Recovering Short Generators of Principal Ideals in Cyclotomic Rings

Size: px
Start display at page:

Download "Recovering Short Generators of Principal Ideals in Cyclotomic Rings"

Transcription

1 Recoering Shor Generaors of Principal Ideals in Cycloomic Rings Léo Ducas CWI, Amserdam, The Neherlands Join work wih Ronald Cramer Chris Peiker Oded Rege Conference on Mahemaics of Crypography, Augus 205, UC Irine Slides reised on Sep. 7, 205. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus 205 / 30

2 Recoering Shor Generaors for Crypanalysis A few cryposysems (Fully Homomorphic Encrypion [Smar and Vercaueren, 200] and Mulilinear Maps [Garg e al., 203, Langlois e al., 204]) share his KeyGen: sk Choose a shor g in some ring R as a priae key pk Gie a bad Z-basis B of he ideal (g) as a public key (e.g. HNF). Crypanalysis in wo seps (Key Recoery Aack) Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

3 Recoering Shor Generaors for Crypanalysis A few cryposysems (Fully Homomorphic Encrypion [Smar and Vercaueren, 200] and Mulilinear Maps [Garg e al., 203, Langlois e al., 204]) share his KeyGen: sk Choose a shor g in some ring R as a priae key pk Gie a bad Z-basis B of he ideal (g) as a public key (e.g. HNF). Crypanalysis in wo seps (Key Recoery Aack) Principal Ideal Problem (PIP) Gien a Z-basis B of a principal ideal I, Recoer some generaor h (i.e. I = (h)) Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

4 Recoering Shor Generaors for Crypanalysis A few cryposysems (Fully Homomorphic Encrypion [Smar and Vercaueren, 200] and Mulilinear Maps [Garg e al., 203, Langlois e al., 204]) share his KeyGen: sk Choose a shor g in some ring R as a priae key pk Gie a bad Z-basis B of he ideal (g) as a public key (e.g. HNF). Crypanalysis in wo seps (Key Recoery Aack) Principal Ideal Problem (PIP) Gien a Z-basis B of a principal ideal I, Recoer some generaor h (i.e. I = (h)) 2 Shor Generaor Problem Gien an arbirary generaor h R of I Recoer g (or some g equialenly shor) Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

5 Cos of hose wo seps Principal Ideal Problem (PIP) sub-exponenial ime (2Õ(n2/3) ) classical algorihm [Biasse and Fieker, 204, Biasse, 204]. progress oward quanum polynomial ime algorihm [Eisenräger e al., 204, Biasse and Song, 205b, Campbell e al., 204, Biasse and Song, 205a]. 2 Shor Generaor Problem equialen o he CVP in he log-uni laice becomes a BDD problem in he crypo cases. claimed o be easy [Campbell e al., 204] in he cycloomic case m = 2 k confirmed by experimens [Schank, 205] This Work [Cramer e al., 205] We focus on sep 2, and proe i can be soled in classical polynomial ime for he aforemenioned crypanalyic insances, when he ring R is he ring of inegers of he cycloomic number field K = Q(ζ m ) for m = p k. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

6 Oeriew Inroducion 2 Preliminary 3 Geomery of Cycloomic Unis 4 Shorness of Log g Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

7 The Logarihmic Embedding Le K be a number field of degree n, σ... σ n : K C be is embeddings, and le R be is ring of inegers. The logarihmic Embedding is defined as I induces Log : K R n x (log σ (x),..., log σ n (x) ) a group morphism from (K \ {0}, ) o (R n, +) a monoid morphism from (R \ {0}, ) o (R n, +) Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

8 The Uni Group Le R denoes he muliplicaie group of unis of R. Le Λ = Log R. By Dirichle Uni Theorem he kernel of Log is he cyclic group T of roos of uniy of R Λ R n is an laice of rank r + c (where K has r real embeddings and 2c complex embeddings) Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

9 The Uni Group Le R denoes he muliplicaie group of unis of R. Le Λ = Log R. By Dirichle Uni Theorem he kernel of Log is he cyclic group T of roos of uniy of R Λ R n is an laice of rank r + c (where K has r real embeddings and 2c complex embeddings) Reducion o CVP Elemens g, h R generae he same ideal if and only if h = g u for some uni u R. In paricular Log g Log h + Λ. and g is he smalles generaor iff Log u Λ is a ecor closes o Log h. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

10 Example: Embedding Z[ 2] R 2 x-axis: a + b 2 a + b 2 y-axis: a + b 2 a b Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

11 Example: Embedding Z[ 2] R 2 x-axis: a + b 2 a + b 2 y-axis: a + b 2 a b Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

12 Example: Embedding Z[ 2] R 2 2 x-axis: a + b 2 a + b 2 y-axis: a + b 2 a b 2 componen-wise muliplicaion Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

13 Example: Embedding Z[ 2] R 2 2 x-axis: a + b 2 a + b 2 y-axis: a + b 2 a b 2 componen-wise muliplicaion Symmeries induced by mul. by conjugaion 2 2 Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

14 Example: Embedding Z[ 2] R 2 2 x-axis: a + b 2 a + b 2 y-axis: a + b 2 a b 2 componen-wise muliplicaion Symmeries induced by mul. by conjugaion 2 2 Orhogonal elemens Unis (algebraic norm ) Isonorms cures Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

15 Example: Logarihmic Embedding Log Z[ 2] ({ }, +) is a sub-monoid of R 2 Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

16 Example: Logarihmic Embedding Log Z[ 2] Λ =({ }, +) is a laice of R 2, orhogonal o (, ) Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

17 Example: Logarihmic Embedding Log Z[ 2] { } are shifed finie copies of Λ Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

18 Example: Logarihmic Embedding Log Z[ 2] Some { } may be empy (e.g. no elemens of Norm 3 in Z[ 2]) Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

19 Reducion modulo Λ = Log Z[ 2] The reducion modλ for arious fundamenal domains. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

20 Reducion modulo Λ = Log Z[ 2] The reducion modλ for arious fundamenal domains. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

21 Reducion modulo Λ = Log Z[ 2] The reducion modλ for arious fundamenal domains. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

22 Reducion modulo Λ = Log Z[ 2] The reducion modλ for arious fundamenal domains. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

23 Decoding wih he RoundOff algorihm The simples algorihm [Babai, 986] o reduce modulo a laice RoundOff(B, ), B a Z-basis of Λ = B (B ) e = reurn (, e) where B Used as a decoding algorihm, is correcness is characerized by he error e and he dual basis B. Fac(Correcness of RoundOff) le = + e for some Λ. If b j, e [ 2, 2 ) for all j, hen RoundOff(B, ) = (, e). Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

24 RoundOff in picures RoundOff algorihm: Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus 205 / 30

25 RoundOff in picures (B ) RoundOff algorihm: use basis B o swich o he laice Z n ( (B ) ) = (B ) ; Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus 205 / 30

26 RoundOff in picures (B ) RoundOff algorihm: use basis B o swich o he laice Z n ( (B ) ) 2 Round each coordinae = (B ) ; = ; Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus 205 / 30

27 RoundOff in picures (B ) B RoundOff algorihm: use basis B o swich o he laice Z n ( (B ) ) 2 Round each coordinae 3 Swich back o he laice L ( B) = (B ) ; = ; = B Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus 205 / 30

