Research article

A renormalization approach to the Riemann zeta function at — 1, 1 + 2 + 3 + …~  — 1/12.

  • Received: 04 May 2018 Accepted: 05 June 2018 Published: 21 June 2018
  • MSC : 11M99, 40C99

  • A scaling and renormalization approach to the Riemann zeta function, ζ, evaluated at 1 is presented in two ways. In the first, one takes the difference between Un:=nq=1q and 4Un2 where n2 is the greatest integer function. Using the Cesaro mean twice, i.e., (C,2), yields convergence to the appropriate value. For values of z for which the zeta function is represented by a convergent infinite sum, the double Cesaro mean also yields ζ(z), suggesting that this could be used as an alternative method for extension from the convergent region of z. In the second approach, the difference Unk2ˉUn/k between Un and a particular average, ˉUn/k, involving terms up to k<n and scaled by k2 is shown to equal exactly 112(1k2) for all k<n. This leads to another perspective for interpreting ζ(1).

    Citation: Gunduz Caginalp. A renormalization approach to the Riemann zeta function at — 1, 1 + 2 + 3 + …~  — 1/12.[J]. AIMS Mathematics, 2018, 3(2): 316-321. doi: 10.3934/Math.2018.2.316

    Related Papers:

    [1] Zhenjiang Pan, Zhengang Wu . The inverse of tails of Riemann zeta function, Hurwitz zeta function and Dirichlet L-function. AIMS Mathematics, 2024, 9(6): 16564-16585. doi: 10.3934/math.2024803
    [2] Vediyappan Govindan, Inho Hwang, Choonkil Park . Hyers-Ulam stability of an n-variable quartic functional equation. AIMS Mathematics, 2021, 6(2): 1452-1469. doi: 10.3934/math.2021089
    [3] Junjie Quan . Explicit formulas of alternating multiple zeta star values $ \zeta^\star({\bar 1}, \{1\}_{m-1}, {\bar 1}) $ and $ \zeta^\star(2, \{1\}_{m-1}, {\bar 1}) $. AIMS Mathematics, 2022, 7(1): 288-293. doi: 10.3934/math.2022019
    [4] Huo Tang, Gangadharan Murugusundaramoorthy, Shu-Hai Li, Li-Na Ma . Fekete-Szegö and Hankel inequalities for certain class of analytic functions related to the sine function. AIMS Mathematics, 2022, 7(4): 6365-6380. doi: 10.3934/math.2022354
    [5] Gunduz Caginalp . Fat tails arise endogenously from supply/demand, with or without jump processes. AIMS Mathematics, 2021, 6(5): 4811-4846. doi: 10.3934/math.2021283
    [6] Robert Reynolds, Allan Stauffer . Extended Prudnikov sum. AIMS Mathematics, 2022, 7(10): 18576-18586. doi: 10.3934/math.20221021
    [7] Ling Zhu . Sharp refined quadratic estimations of Shafer's inequalities. AIMS Mathematics, 2021, 6(5): 5020-5027. doi: 10.3934/math.2021296
    [8] Choonkil Park, K. Tamilvanan, Batool Noori, M. B. Moghimi, Abbas Najati . Fuzzy normed spaces and stability of a generalized quadratic functional equation. AIMS Mathematics, 2020, 5(6): 7161-7174. doi: 10.3934/math.2020458
    [9] Hassen Aydi, Bessem Samet, Manuel De la Sen . A generalization of convexity via an implicit inequality. AIMS Mathematics, 2024, 9(5): 11992-12010. doi: 10.3934/math.2024586
    [10] Rui Zhang, Yang Li, Xiaofei Yan . Exponential sums involving the divisor function over arithmetic progressions. AIMS Mathematics, 2023, 8(5): 11084-11094. doi: 10.3934/math.2023561
  • A scaling and renormalization approach to the Riemann zeta function, ζ, evaluated at 1 is presented in two ways. In the first, one takes the difference between Un:=nq=1q and 4Un2 where n2 is the greatest integer function. Using the Cesaro mean twice, i.e., (C,2), yields convergence to the appropriate value. For values of z for which the zeta function is represented by a convergent infinite sum, the double Cesaro mean also yields ζ(z), suggesting that this could be used as an alternative method for extension from the convergent region of z. In the second approach, the difference Unk2ˉUn/k between Un and a particular average, ˉUn/k, involving terms up to k<n and scaled by k2 is shown to equal exactly 112(1k2) for all k<n. This leads to another perspective for interpreting ζ(1).



