proved that a Banach space X has the Lyapunov property if its subspace Y and the quotient space X/Y have it. Let Σ be a σ-algebra of subsets of a set Ω, X be a Banach space, µ : Σ X be a countably additive measure. The famous theorem of A. A. Lyapunov ([9], [, Theorem 5.5], [2, p. 264]) states that the range µ(σ) of an arbitrary X- valued nonatomic measure µ is convex if X is a finite-dimensional space. Some generalizations of this theorem to infinite-dimensional case have been obtained by G. Knowles [7], I. I. Uhl [2], D. Pecherskii [0], V. Kadets [4], J. Elton and Th. P. Hill [3], V. Kadets and M. Popov [5] under various additional assumptions on the measure and the space. Most of these generalizations consider the closure of the measure range. Without additional restrictions the theorem is valid only in finite-dimensional case [2, p. 256, Corollary 6]. Definition. A Banach space X is said to have the Lyapunov property (X LPr) if for every nonatomic measure µ valued in X the closure of its range clµ(σ) is convex. 99 Mathematics Subject Classification: 46B20, 46G0 Key words: Banach space, vector measure, three spaces problem, Lyapunov convexity theorem

46 V. M. Kadets, O. I. Vladimirskaya The spaces l p ( p < ; p 2) and c 0 [6] have the Lyapunov property. Other examples have not been constructed till now. The other known generalizations have been proved with additional restrictions on the measure (for example, about the measures of bounded variations). Three spaces problem appears for every Banach space property. Namely, do a subspace Y and the quotient space X/Y have the property if X does and does X have the property if Y and X/Y do? Some of these problems can be solved easily in the case of the Lyapunov property. Indeed, if X LPr and Y X, then Y LPr, but X/Y do not need to have the Lyapunov property (for instance, X = l because the set of its quotient spaces contains all separable Banach spaces [8, p. 08]). In the same time the answer to the last problem runs into difficulties. The purpose of this paper is the positive solution of the mentioned problem: Theorem. LPr, then X LPr. Let Y be a subspace of a Banach space X. If Y,X/Y Let us remark that some new examples of spaces possessing the Lyapunov property can be constructed due to this theorem (for instance l p l p2 l pn, where p k < ; p k 2). To prove the theorem we need some lemmas. Lemma. Let X LPr and µ : Σ X be a nonatomic measure. Then there is a nonatomic nonnegative measure λ : Σ R such that for every A Σ and n N there exists B n Σ A satisfying the following inequalities: µ (B n) 2 µ (A) 2 n and λ(b n) () 2 λ(a) 2 n. Proof. By the Rybakov theorem [2, p. 267] there is a functional x X with x = for which µ x µ. Put λ = x µ. Let A Σ. In accordance with the Hahn decomposition theorem let us denote by Ω + and Ω the positivity and negativity sets for x µ respectively. Then λ(c) = x µ (C Ω + ) x µ (C Ω ) for any C Σ. Put A + = A Ω + and A = A Ω. Since X LPr, we can choose B n + Σ A + and Bn Σ A such that µ (B+ n ) 2 µ ( A +) and 2n+ µ (B n ) 2 µ ( A ) 2n+. Then x µ (B n + ) 2 x µ ( A +) 2 n+ and x µ (Bn ) 2 x µ ( A ) 2 n+. Define B n as B n + B n. It is easy to check that for B n the inequalities () are true.

Three spaces problem for Lyapunov theorem on vector measure 47 Lemma 2. Let X LPr, µ : Σ X be a nonatomic measure, λ be the measure from Lemma. Then for every A Σ with λ(a) 0 and ε > 0 there exist G Σ A, G = A\G such that (i) (ii) λ ( G ) = λ ( G ) = 2 λ(a), µ ( G ) 2 µ (A) < ε. Proof. Let us choose B n as in Lemma. We can select C n Σ Bn if λ(b n ) 2 λ(a) or C n Σ A\Bn if λ(b n ) < λ(a) for which 2 λ(c n ) = 2 λ(a) λ(b n) (because λ is a nonatomic real-valued measure). By (), λ(c n ) 0. Put G n = B n C n,g n = A\G n. Then λ(g n ) = λ(g n ) = 2 λ(a), λ(g n \B n) 0 and λ(b n \G n ) 0. Since λ µ the last condition implies that µ (B n \G n ) 0 and µ (G n \B n) 0. Together with inequality () it gives us µ ( G ) n 2 µ (A) 0. So for sufficiently large n the sets G = G n and G = G n will satisfy the conditions (i) and (ii). Lemma 3. Under the conditions of Lemma 2 for every A Σ with λ(a) 0 and ε > 0 there exists a σ-algebra Σ Σ A such that for every B Σ we have µ (B) λ(b) µ (A) (2) λ(a) ελ(b) and measure λ is nonatomic on Σ. Proof. Take A Σ and ε > 0. Employing Lemma 2, we choose sets A Σ A, A 2 =A\A with λ(a )=λ(a 2 ) = 2 λ(a) and µ (A ) 2 µ (A) 4 ε (note that µ (A ) 2 µ (A) = 2 µ (A ) µ (A 2 ) = µ (A 2) 2 µ (A) 4 ε). Employing Lemma 2 twice (for A = A and A = A 2 ) we obtain A, Σ A,A,2 = A \A, ;A 2, Σ A2,A 2,2 = A 2 \A 2, with λ(a, ) = λ(a,2 ) = λ(a 2, ) =λ(a 2,2 )= 4 λ(a) and µ (A, ) 2 µ (A ) ε 6, µ (A 2,) 2 µ (A 2)