28 Recoering Shor Generaor: Proof Plan Folklore sraegy [Bernsein, 204, Campbell e al., 204] o recoer a shor generaor g Consruc a basis B of he uni-log laice Log R For K = Q(ζ m ), m = p k, an (almos 2 ) canonical basis is gien by b j = Log ζj, j {2,..., m/2}, j co-prime wih m ζ 2 Proe ha he basis is good, ha is b j are all small 3 Proe ha e = Log g is small enough 2 i only spans a super-laice of finie index h + which is conjecured o be small Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

29 Recoering Shor Generaor: Proof Plan Folklore sraegy [Bernsein, 204, Campbell e al., 204] o recoer a shor generaor g Consruc a basis B of he uni-log laice Log R For K = Q(ζ m ), m = p k, an (almos 2 ) canonical basis is gien by b j = Log ζj, j {2,..., m/2}, j co-prime wih m ζ 2 Proe ha he basis is good, ha is b j are all small 3 Proe ha e = Log g is small enough Technical conribuions [CDPR5] 2 Esimae b j precisely using analyic ools [Washingon, 997, Lilewood, 924] 3 Bound e using heory of sub-exponenial random ariables [Vershynin, 202] 2 i only spans a super-laice of finie index h + which is conjecured o be small Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

30 Oeriew Inroducion 2 Preliminary 3 Geomery of Cycloomic Unis 4 Shorness of Log g Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

31 Cycloomic unis We fix he number field K = Q(ζ m ) where m = p k for some prime p. Se z j = ζ j and b j = z j /z for all j coprimes wih m. The b j are unis, and he group C generaed by ζ, b j for j = 2,... m/2, j coprime wih m is known as he group of cycloomic unis. 3 One jus need he index [R : C] = h + (m) o be small. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

32 Cycloomic unis We fix he number field K = Q(ζ m ) where m = p k for some prime p. Se z j = ζ j and b j = z j /z for all j coprimes wih m. The b j are unis, and he group C generaed by ζ, b j for j = 2,... m/2, j coprime wih m is known as he group of cycloomic unis. Simplificaion (Weber s Class Number Problem) We assume 3 ha R = C. I is conjecured o be rue for m = 2 k. 3 One jus need he index [R : C] = h + (m) o be small. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

33 Cycloomic unis We fix he number field K = Q(ζ m ) where m = p k for some prime p. Se z j = ζ j and b j = z j /z for all j coprimes wih m. The b j are unis, and he group C generaed by ζ, b j for j = 2,... m/2, j coprime wih m is known as he group of cycloomic unis. Simplificaion (Weber s Class Number Problem) We assume 3 ha R = C. I is conjecured o be rue for m = 2 k. Simplificaion 2 (for his alk) We sudy he dual marix Z, where z j = Log z j. I can be proed o close o B where b j = z j z. 3 One jus need he index [R : C] = h + (m) o be small. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

34 The marix Z The field K admis exacly ϕ(m)/2 pairs of conjugae complex embeddings σ i = σ i, where σ i : ζ ω i is defined for all i Z m. where ω = exp(2ıπ/m) C is a primiie roo of uniy. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

35 The marix Z The field K admis exacly ϕ(m)/2 pairs of conjugae complex embeddings σ i = σ i, where σ i : ζ ω i is defined for all i Z m. where ω = exp(2ıπ/m) C is a primiie roo of uniy. cycliciy.pdf Figure : Naïe Indexing (i =, 3, 5,... ) Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

36 The marix Z The field K admis exacly ϕ(m)/2 pairs of conjugae complex embeddings σ i = σ i, where σ i : ζ ω i is defined for all i Z m. where ω = exp(2ıπ/m) C is a primiie roo of uniy. cycliciy2.pdf Figure : Muliplicaie Indexing (i = 3 0, 3, 3 2,... ) Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

37 Dual of a Circulan Basis Noice ha Z ij = log σ j ( ζ i ) = log ω ij : he marix Z is G-circulan for he cyclic group G = Z m/ ±. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

38 Dual of a Circulan Basis Noice ha Z ij = log σ j ( ζ i ) = log ω ij : he marix Z is G-circulan for he cyclic group G = Z m/ ±. Fac If M is a non-singular, G-circulan marix, hen is eigenalues are gien by λ χ = g G χ(g) M,g where χ Ĝ is a characer G C All he ecors of M hae he same norm m i 2 = χ Ĝ λ χ 2 Noe: The characers of G can be exended o een Dirichle characers mod m: χ : Z C, by seing χ(a) = 0 if gcd(a, m) >. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

39 Compuing he Eigenalues We wish o gie a lower bound on λ χ where λ χ = a G χ(a) log ω a. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

40 Compuing he Eigenalues We wish o gie a lower bound on λ χ where λ χ = a G χ(a) log ω a. Why no sop here? This formula is prey easy o ealuae numerically: a his poin we can already check RoundOff s correcness numerically up o m = 0 6 or more. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

41 Compuing he Eigenalues We wish o gie a lower bound on λ χ where λ χ = a G χ(a) log ω a. Why no sop here? This formula is prey easy o ealuae numerically: a his poin we can already check RoundOff s correcness numerically up o m = 0 6 or more. Somehing cue o be learned! The equaions looks no ery algebraic (log?), ye appears quie naurally... Surely mahemaicians knows how o deal wih his. Indeed, compuaion of he olume of ha basis appears in [Washingon, 997]. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

42 Compuing he Eigenalues We wish o gie a lower bound on λ χ where λ χ = a G χ(a) log ω a. We deelop using he Taylor series log x = k x k /k Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

43 Compuing he Eigenalues We wish o gie a lower bound on λ χ where λ χ = a G χ(a) log ω a. We deelop using he Taylor series log x = k x k /k and obain λ χ = a G k χ(a) ωka k. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

44 Compuing he Eigenalues (coninued) We were rying o lower bound λ χ where λ χ = k χ(a) ω ka. k a G Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

45 Compuing he Eigenalues (coninued) We were rying o lower bound λ χ where λ χ = k χ(a) ω ka. k a G Fac (Separabiliy of Gauss Sums) If χ is a primiie Dirichle characer modm hen χ(a) ω ka = χ(k) G(χ) where G(χ) = m. a Z m Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

46 Compuing he Eigenalues (coninued) We were rying o lower bound λ χ where λ χ = k χ(a) ω ka. k a G Fac (Separabiliy of Gauss Sums) If χ is a primiie Dirichle characer modm hen χ(a) ω ka = χ(k) G(χ) where G(χ) = m. a Z m For his alk, le s ignore non-primiie characers. We rewrie λ χ m = 2 χ(k) k. k Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

47 The Analyical Hammer We were rying o lower bound λχ = m 2 k One recognizes a Dirichle L-series L(s, χ) = χ(k) k s. χ(k) k. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

48 The Analyical Hammer We were rying o lower bound λχ = m 2 k One recognizes a Dirichle L-series L(s, χ) = χ(k) k s. Theorem ([Lilewood, 924, Youness e al., 203]) χ(k) k. Under he Generalized Riemann Hypohesis, for any primiie Dirichle characer χ mod m i holds ha /l(m) L(, χ) l(m) where l(m) = C ln ln m for some uniersal consan C > 0. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

49 Geomeric Conclusion Theorem (Cramer, D., Peiker, Rege) Le m = p k, and B = ( Log(b j )) j G\{} be he canonical basis of Log C. Then, all he ecors of B hae he same norm and, under GRH, his norm is upper bounded as follows b 2 j O ( m log 3 m ). Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

