Skip to main content
10 of 13
added image conc. uniformity
Gottfried Helms
  • 5.3k
  • 1
  • 22
  • 38

This is a comment at the comments of Gerhard "Still Computing Oh So Slowly" Paseman's answer, giving just indexes n for more record-holders.

I used the function fharm(n,eps) = frac(h(n))*n^(1+eps) to find the local minima for a fixed eps and consecutive arguments n. The n-1 of my list should agree with the n in the comments. (The harmonic numbers can be computed in Pari/GP using h(n) = psi(1+n) + Euler )

  • Seek manually the first n having a local minimum for w=fharm(n,eps) and document n,w.
  • Guess the next n by n=ceil(n*exp(1))+10 compute w and decrement n as long as also w=fharm(n,eps) decreases .

This is what I got using Pari/GP (and 800 digits internal precision, don't know exactly what it needs for the psi-function at this arguments n) in a couple of seconds:

               n     |   fharm(n,0.1) 
 --------------------+----------------        
                   1    0.0 
                  11    0.277901138881
                  31    1.19066007386
                  83    0.267050685436
                 227    1.70522868276
                 616    1.49190552481
                1674    1.70759404228
                4550    2.19789655729
               12367    1.36471771489
               33617    1.68810700160
               91380    0.873923093872
              248397    1.05774925083
              675214    3.52030034776
             1835421    2.93703145896
             4989191    2.22651939403
            13562027    1.04059409912
            36865412    0.783097603793
           100210581    6.15552338765
           272400600    3.07296513521
           740461601    2.29064626275
          2012783315    2.37389093860
          5471312310    1.01950811681
         14872568831    3.51618209965
         40427833596    2.82622840722
        109894245429   10.6250101261
        298723530401    7.64454034138
        812014744422    6.96806150688
       2207284924203    3.81951285918
       6000022499693    2.46795156044
      16309752131262   12.4771965474
      44334502845080    1.85826500223
     120513673457548   14.1650514186
     327590128640500   21.4949794587
     890482293866031    0.75550636057
    2420581837980561   21.3699821691
    6579823624480555    3.02859881920
   17885814992891026    3.21976135398
   48618685882356024    1.64093320527
  132159290357566703   13.7707827691
  359246197441016284   14.6487253696

The set $M$ is here the set of all $n$ where fharm(n,eps) < 1 . The number of such entries for n=359246197441016284 ~ 10^17 is here 6 . The logarithm of the indexes nare

    ln(n)         ln(n) + gamma
  -------------------------------
        0.E-809  0.577215664902
  2.39789527280   2.97511093770
  4.41884060780   4.99605627270
  11.4227819151   11.9999975800
  17.4227843253   17.9999999902
  34.4227843351   35.0000000000

This - and the differences - might be interesting for extrapolating a tendency and a guess for the cardinality of $M$ depending on eps and the range of n being checked.
Anyway, all numerical test which I've done indicate that the cardinality of $M$ is finite and even decreases with increasing $\varepsilon$ and only if $\varepsilon=0$ might be infinite.


This is the Pari/GP-program which I used. Note, that the quotient of two consecutive $n$ approaches $\small \exp(1)$ so I need only the following guess:

Using the function

  fharm(n,epsilon=0.1) = frac(psi(1+n)+Euler) * n^(1+epsilon) 

the following needs only a couple of steps to find the n with the next local minimum when called with n having the current local minimum:

{findnext_n(n,eps=0.1)=local(n1,w1,n2,w2);
 n1=ceil(n*exp(1)+10); w1 = fharm(n1,eps);
 n2=n1-1;              w2 = fharm(n2,eps);
 while( w2<w1,   n1=n2;w1=w2; 
                 n2=n1-1;w2=fharm(n2,eps)
      );
 return(n1);}               
         

So it is applied:

 \\ test it --------------------
 eps=0.1
 {listlen=40;
 list=matrix(listlen,2);
 list[1,]=[n=1,fharm(n,eps)];
 for(k=2,listlen,
       n=findnext_n(n,eps);
       list[k,]=[n,fharm(n,eps)];
      );
 printp(list); }

***[Update]*** This is new data for the OP's plot of the cardinality of $M$ by the argument $\varepsilon$ where $\small n <= \lceil(\exp(250-\gamma) \rceil$ :
 eps   | c=#M | r=c*eps  | c= card(M) for n<= approx 10^108
 ------+------------------
  0.01  104     1.040
  0.02   55     1.100
  0.03   36     1.080
  0.04   29     1.160
  0.05   21     1.050
  0.06   16     0.960
  0.07   12     0.840
  0.08   12     0.960
  0.09   10     0.900
  0.10    7     0.700
  0.11    6     0.660
  0.12    4     0.480
  0.13    4     0.520
  0.14    4     0.560
  0.15    4     0.600
  0.16    4     0.640
  0.17    4     0.680
  0.18    4     0.720
  0.19    4     0.760
  0.20    4     0.800

***[update 2]*** I've extended the search-space for $n$ to the range $\small 1 \ldots e^{1000} \approx 10^{434} $ and to check sanity to the range $\small 1 \ldots e^{2000} \approx 10^{868} $. For epsilons $\varepsilon$ from $0.001$ in $200$ steps up to $0.2$ I made the following graph: [![picture][1]][1]

For the very small epsilon the increase of the search-space gives slightly higher results, which also illustrates, that for "larger" epsilon the cardinality of $\small M(\varepsilon)$ is finite