    1. Introduction

    The Riemann zeta function is defined as the analytic continuation of the infinite sum, ζ(z)=q=1qz where z=x+iyC for Rez=x>1. For x>1 the series converges absolutely to an analytic function. For all other values of z it diverges. Riemann showed [1] that it can be continued analytically for complex values of zC {1}, i.e., except for the value corresponding to the harmonic series. For z=1 one has the (divergent) sum of natural numbers. The analytic continuation of the series yields the result ζ(1)=1/12, with the formal representation that appears to be an obvious contradiction:

    1+2+3+ ... ζ(1)=112 . (1)

    In this note we examine this relation using an approach that involves scaling the truncated (finite) sum and renormalizing in order to obtain a finite result as one takes the infinite limit of the sum.

    Renormalization consists of a set of methodologies constituting a philosophy and approach to problems exhibiting a divergence in some form. Originally introduced for statistical mechanics and quantum field theory by Ken Wilson in the 1970's, renormalization was able to yield the exponents with which key physical properties diverge (see for example, [2,3]). The basic idea is first to average spins within a particular geometric configuration, thereby reducing the size of the system by a factor greater than unity. The reduction in size must be compensated by adjusting the interaction strengths. If this were not done, then iteration of this process would yield a trivial fixed point of zero or infinity. With the appropriate renormalization, however, one can iterate the procedure repeatedly. The key ansatz is that the exponent of the divergent quantity should not change due to this averaging process (with the interactions appropriately renormalized) since the singularity is due to the divergence of the "correlation length" which is the a measure of the distance at which spins can influence one another.

    This approach to statistical mechanics revolutionized many calculations, as very simple calculations yielded the results previously obtained by a tour de force, and led to its adaptation in a number of other areas. The text by Creswick, Poole and Farach [3] describes the implementation of this approach to classical mathematical problems such as fractals and random walk. For example, in random walk, the classical result under robust conditions is that after n steps the random walk has mean distance n1/2 from the original point. This result can also be obtained by averaging sets of k steps, and readjusting (i.e., renormalizing) the step size so that one considers a walk of n/k steps with the new step size. The unique renormalization (i.e., setting the new step size) that leads to a non-trivial result (i.e., not 0 or ) yields the exponent 1/2 in n1/2.

    In this paper we describe methodology along the lines of this approach to obtain an analog of (1) that is well-defined.

    The expression (1) has been of interest in applications such as string theory [4]. In addition to this perspective, two physicists [5] have also provided an explanation of (1) based on shifting infinite sums.


    2. Averaging and re-scaling (Method 1)

    Using the notation Un=nq=1q and r as the greatest integer less than or equal to r we define

    Yn=Un4Un2

    One has from a simple calculation,

    Yn={n/2ifn even(n+1)/2ifn odd.

    Now, let ZN be the Cesaro mean of {Yn}, which is also known as the Cesaro sum and plays an important role in Fourier analysis (see for example, [6], p.52), i.e.,

    ZN:=Avg{Yn:nN}=1NNn=1Yn.

    Considering the odd and even terms separately, one can readily observe that

    Z2K+1=12K+1{11+22+...+2K+22}=12+14K+2 .Z2K=0.

    Let XM:=Avg{ZN:NM}, i.e., the Cesaro mean of ZN, which is the Cesaro mean of the Cesaro mean, i.e., (C,2), of the original {Yn}.

    Theorem 1. For KN one has the following:

    X2K=14+18KKj=11j1/2,    X2K+1=K+14K+2+18K+4K+1j=11j1/2 (3)
    |X2K14|13K+log(K+1)8K (4)
    |X2K+114|16/3+log(K+1)8K+4 (5)

    and thus the limit

    limMXM=14, (6)

    which can also be expressed as

    limMAvgNM{AvgnN{Un4Un214}}=112 . (7)

    Proof. A computation using (2) for even and odd values of M results in (4) and (5). The inequalities

    log(K+1)K+1j=11j1/2=83+K+1j=31j1/283+log(K+1)

    yield the result (6).

    Remark 1. One can summarize this heuristically as

    E[Un4Un2]=P{n=odd}(n+12)+P{n=even}(n2)=12(n+12n2)=14. (8)

    In order to make (8) precise, one would need to invoke some basic probabilistic ideas, primarily the Kolmogorov extension, or existence, theorem (see for example, [7], p. 514) whereby the probability on a finite subset of N can be extended to all of N. Formally identifying Un and Un2 as n as though they were convergent leads to (1).

