Polymath15 test problem
We are initially focusing attention on the following
- Test problem For [math]\displaystyle{ t=y=0.4 }[/math], can one prove that [math]\displaystyle{ H_t(x+iy) \neq 0 }[/math] for all [math]\displaystyle{ x \geq 0 }[/math]?
If we can show this, it is likely that (with the additional use of the argument principle, and some further information on the behaviour of [math]\displaystyle{ H_t(x+iy) }[/math] at [math]\displaystyle{ y=0.4 }[/math]) that one can show that [math]\displaystyle{ H_t(x+iy) \neq 0 }[/math] for all [math]\displaystyle{ y \geq 0.4 }[/math] as well. This would give a new upper bound
- [math]\displaystyle{ \Lambda \leq 0.4 + \frac{1}{2} (0.4)^2 = 0.48 }[/math]
for the de Bruijn-Newman constant.
For very small values of [math]\displaystyle{ x }[/math] we expect to be able to establish this by direct calculation of [math]\displaystyle{ H_t(x+iy) }[/math]. For medium or large values, the strategy is to use a suitable approximation
- [math]\displaystyle{ H_t(x+iy) \approx A + B }[/math]
for some relatively easily computable quantities [math]\displaystyle{ A = A_t(x+iy), B = B_t(x+iy) }[/math] (it may possibly be necessary to use a refined approximation [math]\displaystyle{ A+B-C }[/math] instead). The quantity [math]\displaystyle{ B }[/math] contains a non-zero main term [math]\displaystyle{ B_0 }[/math] which is expected to roughly dominate. To show [math]\displaystyle{ H_t(x+iy) }[/math] is non-zero, it would suffice to show that
- [math]\displaystyle{ \frac{|H_t - A - B|}{|B_0|} \lt \frac{|A + B|}{|B_0|}. }[/math]
Thus one will seek upper bounds on the error [math]\displaystyle{ \frac{|H_t - A - B|}{|B_0|} }[/math] and lower bounds on [math]\displaystyle{ \frac{|A+B|}{|B_0|} }[/math] for various ranges of [math]\displaystyle{ x }[/math]. Numerically it seems that the RHS stays above 0.4 as soon as [math]\displaystyle{ x }[/math] is moderately large, while the LHS stays below 0.1, which looks promising for the rigorous arguments.
Choices of approximation
There are a number of slightly different approximations we have used in previous discussion. The first approximation was
- [math]\displaystyle{ A := \frac{1}{8} \frac{s(s-1)}{2} \pi^{-s/2} \Gamma(s/2) \sum_{n=1}^N \frac{\exp(\frac{t}{16} \log^2 \frac{s+4}{2\pi n^2})}{n^s} }[/math]
- [math]\displaystyle{ B := \frac{1}{8} \frac{s(s-1)}{2} \pi^{-(1-s)/2} \Gamma((1-s)/2) \sum_{n=1}^N \frac{\exp(\frac{t}{16} \log^2 \frac{5-s}{2\pi n^2})}{n^{1-s}} }[/math]
- [math]\displaystyle{ B_0 := \frac{1}{8} \frac{s(s-1)}{2} \pi^{-(1-s)/2} \Gamma((1-s)/2) \exp( \frac{t}{16} \log^2 \frac{5-s}{2\pi} ) }[/math]
- [math]\displaystyle{ s := \frac{1-y+ix}{2} }[/math]
- [math]\displaystyle{ N := \lfloor \frac{\mathrm{Im} s}{2\pi} \rfloor = \lfloor \frac{x}{4\pi} \rfloor. }[/math]
This was modified slightly to
- [math]\displaystyle{ A' := \frac{2}{8} \pi^{-s/2} \sqrt{2\pi} \exp( (\frac{s+4}{2}-\frac{1}{2}) \log \frac{s+4}{2} - \frac{s+4}{2}) \sum_{n=1}^N \frac{\exp(\frac{t}{16} \log^2 \frac{s+4}{2\pi n^2})}{n^s} }[/math]
- [math]\displaystyle{ B' := \frac{2}{8} \pi^{-(1-s)/2} \sqrt{2\pi} \exp( (\frac{5-s}{2}-\frac{1}{2}) \log \frac{5-s}{2} - \frac{5-s}{2}) \sum_{n=1}^N \frac{\exp(\frac{t}{16} \log^2 \frac{5-s}{2\pi n^2})}{n^{1-s}} }[/math]
- [math]\displaystyle{ B'_0 := \frac{2}{8} \pi^{-(1-s)/2} \sqrt{2\pi} \exp( (\frac{5-s}{2}-\frac{1}{2}) \log \frac{5-s}{2} - \frac{5-s}{2}) \exp( \frac{t}{16} \log^2 \frac{5-s}{2\pi} ) }[/math]
- [math]\displaystyle{ s := \frac{1-y+ix}{2} }[/math]
- [math]\displaystyle{ N := \lfloor \frac{\mathrm{Im} s}{2\pi} \rfloor = \lfloor \frac{x}{4\pi} \rfloor. }[/math]
In Effective bounds on H_t - second approach, a more refined approximation was introduced:
- [math]\displaystyle{ A^{eff} := \frac{1}{8} \exp( \frac{t}{4} \alpha_1(\frac{1-y+ix}{2})^2 ) H_{0,1}(\frac{1-y+ix}{2}) \sum_{n=1}^N \frac{1}{n^{\frac{1-y+ix}{2} + \frac{t \alpha_1(\frac{1-y+ix}{2})}{2} - \frac{t}{4} \log n}} }[/math]
- [math]\displaystyle{ B^{eff} := \frac{1}{8} \exp( \frac{t}{4} \overline{\alpha_1(\frac{1+y+ix}{2})}^2 ) \overline{H_{0,1}(\frac{1+y+ix}{2})} \sum_{n=1}^N \frac{1}{n^{\frac{1+y-ix}{2} + \frac{t \overline{\alpha_1(\frac{1+y+ix}{2})}}{2} - \frac{t}{4} \log n}} }[/math]
- [math]\displaystyle{ B^{eff} := \frac{1}{8} \exp( \frac{t}{4} \overline{\alpha_1(\frac{1+y+ix}{2})}^2 ) \overline{H_{0,1}(\frac{1+y+ix}{2})} }[/math]
- [math]\displaystyle{ H_{0,1}(s) := \frac{s (s-1)}{2} \pi^{-s/2} \sqrt{2\pi} \exp( (\frac{s}{2} - \frac{1}{2}) \log \frac{s}{2} - \frac{s}{2} ) }[/math]
- [math]\displaystyle{ \alpha_1(s) := \frac{1}{2s} + \frac{1}{s-1} + \frac{1}{2} \log \frac{s}{2\pi} }[/math]
- [math]\displaystyle{ N := \lfloor \sqrt{ \frac{T'}{2\pi}} \rfloor }[/math]
- [math]\displaystyle{ T' := \frac{x}{2} - \frac{\pi t}{8}. }[/math]
Finally, a simplified approximation is
- [math]\displaystyle{ A^{toy} := B^{toy}_0 \exp(i ((\frac{x}{2} + \frac{\pi t}{8}) \log \frac{x}{4\pi} - \frac{x}{2} - \frac{\pi}{4} )) N^{-y} \sum_{n=1}^N \frac{1}{n^{\frac{1-y+ix}{2} + \frac{t}{4} \log \frac{N^2}{n} + \pi i t/8}} }[/math]
- [math]\displaystyle{ B^{toy} := B^{toy}_0 \sum_{n=1}^N \frac{1}{n^{\frac{1+y-ix}{2} + \frac{t}{4} \log \frac{N^2}{n} - \pi i t/8}} }[/math]
- [math]\displaystyle{ B^{toy}_0 := \frac{\sqrt{2}}{4} \pi^2 N^{\frac{7+y}{2}} \exp( i (-\frac{x}{4} \log \frac{x}{4\pi} + \frac{x}{4} + \frac{9-y}{8} \pi) + \frac{t}{16} (\log \frac{x}{4\pi} - \frac{\pi i}{2})^2 ) e^{-\pi x/8} }[/math]
- [math]\displaystyle{ N := \lfloor \sqrt{\frac{x}{4\pi}} \rfloor. }[/math]
Here is a table comparing the size of the various main terms:
| [math]\displaystyle{ x }[/math] | [math]\displaystyle{ B_0 }[/math] | [math]\displaystyle{ B'_0 }[/math] | [math]\displaystyle{ B^{eff}_0 }[/math] | [math]\displaystyle{ B^{toy}_0 }[/math] |
|---|---|---|---|---|
| [math]\displaystyle{ 10^3 }[/math] | [math]\displaystyle{ (3.4405 + 3.5443 i) \times 10^{-167} }[/math] | [math]\displaystyle{ (3.4204 + 3.5383 i) \times 10^{-167} }[/math] | [math]\displaystyle{ (3.4426 + 3.5411 i) \times 10^{-167} }[/math] | [math]\displaystyle{ (2.3040 + 2.3606 i) \times 10^{-167} }[/math] |
| [math]\displaystyle{ 10^4 }[/math] | [math]\displaystyle{ (-1.1843 - 7.7882 i) \times 10^{-1700} }[/math] | [math]\displaystyle{ (-1.1180 - 7.7888 i) \times 10^{-1700} }[/math] | [math]\displaystyle{ (-1.1185 - 7.7879 i) \times 10^{-1700} }[/math] | [math]\displaystyle{ (-1.1155 - 7.5753 i) \times 10^{-1700} }[/math] |
| [math]\displaystyle{ 10^5 }[/math] | [math]\displaystyle{ (-7.6133 + 2.5065 i) * 10^{-17047} }[/math] | [math]\displaystyle{ (-7.6134 + 2.5060 i) * 10^{-17047} }[/math] | [math]\displaystyle{ (-7.6134 + 2.5059 i) * 10^{-17047} }[/math] | [math]\displaystyle{ (-7.5483 + 2.4848 i) * 10^{-17047} }[/math] |
| [math]\displaystyle{ 10^6 }[/math] | [math]\displaystyle{ (-3.1615 - 7.7093 i) * 10^{-170537} }[/math] | [math]\displaystyle{ (-3.1676 - 7.7063 i) * 10^{-170537} }[/math] | [math]\displaystyle{ (-3.1646 - 7.7079 i) * 10^{-170537} }[/math] | [math]\displaystyle{ (-3.1590 - 7.6898 i) * 10^{-170537} }[/math] |
| [math]\displaystyle{ 10^7 }[/math] | [math]\displaystyle{ (2.1676 - 9.6330 i) * 10^{-1705458} }[/math] | [math]\displaystyle{ (2.1711 - 9.6236 i) * 10^{-1705458} }[/math] | [math]\displaystyle{ (2.1571 - 9.6329 i) * 10^{-1705458} }[/math] | [math]\displaystyle{ (2.2566 - 9.6000 i) * 10^{-1705458} }[/math] |
Here some typical values of [math]\displaystyle{ B/B_0 }[/math] (note that [math]\displaystyle{ B/B_0 }[/math] and [math]\displaystyle{ B'/B'_0 }[/math] are identical):
| [math]\displaystyle{ x }[/math] | [math]\displaystyle{ B/B_0 }[/math] | [math]\displaystyle{ B'/B'_0 }[/math] | [math]\displaystyle{ B^{eff}/B^{eff}_0 }[/math] | [math]\displaystyle{ B^{toy}/B^{toy}_0 }[/math] |
|---|---|---|---|---|
| [math]\displaystyle{ 10^3 }[/math] | [math]\displaystyle{ 0.7722 + 0.6102 i }[/math] | [math]\displaystyle{ 0.7722 + 0.6102 i }[/math] | [math]\displaystyle{ 0.7733 + 0.6101 i }[/math] | [math]\displaystyle{ 0.7626 + 0.6192 i }[/math] |
| [math]\displaystyle{ 10^4 }[/math] | [math]\displaystyle{ 0.7434 - 0.0126 i }[/math] | [math]\displaystyle{ 0.7434 - 0.0126 i }[/math] | [math]\displaystyle{ 0.7434 - 0.0126 i }[/math] | [math]\displaystyle{ 0.7434 - 0.0124 i }[/math] |
| [math]\displaystyle{ 10^5 }[/math] | [math]\displaystyle{ 1.1218 - 0.3211 i }[/math] | [math]\displaystyle{ 1.1218 - 0.3211 i }[/math] | [math]\displaystyle{ 1.1218 - 0.3211 i }[/math] | [math]\displaystyle{ 1.1219 - 0.3213 i }[/math] |