50 Oeriew Inroducion 2 Preliminary 3 Geomery of Cycloomic Unis 4 Shorness of Log g Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

51 Proof Plan (Reminder) Consruc a basis B of he uni-log laice Log R Choose he Canonical Cycloomics Unis b j = Log ζj ζ 2 Proe ha he basis is good, ha is b j are all small Proed b 2 j O ( m log 3 m ) 3 Proe ha e = Log g is small enough Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

52 Scaling Inariance Les assume he embeddings (σ i (g)) are i.i.d. of disribuion D. Log (s D n ) (,,... ) log s + Log D n Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

53 Heurisic argumen Using scaling, assume ha E[Log D m ] = 0. Le e Log D m (e = Log g) Each coordinae Log D of e are independens, cenered, of ariance V For any b, he ariance of b, e is V b By Marko Inequaliy, for a fixed i i should hold ha b i, e /2 excep wih o() probabiliy (recall we e proed ha b i = o()) Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

54 Conclusion from beer ail bounds The preious argumen does no allows o conclude simulanously on all i s. We fill his gap using sronger ail bounds, form he heory of sub-exponenial random ariables [Vershynin, 202] Theorem (Cramer, D., Peiker, Rege) If g follows a Coninuous Normal Disribuion, hen for e = Log g, we hae b i, e /2 for all i s excep wih negligible probabiliy. Corollary If g follows a Discree Normal Disribuion of parameer σ poly(m), hen for e = Log g, we hae b i, e /2 for all i s excep wih probabiliy /n Θ(). Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

55 Thanks Figure : The Shinani Domain of Z[ζ 7 + ζ 7 ]. Credi: Paul Gunells hp://people.mah.umass.edu/~gunnells/picures/picures.hml We hank Dan Bernsein, Jean-Franois Biasse, Sorina Ionica, Dimiar Jeche, Paul Kirchner, René Schoof, Dan Shepherd and Harold M. Sark for many insighful conersaions relaed o his work. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

56 References I Babai, L. (986). On Loász laice reducion and he neares laice poin problem. Combinaorica, 6(): 3. Preliminary ersion in STACS 985. Bernsein, D. (204). A subfield-logarihm aack agains ideal laices. hp://blog.cr.yp.o/ ideal.hml. Biasse, J.-F. (204). Subexponenial ime relaions in he class group of large degree number fields. Ad. Mah. Commun., 8(4): Biasse, J.-F. and Fieker, C. (204). Subexponenial class group and uni group compuaion in large degree number fields. LMS Journal of Compuaion and Mahemaics, 7: Biasse, J.-F. and Song, F. (205a). A noe on he quanum aacks agains schemes relying on he hardness of finding a shor generaor of an ideal in Q(z 2ˆn). hp://cacr.uwaerloo.ca/echrepors/205/cacr205-2.pdf. Technical Repor. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

57 References II Biasse, J.-F. and Song, F. (205b). A polynomial ime quanum algorihm for compuing class groups and soling he principal ideal problem in arbirary degree number fields. hp:// In preparaion. Campbell, P., Groes, M., and Shepherd, D. (204). Soliloquy: A cauionary ale. ETSI 2nd Quanum-Safe Crypo Workshop. Aailable a hp://docbox.esi.org/workshop/204/2040_crypto/s07_sysems_ and_aacks/s07_groes_annex.pdf. Cramer, R., Ducas, L., Peiker, C., and Rege, O. (205). Recoering shor generaors of principal ideals in cycloomic rings. Crypology eprin Archie, Repor 205/33. hp://eprin.iacr.org/. Eisenräger, K., Hallgren, S., Kiae, A., and Song, F. (204). A quanum algorihm for compuing he uni group of an arbirary degree number field. In Proceedings of he 46h Annual ACM Symposium on Theory of Compuing, pages ACM. Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

58 References III Garg, S., Genry, C., and Halei, S. (203). Candidae mulilinear maps from ideal laices. In EUROCRYPT, pages 7. Langlois, A., Sehlé, D., and Seinfeld, R. (204). Gghlie: More efficien mulilinear maps from ideal laices. In Adances in Crypology EUROCRYPT 204, pages Springer. Lilewood, J. (924). On he zeros of he riemann zea-funcion. In Mahemaical Proceedings of he Cambridge Philosophical Sociey, olume 22, pages Cambridge Uni Press. Schank, J. (205). LogCp, Pari implemenaion of CVP in log Z[ζ 2 n ]. hps://gihub.com/jschanck-si/logcp. Smar, N. P. and Vercaueren, F. (200). Fully homomorphic encrypion wih relaiely small key and cipherex sizes. In Public Key Crypography, pages Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

59 References IV Vershynin, R. (202). Compressed Sensing, Theory and Applicaions, chaper 5, pages Cambridge Uniersiy Press. Aailable a hp://www-personal.umich.edu/~roman/papers/non-asympoic-rm-plain.pdf. Washingon, L. (997). Inroducion o Cycloomic Fields. Graduae Texs in Mahemaics. Springer New York. Youness, L., Xiannan, L., and Kannan, S. (203). Condiional bounds for he leas quadraic non-residue and relaed problems. hp://arxi.org/abs/ Léo Ducas (CWI, Amserdam) Recoering Shor Generaors UC Irine, Augus / 30

Recovering Short Generators of Principal Ideals in Cyclotomic Rings

Recovering Short Generators of Principal Ideals in Cyclotomic Rings Recoering Shor Generaors of Principal Ideals in Cycloomic Rings Léo Ducas CWI, Amserdam, The Neherlands Join work wih Ronald Cramer Chris Peiker Oded Rege Presened a ICERM, Brown Uniersiy, April 205 Léo

More information

Recovering Short Generators of Principal Ideals in Cyclotomic Rings

Recovering Short Generators of Principal Ideals in Cyclotomic Rings Recovering Short Generators of Principal Ideals in Cyclotomic Rings Ronald Cramer Chris Peikert Léo Ducas Oded Regev University of Leiden, The Netherlands CWI, Amsterdam, The Netherlands University of

More information

Recovering Short Generators of Principal Ideals in Cyclotomic Rings

Recovering Short Generators of Principal Ideals in Cyclotomic Rings Recovering Short Generators of Principal Ideals in Cyclotomic Rings Ronald Cramer, Léo Ducas, Chris Peikert, Oded Regev 9 July 205 Simons Institute Workshop on Math of Modern Crypto / 5 Short Generators

More information

Finding Short Generators of Ideals, and Implications for Cryptography. Chris Peikert University of Michigan

Finding Short Generators of Ideals, and Implications for Cryptography. Chris Peikert University of Michigan Finding Short Generators of Ideals, and Implications for Cryptography Chris Peikert University of Michigan ANTS XII 29 August 2016 Based on work with Ronald Cramer, Léo Ducas, and Oded Regev 1 / 20 Lattice-Based

More information

1 Review of Zero-Sum Games

1 Review of Zero-Sum Games COS 5: heoreical Machine Learning Lecurer: Rob Schapire Lecure #23 Scribe: Eugene Brevdo April 30, 2008 Review of Zero-Sum Games Las ime we inroduced a mahemaical model for wo player zero-sum games. Any

More information

Bernoulli numbers. Francesco Chiatti, Matteo Pintonello. December 5, 2016

Bernoulli numbers. Francesco Chiatti, Matteo Pintonello. December 5, 2016 UNIVERSITÁ DEGLI STUDI DI PADOVA, DIPARTIMENTO DI MATEMATICA TULLIO LEVI-CIVITA Bernoulli numbers Francesco Chiai, Maeo Pinonello December 5, 206 During las lessons we have proved he Las Ferma Theorem

More information

Math-Net.Ru All Russian mathematical portal

Math-Net.Ru All Russian mathematical portal Mah-NeRu All Russian mahemaical poral Roman Popovych, On elemens of high order in general finie fields, Algebra Discree Mah, 204, Volume 8, Issue 2, 295 300 Use of he all-russian mahemaical poral Mah-NeRu

More information

CHAPTER 6: FIRST-ORDER CIRCUITS

CHAPTER 6: FIRST-ORDER CIRCUITS EEE5: CI CUI T THEOY CHAPTE 6: FIST-ODE CICUITS 6. Inroducion This chaper considers L and C circuis. Applying he Kirshoff s law o C and L circuis produces differenial equaions. The differenial equaions

More information

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t...

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t... Mah 228- Fri Mar 24 5.6 Marix exponenials and linear sysems: The analogy beween firs order sysems of linear differenial equaions (Chaper 5) and scalar linear differenial equaions (Chaper ) is much sronger

More information

arxiv:math/ v1 [math.nt] 3 Nov 2005

arxiv:math/ v1 [math.nt] 3 Nov 2005 arxiv:mah/0511092v1 [mah.nt] 3 Nov 2005 A NOTE ON S AND THE ZEROS OF THE RIEMANN ZETA-FUNCTION D. A. GOLDSTON AND S. M. GONEK Absrac. Le πs denoe he argumen of he Riemann zea-funcion a he poin 1 + i. Assuming

More information

An introduction to the theory of SDDP algorithm

An introduction to the theory of SDDP algorithm An inroducion o he heory of SDDP algorihm V. Leclère (ENPC) Augus 1, 2014 V. Leclère Inroducion o SDDP Augus 1, 2014 1 / 21 Inroducion Large scale sochasic problem are hard o solve. Two ways of aacking

More information

Linear Cryptanalysis

Linear Cryptanalysis Linear Crypanalysis T-79.550 Crypology Lecure 5 February 6, 008 Kaisa Nyberg Linear Crypanalysis /36 SPN A Small Example Linear Crypanalysis /36 Linear Approximaion of S-boxes Linear Crypanalysis 3/36

More information

On Ternary Quadratic Forms

On Ternary Quadratic Forms On Ternary Quadraic Forms W. Duke Deparmen of Mahemaics, Universiy of California, Los Angeles, CA 98888. Inroducion. Dedicaed o he memory of Arnold E. Ross Le q(x) = q(x, x, x ) be a posiive definie ernary

More information

Then. 1 The eigenvalues of A are inside R = n i=1 R i. 2 Union of any k circles not intersecting the other (n k)

Then. 1 The eigenvalues of A are inside R = n i=1 R i. 2 Union of any k circles not intersecting the other (n k) Ger sgorin Circle Chaper 9 Approimaing Eigenvalues Per-Olof Persson persson@berkeley.edu Deparmen of Mahemaics Universiy of California, Berkeley Mah 128B Numerical Analysis (Ger sgorin Circle) Le A be

More information

GCD AND LCM-LIKE IDENTITIES FOR IDEALS IN COMMUTATIVE RINGS

GCD AND LCM-LIKE IDENTITIES FOR IDEALS IN COMMUTATIVE RINGS GCD AND LCM-LIKE IDENTITIES FOR IDEALS IN COMMUTATIVE RINGS D. D. ANDERSON, SHUZO IZUMI, YASUO OHNO, AND MANABU OZAKI Absrac. Le A 1,..., A n n 2 be ideals of a commuaive ring R. Le Gk resp., Lk denoe

More information

SELBERG S CENTRAL LIMIT THEOREM ON THE CRITICAL LINE AND THE LERCH ZETA-FUNCTION. II

SELBERG S CENTRAL LIMIT THEOREM ON THE CRITICAL LINE AND THE LERCH ZETA-FUNCTION. II SELBERG S CENRAL LIMI HEOREM ON HE CRIICAL LINE AND HE LERCH ZEA-FUNCION. II ANDRIUS GRIGUIS Deparmen of Mahemaics Informaics Vilnius Universiy, Naugarduko 4 035 Vilnius, Lihuania rius.griguis@mif.vu.l

More information

Stationary Distribution. Design and Analysis of Algorithms Andrei Bulatov

Stationary Distribution. Design and Analysis of Algorithms Andrei Bulatov Saionary Disribuion Design and Analysis of Algorihms Andrei Bulaov Algorihms Markov Chains 34-2 Classificaion of Saes k By P we denoe he (i,j)-enry of i, j Sae is accessible from sae if 0 for some k 0

More information

6.2 Transforms of Derivatives and Integrals.

6.2 Transforms of Derivatives and Integrals. SEC. 6.2 Transforms of Derivaives and Inegrals. ODEs 2 3 33 39 23. Change of scale. If l( f ()) F(s) and c is any 33 45 APPLICATION OF s-shifting posiive consan, show ha l( f (c)) F(s>c)>c (Hin: In Probs.

More information

Lecture 10: The Poincaré Inequality in Euclidean space

Lecture 10: The Poincaré Inequality in Euclidean space Deparmens of Mahemaics Monana Sae Universiy Fall 215 Prof. Kevin Wildrick n inroducion o non-smooh analysis and geomery Lecure 1: The Poincaré Inequaliy in Euclidean space 1. Wha is he Poincaré inequaliy?

More information

18 Biological models with discrete time

18 Biological models with discrete time 8 Biological models wih discree ime The mos imporan applicaions, however, may be pedagogical. The elegan body of mahemaical heory peraining o linear sysems (Fourier analysis, orhogonal funcions, and so

More information

Lecture 33: November 29

Lecture 33: November 29 36-705: Inermediae Saisics Fall 2017 Lecurer: Siva Balakrishnan Lecure 33: November 29 Today we will coninue discussing he boosrap, and hen ry o undersand why i works in a simple case. In he las lecure

More information

PENALIZED LEAST SQUARES AND PENALIZED LIKELIHOOD

PENALIZED LEAST SQUARES AND PENALIZED LIKELIHOOD PENALIZED LEAST SQUARES AND PENALIZED LIKELIHOOD HAN XIAO 1. Penalized Leas Squares Lasso solves he following opimizaion problem, ˆβ lasso = arg max β R p+1 1 N y i β 0 N x ij β j β j (1.1) for some 0.

More information

An Introduction to Malliavin calculus and its applications

An Introduction to Malliavin calculus and its applications An Inroducion o Malliavin calculus and is applicaions Lecure 5: Smoohness of he densiy and Hörmander s heorem David Nualar Deparmen of Mahemaics Kansas Universiy Universiy of Wyoming Summer School 214

More information

A NOTE ON S(t) AND THE ZEROS OF THE RIEMANN ZETA-FUNCTION

A NOTE ON S(t) AND THE ZEROS OF THE RIEMANN ZETA-FUNCTION Bull. London Mah. Soc. 39 2007 482 486 C 2007 London Mahemaical Sociey doi:10.1112/blms/bdm032 A NOTE ON S AND THE ZEROS OF THE RIEMANN ZETA-FUNCTION D. A. GOLDSTON and S. M. GONEK Absrac Le πs denoe he

More information

Announcements: Warm-up Exercise:

Announcements: Warm-up Exercise: Fri Apr 13 7.1 Sysems of differenial equaions - o model muli-componen sysems via comparmenal analysis hp//en.wikipedia.org/wiki/muli-comparmen_model Announcemens Warm-up Exercise Here's a relaively simple

More information

Vehicle Arrival Models : Headway

Vehicle Arrival Models : Headway Chaper 12 Vehicle Arrival Models : Headway 12.1 Inroducion Modelling arrival of vehicle a secion of road is an imporan sep in raffic flow modelling. I has imporan applicaion in raffic flow simulaion where

More information

Finish reading Chapter 2 of Spivak, rereading earlier sections as necessary. handout and fill in some missing details!

Finish reading Chapter 2 of Spivak, rereading earlier sections as necessary. handout and fill in some missing details! MAT 257, Handou 6: Ocober 7-2, 20. I. Assignmen. Finish reading Chaper 2 of Spiva, rereading earlier secions as necessary. handou and fill in some missing deails! II. Higher derivaives. Also, read his

More information

Matlab and Python programming: how to get started

Matlab and Python programming: how to get started Malab and Pyhon programming: how o ge sared Equipping readers he skills o wrie programs o explore complex sysems and discover ineresing paerns from big daa is one of he main goals of his book. In his chaper,

More information

5. Stochastic processes (1)

5. Stochastic processes (1) Lec05.pp S-38.45 - Inroducion o Teleraffic Theory Spring 2005 Conens Basic conceps Poisson process 2 Sochasic processes () Consider some quaniy in a eleraffic (or any) sysem I ypically evolves in ime randomly

More information

Notes for Lecture 17-18

Notes for Lecture 17-18 U.C. Berkeley CS278: Compuaional Complexiy Handou N7-8 Professor Luca Trevisan April 3-8, 2008 Noes for Lecure 7-8 In hese wo lecures we prove he firs half of he PCP Theorem, he Amplificaion Lemma, up

More information

Heat kernel and Harnack inequality on Riemannian manifolds

Heat kernel and Harnack inequality on Riemannian manifolds Hea kernel and Harnack inequaliy on Riemannian manifolds Alexander Grigor yan UHK 11/02/2014 onens 1 Laplace operaor and hea kernel 1 2 Uniform Faber-Krahn inequaliy 3 3 Gaussian upper bounds 4 4 ean-value

More information

Matrix Versions of Some Refinements of the Arithmetic-Geometric Mean Inequality

Matrix Versions of Some Refinements of the Arithmetic-Geometric Mean Inequality Marix Versions of Some Refinemens of he Arihmeic-Geomeric Mean Inequaliy Bao Qi Feng and Andrew Tonge Absrac. We esablish marix versions of refinemens due o Alzer ], Carwrigh and Field 4], and Mercer 5]

More information

Zeta Functions of Representations

Zeta Functions of Representations COMMENTARII MATHEMATICI UNIVERSITATIS SANCTI PAULI Vol. 63, No. &2 204 ed. RIKKYO UNIV/MATH IKEBUKURO TOKYO 7 850 JAPAN Zea Funcions of Represenaions by Nobushige KUROKAWA and Hiroyuki OCHIAI (Received

More information

4.1 - Logarithms and Their Properties

4.1 - Logarithms and Their Properties Chaper 4 Logarihmic Funcions 4.1 - Logarihms and Their Properies Wha is a Logarihm? We define he common logarihm funcion, simply he log funcion, wrien log 10 x log x, as follows: If x is a posiive number,

More information

CHARACTERIZATION OF REARRANGEMENT INVARIANT SPACES WITH FIXED POINTS FOR THE HARDY LITTLEWOOD MAXIMAL OPERATOR

CHARACTERIZATION OF REARRANGEMENT INVARIANT SPACES WITH FIXED POINTS FOR THE HARDY LITTLEWOOD MAXIMAL OPERATOR Annales Academiæ Scieniarum Fennicæ Mahemaica Volumen 31, 2006, 39 46 CHARACTERIZATION OF REARRANGEMENT INVARIANT SPACES WITH FIXED POINTS FOR THE HARDY LITTLEWOOD MAXIMAL OPERATOR Joaquim Marín and Javier

More information

Short Stickelberger Class Relations and application to Ideal-SVP

Short Stickelberger Class Relations and application to Ideal-SVP Short Stickelberger Class Relations and application to Ideal-SVP Ronald Cramer Léo Ducas Benjamin Wesolowski Leiden University, The Netherlands CWI, Amsterdam, The Netherlands EPFL, Lausanne, Switzerland

More information

Spring Ammar Abu-Hudrouss Islamic University Gaza

Spring Ammar Abu-Hudrouss Islamic University Gaza Chaper 7 Reed-Solomon Code Spring 9 Ammar Abu-Hudrouss Islamic Universiy Gaza ١ Inroducion A Reed Solomon code is a special case of a BCH code in which he lengh of he code is one less han he size of he

More information

Chapter 6. Systems of First Order Linear Differential Equations

Chapter 6. Systems of First Order Linear Differential Equations Chaper 6 Sysems of Firs Order Linear Differenial Equaions We will only discuss firs order sysems However higher order sysems may be made ino firs order sysems by a rick shown below We will have a sligh

More information

Research Article Existence and Uniqueness of Periodic Solution for Nonlinear Second-Order Ordinary Differential Equations

Research Article Existence and Uniqueness of Periodic Solution for Nonlinear Second-Order Ordinary Differential Equations Hindawi Publishing Corporaion Boundary Value Problems Volume 11, Aricle ID 19156, 11 pages doi:1.1155/11/19156 Research Aricle Exisence and Uniqueness of Periodic Soluion for Nonlinear Second-Order Ordinary

More information

Solutions from Chapter 9.1 and 9.2

Solutions from Chapter 9.1 and 9.2 Soluions from Chaper 9 and 92 Secion 9 Problem # This basically boils down o an exercise in he chain rule from calculus We are looking for soluions of he form: u( x) = f( k x c) where k x R 3 and k is

More information

INDEPENDENT SETS IN GRAPHS WITH GIVEN MINIMUM DEGREE

INDEPENDENT SETS IN GRAPHS WITH GIVEN MINIMUM DEGREE INDEPENDENT SETS IN GRAPHS WITH GIVEN MINIMUM DEGREE JAMES ALEXANDER, JONATHAN CUTLER, AND TIM MINK Absrac The enumeraion of independen ses in graphs wih various resricions has been a opic of much ineres

More information

Centrum Wiskunde & Informatica, Amsterdam, The Netherlands

Centrum Wiskunde & Informatica, Amsterdam, The Netherlands Logarithmic Lattices Léo Ducas Centrum Wiskunde & Informatica, Amsterdam, The Netherlands Workshop: Computational Challenges in the Theory of Lattices ICERM, Brown University, Providence, RI, USA, April

More information

Approximation Algorithms for Unique Games via Orthogonal Separators

Approximation Algorithms for Unique Games via Orthogonal Separators Approximaion Algorihms for Unique Games via Orhogonal Separaors Lecure noes by Konsanin Makarychev. Lecure noes are based on he papers [CMM06a, CMM06b, LM4]. Unique Games In hese lecure noes, we define