    One can define the analogous relations Un(z):=nq=1qz which, as noted above, converges to ζ(z) for Rez>1. Note that if a series that converges in the ordinary sense, the Cesaro mean must converge to the same limit. Moreover, if a sequence {cj} is convergent to c, the Cesaro mean also converges to c. Thus, for values of zC in the convergent region, the infinite sum is equal to the Cesaro mean, so that the Cesaro mean can be used for both convergent and nonconvergent values.

    In particular for a value z for which Un(z) converges in the usual sense to ζ(z), one has

    limnYn(z)=limn{Un(z)4Un2(z)}=3ζ(z)

    as n. Since Yn(z) is convergent for this value of z, it follows that the Cesaro mean ZN(z):=N1Nn=1Yn(x) also converges to the same limit, 3ζ(z). Similarly, the Cesaro mean, XM(z):=M1MN=1ZN(z) also converges to 3ζ(z). Thus, the interpretation that double Cesaro mean of

    Un(z)4Un2(z)14

    converges to ζ(z) is maintained for values of z for which Un(z)=nq=1qz is convergent.

    For example, setting z=2, so that one has a convergent series,

    ζ(2)=n=1n2=π26, i.e.,  limnYn(2)=(3)π26,

    and consequently limMXM(z)/(3)= π2/6.

    Hence, this approach using the double Cesaro mean may present another avenue to extend the sum from the convergent to the nonconvergent regions, and offer other ways to study the Riemann zeta function.


    3. Averaging and re-scaling (Method 2)

    An alternate approach to averaging (without using the greatest integer concept) can be implemented by fixing k and letting n=mk+j.

    Note that for rN one has Ur=rq=1q=12r(r+1). Define a continuous extension of Ur by Ur:=12r(r+1) to rR. Then define the average of over the values of j{0,...,k1} as

    9ˉUnk:=1kk1j=0Unjk. (9)

    Theorem 2. For n,kN and k<n one has the exact relation

    Unk2ˉUnk1k2=112. (10)

    Proof. From the definition (9) one observes

    Unk2ˉUnk=12n(n+1)k21kk1j=012(njk)(njk+1)=112(1k2).

    Thus, the quotient in (10) is thus independent of both k and n. This averaging and scaling of Un by any factor k together with renormalization by k2 yields the unique number 1/12.

    Formally, the identification of Un and ˉUn/k with U in the limit as n leads to q=1qζ(1)=1/12.

    Remark 2. (a) The number k can be regarded as the analog of the "subwalk" of k steps in the random walk problem discussed in the introduction, with n/k the new walk with the mean step size increased by a factor k2.

    (b) Setting k:=np with p(0,1) one can write expression (10) in the form

    npUnnpˉUn1pnpnp=112.

    (c) Applying this approach for k=2 yields,

    ˉUn2=12(n2(n2+1)2+n12(n12+1)2)=18n+18n2116Un4ˉUn2=14

    so that formally identifying Un and ˉUn2 as U in the limit n yields U112.

    (d) To extend this result to other values of zC, one can utilize again the analogous quantity, U(z)n=nq=1qz, determine whether it is possible to formulate a definition analogous to (9), and consider values of z for which these converges. The left hand side of (10) can be considered in the same manner as described for Method 1.


    Acknowledgments

    The author thanks Dr. Alban Deniz and Prof. Bogdan Ion for useful discussions.


    Conflict of Interest

    The author declares no conflict of interest.


    [1] E. C. Titchmarsh, D. R. Heath-Brown, The theory of the Riemann zeta-function, Oxford University Press, 1986.
    [2] K. G.Wilson, J. B. Kogut, The renormalization group and the ϵ expansion, Phys. Rep., 12 (1974), 75-200.
    [3] R. J. Creswick, C. P. Poole and H. A. Farach, Introduction to renormalization group methods in physics, 1992.
    [4] J. G. Polchinski, String Theory, Volume I, An Introduction to the Bosonic String, Cambridge University Press, 1998.
    [5] A. Padilla, E. Copeland, Available from: https://www.youtube.com/watch?v=w-I6XTVZXww.
    [6] E. M. Stein, R. Shakarchi, Fourier Analysis an introduction, Princeton University Press, 2003.
    [7] P. Billingsley, Probability and Measure, Wiley: Anniversary Edition, 2012.
  • This article has been cited by:

    1. Gunduz Caginalp, Bogdan Ion, Probabilistic renormalization and analytic continuation, 2022, 241, 0022314X, 221, 10.1016/j.jnt.2022.03.007
  • Reader Comments
  • © 2018 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(4996) PDF downloads(1029) Cited by(1)

Article outline

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog