Douglas Modern Chess, Season 2 Semifinal

Herewith the results of the semifinal, which was between Stockfish and three derivatives. I was actually expecting the the Raubfisch variants to come out on top, based on their performance in the heats, but it was not to be. Perhaps the longer time control affected things.

The results revealed a flaw in my own scoring system, which was supposed to prevent confusion about results, as shown below. First and fourth are mostly clear, but the 2nd and 3rd spots are more problematic. So I need to rethink my scoring before deciding who makes it into the finals.

Summary:

Games: 12; Draws: 9, DrawPercentage: 75 %
Whitewins: 0; Blackwins: 3, Draws: 9

Longer time control, and stronger engines, means more draws. Curious that white was unable to win.

Conventional scoring:

Raubfisch X41d3._sl         : 4
Zeus 4.1.7 M                : 3
Stockfish 11                : 3
Raubfisch_ME262_GTZ20d3._sl : 2

Results table:

Engine                 Win     Draw    Lose
Raubfisch X41d3._sl    2 [0/2] 4 [3/1] 0 [0/0]
Stockfish 11           1 [0/1] 4 [2/2] 1 [1/0]
Zeus 4.1.7 M           0 [0/0] 6 [3/3] 0 [0/0]
Raubfisch_ME262_GTZ2   0 [0/0] 4 [1/3] 2 [2/0]

My scoring system which takes black/white and number of moves into account:

Zeus 4.1.7 M                : 14.82
Raubfisch X41d3._sl         : 11.61
Raubfisch_ME262_GTZ20d3._sl : 6.07
Stockfish 11                : 5.94

The problem with these scores is that an engine that failed to win, despite never losing, should not rank higher than an engine that did win (twice) as well as never losing. Hence I need to rethink.

My points-based scoring system, which takes black/white into account:

Engine                        Points  Percentage
Raubfisch X41d3._sl         : 202   : 67.33 %
Stockfish 11                : 152   : 50.67 %
Zeus 4.1.7 M                : 150   : 50 %
Raubfisch_ME262_GTZ20d3._sl : 102   : 34 %

These scores are better.

Cutechess scoring:

Rank Name                         Elo +/- Games Score Draws
1    Raubfisch X41d3._sl          120 162 6     66.7% 66.7%
2    Zeus 4.1.7 M                   0   0 6     50.0% 100.0%
3    Stockfish 11                   0 173 6     50.0% 66.7%
4    Raubfisch_ME262_GTZ20d3._sl -120 162 6     33.3% 66.7%

Cutechess also appears to rank Zeus above Stockfish, but it may just be sorting alphabetically based on score, without taking anything else into account.

So you can see the different scoring systems produce conflicting results, which I need to resolve before running the final.

Here are the games themselves. Time control was 20 minutes plus 20 seconds per move.

The only mate was between Raubfisch X41d3._sl and Zeus 4.1.7 M, the rest were decided by adjudication.

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Douglas Modern Chess, Season 2 Heat 2

Herewith the results from heat 2 (final heat). Time control was 5 minutes plus 10 seconds per move.

Summary:
Games: 12; Draws: 6, DrawPercentage: 50 %
Whitewins: 3; Blackwins: 3, Draws: 6

Conventional scoring:

Raubfisch X41d3._sl  : 5.5
Stockfish 11         : 3
Fire_7.1_x64         : 2
xiphos-0.6-linux-sse : 1.5

Results table:

Engine                    Win     Draw    Lose
Raubfisch X41d3._sl       5 [3/2] 1 [0/1] 0 [0/0]
Stockfish 11              1 [0/1] 4 [3/1] 1 [0/1]
Fire_7.1_x64              0 [0/0] 4 [2/2] 2 [1/1]
xiphos-0.6-linux-sse      0 [0/0] 3 [1/2] 3 [2/1]

My scoring system which takes black/white into account:

Raubfisch X41d3._sl  : 14.08
Stockfish 11         : 7.98
Fire_7.1_x64         : 0.11
xiphos-0.6-linux-sse : -2.42

My points-based scoring system, which takes black/white and number of moves into account:

Engine                 Points  Percentage
Raubfisch X41d3._sl  : 274   : 91.33 %
Stockfish 11         : 150   : 50 %
Fire_7.1_x64         : 100   : 33.33 %
xiphos-0.6-linux-sse : 76    : 25.33 %

Cutechess scoring:

Rank Name                  Elo +/- Games Score Draws
1    Raubfisch X41d3._sl   417 nan 6     91.7% 16.7%
2    Stockfish 11            0 173 6     50.0% 66.7%
3    Fire_7.1_x64         -120 162 6     33.3% 66.7%
4    xiphos-0.6-linux-sse -191 238 6     25.0% 50.0%

So Fire and Xiphos drop out, and Raubfisch and Stockfish go through to the semi-finals.

Here are the games themselves. The “Mate of the Match” award goes to Xiphos-Stockfish match (second one below).

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Douglas Modern Chess, Season 2 Heat 1

Herewith the results from heat 1. Time control was 5 minutes plus 10 seconds per move.