[update 3] Uniformity of the f(n) = frac(h_n) * n^1 at the n, where frac(h_n) has a local minimum (on request of @GerhardPaseman):
picture 2

It is also convenient to show a rescaling of the f(n) so that we can immediately determine the cardinalities $\small |M(\varepsilon)|$ just by counting the number of dots above $\small e(n)\ge \varepsilon$. The derivation of the formula is $$ \begin{array}{lll} f(n) \cdot n^\varepsilon &\lt & 1\\ \ln(f(n)) + \varepsilon \cdot \ln(n) &\lt& 0 \\ {\ln(f(n)) \over \ln(n)} + \varepsilon & \lt& 0 \\ \varepsilon & \lt& -\ln_n(f(n)) \end{array}$$ and we simply count, how many dots in the picture show $\small e(n) = - \ln_n(f(n)) \gt \varepsilon$
picture


# Data for cardinalities
epsilon  |M(eps,n)| |M(eps,n)|       
         n<=e^1000  n<=e^2000
-------------------------------
0.0000     1000     2000
0.0010      633      862
0.0020      430      482
0.0030      315      330
0.0040      258      264
0.0050      204      205
0.0060      171      171
0.0070      151      151
0.0080      135      135
0.0090      120      120
0.0100      109      109
0.0110      100      100
0.0120       98       98
0.0130       89       89
0.0140       84       84
0.0150       79       79
0.0160       73       73
0.0170       69       69
0.0180       62       62
0.0190       57       57
0.0200       55       55
0.0210       50       50
0.0220       47       47
0.0230       44       44
0.0240       42       42
0.0250       41       41
0.0260       39       39
0.0270       39       39
0.0280       37       37
0.0290       37       37
0.0300       36       36
0.0310       36       36
0.0320       36       36
0.0330       36       36
0.0340       34       34
0.0350       34       34
0.0360       34       34
0.0370       33       33
0.0380       32       32
0.0390       31       31
0.0400       29       29
0.0410       29       29
0.0420       29       29
0.0430       26       26
0.0440       26       26
0.0450       25       25
0.0460       25       25
0.0470       24       24
0.0480       24       24
0.0490       23       23
0.0500       21       21
0.0510       21       21
0.0520       21       21
0.0530       20       20
0.0540       20       20
0.0550       20       20
0.0560       20       20
0.0570       19       19
0.0580       18       18
0.0590       18       18
0.0600       16       16
0.0610       16       16
0.0620       16       16
0.0630       16       16
0.0640       16       16
0.0650       16       16
0.0660       16       16
0.0670       16       16
0.0680       15       15
0.0690       14       14
0.0700       12       12
0.0710       12       12
0.0720       12       12
0.0730       12       12
0.0740       12       12
0.0750       12       12
0.0760       12       12
0.0770       12       12
0.0780       12       12
0.0790       12       12
0.0800       12       12
0.0810       11       11
0.0820       11       11
0.0830       11       11
0.0840       11       11
0.0850       11       11
0.0860       11       11
0.0870       11       11
0.0880       10       10
0.0890       10       10
0.0900       10       10
0.0910       10       10
0.0920       10       10
0.0930       10       10
0.0940       10       10
0.0950       10       10
0.0960        9        9
0.0970        9        9
0.0980        8        8
0.0990        8        8
0.1000        7        7
0.1010        7        7
0.1020        7        7
0.1030        7        7
0.1040        7        7
0.1050        7        7
0.1060        7        7
0.1070        7        7
0.1080        7        7
0.1090        6        6
0.1100        6        6
0.1110        6        6
0.1120        5        5
0.1130        5        5
0.1140        5        5
0.1150        4        4
0.1160        4        4
0.1170        4        4
0.1180        4        4
0.1190        4        4
0.1200        4        4
0.1210        4        4
0.1220        4        4
0.1230        4        4
0.1240        4        4
0.1250        4        4
0.1260        4        4
0.1270        4        4
0.1280        4        4
0.1290        4        4
0.1300        4        4
0.1310        4        4
0.1320        4        4
0.1330        4        4
0.1340        4        4
0.1350        4        4
0.1360        4        4
0.1370        4        4
0.1380        4        4
0.1390        4        4
0.1400        4        4
0.1410        4        4
0.1420        4        4
0.1430        4        4
0.1440        4        4
0.1450        4        4
0.1460        4        4
0.1470        4        4
0.1480        4        4
0.1490        4        4
0.1500        4        4
0.1510        4        4
0.1520        4        4
0.1530        4        4
0.1540        4        4
0.1550        4        4
0.1560        4        4
0.1570        4        4
0.1580        4        4
0.1590        4        4
0.1600        4        4
0.1610        4        4
0.1620        4        4
0.1630        4        4
0.1640        4        4
0.1650        4        4
0.1660        4        4
0.1670        4        4
0.1680        4        4
0.1690        4        4
0.1700        4        4
0.1710        4        4
0.1720        4        4
0.1730        4        4
0.1740        4        4
0.1750        4        4
0.1760        4        4
0.1770        4        4
0.1780        4        4
0.1790        4        4
0.1800        4        4
0.1810        4        4
0.1820        4        4
0.1830        4        4
0.1840        4        4
0.1850        4        4
0.1860        4        4
0.1870        4        4
0.1880        4        4
0.1890        4        4
0.1900        4        4
0.1910        4        4
0.1920        4        4
0.1930        4        4
0.1940        4        4
0.1950        4        4
0.1960        4        4
0.1970        4        4
0.1980        4        4
0.1990        4        4
Gottfried Helms
  • 5.3k
  • 1
  • 22
  • 38