More information

Comparison between the Discrete and Continuous Time Models

Comparison between the Discrete and Continuous Time Models Comparison beween e Discree and Coninuous Time Models D. Sulsky June 21, 2012 1 Discree o Coninuous Recall e discree ime model Î = AIS Ŝ = S Î. Tese equaions ell us ow e populaion canges from one day o

More information

Transform Techniques. Moment Generating Function

Transform Techniques. Moment Generating Function Transform Techniques A convenien way of finding he momens of a random variable is he momen generaing funcion (MGF). Oher ransform echniques are characerisic funcion, z-ransform, and Laplace ransform. Momen

More information

Chapter 3 Boundary Value Problem

Chapter 3 Boundary Value Problem Chaper 3 Boundary Value Problem A boundary value problem (BVP) is a problem, ypically an ODE or a PDE, which has values assigned on he physical boundary of he domain in which he problem is specified. Le

More information

QUANTITATIVE DECAY FOR NONLINEAR WAVE EQUATIONS

QUANTITATIVE DECAY FOR NONLINEAR WAVE EQUATIONS QUANTITATIVE DECAY FOR NONLINEAR WAVE EQUATIONS SPUR FINAL PAPER, SUMMER 08 CALVIN HSU MENTOR: RUOXUAN YANG PROJECT SUGGESTED BY: ANDREW LAWRIE Augus, 08 Absrac. In his paper, we discuss he decay rae for

More information

Games Against Nature

Games Against Nature Advanced Course in Machine Learning Spring 2010 Games Agains Naure Handous are joinly prepared by Shie Mannor and Shai Shalev-Shwarz In he previous lecures we alked abou expers in differen seups and analyzed

More information

THE GEOMETRY MONOID OF AN IDENTITY

THE GEOMETRY MONOID OF AN IDENTITY THE GEOMETRY MONOID OF AN IDENTITY Parick DEHORNOY Universié decaen Main idea: For each algebraic ideniy I, (more generally, for each family of algebraic ideniy, acually for each equaional variey), here

More information

Math Week 14 April 16-20: sections first order systems of linear differential equations; 7.4 mass-spring systems.

Math Week 14 April 16-20: sections first order systems of linear differential equations; 7.4 mass-spring systems. Mah 2250-004 Week 4 April 6-20 secions 7.-7.3 firs order sysems of linear differenial equaions; 7.4 mass-spring sysems. Mon Apr 6 7.-7.2 Sysems of differenial equaions (7.), and he vecor Calculus we need

More information

Two Coupled Oscillators / Normal Modes

Two Coupled Oscillators / Normal Modes Lecure 3 Phys 3750 Two Coupled Oscillaors / Normal Modes Overview and Moivaion: Today we ake a small, bu significan, sep owards wave moion. We will no ye observe waves, bu his sep is imporan in is own

More information

U( θ, θ), U(θ 1/2, θ + 1/2) and Cauchy (θ) are not exponential families. (The proofs are not easy and require measure theory. See the references.

U( θ, θ), U(θ 1/2, θ + 1/2) and Cauchy (θ) are not exponential families. (The proofs are not easy and require measure theory. See the references. Lecure 5 Exponenial Families Exponenial families, also called Koopman-Darmois families, include a quie number of well known disribuions. Many nice properies enjoyed by exponenial families allow us o provide

More information

arxiv:math.fa/ v1 31 Oct 2004

arxiv:math.fa/ v1 31 Oct 2004 A sharp isoperimeric bound for convex bodies Ravi Monenegro arxiv:mah.fa/0408 v 3 Oc 2004 Absrac We consider he problem of lower bounding a generalized Minkowski measure of subses of a convex body wih

More information

We just finished the Erdős-Stone Theorem, and ex(n, F ) (1 1/(χ(F ) 1)) ( n

We just finished the Erdős-Stone Theorem, and ex(n, F ) (1 1/(χ(F ) 1)) ( n Lecure 3 - Kövari-Sós-Turán Theorem Jacques Versraëe jacques@ucsd.edu We jus finished he Erdős-Sone Theorem, and ex(n, F ) ( /(χ(f ) )) ( n 2). So we have asympoics when χ(f ) 3 bu no when χ(f ) = 2 i.e.

More information

Computing Generator in Cyclotomic Integer Rings

Computing Generator in Cyclotomic Integer Rings A subfield algorithm for the Principal Ideal Problem in L 1 K 2 and application to the cryptanalysis of a FHE scheme Jean-François Biasse 1 Thomas Espitau 2 Pierre-Alain Fouque 3 Alexandre Gélin 2 Paul

More information

Introduction to Probability and Statistics Slides 4 Chapter 4

Introduction to Probability and Statistics Slides 4 Chapter 4 Inroducion o Probabiliy and Saisics Slides 4 Chaper 4 Ammar M. Sarhan, asarhan@mahsa.dal.ca Deparmen of Mahemaics and Saisics, Dalhousie Universiy Fall Semeser 8 Dr. Ammar Sarhan Chaper 4 Coninuous Random

More information

CHAPTER 2 Signals And Spectra

CHAPTER 2 Signals And Spectra CHAPER Signals And Specra Properies of Signals and Noise In communicaion sysems he received waveform is usually caegorized ino he desired par conaining he informaion, and he undesired par. he desired par

More information

Cryptanalysis of RAKAPOSHI Stream Cipher

Cryptanalysis of RAKAPOSHI Stream Cipher Crypanalysis of RAKAPOSHI Sream Cipher Lin Ding, Jie Guan Zhengzhou Informaion Science and Technology Insiue, China E-mail: dinglin_cipher@63.com; guanie7@63.com Absrac. RAKAPOSHI is a hardware oriened

More information

State-Space Models. Initialization, Estimation and Smoothing of the Kalman Filter

State-Space Models. Initialization, Estimation and Smoothing of the Kalman Filter Sae-Space Models Iniializaion, Esimaion and Smoohing of he Kalman Filer Iniializaion of he Kalman Filer The Kalman filer shows how o updae pas predicors and he corresponding predicion error variances when

More information

Kinetic Equation for Two-Particle Distribution Function in Boltzmann Gas Mixtures and Equation of Motion for Quasiparticle Pairs

Kinetic Equation for Two-Particle Distribution Function in Boltzmann Gas Mixtures and Equation of Motion for Quasiparticle Pairs ineic Equaion for Two-Paricle Disribuion Funcion in Bolzmann Gas Mixures and Equaion of Moion for Quasiparicle Pairs V.L. Saelie a,b a Insiue of Ionosphere, NCSRT, Almay, amenskoe Plao, 5, azakhsan b Insiue

More information

Logarithmic limit sets of real semi-algebraic sets

Logarithmic limit sets of real semi-algebraic sets Ahead of Prin DOI 10.1515 / advgeom-2012-0020 Advances in Geomery c de Gruyer 20xx Logarihmic limi ses of real semi-algebraic ses Daniele Alessandrini (Communicaed by C. Scheiderer) Absrac. This paper

More information

Solution of Integro-Differential Equations by Using ELzaki Transform

Solution of Integro-Differential Equations by Using ELzaki Transform Global Journal of Mahemaical Sciences: Theory and Pracical. Volume, Number (), pp. - Inernaional Research Publicaion House hp://www.irphouse.com Soluion of Inegro-Differenial Equaions by Using ELzaki Transform

More information

On Measuring Pro-Poor Growth. 1. On Various Ways of Measuring Pro-Poor Growth: A Short Review of the Literature