Summary:
Games: 12; Draws: 4, DrawPercentage: 33.3%
Whitewins: 5; Blackwins: 3, Draws: 4

Conventional scoring:

Raubfisch_ME262_GTZ20d3._sl : 5.5
Zeus 4.1.7 M                : 4
rofChade 2.203              : 1.5
Komodo 11                   : 1

Results table:

Engine                     Win     Draw     Lose
Raubfisch_ME262_GTZ2       5 [3/2] 1 [0/1]  0 [0/0] 
Zeus 4.1.7 M               3 [2/1] 2 [1/1]  1 [0/1]
rofChade 2.203             0 [0/0] 3 [2/1]  3 [1/2] 
Komodo 11                  0 [0/0] 2 [1/1]  4 [2/2]

My scoring system which takes black/white into account:

Raubfisch_ME262_GTZ20d3._sl : 16.46
Zeus 4.1.7 M                : 10.18
rofChade 2.203              : -2.9
Komodo 11                   : -9.89

My points-based scoring system, which takes black/white and number of moves into account:

Engine                        Points  Percentage
Raubfisch_ME262_GTZ20d3._sl : 274   : 91.33%
Zeus 4.1.7 M                : 198   : 66%
rofChade 2.203              : 74    : 24.67%
Komodo 11                   : 50    : 16.67%

Cutechess scoring:

Rank Name                        Elo +/- Games Score Draws
1    Raubfisch_ME262_GTZ20d3._sl 417 nan 6     91.7% 16.7%
2    Zeus 4.1.7 M                120 333 6     66.7% 33.3%
3    rofChade 2.203             -191 238 6     25.0% 50.0%
4    Komodo 11                  -280 nan 6     16.7% 33.3%

So Raubfisch_ME262_GTZ20d3._sl and Zeus 4.1.7 M  go through to the semi-finals.

Herewith the games. Mate of the Match award goes to the Raubfisch_ME262_GTZ20d3._sl vs Zeus 4.1.7 M game, towards the bottom.

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Douglas Modern Chess, Season 2

Now that Season 18 is mostly done over at https://tcec-chess.com/, I thought I’d run another round of the Modern Chess, using updated versions of the engines.

I did try to add LC0 and SugarNN, but could not get them to function properly. It may be because my GPU is rather old, or some back-end dependency was not available.

I did some preliminary testing, to give some newcomers a chance to qualify. The following engines did not survive. Ethereal was a surprise, given how well it did compared to Fire on TCEC.

Ethereal 12
Defenchess 2.3 dev
Godel 7.0
Raven 0.8
zct-032500-64-ja

The following engines did make the cut. In essence it’s a bit of a Stockfish bloodfest, since apart from Stockfish itself, there are three derivatives.

Stockfish 11 (not the latest available, but latest official release)
Raubfisch_ME262_GTZ20d3._sl (based on Stockfish)
Raubfisch X41d3._sl (based on Stockfish)
Zeus 4.1.7 M (based on Stockfish)
Komodo 11
xiphos-0.6-linux-sse  (not updated since Season 1)
Fire_7.1_x64 (not updated since Season 1)
rofChade 2.203

The results from Heat 1 will follow.

 

 

Fake News part 1

There has been a lot of fuss in recent years about the so-called “fake news,” as if this is a new development. Governments and religions have been blatantly lying since forever, and many things written as fiction somehow got accepted as “truth.”

Once the printing presses arrived, the problem exploded exponentially, and, since it is not illegal to publish lies, publishers had a field day, conveniently claiming their “news” was “entertainment” when challenged. So Elvis swims with the Loch Ness monster.

Anyway, the supermarket checkout aisles are stacked with examples of “fake news” which is never condemned, so this is a series of such covers. They’re not current, lest someone accuse me of spreading fake news.

Fake news

Fake news

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Approximating the Fine Structure Constant (again) aka There’s Something About φ

While poking around Giza, I stumbled on this approximation for the inverse of the fine structure constant. It’s not as good as my previous one, but since it relies on cubit -> metre conversion, it qualifies as “interesting.”

It’s just 100φ² ₢, expressed as metres, So we just multiply that by π/6, and voila!

137.0799391

Which according to Wolfram Alpha,

100 / (100φ²π/6) / (fine structure constant)

is 99.9679457% accurate …

Well, according to the current known value, which is a moving target.

Covid-19 decoded

I’ve been tracking Covid-19 since January, and even have an analysis site at https://yo.co.za. Based on all the information available to date, this image shows how I think the disease actually works … it’s not just another type of influenza, but an accelerator of multiplier of whatever illness you have or get.

Disclaimer: I am not a doctor or medical professional, this is just my understanding of how it actually works.

 

Approximating the Fine Structure Constant

The fine structure constant is described as one of the most fundamental physical constants. I don’t pretend to understand anything about it apart from its value, which is close to 1/137. We’ve only been using it for around 100 years.

So the fact that the Khafre pyramid uses 137 as a size multiplier (base is 3 x 137, height is 2 x 137) is annoying, especially since the Khufu pyramid references the speed of light in metres per second, twice. The ancient Egyptians are not supposed to know those things.

Since the fine structure constant itself is a messy decimal number (0.0072973525693…) it is usually referenced via its inverse, as 1/137, which provides a reasonable approximation.

However there have been attempts to find a better approximation, and Scott Onstott has a page with some approximations. Which naturally was a challenge I could not resist….

So I saw that one of the better ones was based on 137²+π²…. and since the royal cubit is π/6, and I have lots of approximations for that, it was simply a matter of finding the right one that produced a better result. That turned out to be based on the plastic number… so without further fanfare, here we are:

\frac{1}{\alpha} \approx \sqrt{{137^{2} + (\frac{\rho^{9}}{4}})^{2}}

 

The WolframAlpha version of the formula is √(137² + ((plastic number^9)/4)²), which produces

137.0359992970725102075551820936909082242952278384186387671

We can check the percentage accuracy as well:

100/137.0359992970725102075551820936909082242952278384186387671 / (fine structure constant)

produces 99.9999998% accurate. Not bad.