large deviations principles for lacunary sums
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Large deviations principles for lacunary sums Nina Gantert joint work, soon to be finished with Christoph Aistleitner, Zakhar Kabluchko, Joscha Prochno, Kavita Ramanan 1/20 Thanks to: Aicke Hinrichs, Joscha Prochno, Christoph Th ale,


  1. Large deviations principles for lacunary sums Nina Gantert joint work, soon to be finished with Christoph Aistleitner, Zakhar Kabluchko, Joscha Prochno, Kavita Ramanan 1/20

  2. Thanks to: Aicke Hinrichs, Joscha Prochno, Christoph Th¨ ale, Elisabeth Werner for organizing “New Perspectives and Computational Challenges in High Dimensions” MFO, February 2020 2/20

  3. What is a lacunary sum? First: What is a lacunary sum? Let Ω = [0 , 1] , P = Lebesgue measure, take an increasing sequence ( a k ) k ∈ N of positive integers satifying the Hadamard gap condition a k +1 > q for some q > 1 . a k Then, n � S n ( ω ) = cos(2 π a k ω ) k =1 is called lacunary (trigonometric) sum. 3/20

  4. What is a lacunary sum? Question Does ( S n ) share the properties of a sum of i.i.d. random variables? Remark n � S n = X k with X k = cos(2 π a k ω ) k =1 X j and X k are not independent if j � = k. X 1 , X 2 , . . . are identically distributed X j and X k are uncorrelated if j � = k. 4/20

  5. Law of large numbers Law of large numbers: Theorem (Hermann Weyl) S n n → 0 P − a.s. for n → ∞ . (1) Indeed this is true for all ω ∈ [0 , 1] \ Q . Remark If a k = q k for some q ∈ { 2 , 3 , 4 , . . . } , (1) follows from the ergodic theorem: ω = ( ω 1 , ω 2 , ω 3 , . . . ) where the ω i are i.i.d. and uniform on { 0 , 1 , . . . , q − 1 } . q k ω mod 1 = T k ω where T is the shift transformation: T ω = ( ω 2 , ω 3 , ω 4 , . . . ) . Hence n � f ( T k ω ) S n ( ω ) = k =1 with f ( x ) = cos(2 π x ) . 5/20

  6. Law of large numbers Remark The last argument is still true if we replace x → cos(2 π x ) by another 1 -periodic function f . 6/20

  7. Central limit theorem Central limit theorem: Theorem (Salem, Zygmund) � � � t � � n � − u 2 1 1 √ P � cos(2 π a k ω ) ≤ t → exp du 2 n / 2 2 π k =1 −∞ 7/20

  8. Central limit theorem Question Does the CLT still hold if we replace x → cos(2 π x ) by another 1 -periodic function f ? Answer: in general, no! Example (Erd¨ os, Fortet) Take f ( x ) = cos(2 π x ) + cos(4 π x ) and a k = 2 k − 1, then � � n � 1 � cos(2 π a k ω ) ≤ t → F ( t ) P n / 2 k =1 where F is not the distribution function of a Gaussian law. 8/20

  9. Central limit theorem Theorem (Kac) � 1 0 f ( x ) dx = 0 and a k = 2 k , the CLT holds with If f is BV and � 1 � 1 � ∞ σ 2 = f ( x ) 2 dx + 2 f ( x ) f (2 k x ) dk . k =1 0 0 . 9/20

  10. Law of the iterated logarithm Law of the iterated logarithm: Theorem (Erd¨ os, Gal) � n cos(2 π a k ω ) k =1 lim sup √ n log log n = 1 P -a.s. . n →∞ 10/20

  11. Our question: large deviations? Our question: large deviations? Let x > 0. Then, � S n � n ≥ x → 0 for n → ∞ . P Exponential rate of decay? 11/20

  12. Our question: large deviations? Theorem If ( a k ) obeys the large gap condition a k +1 / a k → ∞ , then the random variables S n / n satisfy a large deviation principle with rate function � I, where � I is given by � � � 1 S n � I ( x ) = − lim n log P n ≥ x n →∞ � n for x > 0 , where � S n = cos(2 π a k U k ) with U 1 , U 2 , . . . i.i.d. and uniform k =1 on [0 , 1] . Hence, the rate function is the same as for a sum of i.i.d random variables. I is convex, � � I (1) = � I ( − 1) = + ∞ . 12/20