| [math]\displaystyle{ 10^6 }[/math] | [math]\displaystyle{ 1.3956 - 0.5682 i }[/math] | [math]\displaystyle{ 1.3956 - 0.5682 i }[/math] | [math]\displaystyle{ 1.3955 - 0.5682 i }[/math] | [math]\displaystyle{ 1.3956 - 0.5683 i }[/math] |
| [math]\displaystyle{ 10^7 }[/math] | [math]\displaystyle{ 1.6400 + 0.0198 i }[/math] | [math]\displaystyle{ 1.6400 + 0.0198 i }[/math] | [math]\displaystyle{ 1.6401 + 0.0198 i }[/math] | [math]\displaystyle{ 1.6400 - 0.0198 i }[/math] |
Here some typical values of [math]\displaystyle{ A/B_0 }[/math], which seems to be about an order of magnitude smaller than [math]\displaystyle{ B/B_0 }[/math] in many cases:
| [math]\displaystyle{ x }[/math] | [math]\displaystyle{ A/B_0 }[/math] | [math]\displaystyle{ A'/B'_0 }[/math] | [math]\displaystyle{ A^{eff}/B^{eff}_0 }[/math] | [math]\displaystyle{ A^{toy}/B^{toy}_0 }[/math] |
|---|---|---|---|---|
| [math]\displaystyle{ 10^3 }[/math] | [math]\displaystyle{ -0.3856 - 0.0997 i }[/math] | [math]\displaystyle{ -0.3857 - 0.0953 i }[/math] | [math]\displaystyle{ -0.3854 - 0.1002 i }[/math] | [math]\displaystyle{ -0.4036 - 0.0968 i }[/math] |
| [math]\displaystyle{ 10^4 }[/math] | [math]\displaystyle{ -0.2199 - 0.0034 i }[/math] | [math]\displaystyle{ -0.2199 - 0.0036 i }[/math] | [math]\displaystyle{ -0.2199 - 0.0033 i }[/math] | [math]\displaystyle{ -0.2208 - 0.0033 i }[/math] |
| [math]\displaystyle{ 10^5 }[/math] | [math]\displaystyle{ 0.1543 + 0.1660 i }[/math] | [math]\displaystyle{ 0.1543 + 0.1660 i }[/math] | [math]\displaystyle{ 0.1543 + 0.1660 i }[/math] | [math]\displaystyle{ 0.1544 + 0.1663 i }[/math] |
| [math]\displaystyle{ 10^6 }[/math] | [math]\displaystyle{ -0.1013 - 0.1887 i }[/math] | [math]\displaystyle{ -0.1010 - 0.1889 i }[/math] | [math]\displaystyle{ -0.1011 - 0.1890 i }[/math] | [math]\displaystyle{ -0.1012 - 0.1888 i }[/math] |
| [math]\displaystyle{ 10^7 }[/math] | [math]\displaystyle{ -0.1018 + 0.1135 i }[/math] | [math]\displaystyle{ -0.1022 + 0.1133 i }[/math] | [math]\displaystyle{ -0.1025 + 0.1128 i }[/math] | [math]\displaystyle{ -0.0986 + 0.1163 i }[/math] |
Controlling |A+B|/|B_0|
Some numerical data on [math]\displaystyle{ |A+B/B_0| }[/math] source and also [math]\displaystyle{ \mathrm{Re} \frac{A+B}{B_0} }[/math] source, using a step size of 1 for [math]\displaystyle{ x }[/math], suggesting that this ratio tends to oscillate roughly between 0.5 and 3 for medium values of [math]\displaystyle{ x }[/math]:
| range of [math]\displaystyle{ x }[/math] | minimum value | max value | average value | standard deviation | min real part | max real part |
|---|---|---|---|---|---|---|
| 0-1000 | 0.179 | 4.074 | 1.219 | 0.782 | -0.09 | 4.06 |
| 1000-2000 | 0.352 | 4.403 | 1.164 | 0.712 | 0.02 | 4.43 |