48 V. M. Kadets, O. I. Vladimirskaya ε 6. When we continue this process we receive a tree of sets A i,i 2,...,i n, i k {,2}, n N with A i,i 2,...,i n+ A i,i 2,...,i n, A i,i 2,...,i n,2 = A i,i 2,...,i n \A i,i 2,...,i n,, µ (A i,i 2,...,i n ) 2 µ ( ) A i,i 2,...,i n 4 nε, λ(a i,i 2,...,i n ) = 2 n λ(a) Let Σ be a σ-algebra generated by the sets A i,i 2,...,i n. We are going to show that algebra Σ has the required property. Let B = A i,i 2,...,i n. Then µ (B) λ(b) λ(a) µ (A) = µ (A i,i 2,...,i n ) 2 nµ(a) µ (A i,i 2,...,i n ) 2 µ ( ) A i,i 2,...,i n + 2 µ ( ) A i,i 2,...,i n 2 µ ( ) A i,i 2,...,i n 2 + + 2 n µ (A i ) 2 µ (A) 4 nε + 2 4n ε +... + 2 n 4 ε ( = ε 2 2n + 2 2(n ) + + ) 2 n+ = ελ(a i,i 2,...,i n ). 2 nε Hence by triangle inequality and σ-additivity of µ and λ we get (2) for B = B n, where B n are disjoint sets of the form A i,i 2,...,i k. Then we obtain (2) n= for every B Σ using approximation of λ(b) by bigger sets of the form B = B n. n= Lemma 4. The statements of Lemmas 2 and 3 are valid for arbitrary nonatomic measure λ.

Three spaces problem for Lyapunov theorem on vector measure 49 Proof. Let µ : Σ X, λ : Σ R + be nonatomic measures. Let ν be the measure which played the role of λ in Lemma. Consider two cases. Case : λ ν. Take A Σ, n N. In view of Lemma 3, there is Σ Σ A such that for any B Σ (3) ν (B) µ (B) ν (A) µ (A) 2 n ν (B), ν is nonatomic measure with respect to Σ. Applying the Lyapunov theorem to the measure σ : Σ R 2 : σ (A) = (ν (A), λ(a)), we obtain sets G,G Σ such that λ(g ) = λ(g ) = 2 λ(a) and ν (G ) = ν (G ) = ν (A). Then (3) 2 implies inequality (ii) which we need. Case 2: λ ν. We decompose λ into the sum of absolutely continuous and strictly singular measures with respect to ν : λ = λ + λ 2. Then λ 2 is concentrated on a ν-negligible set S. Now we consider A\S and S A separately. By the case chose G A\S so that λ (G ) = 2 λ (A), µ (G ) 2 µ (A) 2 n and G 2 S A with λ 2 (G 2 ) = 2 λ(s A). Because λ (G 2 ) = 0, µ (G 2 ) = 0 and λ 2 (G ) = 0 it is clear that G = G G 2 satisfies (ii). Obviously, if Lemma 2 is valid for arbitrary λ then Lemma 3 is valid too. The following statement is evident. Lemma 5. If X is a Banach space, Y is a subspace of X, µ : Σ X is a nonatomic measure, then µ : Σ X/Y (µ (A) = µ (A)-the equivalence class of µ (A)) is a nonatomic measure too. Let X,Y be from the theorem, µ : Σ X, λ : Σ R + be nonatomic measures, λ(ω) =. Fix A Σ, λ(a) 0 and ε > 0. By lemmas 3 and 4 there is a σ-algebra Σ Σ A such that (4) λ(b) µ (B) λ(a) µ (A) < 2 ελ(b) for all B Σ and λ is nonatomic on Σ. Define σ : Σ X by the rule σ (B) = µ (B) λ(b) λ(a) µ (A). Lemma 6. β : Σ Y such that There exist a σ-algebra Σ Σ and a nonatomic measure σ (B) β (B) < 2ε