On Measuring Pro-Poor Growth. 1. On Various Ways of Measuring Pro-Poor Growth: A Short Review of the Literature On Measuring Pro-Poor Growh 1. On Various Ways of Measuring Pro-Poor Growh: A Shor eview of he Lieraure During he pas en years or so here have been various suggesions concerning he way one should check

More information

Lecture 6: Wiener Process

Lecture 6: Wiener Process Lecure 6: Wiener Process Eric Vanden-Eijnden Chapers 6, 7 and 8 offer a (very) brief inroducion o sochasic analysis. These lecures are based in par on a book projec wih Weinan E. A sandard reference for

More information

Random Walk on Circle Imagine a Markov process governing the random motion of a particle on a circular

Random Walk on Circle Imagine a Markov process governing the random motion of a particle on a circular Random Walk on Circle Imagine a Markov process governing he random moion of a paricle on a circular laice: 1 2 γ γ γ The paricle moves o he righ or lef wih probabiliy γ and says where i is wih probabiliy

More information

Section 4.4 Logarithmic Properties

Section 4.4 Logarithmic Properties Secion. Logarihmic Properies 59 Secion. Logarihmic Properies In he previous secion, we derived wo imporan properies of arihms, which allowed us o solve some asic eponenial and arihmic equaions. Properies

More information

Reliability of Technical Systems

Reliability of Technical Systems eliabiliy of Technical Sysems Main Topics Inroducion, Key erms, framing he problem eliabiliy parameers: Failure ae, Failure Probabiliy, Availabiliy, ec. Some imporan reliabiliy disribuions Componen reliabiliy

More information

A universal ordinary differential equation

A universal ordinary differential equation 1 / 10 A universal ordinary differenial equaion Olivier Bournez 1, Amaury Pouly 2 1 LIX, École Polyechnique, France 2 Max Planck Insiue for Sofware Sysems, Germany 12 july 2017 2 / 10 Universal differenial

More information

Object tracking: Using HMMs to estimate the geographical location of fish

Object tracking: Using HMMs to estimate the geographical location of fish Objec racking: Using HMMs o esimae he geographical locaion of fish 02433 - Hidden Markov Models Marin Wæver Pedersen, Henrik Madsen Course week 13 MWP, compiled June 8, 2011 Objecive: Locae fish from agging

More information

Hamilton- J acobi Equation: Explicit Formulas In this lecture we try to apply the method of characteristics to the Hamilton-Jacobi equation: u t

Hamilton- J acobi Equation: Explicit Formulas In this lecture we try to apply the method of characteristics to the Hamilton-Jacobi equation: u t M ah 5 2 7 Fall 2 0 0 9 L ecure 1 0 O c. 7, 2 0 0 9 Hamilon- J acobi Equaion: Explici Formulas In his lecure we ry o apply he mehod of characerisics o he Hamilon-Jacobi equaion: u + H D u, x = 0 in R n

More information

Space-time Galerkin POD for optimal control of Burgers equation. April 27, 2017 Absolventen Seminar Numerische Mathematik, TU Berlin

Space-time Galerkin POD for optimal control of Burgers equation. April 27, 2017 Absolventen Seminar Numerische Mathematik, TU Berlin Space-ime Galerkin POD for opimal conrol of Burgers equaion Manuel Baumann Peer Benner Jan Heiland April 27, 207 Absolvenen Seminar Numerische Mahemaik, TU Berlin Ouline. Inroducion 2. Opimal Space Time

More information

INSTANTANEOUS VELOCITY

INSTANTANEOUS VELOCITY INSTANTANEOUS VELOCITY I claim ha ha if acceleraion is consan, hen he elociy is a linear funcion of ime and he posiion a quadraic funcion of ime. We wan o inesigae hose claims, and a he same ime, work

More information

Monotonic Solutions of a Class of Quadratic Singular Integral Equations of Volterra type

Monotonic Solutions of a Class of Quadratic Singular Integral Equations of Volterra type In. J. Conemp. Mah. Sci., Vol. 2, 27, no. 2, 89-2 Monoonic Soluions of a Class of Quadraic Singular Inegral Equaions of Volerra ype Mahmoud M. El Borai Deparmen of Mahemaics, Faculy of Science, Alexandria

More information

MATH 4330/5330, Fourier Analysis Section 6, Proof of Fourier s Theorem for Pointwise Convergence

MATH 4330/5330, Fourier Analysis Section 6, Proof of Fourier s Theorem for Pointwise Convergence MATH 433/533, Fourier Analysis Secion 6, Proof of Fourier s Theorem for Poinwise Convergence Firs, some commens abou inegraing periodic funcions. If g is a periodic funcion, g(x + ) g(x) for all real x,

More information

Lecture 2 October ε-approximation of 2-player zero-sum games

Lecture 2 October ε-approximation of 2-player zero-sum games Opimizaion II Winer 009/10 Lecurer: Khaled Elbassioni Lecure Ocober 19 1 ε-approximaion of -player zero-sum games In his lecure we give a randomized ficiious play algorihm for obaining an approximae soluion

More information

The Zarankiewicz problem in 3-partite graphs

The Zarankiewicz problem in 3-partite graphs The Zarankiewicz problem in 3-parie graphs Michael Tai Craig Timmons Absrac Le F be a graph, k 2 be an ineger, and wrie ex χ k (n, F ) for he maximum number of edges in an n-verex graph ha is k-parie and

More information

Course Notes for EE227C (Spring 2018): Convex Optimization and Approximation

Course Notes for EE227C (Spring 2018): Convex Optimization and Approximation Course Noes for EE7C Spring 018: Convex Opimizaion and Approximaion Insrucor: Moriz Hard Email: hard+ee7c@berkeley.edu Graduae Insrucor: Max Simchowiz Email: msimchow+ee7c@berkeley.edu Ocober 15, 018 3

More information

Ramanujan and Euler's Constant

Ramanujan and Euler's Constant Proceedings of Symposia in Applied Mahemaics Volume 00, 0000 Ramanujan and Euler's Consan RICHARD P. BRENT Absrac. We consider Ramanujan's conribuion o formulas for Euler's consan. For eample, in his second

More information

Positive continuous solution of a quadratic integral equation of fractional orders

Positive continuous solution of a quadratic integral equation of fractional orders Mah. Sci. Le., No., 9-7 (3) 9 Mahemaical Sciences Leers An Inernaional Journal @ 3 NSP Naural Sciences Publishing Cor. Posiive coninuous soluion of a quadraic inegral equaion of fracional orders A. M.