| 2000-3000 | 0.352 | 4.050 | 1.145 | 0.671 | 0.15 | 3.99 |
| 3000-4000 | 0.338 | 4.174 | 1.134 | 0.640 | 0.34 | 4.48 |
| 4000-5000 | 0.386 | 4.491 | 1.128 | 0.615 | 0.33 | 4.33 |
| 5000-6000 | 0.377 | 4.327 | 1.120 | 0.599 | 0.377 | 4.327 |
| [math]\displaystyle{ 1-10^5 }[/math] | 0.179 | 4.491 | 1.077 | 0.455 | -0.09 | 4.48 |
| [math]\displaystyle{ 10^5-2 \times 10^5 }[/math] | 0.488 | 3.339 | 1.053 | 0.361 | 0.48 | 3.32 |
| [math]\displaystyle{ 2 \times 10^5-3 \times 10^5 }[/math] | 0.508 | 3.049 | 1.047 | 0.335 | 0.50 | 3.00 |
| [math]\displaystyle{ 3 \times 10^5-4 \times 10^5 }[/math] | 0.517 | 2.989 | 1.043 | 0.321 | 0.52 | 2.97 |
| [math]\displaystyle{ 4 \times 10^5-5 \times 10^5 }[/math] | 0.535 | 2.826 | 1.041 | 0.310 | 0.53 | 2.82 |
| [math]\displaystyle{ 5 \times 10^5-6 \times 10^5 }[/math] | 0.529 | 2.757 | 1.039 | 0.303 | 0.53 | 2.75 |
| [math]\displaystyle{ 6 \times 10^5-7 \times 10^5 }[/math] | 0.548 | 2.728 | 1.038 | 0.296 | 0.55 | 2.72 |
Here is a computation on the magnitude [math]\displaystyle{ |\frac{d}{dx}(B'/B'_0)| }[/math] of the derivative of [math]\displaystyle{ B'/B'_0 }[/math], sampled at steps of 1 in [math]\displaystyle{ x }[/math] source, together with a crude upper bound coming from the triangle inequality source, to give some indication of the oscillation:
| range of [math]\displaystyle{ T=x/2 }[/math] | max value | average value | standard deviation | triangle inequality bound |
|---|---|---|---|---|
| 0-1000 | 1.04 | 0.33 | 0.19 | |
| 1000-2000 | 1.25 | 0.39 | 0.24 | |
| 2000-3000 | 1.31 | 0.39 | 0.25 | |
| 3000-4000 | 1.39 | 0.38 | 0.27 | |
| 4000-5000 | 1.64 | 0.37 | 0.26 | |
| 5000-6000 | 1.60 | 0.36 | 0.27 | |
| 6000-7000 | 1.61 | 0.36 | 0.26 | |
| 7000-8000 | 1.55 | 0.36 | 0.27 | |
| 8000-9000 | 1.65 | 0.34 | 0.26 | |
| 9000-10000 | 1.47 | 0.34 | 0.26 | |
| [math]\displaystyle{ 1-10^5 }[/math] | 1.78 | 0.28 | 0.23 | 2.341 |
| [math]\displaystyle{ 10^5-2 \times 10^5 }[/math] | 1.66 | 0.22 | 0.18 | 2.299 |
| [math]\displaystyle{ 2 \times 10^5-3 \times 10^5 }[/math] | 1.55 | 0.20 | 0.17 | 2.195 |
| [math]\displaystyle{ 3 \times 10^5-4 \times 10^5 }[/math] | 1.53 | 0.19 | 0.16 | 2.109 |
| [math]\displaystyle{ 4 \times 10^5-5 \times 10^5 }[/math] | 1.31 | 0.18 | 0.15 | 2.039 |
| [math]\displaystyle{ 5 \times 10^5-6 \times 10^5 }[/math] | 1.34 | 0.18 | 0.14 | |
| [math]\displaystyle{ 6 \times 10^5-7 \times 10^5 }[/math] | 1.33 | 0.17 | 0.14 |
...
Controlling |H_t-A-B|/|B_0|
val1 = |Heff|/|B’0| val2 = |A’+B’|/|B’0| val3 = |Heff-A’-B’|/|B’0| val4 = (|Heff-A’-B’| + |Heff_error|)/|B’0|
t——x——–y——val1–val2–val3——val4 0.4–10000–0.4—0.52–0.52–0.0006–0.039 0.4–12131–0.4—1.28–1.28–0.0004–0.033 0.4–15256–0.4—0.97–0.97–0.0003–0.027 0.4–18432–0.4—0.68–0.68–0.0003–0.023 0.4–20567–0.4—0.98–0.98–0.0004–0.022 0.4–30654–0.4—1.93–1.93–0.0004–0.016 ...