50 V. M. Kadets, O. I. Vladimirskaya for all B Σ. Proof. By inequality (4) and nonatomicity of λ we can choose sets A, A 2 Σ such that A = A A2,λ(A ) = λ(a 2 ) = 2 λ(a), and σ (A ) < ε 2 λ(a). Clearly, there is x σ (A ) such that x ε 2λ(A). Denote α (A ) = x, α (A 2 ) = x, Applying step by step Lemma 2 and Lemma 4, we get sets A i,...,i κ Σ, k = 2,3,...; i,...,i k =,2, such that A i,...,i k = A i,...,i k, Ai,...,i k,2, λ(a i,...,i k ) = 2 λ( ) A i,...,i k = λ(a), and 2k σ ( ) A i,...,i k, 2 σ ( ) A i,...,i k < ε 2 2k λ(a). It is readily seen that in every equivalence class σ ( ) A i,...,i k, 2 σ ( ) A i,...,i k X there exists an element xi,...,i k such that x i,...,i k ε λ(a). Put 22k α ( ) A i,...,i k, = 2 α( ) A i,...,i k + xi,...,i k, α ( ) A i,...,i k,2 = 2 α( ) A i,...,i k xi,...,i k. Evidently, α ( ( ( ( A i,...,i k,) σ Ai,...,i k,) and α Ai,...,i k,2) σ Ai,...,i k,2). By Σ denote σ-algebra generated by the sets A i,...,i k. Iterating the inequality α (A i,...,i k ) ( ) α Ai,...,i 2 k + ε 2 2k λ(a), we obtain α(a i,...,i k ) ε 2 k λ(a) = 2ελ(A i,...,i k ). Let us extend α to Σ and show that (5) α (B) 2ελ(B) for any B Σ. For this purpose we take B = I A i,...,i k, where I is a finite set of indices and A i,...,i k are mutually disjoint sets. Put α(b) = I Clearly, α(a i,...,i k ). α(b) I α (A i,...,i k ) 2ε I λ(a i,...,i k ) = 2ελ(B). This proves that inequality (5) is valid for elements of algebra S, generated by the sets A i,...,i k. Now applying the Kluvanek-Uhl extension theorem [] we obtain

Three spaces problem for Lyapunov theorem on vector measure 5 the extension of α to Σ. Thus, we have constructed the measure α : Σ X such that α (B) σ (B) for any B Σ and α (B) 2ελ(B). α is a nonatomic measure because λ is nonatomic by construction. It is clear that β = α σ has the required property. The lemma is proved. Let us complete the proof of the theorem. Since β : Σ Y is nonatomic measure and Y LPr, we see that by Lemma 2 there is B Σ such that λ(b) = λ(a) and 2 β (B) 2 β (A) ε. Thus we have σ (B) 2 σ (A) σ (B) β (B) + 2 σ (A) 2 β (A) + β (B) 2 β (A) 3ε. Since σ (B) 2 σ (A) = µ (B) µ (A), the proof is completed. 2 REFERENCES [] J. Diestel. Geometry of Banach spaces. Lecture Notes in Math. vol. 485, Springer-Verlag, 975. [2] J. Diestel, I. I. Uhl, Jr. Vector measures. Math. Surveys, vol. 5, Amer. Math. Soc, Providendence, RI, 977. [3] J. Elton, Th. P. Hill. A generalization of Lyapounov s convexity theorem to measures with atoms. Proc. Amer. Math. Soc. 99, 2 (987), 297-304 [4] V. M. Kadets. Notes to Lyapunov theorem on vector measure. Funktsional. Anal. i Prilozhen. 25, 4 (99), 78-80 (in Russian). [5] V. M. Kadets, M. M. Popov. On the Lyapunov convexity theorem with applications to sign-embeddings. Ukrainian Math. J. 4, 9 (99), 92-200. [6] V. M. Kadets, G. Schechtman. The Lyapunov theorem for l p valued measures. Algebra i Analiz 4, 5 (992), 48-54 (in Russian); translated as St. Peterburg Math. J. 4, 5 (993), 96-966. [7] G. Knowles. Lyapunov vector measure. SIAM J. Control Optim. 3 (974), 294-303.

52 V. M. Kadets, O. I. Vladimirskaya [8] J. Lindenstrauss, L. Tzafriri. Classical Banach Spaces I. Springer- Verlag, 977. [9] A. A. Lyapunov. On completely additive vector-valued functions. Izv. Acad. Nauk SSSR Ser. Mat. 4 (940), 465-478, (in Russian, French summary). [0] D. Pecherskii. Theorem on projection of rearranged series in L p. Izv. Akad. Nauk SSSR Ser. Mat. 4, (977), 203-24. [] Walter Rudin. Functional Analysis. Mc Graw-Hill, New York, 973. V. M. Kadets Department of Mathematics Kharkov State University Kharkov Ukraine O. I. Vladimirskaya Chair of Mathematics Kharkov Academy of Municipal Economy Kharkov Ukraine Received March 8, 996 Revised December 7, 997