  13. Our question: large deviations? Remark n n � � � S n = cos(2 π a k U 1 ) , S n = cos(2 π a k U k ) . k =1 k =1 To show the statement, it suffices to show that for all θ ∈ R � e θ S n � � S n � 1 1 e θ � lim n log E = lim n log E = Λ( θ ) (2) n →∞ n →∞ and that θ → Λ( θ ) is differentiable. 13/20

  14. Our question: large deviations? The proof of (2) is simpler in the case when m k := a k +1 / a k ∈ N , ∀ k . Again, in this case ω can be written as a sequence ω = ( ω 1 , ω 2 , ω 3 , . . . ) where the ω k are independent, with uniform distribution on { 0 , 1 , . . . , m k − 1 } . More precisely, define the filtration F 1 ⊂ F 2 ⊂ . . . , where � � F k +1 := σ J k +1 , i , i = 0 , . . . , a k +1 − 1 , k ∈ N 0 , where � � , i + 1 i J k +1 , i := , i = 0 , . . . , a k +1 − 1 . a k +1 a k +1 Let Y k := E [ X k | F k +1 ] Then Y k , k ∈ N 0 are independent ( Y k is a function of ω k !) a k � X k − Y k � ∞ ≤ 2 π . (3) a k +1 14/20

  15. Our question: large deviations? Reason for (3): � � � � � � � max | X k ( ω ) − Y k ( ω ) | = max � X k ( ω ) − a k +1 X k ( y ) dy � ω ∈ J k +1 , i ω ∈ J k +1 , i J k +1 , i � � � X k ( ω ) − X k ( y 0 ) � = max ω ∈ J k +1 , i � � � ω − y 0 � ≤ max 2 π a k ω ∈ J k +1 , i ≤ 2 π a k , a k +1 where y 0 ∈ J k +1 , i comes from the mean value theorem. Hence, for S n := � n S n := � n k =1 X k and � k =1 Y k , n � a k � S n − � S n � ∞ ≤ 2 π = o ( n ) , n → ∞ , a k +1 k =1 because by assumption a k / a k +1 → 0 as k → ∞ . This suffices to show (2). 15/20

  16. Our question: large deviations? Theorem If a k = q k for some q ∈ { 2 , 3 , 4 , . . . } , the random variables S n / n satisfy a large deviation principle with rate function I q , I q � = � I, I q ( x ) → � I ( x ) for q → ∞ , for all x ∈ ( − 1 , 1) . 16/20

  17. Our question: large deviations? Theorem There exists a sequence of positive integers ( a k ) k ∈ N satisfying a k +1 / a k ≥ q for some q > 1 and all k ∈ N , for which S n / n does not satisfy a large deviation principle. More precisely, for this sequence ( a k ) k ∈ N there exists ¯ x 0 ∈ (0 , 1) such that for all x 0 ∈ (0 , ¯ x 0 ) , n →∞ − 1 n →∞ − 1 0 < lim inf n log P ( S n > nx 0 ) < lim sup n log P ( S n > nx 0 ) < ∞ . 17/20

  18. Our question: large deviations? Theorem There is a sequence ( a k ) such that a k +1 / a k → 2 and the random variables S n / n satisfy a large deviation principle with rate function � I � = I 2 . Hence, large deviations are sensitive to the properties (not only the growth) of the sequence ( a k )! 18/20

  19. Our question: large deviations? Remark (Sublacunary case) Assume a k → ∞ , 1 k log a k → 0 , i.e. the Hadamard gap condition is not satisfied. Then � S n � 1 n log P n ≥ 1 − ε → 0 . Proof There is δ > 0 such that 2 π a k ω ≤ δ ⇒ cos(2 π a k ω ) ≥ 1 − ε . But δ P [2 π a k ω ≤ δ for k ∈ { 1 , 2 , . . . n } ] = P [2 π a n ω ≤ δ ] = . 2 π a n Hence � S n � 1 ≥ 1 δ n log P n ≥ 1 − ε n log → 0 . 2 π a n 19/20

  20. Our question: large deviations? Thanks for your attention! 20/20

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