More information

dt = C exp (3 ln t 4 ). t 4 W = C exp ( ln(4 t) 3) = C(4 t) 3.

dt = C exp (3 ln t 4 ). t 4 W = C exp ( ln(4 t) 3) = C(4 t) 3. Mah Rahman Exam Review Soluions () Consider he IVP: ( 4)y 3y + 4y = ; y(3) = 0, y (3) =. (a) Please deermine he longes inerval for which he IVP is guaraneed o have a unique soluion. Soluion: The disconinuiies

More information

T L. t=1. Proof of Lemma 1. Using the marginal cost accounting in Equation(4) and standard arguments. t )+Π RB. t )+K 1(Q RB

T L. t=1. Proof of Lemma 1. Using the marginal cost accounting in Equation(4) and standard arguments. t )+Π RB. t )+K 1(Q RB Elecronic Companion EC.1. Proofs of Technical Lemmas and Theorems LEMMA 1. Le C(RB) be he oal cos incurred by he RB policy. Then we have, T L E[C(RB)] 3 E[Z RB ]. (EC.1) Proof of Lemma 1. Using he marginal

More information

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients Secion 3.5 Nonhomogeneous Equaions; Mehod of Undeermined Coefficiens Key Terms/Ideas: Linear Differenial operaor Nonlinear operaor Second order homogeneous DE Second order nonhomogeneous DE Soluion o homogeneous

More information

The Arcsine Distribution

The Arcsine Distribution The Arcsine Disribuion Chris H. Rycrof Ocober 6, 006 A common heme of he class has been ha he saisics of single walker are ofen very differen from hose of an ensemble of walkers. On he firs homework, we

More information

Convergence of the Neumann series in higher norms

Convergence of the Neumann series in higher norms Convergence of he Neumann series in higher norms Charles L. Epsein Deparmen of Mahemaics, Universiy of Pennsylvania Version 1.0 Augus 1, 003 Absrac Naural condiions on an operaor A are given so ha he Neumann

More information

On composite integers n for which ϕ(n) n 1

On composite integers n for which ϕ(n) n 1 On composie inegers n for which ϕn) n Florian Luca Insiuo de Maemáicas Universidad Nacional Auonoma de México C.P. 58089, Morelia, Michoacán, México fluca@mamor.unam.mx Carl Pomerance Deparmen of Mahemaics

More information

t j i, and then can be naturally extended to K(cf. [S-V]). The Hasse derivatives satisfy the following: is defined on k(t) by D (i)

t j i, and then can be naturally extended to K(cf. [S-V]). The Hasse derivatives satisfy the following: is defined on k(t) by D (i) A NOTE ON WRONSKIANS AND THE ABC THEOREM IN FUNCTION FIELDS OF RIME CHARACTERISTIC Julie Tzu-Yueh Wang Insiue of Mahemaics Academia Sinica Nankang, Taipei 11529 Taiwan, R.O.C. May 14, 1998 Absrac. We provide

More information

Ordinary Differential Equations

Ordinary Differential Equations Ordinary Differenial Equaions 5. Examples of linear differenial equaions and heir applicaions We consider some examples of sysems of linear differenial equaions wih consan coefficiens y = a y +... + a

More information

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles Diebold, Chaper 7 Francis X. Diebold, Elemens of Forecasing, 4h Ediion (Mason, Ohio: Cengage Learning, 006). Chaper 7. Characerizing Cycles Afer compleing his reading you should be able o: Define covariance

More information

For example, the comb filter generated from. ( ) has a transfer function. e ) has L notches at ω = (2k+1)π/L and L peaks at ω = 2π k/l,

For example, the comb filter generated from. ( ) has a transfer function. e ) has L notches at ω = (2k+1)π/L and L peaks at ω = 2π k/l, Comb Filers The simple filers discussed so far are characeried eiher by a single passband and/or a single sopband There are applicaions where filers wih muliple passbands and sopbands are required The

More information

di Bernardo, M. (1995). A purely adaptive controller to synchronize and control chaotic systems.

di Bernardo, M. (1995). A purely adaptive controller to synchronize and control chaotic systems. di ernardo, M. (995). A purely adapive conroller o synchronize and conrol chaoic sysems. hps://doi.org/.6/375-96(96)8-x Early version, also known as pre-prin Link o published version (if available):.6/375-96(96)8-x

More information

Representing a Signal. Continuous-Time Fourier Methods. Linearity and Superposition. Real and Complex Sinusoids. Jean Baptiste Joseph Fourier

Representing a Signal. Continuous-Time Fourier Methods. Linearity and Superposition. Real and Complex Sinusoids. Jean Baptiste Joseph Fourier Represening a Signal Coninuous-ime ourier Mehods he convoluion mehod for finding he response of a sysem o an exciaion aes advanage of he lineariy and imeinvariance of he sysem and represens he exciaion

More information

R.#W.#Erickson# Department#of#Electrical,#Computer,#and#Energy#Engineering# University#of#Colorado,#Boulder#

R.#W.#Erickson# Department#of#Electrical,#Computer,#and#Energy#Engineering# University#of#Colorado,#Boulder# .#W.#Erickson# Deparmen#of#Elecrical,#Compuer,#and#Energy#Engineering# Universiy#of#Colorado,#Boulder# Chaper 2 Principles of Seady-Sae Converer Analysis 2.1. Inroducion 2.2. Inducor vol-second balance,

More information

FREE ODD PERIODIC ACTIONS ON THE SOLID KLEIN BOTTLE

FREE ODD PERIODIC ACTIONS ON THE SOLID KLEIN BOTTLE An-Najah J. Res. Vol. 1 ( 1989 ) Number 6 Fawas M. Abudiak FREE ODD PERIODIC ACTIONS ON THE SOLID LEIN BOTTLE ey words : Free acion, Periodic acion Solid lein Bole. Fawas M. Abudiak * V.' ZZ..).a11,L.A.;15TY1

More information

Stochastic models and their distributions

Stochastic models and their distributions Sochasic models and heir disribuions Couning cusomers Suppose ha n cusomers arrive a a grocery a imes, say T 1,, T n, each of which akes any real number in he inerval (, ) equally likely The values T 1,,

More information

MODULE 3 FUNCTION OF A RANDOM VARIABLE AND ITS DISTRIBUTION LECTURES PROBABILITY DISTRIBUTION OF A FUNCTION OF A RANDOM VARIABLE

MODULE 3 FUNCTION OF A RANDOM VARIABLE AND ITS DISTRIBUTION LECTURES PROBABILITY DISTRIBUTION OF A FUNCTION OF A RANDOM VARIABLE Topics MODULE 3 FUNCTION OF A RANDOM VARIABLE AND ITS DISTRIBUTION LECTURES 2-6 3. FUNCTION OF A RANDOM VARIABLE 3.2 PROBABILITY DISTRIBUTION OF A FUNCTION OF A RANDOM VARIABLE 3.3 EXPECTATION AND MOMENTS

More information

Online Convex Optimization Example And Follow-The-Leader

Online Convex Optimization Example And Follow-The-Leader CSE599s, Spring 2014, Online Learning Lecure 2-04/03/2014 Online Convex Opimizaion Example And Follow-The-Leader Lecurer: Brendan McMahan Scribe: Sephen Joe Jonany 1 Review of Online Convex Opimizaion

More information

CHAPTER 2: Mathematics for Microeconomics

CHAPTER 2: Mathematics for Microeconomics CHAPTER : Mahemaics for Microeconomics The problems in his chaper are primarily mahemaical. They are inended o give sudens some pracice wih he conceps inroduced in Chaper, bu he problems in hemselves offer

More information

Some Ramsey results for the n-cube

Some Ramsey results for the n-cube Some Ramsey resuls for he n-cube Ron Graham Universiy of California, San Diego Jozsef Solymosi Universiy of Briish Columbia, Vancouver, Canada Absrac In his noe we esablish a Ramsey-ype resul for cerain

More information

Modeling Economic Time Series with Stochastic Linear Difference Equations

Modeling Economic Time Series with Stochastic Linear Difference Equations A. Thiemer, SLDG.mcd, 6..6 FH-Kiel Universiy of Applied Sciences Prof. Dr. Andreas Thiemer e-mail: andreas.hiemer@fh-kiel.de Modeling Economic Time Series wih Sochasic Linear Difference Equaions Summary:

More information

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,

More information